case study personality traits

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 22 May 2020

Assessing the Big Five personality traits using real-life static facial images

• Alexander Kachur   ORCID: orcid.org/0000-0003-1165-2672 1 ,
• Evgeny Osin   ORCID: orcid.org/0000-0003-3330-5647 2 ,
• Denis Davydov   ORCID: orcid.org/0000-0003-3747-7403 3 ,
• Konstantin Shutilov 4 &
• Alexey Novokshonov 4  

Scientific Reports volume  10 , Article number:  8487 ( 2020 ) Cite this article

123k Accesses

42 Citations

348 Altmetric

Metrics details

• Computer science
• Human behaviour

There is ample evidence that morphological and social cues in a human face provide signals of human personality and behaviour. Previous studies have discovered associations between the features of artificial composite facial images and attributions of personality traits by human experts. We present new findings demonstrating the statistically significant prediction of a wider set of personality features (all the Big Five personality traits) for both men and women using real-life static facial images. Volunteer participants (N = 12,447) provided their face photographs (31,367 images) and completed a self-report measure of the Big Five traits. We trained a cascade of artificial neural networks (ANNs) on a large labelled dataset to predict self-reported Big Five scores. The highest correlations between observed and predicted personality scores were found for conscientiousness (0.360 for men and 0.335 for women) and the mean effect size was 0.243, exceeding the results obtained in prior studies using ‘selfies’. The findings strongly support the possibility of predicting multidimensional personality profiles from static facial images using ANNs trained on large labelled datasets. Future research could investigate the relative contribution of morphological features of the face and other characteristics of facial images to predicting personality.

Similar content being viewed by others

Facial recognition technology can expose political orientation from naturalistic facial images

Michal Kosinski

Individual differences and the multidimensional nature of face perception

David White & A. Mike Burton

Professional actors demonstrate variability, not stereotypical expressions, when portraying emotional states in photographs

Tuan Le Mau, Katie Hoemann, … Lisa Feldman Barrett

Introduction

A growing number of studies have linked facial images to personality. It has been established that humans are able to perceive certain personality traits from each other’s faces with some degree of accuracy 1 , 2 , 3 , 4 . In addition to emotional expressions and other nonverbal behaviours conveying information about one’s psychological processes through the face, research has found that valid inferences about personality characteristics can even be made based on static images of the face with a neutral expression 5 , 6 , 7 . These findings suggest that people may use signals from each other’s faces to adjust the ways they communicate, depending on the emotional reactions and perceived personality of the interlocutor. Such signals must be fairly informative and sufficiently repetitive for recipients to take advantage of the information being conveyed 8 .

Studies focusing on the objective characteristics of human faces have found some associations between facial morphology and personality features. For instance, facial symmetry predicts extraversion 9 . Another widely studied indicator is the facial width to height ratio (fWHR), which has been linked to various traits, such as achievement striving 10 , deception 11 , dominance 12 , aggressiveness 13 , 14 , 15 , 16 , and risk-taking 17 . The fWHR can be detected with high reliability irrespective of facial hair. The accuracy of fWHR-based judgements suggests that the human perceptual system may have evolved to be sensitive to static facial features, such as the relative face width 18 .

There are several theoretical reasons to expect associations between facial images and personality. First, genetic background contributes to both face and personality. Genetic correlates of craniofacial characteristics have been discovered both in clinical contexts 19 , 20 and in non-clinical populations 21 . In addition to shaping the face, genes also play a role in the development of various personality traits, such as risky behaviour 22 , 23 , 24 , and the contribution of genes to some traits exceeds the contribution of environmental factors 25 . For the Big Five traits, heritability coefficients reflecting the proportion of variance that can be attributed to genetic factors typically lie in the 0.30–0.60 range 26 , 27 . From an evolutionary perspective, these associations can be expected to have emerged by means of sexual selection. Recent studies have argued that some static facial features, such as the supraorbital region, may have evolved as a means of social communication 28 and that facial attractiveness signalling valuable personality characteristics is associated with mating success 29 .

Second, there is some evidence showing that pre- and postnatal hormones affect both facial shape and personality. For instance, the face is a visible indicator of the levels of sex hormones, such as testosterone and oestrogen, which affect the formation of skull bones and the fWHR 30 , 31 , 32 . Given that prenatal and postnatal sex hormone levels do influence behaviour, facial features may correlate with hormonally driven personality characteristics, such as aggressiveness 33 , competitiveness, and dominance, at least for men 34 , 35 . Thus, in addition to genes, the associations of facial features with behavioural tendencies may also be explained by androgens and potentially other hormones affecting both face and behaviour.

Third, the perception of one’s facial features by oneself and by others influences one’s subsequent behaviour and personality 36 . Just as the perceived ‘cleverness’ of an individual may lead to higher educational attainment 37 , prejudice associated with the shape of one’s face may lead to the development of maladaptive personality characteristics (i.e., the ‘Quasimodo complex’ 38 ). The associations between appearance and personality over the lifespan have been explored in longitudinal observational studies, providing evidence of ‘self-fulfilling prophecy’-type and ‘self-defeating prophecy’-type effects 39 .

Fourth and finally, some personality traits are associated with habitual patterns of emotionally expressive behaviour. Habitual emotional expressions may shape the static features of the face, leading to the formation of wrinkles and/or the development of facial muscles.

Existing studies have revealed the links between objective facial picture cues and general personality traits based on the Five-Factor Model or the Big Five (BF) model of personality 40 . However, a quick glance at the sizes of the effects found in these studies (summarized in Table  1 ) reveals much controversy. The results appear to be inconsistent across studies and hardly replicable 41 . These inconsistencies may result from the use of small samples of stimulus faces, as well as from the vast differences in methodologies. Stronger effect sizes are typically found in studies using composite facial images derived from groups of individuals with high and low scores on each of the Big Five dimensions 6 , 7 , 8 . Naturally, the task of identifying traits using artificial images comprised of contrasting pairs with all other individual features eliminated or held constant appears to be relatively easy. This is in contrast to realistic situations, where faces of individuals reflect a full range of continuous personality characteristics embedded in a variety of individual facial features.

Studies relying on photographic images of individual faces, either artificially manipulated 2 , 42 or realistic, tend to yield more modest effects. It appears that studies using realistic photographs made in controlled conditions (neutral expression, looking straight at the camera, consistent posture, lighting, and distance to the camera, no glasses, no jewellery, no make-up, etc.) produce stronger effects than studies using ‘selfies’ 25 . Unfortunately, differences in the methodologies make it hard to hypothesize whether the diversity of these findings is explained by variance in image quality, image background, or the prediction models used.

Research into the links between facial picture cues and personality traits faces several challenges. First, the number of specific facial features is very large, and some of them are hard to quantify. Second, the effects of isolated facial features are generally weak and only become statistically noticeable in large samples. Third, the associations between objective facial features and personality traits might be interactive and nonlinear. Finally, studies using real-life photographs confront an additional challenge in that the very characteristics of the images (e.g., the angle of the head, facial expression, makeup, hairstyle, facial hair style, etc.) are based on the subjects’ choices, which are potentially influenced by personality; after all, one of the principal reasons why people make and share their photographs is to signal to others what kind of person they are. The task of isolating the contribution of each variable out of the multitude of these individual variables appears to be hardly feasible. Instead, recent studies in the field have tended to rely on a holistic approach, investigating the subjective perception of personality based on integral facial images.

The holistic approach aims to mimic the mechanisms of human perception of the face and the ways in which people make judgements about each other’s personality. This approach is supported by studies of human face perception, showing that faces are perceived and encoded in a holistic manner by the human brain 43 , 44 , 45 , 46 . Put differently, when people identify others, they consider individual facial features (such as a person’s eyes, nose, and mouth) in concert as a single entity rather than as independent pieces of information 47 , 48 , 49 , 50 . Similar to facial identification, personality judgements involve the extraction of invariant facial markers associated with relatively stable characteristics of an individual’s behaviour. Existing evidence suggests that various social judgements might be based on a common visual representational system involving the holistic processing of visual information 51 , 52 . Thus, even though the associations between isolated facial features and personality characteristics sought by ancient physiognomists have emerged to be weak, contradictory or even non-existent, the holistic approach to understanding the face-personality links appears to be more promising.

An additional challenge faced by studies seeking to reveal the face-personality links is constituted by the inconsistency of the evaluations of personality traits by human raters. As a result, a fairly large number of human raters is required to obtain reliable estimates of personality traits for each photograph. In contrast, recent attempts at using machine learning algorithms have suggested that artificial intelligence may outperform individual human raters. For instance, S. Hu and colleagues 40 used the composite partial least squares component approach to analyse dense 3D facial images obtained in controlled conditions and found significant associations with personality traits (stronger for men than for women).

A similar approach can be implemented using advanced machine learning algorithms, such as artificial neural networks (ANNs), which can extract and process significant features in a holistic manner. The recent applications of ANNs to the analysis of human faces, body postures, and behaviours with the purpose of inferring apparent personality traits 53 , 54 indicate that this approach leads to a higher accuracy of prediction compared to individual human raters. The main difficulty of the ANN approach is the need for large labelled training datasets that are difficult to obtain in laboratory settings. However, ANNs do not require high-quality photographs taken in controlled conditions and can potentially be trained using real-life photographs provided that the dataset is large enough. The interpretation of findings in such studies needs to acknowledge that a real-life photograph, especially one chosen by a study participant, can be viewed as a holistic behavioural act, which may potentially contain other cues to the subjects’ personality in addition to static facial features (e.g., lighting, hairstyle, head angle, picture quality, etc.).

The purpose of the current study was to investigate the associations of facial picture cues with self-reported Big Five personality traits by training a cascade of ANNs to predict personality traits from static facial images. The general hypothesis is that a real-life photograph contains cues about personality that can be extracted using machine learning. Due to the vast diversity of findings concerning the prediction accuracy of different traits across previous studies, we did not set a priori hypotheses about differences in prediction accuracy across traits.

Prediction accuracy

We used data from the test dataset containing predicted scores for 3,137 images associated with 1,245 individuals. To determine whether the variance in the predicted scores was associated with differences across images or across individuals, we calculated the intraclass correlation coefficients (ICCs) presented in Table  2 . The between-individual proportion of variance in the predicted scores ranged from 79 to 88% for different traits, indicating a general consistency of predicted scores for different photographs of the same individual. We derived the individual scores used in all subsequent analyses as the simple averages of the predicted scores for all images provided by each participant.

The correlation coefficients between the self-report test scores and the scores predicted by the ANN ranged from 0.14 to 0.36. The associations were strongest for conscientiousness and weakest for openness. Extraversion and neuroticism were significantly better predicted for women than for men (based on the z test). We also compared the prediction accuracy within each gender using Steiger’s test for dependent sample correlation coefficients. For men, conscientiousness was predicted more accurately than the other four traits (the differences among the latter were not statistically significant). For women, conscientiousness was predicted more accurately, and openness was predicted less accurately compared to the three other traits.

The mean absolute error (MAE) of prediction ranged between 0.89 and 1.04 standard deviations. We did not find any associations between the number of photographs and prediction error.

Trait intercorrelations

The structure of the correlations between the scales was generally similar for the observed test scores and the predicted values, but some coefficients differed significantly (based on the z test) (see Table  3 ). Most notably, predicted openness was more strongly associated with conscientiousness (negatively) and extraversion (positively), whereas its association with agreeableness was negative rather than positive. The associations of predicted agreeableness with conscientiousness and neuroticism were stronger than those between the respective observed scores. In women, predicted neuroticism demonstrated a stronger inverse association with conscientiousness and a stronger positive association with openness. In men, predicted neuroticism was less strongly associated with extraversion than its observed counterpart.

To illustrate the findings, we created composite images using Abrosoft FantaMorph 5 by averaging the uploaded images across contrast groups of 100 individuals with the highest and the lowest test scores on each trait. The resulting morphed images in which individual features are eliminated are presented in Fig.  1 .

Composite facial images morphed across contrast groups of 100 individuals for each Big Five trait.

This study presents new evidence confirming that human personality is related to individual facial appearance. We expected that machine learning (in our case, artificial neural networks) could reveal multidimensional personality profiles based on static morphological facial features. We circumvented the reliability limitations of human raters by developing a neural network and training it on a large dataset labelled with self-reported Big Five traits.

We expected that personality traits would be reflected in the whole facial image rather than in its isolated features. Based on this expectation, we developed a novel two-tier machine learning algorithm to encode the invariant facial features as a vector in a 128-dimensional space that was used to predict the BF traits by means of a multilayer perceptron. Although studies using real-life photographs do not require strict experimental conditions, we had to undertake a series of additional organizational and technological steps to ensure consistent facial image characteristics and quality.

Our results demonstrate that real-life photographs taken in uncontrolled conditions can be used to predict personality traits using complex computer vision algorithms. This finding is in contrast to previous studies that mostly relied on high-quality facial images taken in controlled settings. The accuracy of prediction that we obtained exceeds that in the findings of prior studies that used realistic individual photographs taken in uncontrolled conditions (e.g., selfies 55 ). The advantage of our methodology is that it is relatively simple (e.g., it does not rely on 3D scanners or 3D facial landmark maps) and can be easily implemented using a desktop computer with a stock graphics accelerator.

In the present study, conscientiousness emerged to be more easily recognizable than the other four traits, which is consistent with some of the existing findings 7 , 40 . The weaker effects for extraversion and neuroticism found in our sample may be because these traits are associated with positive and negative emotional experiences, whereas we only aimed to use images with neutral or close to neutral emotional expressions. Finally, this appears to be the first study to achieve a significant prediction of openness to experience. Predictions of personality based on female faces appeared to be more reliable than those for male faces in our sample, in contrast to some previous studies 40 .

The BF factors are known to be non-orthogonal, and we paid attention to their intercorrelations in our study 56 , 57 . Various models have attempted to explain the BF using higher-order dimensions, such as stability and plasticity 58 or a single general factor of personality (GFP) 59 . We discovered that the intercorrelations of predicted factors tend to be stronger than the intercorrelations of self-report questionnaire scales used to train the model. This finding suggests a potential biological basis of GFP. However, the stronger intercorrelations of the predicted scores can be explained by consistent differences in picture quality (just as the correlations between the self-report scales can be explained by social desirability effects and other varieties of response bias 60 ). Clearly, additional research is needed to understand the context of this finding.

We believe that the present study, which did not involve any subjective human raters, constitutes solid evidence that all the Big Five traits are associated with facial cues that can be extracted using machine learning algorithms. However, despite having taken reasonable organizational and technical steps to exclude the potential confounds and focus on static facial features, we are still unable to claim that morphological features of the face explain all the personality-related image variance captured by the ANNs. Rather, we propose to see facial photographs taken by subjects themselves as complex behavioural acts that can be evaluated holistically and that may contain various other subtle personality cues in addition to static facial features.

The correlations reported above with a mean r = 0.243 can be viewed as modest; indeed, facial image-based personality assessment can hardly replace traditional personality measures. However, this effect size indicates that an ANN can make a correct guess about the relative standing of two randomly chosen individuals on a personality dimension in 58% of cases (as opposed to the 50% expected by chance) 61 . The effect sizes we observed are comparable with the meta-analytic estimates of correlations between self-reported and observer ratings of personality traits: the associations range from 0.30 to 0.49 when one’s personality is rated by close relatives or colleagues, but only from −0.01 to 0.29 when rated by strangers 62 . Thus, an artificial neural network relying on static facial images outperforms an average human rater who meets the target in person without any prior acquaintance. Given that partner personality and match between two personalities predict friendship formation 63 , long-term relationship satisfaction 64 , and the outcomes of dyadic interaction in unstructured settings 65 , the aid of artificial intelligence in making partner choices could help individuals to achieve more satisfying interaction outcomes.

There are a vast number of potential applications to be explored. The recognition of personality from real-life photos can be applied in a wide range of scenarios, complementing the traditional approaches to personality assessment in settings where speed is more important than accuracy. Applications may include suggesting best-fitting products or services to customers, proposing to individuals a best match in dyadic interaction settings (such as business negotiations, online teaching, etc.) or personalizing the human-computer interaction. Given that the practical value of any selection method is proportional to the number of decisions made and the size and variability of the pool of potential choices 66 , we believe that the applied potential of this technology can be easily revealed at a large scale, given its speed and low cost. Because the reliability and validity of self-report personality measures is not perfect, prediction could be further improved by supplementing these measures with peer ratings and objective behavioural indicators of personality traits.

The fact that conscientiousness was predicted better than the other traits for both men and women emerges as an interesting finding. From an evolutionary perspective, one would expect the traits most relevant for cooperation (conscientiousness and agreeableness) and social interaction (certain facets of extraversion and neuroticism, such as sociability, dominance, or hostility) to be reflected more readily in the human face. The results are generally in line with this idea, but they need to be replicated and extended by incorporating trait facets in future studies to provide support for this hypothesis.

Finally, although we tried to control the potential sources of confounds and errors by instructing the participants and by screening the photographs (based on angles, facial expressions, makeup, etc.), the present study is not without limitations. First, the real-life photographs we used could still carry a variety of subtle cues, such as makeup, angle, light facial expressions, and information related to all the other choices people make when they take and share their own photographs. These additional cues could say something about their personality, and the effects of all these variables are inseparable from those of static facial features, making it hard to draw any fundamental conclusions from the findings. However, studies using real-life photographs may have higher ecological validity compared to laboratory studies; our results are more likely to generalize to real-life situations where users of various services are asked to share self-pictures of their choice.

Another limitation pertains to a geographically bounded sample of individuals; our participants were mostly Caucasian and represented one cultural and age group (Russian-speaking adults). Future studies could replicate the effects using populations representing a more diverse variety of ethnic, cultural, and age groups. Studies relying on other sources of personality data (e.g., peer ratings or expert ratings), as well as wider sets of personality traits, could complement and extend the present findings.

Sample and procedure

The study was carried out in the Russian language. The participants were anonymous volunteers recruited through social network advertisements. They did not receive any financial remuneration but were provided with a free report on their Big Five personality traits. The data were collected online using a dedicated research website and a mobile application. The participants provided their informed consent, completed the questionnaires, reported their age and gender and were asked to upload their photographs. They were instructed to take or upload several photographs of their face looking directly at the camera with enough lighting, a neutral facial expression and no other people in the picture and without makeup.

Our goal was to obtain an out-of-sample validation dataset of 616 respondents of each gender to achieve 80% power for a minimum effect we considered to be of practical significance ( r  = 0.10 at p < 0.05), requiring a total of 6,160 participants of each gender in the combined dataset comprising the training and validation datasets. However, we aimed to gather more data because we expected that some online respondents might provide low-quality or non-genuine photographs and/or invalid questionnaire responses.

The initial sample included 25,202 participants who completed the questionnaire and uploaded a total of 77,346 photographs. The final combined dataset comprised 12,447 valid questionnaires and 31,367 associated photographs after the data screening procedures (below). The participants ranged in age from 18 to 60 (59.4% women, M = 27.61, SD = 12.73, and 40.6% men, M = 32.60, SD = 11.85). The dataset was split randomly into a training dataset (90%) and a test dataset (10%) used to validate the prediction model. The validation dataset included the responses of 505 men who provided 1224 facial images and 740 women who provided 1913 images. Due to the sexually dimorphic nature of facial features and certain personality traits (particularly extraversion 1 , 67 , 68 ), all the predictive models were trained and validated separately for male and female faces.

Ethical approval

The research was carried out in accordance with the Declaration of Helsinki. The study protocol was approved by the Research Ethics Committee of the Open University for the Humanities and Economics. We obtained the participants’ informed consent to use their data and photographs for research purposes and to publish generalized findings. The morphed group average images presented in the paper do not allow the identification of individuals. No information or images that could lead to the identification of study participants have been published.

Data screening

We excluded incomplete questionnaires (N = 3,035) and used indices of response consistency to screen out random responders 69 . To detect systematic careless responses, we used the modal response category count, maximum longstring (maximum number of identical responses given in sequence by participant), and inter-item standard deviation for each questionnaire. At this stage, we screened out the answers of individuals with zero standard deviations (N = 329) and a maximum longstring above 10 (N = 1,416). To detect random responses, we calculated the following person-fit indices: the person-total response profile correlation, the consistency of response profiles for the first and the second half of the questionnaire, the consistency of response profiles obtained based on equivalent groups of items, the number of polytomous Guttman errors, and the intraclass correlation of item responses within facets.

Next, we conducted a simulation by generating random sets of integers in the 1–5 range based on a normal distribution (µ = 3, σ = 1) and on the uniform distribution and calculating the same person-fit indices. For each distribution, we generated a training dataset and a test dataset, each comprised of 1,000 simulated responses and 1,000 real responses drawn randomly from the sample. Next, we ran a logistic regression model using simulated vs real responses as the outcome variable and chose an optimal cutoff point to minimize the misclassification error (using the R package optcutoff). The sensitivity value was 0.991 for the uniform distribution and 0.960 for the normal distribution, and the specificity values were 0.923 and 0.980, respectively. Finally, we applied the trained model to the full dataset and identified observations predicted as likely to be simulated based on either distribution (N = 1,618). The remaining sample of responses (N = 18,804) was used in the subsequent analyses.

Big Five measure

We used a modified Russian version of the 5PFQ questionnaire 70 , which is a 75-item measure of the Big Five model, with 15 items per trait grouped into five three-item facets. To confirm the structural validity of the questionnaire, we tested an exploratory structural equation (ESEM) model with target rotation in Mplus 8.2. The items were treated as ordered categorical variables using the WLSMV estimator, and facet variance was modelled by introducing correlated uniqueness values for the items comprising each facet.

The theoretical model showed a good fit to the data (χ 2  = 147854.68, df = 2335, p < 0.001; CFI = 0.931; RMSEA = 0.040 [90% CI: 0.040, 0.041]; SRMR = 0.024). All the items showed statistically significant loadings on their theoretically expected scales (λ ranged from 0.14 to 0.87, M = 0.51, SD = 0.17), and the absolute cross-loadings were reasonably low (M = 0.11, SD = 0.11). The distributions of the resulting scales were approximately normal (with skewness and kurtosis values within the [−1; 1] range). To assess the reliability of the scales, we calculated two internal consistency indices, namely, robust omega (using the R package coefficientalpha) and algebraic greatest lower bound (GLB) reliability (using the R package psych) 71 (see Table  4 ).

Image screening and pre-processing

The images (photographs and video frames) were subjected to a three-step screening procedure aimed at removing fake and low-quality images. First, images with no human faces or with more than one human face were detected by our computer vision (CV) algorithms and automatically removed. Second, celebrity images were identified and removed by means of a dedicated neural network trained on a celebrity photo dataset (CelebFaces Attributes Dataset (CelebA), N > 200,000) 72 that was additionally enriched with pictures of Russian celebrities. The model showed a 98.4% detection accuracy. Third, we performed a manual moderation of the remaining images to remove images with partially covered faces, those that were evidently photoshopped or any other fake images not detected by CV.

The images retained for subsequent processing were converted to single-channel 8-bit greyscale format using the OpenCV framework (opencv.org). Head position (pitch, yaw, roll) was measured using our own dedicated neural network (multilayer perceptron) trained on a sample of 8 000 images labelled by our team. The mean absolute error achieved on the test sample of 800 images was 2.78° for roll, 1.67° for pitch, and 2.34° for yaw. We used the head position data to retain the images with yaw and roll within the −30° to 30° range and pitch within the −15° to 15° range.

Next, we assessed emotional neutrality using the Microsoft Cognitive Services API on the Azure platform (score range: 0 to 1) and used 0.50 as a threshold criterion to remove emotionally expressive images. Finally, we applied the face and eye detection, alignment, resize, and crop functions available within the Dlib (dlib.net) open-source toolkit to arrive at a set of standardized 224 × 224 pixel images with eye pupils aligned to a standard position with an accuracy of 1 px. Images with low resolution that contained less than 60 pixels between the eyes, were excluded in the process.

The final photoset comprised 41,835 images. After the screened questionnaire responses and images were joined, we obtained a set of 12,447 valid Big Five questionnaires associated with 31,367 validated images (an average of 2.59 images per person for women and 2.42 for men).

Neural network architecture

First, we developed a computer vision neural network (NNCV) aiming to determine the invariant features of static facial images that distinguish one face from another but remain constant across different images of the same person. We aimed to choose a neural network architecture with a good feature space and resource-efficient learning, considering the limited hardware available to our research team. We chose a residual network architecture based on ResNet 73 (see Fig.  2 ).

Layer architecture of the computer vision neural network (NNCV) and the personality diagnostics neural network (NNPD).

This type of neural network was originally developed for image classification. We dropped the final layer from the original architecture and obtained a NNCV that takes a static monochrome image (224 × 224 pixels in size) and generates a vector of 128 32-bit dimensions describing unique facial features in the source image. As a measure of success, we calculated the Euclidean distance between the vectors generated from different images.

Using Internet search engines, we collected a training dataset of approximately 2 million openly available unlabelled real-life photos taken in uncontrolled conditions stratified by race, age and gender (using search engine queries such as ‘face photo’, ‘face pictures’, etc.). The training was conducted on a server equipped with four NVidia Titan accelerators. The trained neural network was validated on a dataset of 40,000 images belonging to 800 people, which was an out-of-sample part of the original dataset. The Euclidean distance threshold for the vectors belonging to the same person was 0.40 after the training was complete.

Finally, we trained a personality diagnostics neural network (NNPD), which was implemented as a multilayer perceptron (see Fig.  2 ). For that purpose, we used a training dataset (90% of the final sample) containing the questionnaire scores of 11,202 respondents and a total of 28,230 associated photographs. The NNPD takes the vector of the invariants obtained from NNCV as an input and predicts the Big Five personality traits as the output. The network was trained using the same hardware, and the training process took 9 days. The whole process was performed for male and female faces separately.

Data availability

The set of photographs is not made available because we did not solicit the consent of the study participants to publish the individual photographs. The test dataset with the observed and predicted Big Five scores is available from the openICPSR repository: https://doi.org/10.3886/E109082V1 .

Kramer, R. S. S., King, J. E. & Ward, R. Identifying personality from the static, nonexpressive face in humans and chimpanzees: Evidence of a shared system for signaling personality. Evol. Hum. Behav . https://doi.org/10.1016/j.evolhumbehav.2010.10.005 (2011).

Walker, M. & Vetter, T. Changing the personality of a face: Perceived big two and big five personality factors modeled in real photographs. J. Pers. Soc. Psychol. 110 , 609–624 (2016).

Article   Google Scholar  

Naumann, L. P., Vazire, S., Rentfrow, P. J. & Gosling, S. D. Personality Judgments Based on Physical Appearance. Personal. Soc. Psychol. Bull. 35 , 1661–1671 (2009).

Borkenau, P., Brecke, S., Möttig, C. & Paelecke, M. Extraversion is accurately perceived after a 50-ms exposure to a face. J. Res. Pers. 43 , 703–706 (2009).

Shevlin, M., Walker, S., Davies, M. N. O., Banyard, P. & Lewis, C. A. Can you judge a book by its cover? Evidence of self-stranger agreement on personality at zero acquaintance. Pers. Individ. Dif . https://doi.org/10.1016/S0191-8869(02)00356-2 (2003).

Penton-Voak, I. S., Pound, N., Little, A. C. & Perrett, D. I. Personality Judgments from Natural and Composite Facial Images: More Evidence For A “Kernel Of Truth” In Social Perception. Soc. Cogn. 24 , 607–640 (2006).

Little, A. C. & Perrett, D. I. Using composite images to assess accuracy in personality attribution to faces. Br. J. Psychol. 98 , 111–126 (2007).

Kramer, R. S. S. & Ward, R. Internal Facial Features are Signals of Personality and Health. Q. J. Exp. Psychol. 63 , 2273–2287 (2010).

Pound, N., Penton-Voak, I. S. & Brown, W. M. Facial symmetry is positively associated with self-reported extraversion. Pers. Individ. Dif. 43 , 1572–1582 (2007).

Lewis, G. J., Lefevre, C. E. & Bates, T. Facial width-to-height ratio predicts achievement drive in US presidents. Pers. Individ. Dif. 52 , 855–857 (2012).

Haselhuhn, M. P. & Wong, E. M. Bad to the bone: facial structure predicts unethical behaviour. Proc. R. Soc. B Biol. Sci. 279 , 571 LP–576 (2012).

Valentine, K. A., Li, N. P., Penke, L. & Perrett, D. I. Judging a Man by the Width of His Face: The Role of Facial Ratios and Dominance in Mate Choice at Speed-Dating Events. Psychol. Sci . 25 , (2014).

Carre, J. M. & McCormick, C. M. In your face: facial metrics predict aggressive behaviour in the laboratory and in varsity and professional hockey players. Proc. R. Soc. B Biol. Sci. 275 , 2651–2656 (2008).

Carré, J. M., McCormick, C. M. & Mondloch, C. J. Facial structure is a reliable cue of aggressive behavior: Research report. Psychol. Sci . https://doi.org/10.1111/j.1467-9280.2009.02423.x (2009).

Haselhuhn, M. P., Ormiston, M. E. & Wong, E. M. Men’s Facial Width-to-Height Ratio Predicts Aggression: A Meta-Analysis. PLoS One 10 , e0122637 (2015).

Lefevre, C. E., Etchells, P. J., Howell, E. C., Clark, A. P. & Penton-Voak, I. S. Facial width-to-height ratio predicts self-reported dominance and aggression in males and females, but a measure of masculinity does not. Biol. Lett . 10 , (2014).

Welker, K. M., Goetz, S. M. M. & Carré, J. M. Perceived and experimentally manipulated status moderates the relationship between facial structure and risk-taking. Evol. Hum. Behav . https://doi.org/10.1016/j.evolhumbehav.2015.03.006 (2015).

Geniole, S. N. & McCormick, C. M. Facing our ancestors: judgements of aggression are consistent and related to the facial width-to-height ratio in men irrespective of beards. Evol. Hum. Behav. 36 , 279–285 (2015).

Valentine, M. et al . Computer-Aided Recognition of Facial Attributes for Fetal Alcohol Spectrum Disorders. Pediatrics 140 , (2017).

Ferry, Q. et al . Diagnostically relevant facial gestalt information from ordinary photos. Elife 1–22 https://doi.org/10.7554/eLife.02020.001 (2014).

Claes, P. et al . Modeling 3D Facial Shape from DNA. PLoS Genet. 10 , e1004224 (2014).

Carpenter, J. P., Garcia, J. R. & Lum, J. K. Dopamine receptor genes predict risk preferences, time preferences, and related economic choices. J. Risk Uncertain. 42 , 233–261 (2011).

Dreber, A. et al . The 7R polymorphism in the dopamine receptor D4 gene (<em>DRD4</em>) is associated with financial risk taking in men. Evol. Hum. Behav. 30 , 85–92 (2009).

Bouchard, T. J. et al . Sources of human psychological differences: the Minnesota Study of Twins Reared Apart. Science (80-.). 250 , 223 LP–228 (1990).

Article   ADS   Google Scholar  

Livesley, W. J., Jang, K. L. & Vernon, P. A. Phenotypic and genetic structure of traits delineating personality disorder. Arch. Gen. Psychiatry https://doi.org/10.1001/archpsyc.55.10.941 (1998).

Bouchard, T. J. & Loehlin, J. C. Genes, evolution, and personality. Behavior Genetics https://doi.org/10.1023/A:1012294324713 (2001).

Vukasović, T. & Bratko, D. Heritability of personality: A meta-analysis of behavior genetic studies. Psychol. Bull. 141 , 769–785 (2015).

Godinho, R. M., Spikins, P. & O’Higgins, P. Supraorbital morphology and social dynamics in human evolution. Nat. Ecol. Evol . https://doi.org/10.1038/s41559-018-0528-0 (2018).

Rhodes, G., Simmons, L. W. & Peters, M. Attractiveness and sexual behavior: Does attractiveness enhance mating success? Evol. Hum. Behav . https://doi.org/10.1016/j.evolhumbehav.2004.08.014 (2005).

Lefevre, C. E., Lewis, G. J., Perrett, D. I. & Penke, L. Telling facial metrics: Facial width is associated with testosterone levels in men. Evol. Hum. Behav. 34 , 273–279 (2013).

Whitehouse, A. J. O. et al . Prenatal testosterone exposure is related to sexually dimorphic facial morphology in adulthood. Proceedings. Biol. Sci. 282 , 20151351 (2015).

Penton-Voak, I. S. & Chen, J. Y. High salivary testosterone is linked to masculine male facial appearance in humans. Evol. Hum. Behav . https://doi.org/10.1016/j.evolhumbehav.2004.04.003 (2004).

Carré, J. M. & Archer, J. Testosterone and human behavior: the role of individual and contextual variables. Curr. Opin. Psychol. 19 , 149–153 (2018).

Swaddle, J. P. & Reierson, G. W. Testosterone increases perceived dominance but not attractiveness in human males. Proc. R. Soc. B Biol. Sci . https://doi.org/10.1098/rspb.2002.2165 (2002).

Eisenegger, C., Kumsta, R., Naef, M., Gromoll, J. & Heinrichs, M. Testosterone and androgen receptor gene polymorphism are associated with confidence and competitiveness in men. Horm. Behav. 92 , 93–102 (2017).

Article   CAS   Google Scholar  

Kaplan, H. B. Social Psychology of Self-Referent Behavior . https://doi.org/10.1007/978-1-4899-2233-5 . (Springer US, 1986).

Rosenthal, R. & Jacobson, L. Pygmalion in the classroom. Urban Rev . https://doi.org/10.1007/BF02322211 (1968).

Masters, F. W. & Greaves, D. C. The Quasimodo complex. Br. J. Plast. Surg . 204–210 (1967).

Zebrowitz, L. A., Collins, M. A. & Dutta, R. The Relationship between Appearance and Personality Across the Life Span. Personal. Soc. Psychol. Bull. 24 , 736–749 (1998).

Hu, S. et al . Signatures of personality on dense 3D facial images. Sci. Rep. 7 , 73 (2017).

Kosinski, M. Facial Width-to-Height Ratio Does Not Predict Self-Reported Behavioral Tendencies. Psychol. Sci. 28 , 1675–1682 (2017).

Walker, M., Schönborn, S., Greifeneder, R. & Vetter, T. The basel face database: A validated set of photographs reflecting systematic differences in big two and big five personality dimensions. PLoS One 13 , (2018).

Goffaux, V. & Rossion, B. Faces are ‘spatial’ - Holistic face perception is supported by low spatial frequencies. J. Exp. Psychol. Hum. Percept. Perform . https://doi.org/10.1037/0096-1523.32.4.1023 (2006).

Schiltz, C. & Rossion, B. Faces are represented holistically in the human occipito-temporal cortex. Neuroimage https://doi.org/10.1016/j.neuroimage.2006.05.037 (2006).

Van Belle, G., De Graef, P., Verfaillie, K., Busigny, T. & Rossion, B. Whole not hole: Expert face recognition requires holistic perception. Neuropsychologia https://doi.org/10.1016/j.neuropsychologia.2010.04.034 (2010).

Quadflieg, S., Todorov, A., Laguesse, R. & Rossion, B. Normal face-based judgements of social characteristics despite severely impaired holistic face processing. Vis. cogn. 20 , 865–882 (2012).

McKone, E. Isolating the Special Component of Face Recognition: Peripheral Identification and a Mooney Face. J. Exp. Psychol. Learn. Mem. Cogn . https://doi.org/10.1037/0278-7393.30.1.181 (2004).

Sergent, J. An investigation into component and configural processes underlying face perception. Br. J. Psychol . https://doi.org/10.1111/j.2044-8295.1984.tb01895.x (1984).

Tanaka, J. W. & Farah, M. J. Parts and Wholes in Face Recognition. Q. J. Exp. Psychol. Sect. A https://doi.org/10.1080/14640749308401045 (1993).

Young, A. W., Hellawell, D. & Hay, D. C. Configurational information in face perception. Perception https://doi.org/10.1068/p160747n (2013).

Calder, A. J. & Young, A. W. Understanding the recognition of facial identity and facial expression. Nature Reviews Neuroscience https://doi.org/10.1038/nrn1724 (2005).

Todorov, A., Loehr, V. & Oosterhof, N. N. The obligatory nature of holistic processing of faces in social judgments. Perception https://doi.org/10.1068/p6501 (2010).

Junior, J. C. S. J. et al . First Impressions: A Survey on Computer Vision-Based Apparent Personality Trait Analysis. (2018).

Wang, Y. & Kosinski, M. Deep neural networks are more accurate than humans at detecting sexual orientation from facial images. J. Pers. Soc. Psychol. 114 , 246–257 (2018).

Qiu, L., Lu, J., Yang, S., Qu, W. & Zhu, T. What does your selfie say about you? Comput. Human Behav. 52 , 443–449 (2015).

Digman, J. M. Higher order factors of the Big Five. J.Pers.Soc.Psychol . https://doi.org/10.1037/0022-3514.73.6.1246 (1997).

Musek, J. A general factor of personality: Evidence for the Big One in the five-factor model. J. Res. Pers . https://doi.org/10.1016/j.jrp.2007.02.003 (2007).

DeYoung, C. G. Higher-order factors of the Big Five in a multi-informant sample. J. Pers. Soc. Psychol. 91 , 1138–1151 (2006).

Rushton, J. P. & Irwing, P. A General Factor of Personality (GFP) from two meta-analyses of the Big Five: Digman (1997) and Mount, Barrick, Scullen, and Rounds (2005). Pers. Individ. Dif. 45 , 679–683 (2008).

Wood, D., Gardner, M. H. & Harms, P. D. How functionalist and process approaches to behavior can explain trait covariation. Psychol. Rev. 122 , 84–111 (2015).

Dunlap, W. P. Generalizing the Common Language Effect Size indicator to bivariate normal correlations. Psych. Bull. 116 , 509–511 (1994).

Connolly, J. J., Kavanagh, E. J. & Viswesvaran, C. The convergent validity between self and observer ratings of personality: A meta-analytic review. Int. J. of Selection and Assessment. 15 , 110–117 (2007).

Harris, K. & Vazire, S. On friendship development and the Big Five personality traits. Soc. and Pers. Psychol. Compass. 10 , 647–667 (2016).

Weidmann, R., Schönbrodt, F. D., Ledermann, T. & Grob, A. Concurrent and longitudinal dyadic polynomial regression analyses of Big Five traits and relationship satisfaction: Does similarity matter? J. Res. in Personality. 70 , 6–15 (2017).

Cuperman, R. & Ickes, W. Big Five predictors of behavior and perceptions in initial dyadic interactions: Personality similarity helps extraverts and introverts, but hurts “disagreeables”. J. of Pers. and Soc. Psychol. 97 , 667–684 (2009).

Schmidt, F. L. & Hunter, J. E. The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings. Psychol. Bull. 124 , 262–274 (1998).

Brown, M. & Sacco, D. F. Unrestricted sociosexuality predicts preferences for extraverted male faces. Pers. Individ. Dif. 108 , 123–127 (2017).

Lukaszewski, A. W. & Roney, J. R. The origins of extraversion: joint effects of facultative calibration and genetic polymorphism. Pers. Soc. Psychol. Bull. 37 , 409–21 (2011).

Curran, P. G. Methods for the detection of carelessly invalid responses in survey data. J. Exp. Soc. Psychol. 66 , 4–19 (2016).

Khromov, A. B. The five-factor questionnaire of personality [Pjatifaktornyj oprosnik lichnosti]. In Rus. (Kurgan State University, 2000).

Trizano-Hermosilla, I. & Alvarado, J. M. Best alternatives to Cronbach’s alpha reliability in realistic conditions: Congeneric and asymmetrical measurements. Front. Psychol . https://doi.org/10.3389/fpsyg.2016.00769 (2016).

Liu, Z., Luo, P., Wang, X. & Tang, X. Deep Learning Face Attributes in the Wild. in 2015 IEEE International Conference on Computer Vision (ICCV) 3730–3738 https://doi.org/10.1109/ICCV.2015.425 (IEEE, 2015).

He, K., Zhang, X., Ren, S. & Sun, J. Deep Residual Learning for Image Recognition. in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 770–778 https://doi.org/10.1109/CVPR.2016.90 (IEEE, 2016).

Download references

Acknowledgements

We appreciate the assistance of Oleg Poznyakov, who organized the data collection, and we are grateful to the anonymous peer reviewers for their detailed and insightful feedback.

Contributions

A.K., E.O., D.D. and A.N. designed the study. K.S. and A.K. designed the ML algorithms and trained the ANN. A.N. contributed to the data collection. A.K., K.S. and D.D. contributed to data pre-processing. E.O., D.D. and A.K. analysed the data, contributed to the main body of the manuscript, and revised the text. A.K. prepared Figs. 1 and 2. All the authors contributed to the final version of the manuscript.

Corresponding authors

Correspondence to Alexander Kachur or Evgeny Osin .

Ethics declarations

Competing interests.

A.K., K.S. and A.N. were employed by the company that provided the datasets for the research. E.O. and D.D. declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary information., rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Kachur, A., Osin, E., Davydov, D. et al. Assessing the Big Five personality traits using real-life static facial images. Sci Rep 10 , 8487 (2020). https://doi.org/10.1038/s41598-020-65358-6

Download citation

Received : 12 April 2019

Accepted : 28 April 2020

Published : 22 May 2020

DOI : https://doi.org/10.1038/s41598-020-65358-6

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

Seeing the darkness: identifying the dark triad from emotionally neutral faces.

• Danielle Haroun
• Yaarit Amram
• Joseph Glicksohn

Current Psychology (2024)

A Richer Vocabulary of Chinese Personality Traits: Leveraging Word Embedding Technology for Mining Personality Descriptors

• Yigang Ding
• Feijun Zheng

Journal of Psycholinguistic Research (2024)

Unravelling the many facets of human cooperation in an experimental study

• Victoria V. Rostovtseva
• Mikael Puurtinen
• Franz J. Weissing

Scientific Reports (2023)

Using deep learning to predict ideology from facial photographs: expressions, beauty, and extra-facial information

• Stig Hebbelstrup Rye Rasmussen
• Steven G. Ludeke
• Robert Klemmensen

Facial Expression of TIPI Personality and CHMP-Tri Psychopathy Traits in Chimpanzees (Pan troglodytes)

• Lindsay Murray
• Jade Goddard
• David Gordon

Human Nature (2023)

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

• school Campus Bookshelves
• menu_book Bookshelves
• perm_media Learning Objects
• login Login
• how_to_reg Request Instructor Account
• hub Instructor Commons
• Download Page (PDF)
• Download Full Book (PDF)
• Periodic Table
• Physics Constants
• Scientific Calculator
• Reference & Cite
• Tools expand_more
• Readability

selected template will load here

This action is not available.

1.4: Methods of Studying Personality

• Last updated
• Save as PDF
• Page ID 12176

• Mark D. Kelland
• Lansing Commnunity College via OpenStax CNX

In all types of research, we need to consider two closely related concepts: hypothesis vs. theory. An hypothesis can loosely be defined as an educated guess about some relationship or circumstance that we have observed, and the purpose of the hypothesis is to explain what we have experienced and to provide a starting point for further research. When a set of observations seems to come together, especially as the result of testing our hypotheses, we might then propose a theory to bring those observations together. However, a theory is not necessarily our end point, since the theory itself may generate new hypotheses and more research. In this way, all scientific endeavors continue to develop, expand, clarify, change, whatever the case may be, over time. As a result, we have many different personality theories, since different theorists have viewed the human condition differently, and they have also used different techniques to study personality.

A variety of methods have been used to study personality. Much of the early research was based on clinical observations, which were not done according to strict experimental methods. Today, ethical restrictions on the types of research we can conduct with people limit our ability to re-evaluate many of those classic studies. So we are left with a field that is rich in theory, but somewhat poor in the validation of those theories. Of course some personality theorists have approached personality in a more scientific manner, or at least they have tried, but that has limited the questions they have been able to ask. Since a detailed analysis of experimental psychology and research design is beyond the scope of this textbook, we will only cover this topic briefly (though it may come up again within individual chapters).

Case Studies

Many of the best-known personality theorists relied on case studies to develop their theories. Indeed, it was after seeing a number of patients with seemingly impossible neurological complaints that Freud began to seek an explanation of psychological disorders. Basically, the case study approach relies on a detailed analysis of interesting and unique individuals. Because these individuals are unique, the primary criticism of the case study approach is that its results may not generalize to other people. Of greater concern, is the possibility that early theorists chose to report only those cases that seemed to support their theories, or perhaps they only recognized those elements of a patient’s personality that fit their theory? Another problem, as mentioned above, is that two different theorists might view the same cases in very different ways. For example, since Carl Rogers worked initially with children, he found it difficult to accept Freud’s suggestions that even children were motivated primarily by sexual and aggressive urges. Consequently, Rogers sought a more positive view of personality development, which led to the establishment of the humanistic perspective. Thus, the case study approach can lead to very different conclusions depending on one’s own perspective while conducting research. In other words, it can easily be more subjective than objective, and psychologists who focus on our field as a scientific discipline always strive for more objective research.

Correlational Designs

When conducting correlational research psychologists examine the relationships that exist between variables, but they do not control those variables. The measure that is typically used is the correlation coefficient , which can range from –1.0 to 0.0 to +1.0. A value close to zero suggests that there is no relationship between the variables, whereas a value closer to –1.0 or +1.0 suggests a strong relationship, with the direction of the relationship determining whether the value is positive or negative. It is important to remember that the strength of the correlation is determined by how far the correlation coefficient is from zero, not whether it is positive or negative. For example, we would most likely find a positive correlation between the number of hours you study for a test and the number of correct answers you get (i.e., the more you study, the more questions you get right on the test). On the other hand, the exact same data will give us a negative correlation if we compare the number of hours you study to the number of questions you get wrong (i.e., the more you study, they fewer questions you get wrong). So the way in which you ask the question can determine whether you have a positive or negative correlation, but it should not affect the strength of the relationship.

Since the investigator does not control the variables in correlational research, it is not possible to determine whether or not one variable causes the relationship. In the example used above, it certainly seems that studying more would lead to getting a better grade on a test. But consider another example: can money buy happiness? There is some evidence that wealthy people are happier than the average person, and that people in wealthy countries are happier than those in poorer countries. But does the money affect happiness? Certainly a million dollars in cash wouldn’t help much if you were stranded on a desert island, so what can it do for you at home? People with money can live in nicer, safer communities, they have access to better health care (so they may feel better physically), they may have more time to spend with their family and friends, and so in many ways their lives might be different. We can also look at the correlation the other way around; maybe happy people get more money. If you ran a company, and were going to hire or promote someone, wouldn’t you want to find someone who is friendly and outgoing? Wouldn’t you look for someone who other people will enjoy working with? So, maybe happy people do find it easier to be successful financially. Either way, we simply can’t be sure about which variable influences the other, or even if they influence each other at all. In order to do that, we must pursue experimental research.

Figure \(\PageIndex{1}\)

In these figures, adapted from research conducted by the author (Kelland et al., 1989), we see two correlations reported in an actual study. In the figure on the left, we can see a significant positive correlation between the firing rate of dopamine neurons in the rat brain and the dose of the drug quinpirole needed to inhibit those cells. In the figure on the right, we can see that the correlation is eliminated (the dose of quinpirole needed is not related to the firing rate of the cell) following administration of the drug MDMA (more commonly known as Ecstasy!).

Experimental and Quasi-Experimental Designs

The experimental design is usually preferred within psychology, as with any other science. The goal is to control every aspect of the experiment and then manipulate a single variable, thus allowing us to attribute the results to that single manipulation. As a result, experiments allow us to make cause-and-effect statements about the relationships between the variables.

A simple experiment begins with defining the independent variable , the factor that will be manipulated, and the dependent variable , the factor that will be measured. Ideally, we then select our subjects in a random fashion, and assign them randomly to a control group and an experimental group . The experimental group is then exposed to the independent variable, whereas the control group is not. If we have successfully controlled all other variables through random selection of subjects (i.e., all subjects in a specified population have an equal chance of being selected for the study) and random assignment to the control and experimental groups (so that hopefully each group has an equal representation of gender, races, age, intelligence, personal habits, etc.), we should see a difference in the dependent variable that was caused by the independent variable.

Unlike the natural sciences, however, we can seldom control human behavior in the precise ways that true experimental designs require. For example, if we want to study the effects of prenatal exposure to cocaine on personality development, we certainly cannot ask pregnant women to use cocaine. Unfortunately, there are pregnant women who abuse cocaine and other illegal drugs. Therefore, we can try to identify those women, and subsequently study the development of their children. Since a variety of other factors led these women to abuse illegal drugs, we lose the control that is desired in an experiment. Such studies are called quasi-experimental, because they are set up as if we did an experiment, and can be analyzed in similar ways. The quasi-experimental approach has many applications, and can provide valuable information not available otherwise, so long as the investigators keep in mind the limitations of the technique (for the classic discussion of this design see Campbell & Stanley, 1963).

Cross-Cultural Approaches to the Study of Personality

Cross-cultural approaches to studying personality do not really represent a different type of research, but rather an approach to research that does not assume all people are influenced equally by the same factors. More importantly, cross-cultural psychologists recognize that seemingly common factors may, in reality, be quite different when viewed by people of very different cultures. The most obvious problem that arises when considering these issues is the potential difference between cross-cultural and multicultural research. Cross-cultural research is based on a comparison of cultures; two well-known categorizations are Eastern vs. Western perspectives and the somewhat related topic of individualistic vs. collectivistic cultures. However, a multicultural approach tells us that we must consider the true complexity of the human race. What is “Eastern,” is it Asia, China, Japan, does it include India, and what about Muslim groups of people? Should Buddhism be viewed as an Eastern perspective or a religious perspective? This book will address a variety of spiritual paths toward positive psychological development, but none of the associated religions are indigenous to Africa, so will our discussions be complete? The list goes on and on, because there are so many different cultures in the world. And finally, is it practical to really try coming up with a theory of personality that can encompass all the different groups of people throughout the world? Only by pursuing an understanding of different cultures can psychology truly be considered a global science, and that pursuit has only just begun. Since we have a long way to go, the future is ripe for new students to pursue careers in psychology and the study of personality.

Discussion Question: Do you consider psychology to be a science? Has psychology successfully applied the scientific method to the study of mind and behavior, particularly the study of personality and personality development?

• Free Case Studies
• Business Essays

Write My Case Study

Buy Case Study

Case Study Help

• Case Study For Sale
• Case Study Service
• Hire Writer

Case Study on Personality Traits

Case study on personality traits:.

Personality traits are the set of the qualities and traits of human character which define a certain type of a human being judging from his psychics. Today the most popular model of the definition of the personality traits is the Big Five personality traits which concentrate on the certain core traits which define the psychological type of the individual.

The factors which influence the results of the theory of the personality traits are: extraversion, openness, neuroticism, agreeableness and conscientiousness. All these traits are independent and according to their level in the human being it is possible to define the type of the individual. The first factor, called the openness to experience is characterised with the high interest in the human being to discover new things, appreciate art, adventure and brainstorm various unique and creative ideas.This trait is also associated the intellectual abilities of the person and openness of her horizons.Conscientiousness is the ability of self-control and self-disciplining.

We Will Write a Custom Case Study Specifically For You For Only $13.90/page!

The person is able to organize her time and activity logically and reasonably and fulfil the job on time. Extraversion is the characteristic feature of the communicative people, who are always the heart of the company.Agreeableness is the will to coexist and cooperate with the others and avoidance of any conflicts.Neuroticism is the trait associated with anger, emotional breakdowns and unstable psychology, impulsive behaviour, etc. In fact, the theory of the five personality traits is strictly criticised by the experts, because it can not be applied to everyone.

For example, children are characterized with more than five traits, as there are at least two additional ones: irritability and activeness.The value of the discovery of the individual personality traits is very high, because on the basis of these traits one can find the appropriate job and build the career which suits to the one’s character.The success of personality traits case study depends on the ability of the student to analyze the direct problem correctly. One should focus on the collection of facts about the case and learn about the cause and effect of the problem and think about the best solutions to the problem form the professional point of view.If one has troubles with case study writing, he can apply for the high-quality help of the Internet and read a free example case study on personality traits improving his knowledge about the appropriate manner of paper writing. The student can look through a good free sample case study on personality traits and discover the standards and rules of formatting and composition of the paper on the direct models of writing prepared by the experienced writers online.

Related posts:

• Individual’s Traits
• Case Study – Personality and the Virgin Group
• Personality Case Study
• Case Study on Personality Disorders
• Case Study on Unique Personality
• Case Study on Personality Types
• Case Study on Personality Development

Quick Links

Privacy Policy

Terms and Conditions

Testimonials

Our Services

Case Study Writing Service

Case Studies For Sale

Our Company

Welcome to the world of case studies that can bring you high grades! Here, at ACaseStudy.com, we deliver professionally written papers, and the best grades for you from your professors are guaranteed!

[email protected] 804-506-0782 350 5th Ave, New York, NY 10118, USA

Acasestudy.com © 2007-2019 All rights reserved.

Hi! I'm Anna

Would you like to get a custom case study? How about receiving a customized one?

Haven't Found The Case Study You Want?

For Only $13.90/page

• Research article
• Open access
• Published: 05 May 2020

Personality traits, emotional intelligence and decision-making styles in Lebanese universities medical students

• Radwan El Othman 1 ,
• Rola El Othman 2 ,
• Rabih Hallit 1 , 3 , 4   na1 ,
• Sahar Obeid 5 , 6 , 7   na1 &
• Souheil Hallit 1 , 5 , 7   na1  

BMC Psychology volume  8 , Article number:  46 ( 2020 ) Cite this article

55k Accesses

30 Citations

16 Altmetric

Metrics details

This study aims to assess the impact of personality traits on emotional intelligence (EI) and decision-making among medical students in Lebanese Universities and to evaluate the potential mediating role-played by emotional intelligence between personality traits and decision-making styles in this population.

This cross-sectional study was conducted between June and December 2019 on 296 general medicine students.

Higher extroversion was associated with lower rational decision-making style, whereas higher agreeableness and conscientiousness were significantly associated with a higher rational decision-making style. More extroversion and openness to experience were significantly associated with a higher intuitive style, whereas higher agreeableness and conscientiousness were significantly associated with lower intuitive style. More agreeableness and conscientiousness were significantly associated with a higher dependent decision-making style, whereas more openness to experience was significantly associated with less dependent decision-making style. More agreeableness, conscientiousness, and neuroticism were significantly associated with less spontaneous decision-making style. None of the personality traits was significantly associated with the avoidant decision-making style. Emotional intelligence seemed to fully mediate the association between conscientiousness and intuitive decision-making style by 38% and partially mediate the association between extroversion and openness to experience with intuitive decision-making style by 49.82 and 57.93% respectively.

Our study suggests an association between personality traits and decision-making styles. The results suggest that EI showed a significant positive effect on intuitive decision-making style and a negative effect on avoidant and dependent decision-making styles. Additionally, our study underlined the role of emotional intelligence as a mediator factor between personality traits (namely conscientiousness, openness, and extroversion) and decision-making styles.

Peer Review reports

Decision-making is a central part of daily interactions; it was defined by Scott and Bruce in 1995 as «the learned habitual response pattern exhibited by an individual when confronted with a decision situation. It is not a personality trait, but a habit-based propensity to react in a certain way in a specific decision context» [ 1 ]. Understanding how people make decisions within the moral domain is of great importance theoretically and practically. Its theoretical value is related to the importance of understanding the moral mind to further deepen our knowledge on how the mind works, thus understanding the role of moral considerations in our cognitive life. Practically, this understanding is important because we are highly influenced by the moral decisions of people around us [ 2 ]. According to Scott and Bruce (1995), there are five distinct decision-making styles (dependent, avoidant, spontaneous, rational, intuitive) [ 1 ] and each individuals’ decision-making style has traits from these different styles with one dominant style [ 3 ].

The dependent decision-making style can be regarded as requiring support, advice, and guidance from others when making decisions. Avoidant style is characterized by its tendency to procrastinate and postpone decisions if possible. On the other hand, spontaneous decision-making style is hallmarked by making snap and impulsive decisions as a way to quickly bypass the decision-making process. In other words, spontaneous decision-makers are characterized by the feeling of immediacy favoring to bypass the decision-making process rapidly without employing much effort in considering their options analytically or relying on their instinct. Rational decision-making style is characterized by the use of a structured rational approach to analyze information and options to make decision [ 1 ]. In contrast, intuitive style is highly dependent upon premonitions, instinct, and feelings when it comes to making decisions driving focus toward the flow of information rather than systematic procession and analysis of information, thus relying on hunches and gut feelings. Several studies have evaluated the factors that would influence an individual’s intuition and judgment. Rand et al. (2016) discussed the social heuristics theory and showed that women and not men tend to internalize altruism _ the selfless concern for the well-being of others_ in their intuition and thus in their intuitive decision-making process [ 4 ]. Additionally, intuitive behavior honesty is influenced by the degree of social relationships with individuals affected by the outcome of our decision: when dishonesty harms abstract others, intuition promotion causes more dishonesty. On the contrary, when dishonesty harms concrete others, intuition promotion has no significant effect on dishonesty. Hence, the intuitive appeal of pro-sociality may cancel out the intuitive selfish appeal of dishonesty [ 5 ]. Moreover, the decision-making process and styles have been largely evaluated in previous literature. Greene et al. (2008) and Rand (2016) showed that utilitarian moral judgments aiming to minimize cost and maximize benefits across concerned individuals are driven by controlled cognitive process (i.e. rational); whereas, deontological moral judgments _where rights and duties supersede utilitarian considerations_ are dictated by an automatic emotional response (e.g. spontaneous decision-making) [ 6 , 7 ]. Trémolière et al. (2012) found that mortality salience makes people less utilitarian [ 8 ].

Another valuable element influencing our relationships and career success [ 9 ] is emotional intelligence (EI) a cardinal factor to positive patient experience in the medical field [ 10 ]. EI was defined by Goleman as «the capacity of recognizing our feelings and those of others, for motivating ourselves, and for managing emotions both in us and in our relationships» [ 11 ]. Hence, an important part of our success in life nowadays is dependent on our ability to develop and preserve social relationships, depict ourselves positively, and control the way people descry us rather than our cognitive abilities and traditional intelligence measured by IQ tests [ 12 ]. In other words, emotional intelligence is a subtype of social intelligence involving observation and analyses of emotions to guide thoughts and actions. Communication is a pillar of modern medicine; thus, emotional intelligence should be a cornerstone in the education and evaluation of medical students’ communication and interpersonal skills.

An important predictor of EI is personality [ 13 ] defined as individual differences in characteristic patterns of thinking, feeling and behaving [ 14 ]. An important property of personality traits is being stable across time [ 15 ] and situations [ 16 ], which makes it characteristic of each individual. One of the most widely used assessment tools for personality traits is the Five-Factor model referring to «extroversion, openness to experience, agreeableness, conscientiousness, neuroticism». In fact, personality traits have an important impact on individuals’ life, students’ academic performance [ 17 ] and decision-making [ 18 ].

Extroversion is characterized by higher levels of self-confidence, positive emotions, enthusiasm, energy, excitement seeking, and social interactions. Openness to experience individuals are creative, imaginative, intellectually curious, impulsive, and original, open to new experiences and ideas [ 19 ]. Agreeableness is characterized by cooperation, morality, sympathy, low self-confidence, high levels of trust in others, and tend to be happy and satisfied because of their close interrelationships [ 19 ]. Conscientiousness is characterized by competence, hard work, self-discipline, organization, strive for achievement and goal orientation [ 20 ] with a high level of deliberation making conscientious individuals capable of analyzing the pros and cons of a given situation [ 21 ]. Neuroticism is characterized by anxiety, anger, insecurity, impulsiveness, self-consciousness,and vulnerability [ 20 ]. High neurotic individuals have higher levels of negative affect, are easily irritated, and more likely to turn to inappropriate coping responses, such as interpersonal hostility [ 22 ].

Multiple studies have evaluated the impact of personality traits on decision-making styles. Narooi and Karazee (2015) studied personality traits, attitude to life, and decision-making styles among university students in Iran [ 23 ]. They deduced the presence of a strong relationship between personality traits and decision-making styles [ 23 ]. Riaz and Batool (2012) evaluated the relationship between personality traits and decision-making among a group of university students (Fig. 1 ). They concluded that «15.4 to 28.1% variance in decision-making styles is related to personality traits» [ 24 ]. Similarly, Bajwa et al. (2016) studied the relationship between personality traits and decision-making among students. They concluded that conscientiousness personality trait is associated with rational decision-making style [ 25 ]. Bayram and Aydemir (2017) studied the relationship between personality traits and decision-making styles among a group of university students in Turkey [ 26 ]. Their work yielded to multiple conclusion namely a significant association between rational and intuitive decision-making styles and extroversion, openness to experience, conscientiousness, and agreeableness personality traits [ 26 ]. The dependent decision-making style had a positive relation with both neuroticism and agreeableness. The spontaneous style had a positive relation with neuroticism and significant negative relation with agreeableness and conscientiousness. Extroversion personality traits had a positive effect on spontaneous style. Agreeableness personality had a positive effect on the intuitive and dependent decision-making style. Conscientiousness personality had a negative effect on avoidant and spontaneous decision-making style and a positive effect on rational style. Neuroticism trait had a positive effect on intuitive, dependent and spontaneous decision-making style. Openness to experience personality traits had a positive effect on rational style [ 26 ].

Schematic representation of the effect of the big five personality types on decision-making styles [ 24 ]

Furthermore, several studies have evaluated the relationship between personality traits and emotional intelligence. Dawda and Hart (2000) found a significant relationship between emotional intelligence and all Big Five personality traits [ 27 ]. Day and al. (2005) found a high correlation between emotional intelligence and extroversion and conscientiousness personality traits [ 28 ]. A study realized by Avsec and al. (2009) revealed that emotional intelligence is a predictor of the Big Five personality traits [ 29 ]. Alghamdi and al. (2017) investigated the predictive role of EI on personality traits among university advisors in Saudi Arabia. They found that extroversion, agreeableness, and openness to experience emerged as significant predictors of EI. The study also concluded that conscientiousness and neuroticism have no impact on EI [ 13 ].

Nonetheless, decision-making is highly influenced by emotion making it an emotional process. The degree of emotional involvement in a decision may influence our choices [ 30 ] especially that emotions serve as a motivational process for decision-making [ 31 ]. For instance, patients suffering from bilateral lesions of the ventromedial prefrontal cortex (interfering with normal processing of emotional signals) develop severe impairments in personal and social decision-making despite normal cognitive capabilities (intelligence and creativity); highlighting the guidance role played by emotions in the decision-making process [ 32 ]. Furthermore, EI affects attention, memory, and cognitive intelligence [ 33 , 34 ] with higher levels of EI indicating a more efficient decision-making [ 33 ]. In one study, Khan and al. concluded that EI had a significant positive effect on rational and intuitive decision-making styles and negative effect on dependent and spontaneous decision-making styles among a group of university students in Pakistan [ 35 ].

This study aims to assess the impact of personality traits on both emotional intelligence and decision-making among medical students in Lebanese Universities and to test the potential mediating role played by emotional intelligence between personality and decision-making styles in this yet unstudied population to our knowledge. The goal of the present research is to evaluate the usefulness of implementing such tools in the selection process of future physicians. It also aimed at assessing the need for developing targeted measures, aiming to ameliorate the psychosocial profile of Lebanese medical students, in order to have a positive impact on patients experience and on medical students’ career success.

Study design

This cross-sectional study was conducted between June and December 2019. A total of 296 participants were recruited from all the 7 faculties of medicine in Lebanon. Data collection was done through filling an anonymous online or paper-based self-administered English questionnaire upon the participant choice. All participants were aware of the purpose of the study, the quality of data collected and gave prior informed consent. Participation in this study was voluntary and no incentive was given to the participants. All participants were General medicine students registered as full-time students in one of the 7 national schools of medicine aged 18 years and above regardless of their nationality. The questionnaire was only available in English since the 7 faculties of medicine in Lebanon require a minimum level of good English knowledge in their admission criteria. A pilot test was conducted on 15 students to check the clarity of the questionnaire. To note that these 15 questionnaires related data was not entered in the final database. The methodology used in similar to the one used in a previous paper [ 36 ]

Questionnaire and variables

The questionnaire assessed demographic and health characteristics of participants, including age, gender, region, university, current year in medical education, academic performance (assessed using the current cumulative GPA), parental highest level of education, and health questions regarding the personal history of somatic, and psychiatric illnesses.

The personality traits were evaluated using the Big Five Personality Test, a commonly used test in clinical psychology. Since its creation by John, Donahue, and Kentle (1991) [ 37 ], the five factor model was widely used in different countries including Lebanon [ 38 ]; it describes personality in terms of five board factors: extroversion, openness to experience, agreeableness, conscientiousness and neuroticism according to an individual’s response to a set of 50 questions on a 5-point Likert scale: 1 (disagree) to 5 (agree). A score for each personality trait is calculated in order to determine the major trait(s) in an individual personality (i.e. the trait with the highest score). The Cronbach’s alpha values were as follows: total scale (0.885), extroversion (0.880), openness to experience (0.718), agreeableness (0.668), conscientiousness (0.640), and neuroticism (0.761).

Emotional intelligence was assessed using the Quick Emotional Intelligence Self-Assessment scale [ 38 ]. The scale is divided into four domains: «emotional alertness, emotional control, social-emotional awareness, and relationship management». Each domain is composed of 10 questions, with answers measured on a 5-point Likert scale: 0 (never) to 4 (always). Higher scores indicate higher emotional intelligence [ 38 ] (α Cronbach  = 0.950).

The decision-making style was assessed using the Scott and Bruce General Decision-Making Style Inventory commonly used worldwide since its creation in 1995 for this purpose [ 1 ]. The inventory consists of 25 questions answered according to a 5-point Likert scale: 1 (strongly disagree) to 5 (strongly agree) intended to evaluate the importance of each decision-making style among the 5 styles proposed by Scott and Bruce: dependent, avoidant, spontaneous, rational and intuitive. The score for each decision-making style is computed in order to determine the major style for each responder (α Cronbach total scale  = 0.744; α Cronbach dependent style  = 0.925; α Cronbach avoidant style  = 0.927; α Cronbach spontaneous style  = 0.935; α Cronbach rational style  = 0.933; α Cronbach intuitive style  = 0.919).

Sample size calculation

The Epi info program (Centers for Disease Control and Prevention (CDC), Epi Info™) was employed for the calculation of the minimal sample size needed for our study, with an acceptable margin of error of 5% and an expected variance of decision-making styles that is related to personality types estimated by 15.4 to 28.1% [ 24 ] for 5531 general medicine student in Lebanon [ 39 ]. The result showed that 294 participants are needed.

Statistical analysis

Statistical Package for Social Science (SPSS) version 23 was used for the statistical analysis. The Student t-test and ANOVA test were used to assess the association between each continuous independent variable (decision-making style scores) and dichotomous and categorical variables respectively. The Pearson correlation test was used to evaluate the association between two continuous variables. Reliability of all scales and subscales was assessed using Cronbach’s alpha.

Mediation analysis

The PROCESS SPSS Macro version 3.4, model four [ 40 ] was used to calculate five pathways (Fig.  2 ). Pathway A determined the regression coefficient for the effect of each personality trait on emotional intelligence, Pathway B examined the association between EI and each decision-making style, independent of the personality trait, and Pathway C′ estimated the total and direct effect of each personality trait on each decision-making style respectively. Pathway AB calculated the indirect intervention effects. To test the significance of the indirect effect, the macro generated bias-corrected bootstrapped 95% confidence intervals (CI) [ 40 ]. A significant mediation was determined if the CI around the indirect effect did not include zero [ 40 ]. The covariates that were included in the mediation model were those that showed significant associations with each decision-making style in the bivariate analysis.

Summary of the pathways followed during the mediation analysis

Sociodemographic and other characteristics of the participants

The mean age of the participants was 22.41 ± 2.20 years, with 166 (56.1%) females. The mean scores of the scales used were as follows: emotional intelligence (108.27 ± 24.90), decision-making: rationale style (13.07 ± 3.17), intuitive style (16.04 ± 3.94), dependent style (15.53 ± 4.26), spontaneous style (13.52 ± 4.22), avoidant style (12.44 ± 4.11), personality trait: extroversion (21.18 ± 8.96), agreeableness (28.01 ± 7.48), conscientiousness (25.20 ± 7.06), neuroticism (19.29 ± 8.94) and openness (27.36 ± 7.81). Other characteristics of the participants are summarized in Table  1 .

Bivariate analysis

Males vs females, having chronic pain compared to not, originating from South Lebanon compared to other governorates, having an intermediate income compared to other categories, those whose mothers had a primary/complementary education level and those whose fathers had an undergraduate diploma vs all other categories had higher mean rationale style scores. Those fathers, who had a postgraduate diploma, had a higher mean intuitive style scores compared to all other education levels. Those who have chronic pain compared to not and living in South Lebanon compared to other governorates had higher dependent style scores. Those who have chronic pain compared to not, those who take medications for a mental illness whose mothers had a primary/complementary education level vs all other categories and those whose fathers had a postgraduate diploma vs all other categories had higher spontaneous style scores (Table  2 ).

Higher agreeableness and conscientiousness scores were significantly associated with higher rational style scores, whereas higher extroversion and neuroticism scores were significantly associated with lower rational style scores. Higher extroversion, openness and emotional intelligence scores were significantly associated with higher intuitive scores, whereas higher agreeableness, conscientiousness and neuroticism scores were significantly associated with lower intuitive style scores. Higher agreeableness and conscientiousness were associated with higher dependent style scores, whereas higher openness and emotional intelligence scores were significantly associated with lower dependent styles scores. Higher agreeableness, conscientiousness, neuroticism, and emotional intelligence scores were significantly associated with lower spontaneous style scores. Finally, higher extroversion, neuroticism and emotional intelligence scores were significantly associated with lower avoidant style scores (Table  3 ).

Post hoc analysis: rationale style: governorate (Beirut vs Mount Lebanon p  = 0.022; Beirut vs South p  < 0.001; Mount Lebanon vs South p  = 0.004; South vs North p  = 0.001; South vs Bekaa p  = 0.047); monthly income (intermediate vs high p  = 0.024); mother’s educational level (high school vs undergraduate diploma p  = 0.048); father’s education level (undergraduate vs graduate diploma p = 0.01).

Intuitive style: father’s education level (high school vs postgraduate diploma p  = 0.046).

Dependent style: governorate (Beirut vs Mount Lebanon p  = 0.006; Beirut vs South p  = 0.003);

Avoidant style: mother’s educational level (high school vs undergraduate diploma p  = 0.008; undergraduate vs graduate diploma p  = 0.004; undergraduate vs postgraduate diploma p  = 0.001).

Mediation analysis was run to check if emotional intelligence would have a mediating role between each personality trait and each decision-making style, after adjusting overall covariates that showed a p  < 0.05 with each decision-making style in the bivariate analysis.

Rational decision-making style (Table  4 , model 1)

Higher extroversion was significantly associated with higher EI, b = 0.91, 95% BCa CI [0.60, 1.23], t = 5.71, p  < 0.001 (R2 = 0.31). Higher extroversion was significantly associated with lower rational decision-making even with EI in the model, b = − 0.06, 95% BCa CI [− 0.11, − 0.02], t = − 2.81, p  = 0.003; EI was not significantly associated with rational decision-making, b = 0.02, 95% BCa CI [− 0.0003, 0.03], t = 1.93, p  = 0.054 (R2 = 0.29). When EI was not in the model, higher extroversion was significantly associated with lower rational decision-making, b = − 0.05, 95% BCa CI [− 0.09, − 0.01], t = − 2.43, p  = 0.015 (R2 = 0.28). The mediating effect of EI was 21.22%.

Higher agreeableness was not significantly associated with EI, b = − 0.05, 95% BCa CI [− 0.40, 0.31], t = − 0.26, p  = 0.798 (R2 = 0.31). Higher agreeableness was significantly associated with higher rational decision-making style even with EI in the model, b = 0.07, 95% BCa CI [0.02, 0.11], t = 2.89, p  = 0.004; EI was not significantly associated with the rational decision-making, b = 0.01, 95% BCa CI [− 0.0003, 0.03], t = 1.92, p  = 0.055 (R2 = 0.29). When EI was not in the model, higher agreeableness was significantly associated with higher rational decision-making, b = 0.07, 95% BCa CI [0.02, 0.11], t = 2.86, p = 0.004 (R2 = 0.28). The mediating effect of EI was 0.10%.

Higher conscientiousness was significantly associated with higher EI, b = 1.40, 95% BCa CI [1.04, 1.76], t = 7.62, p  < 0.001 (R2 = 0.31). Higher conscientiousness was significantly associated with the rational decision-making style even with EI in the model, b = 0.09, 95% BCa CI [0.04, 0.14], t = 3.55, p < 0.001; EI was not significantly associated with the rational decision-making, b = 0.01, 95% BCa CI [− 0.0003, 0.03], t = 1.93, p  = 0.055 (R2 = 0.29). When EI was not in the model, conscientiousness was significantly associated with the rational decision-making style, b = 0.11, 95% BCa CI [0.07, 0.16], t = 4.76, p < 0.001 (R2 = 0.28). The mediating effect of EI was 22.47%.

Higher neuroticism was significantly associated with lower EI, b = − 0.50, 95% BCa CI [− 0.80, − 0.20], t = − 3.26, p  = 0.001 (R2 = 0.31). Neuroticism was not significantly associated with rational decision-making style with EI in the model, b = − 0.09, 95% BCa CI [− 0.05, 0.03], t = − 0.43, p  = 0.668; EI was not significantly associated with rational decision-making, b = 0.01, 95% BCa CI [− 0.0003, 0.03], t = 1.93, p  = 0.055 (R2 = 0.29). When EI was not in the model, neuroticism was not significantly associated with the rational decision-making style, b = − 0.02, 95% BCa CI [− 0.06, 0.02], t = − 0.81, p  = 0.418 (R2 = 0.28).

No calculations were done for the openness to experience personality traits since it was not significantly associated with the rational decision-making style in the bivariate analysis.

Intuitive decision-making style (Table 4 , model 2)

Higher extroversion was significantly associated with higher EI, b = 0.86, 95% BCa CI [0.59, 1.13], t = 6.28, p  < 0.001 (R2 = 0.41). Higher extroversion was significantly associated with higher intuitive decision-making even with EI in the model, b = 0.05, 95% BCa CI [0.002, 0.11], t = 2.03, p  = 0.043; EI was significantly associated with intuitive decision-making style, b = 0.03, 95% BCa CI [0.01, 0.05], t = 2.91, p  = 0.003 (R2 = 0.21). When EI was not in the model, higher extroversion was significantly associated with higher intuitive decision-making, b = 0.08, 95% BCa CI [0.03, 0.13], t = 3.21, p  = 0.001 (R2 = 0.18). The mediating effect of EI was 49.82%.

Higher agreeableness was significantly associated with EI, b = − 0.33, 95% BCa CI [− 0.65, − 0.02], t = − 2.06, p  = 0.039 (R2 = 0.41). Higher agreeableness was significantly associated with lower intuitive decision-making style even with EI in the model, b = − 0.15, 95% BCa CI [− 0.21, − 0.10], t = − 5.16, p  < 0.001; higher EI was significantly associated with higher intuitive decision-making, b = 0.03, 95% BCa CI [0.01, 0.05], t = 2.91, p  = 0.004 (R2 = 0.21). When EI was not in the model, higher agreeableness was significantly associated with lower intuitive decision-making, b = − 0.17, 95% BCa CI [− 0.22, − 0.11], t = − 5.48, p < 0.001 (R2 = 0.18). The mediating effect of EI was 6.80%.

Higher conscientiousness was significantly associated with higher EI, b = 1.18, 95% BCa CI [0.85, 1.51], t = 7.06, p < 0.001 (R2 = 0.41). Higher conscientiousness was significantly associated with lower intuitive decision-making style even with EI in the model, b = − 0.10, 95% BCa CI [− 0.16, − 0.03], t = − 2.95, p  = 0.003; higher EI was also significantly associated with higher intuitive decision-making, b = 0.03, 95% BCa CI [0.01, 0.05], t = 2.91, p  = 0.004 (R2 = 0.21). When EI was not in the model, conscientiousness was not significantly associated with the intuitive decision-making style, b = − 0.06, 95% BCa CI [− 0.12, 0.0004], t = − 1.95, p  = 0.051 (R2 = 0.18). The mediating effect of EI was 38%.

Higher openness to experience was significantly associated with higher EI, b = 1.44, 95% BCa CI [1.13, 1.75], t = 9.11, p  < 0.001 (R2 = 0.41). Higher openness to experience was significantly associated with higher intuitive decision-making style with EI in the model, b = 0.08, 95% BCa CI [0.01, 0.14], t = 2.38, p  = 0.017; higher EI was also significantly associated with intuitive decision-making style, b = 0.03, 95% BCa CI [0.01, 0.05], t = 2.91, p  = 0.004 (R2 = 0.21). When EI was not in the model, higher openness to experience was significantly associated with intuitive decision-making style, b = 0.12, 95% BCa CI [0.06, 0.18], t = 4.22, p  < 0.001 (R2 = 0.18). The mediating effect of EI was 57.93%.

No calculations were done for neuroticism personality trait since it was not significantly associated with the intuitive decision-making style in the bivariate analysis.

Dependent decision-making style (Table 4 , model 3)

Agreeableness was not significantly associated with EI, b = − 0.15, 95% BCa CI [− 0.49, 0.17], t = − 0.94, p  = 0.345 (R2 = 0.32). Higher agreeableness was significantly associated with higher dependent decision-making style even with EI in the model, b = 0.29, 95% BCa CI [0.23, 0.34], t = 10.51, p  < 0.001; higher EI was significantly associated with lower dependent decision-making, b = − 0.04, 95% BCa CI [− 0.06, − 0.02], t = − 4.50, p  < 0.001 (R2 = 0.40). When EI was not in the model, higher agreeableness was significantly associated with higher dependent decision-making, b = 0.29, 95% BCa CI [0.24, 0.35], t = 10.44, p  < 0.001 (R2 = 0.18). The mediating effect of EI was 2.38%.

Higher conscientiousness was significantly associated with higher EI, b = 1.04, 95% BCa CI [0.69, 1.38], t = 5.93, p  < 0.001 (R2 = 0.32). Higher conscientiousness was significantly associated with higher dependent decision-making style even with EI in the model, b = 0.15, 95% BCa CI [0.09, 0.20], t = 4.88, p  < 0.001; higher EI was also significantly associated with lower dependent decision-making, b = − 0.04, 95% BCa CI [− 0.06, − 0.02], t = − 4.50, p  < 0.001 (R2 = 0.40). When EI was not in the model, higher conscientiousness was significantly associated with a higher dependent decision-making style, b = 0.10, 95% BCa CI [0.04, 0.16], t = 3.49, p  < 0.001 (R2 = 0.36). The mediating effect of EI was 30.25%.

Higher openness to experience was significantly associated with higher EI, b = 1.37, 95% BCa CI [1.05, 1.69], t = 8.41, p  < 0.001 (R2 = 0.32). Higher openness to experience was significantly associated with lower dependent decision-making style even with EI in the model, b = − 0.13, 95% BCa CI [− 0.19, − 0.08], t = − 4.55, p < 0.001; higher EI was also significantly associated with dependent decision-making style, b = − 0.04, 95% BCa CI [− 0.19, − 0.08], t = − 4.50, p < 0.001 (R2 = 0.40). When EI was not in the model, higher openness to experience was significantly associated with lower dependent decision-making style, b = − 0.19, 95% BCa CI [− 0.24, − 0.14], t = − 7.06, p < 0.001 (R2 = 0.36). The mediating effect of EI was 43.69%.

No calculations were done for neuroticism and extroversion personality traits since they were not significantly associated with the dependent decision-making style in the bivariate analysis.

Spontaneous decision-making style (Table 4 , model 4)

Agreeableness was not significantly associated with EI, b = 0.17, 95% BCa CI [− 0.19, 0.53], t = 0.91, p  = 0.364 (R2 = 0.17). Higher agreeableness was significantly associated with lower spontaneous decision-making style even with EI in the model, b = − 0.10, 95% BCa CI [− 0.16, − 0.03], t = − 3.07, p  = 0.002; EI was not significantly associated with spontaneous decision-making, b = − 0.01, 95% BCa CI [− 0.03, 0.01], t = − 0.71, p  = 0.476 (R2 = 0.15). When EI was not in the model, higher agreeableness was significantly associated with lower spontaneous decision-making, b = − 0.10, 95% BCa CI [− 0.16, − 0.04], t = − 3.11, p = 0.002 (R2 = 0.15). The mediating effect of EI was 1.25%.

Higher conscientiousness was significantly associated with higher EI, b = 1.26, 95% BCa CI [0.88, 1.64], t = 6.56, p  < 0.001 (R2 = 0.17). Higher conscientiousness was significantly associated with lower spontaneous decision-making style even with EI in the model, b = − 0.16, 95% BCa CI [− 0.23, − 0.09], t = − 4.51, p  < 0.001; EI was not significantly associated with spontaneous decision-making style, b = − 0.01, 95% BCa CI [− 0.03, 0.01], t = − 0.71, p  = 0.476 (R2 = 0.15). When EI was not in the model, higher conscientiousness was significantly associated with lower spontaneous decision-making style, b = − 0.17, 95% BCa CI [− 0.23, − 0.10], t = − 5.11, p  < 0.001 (R2 = 0.15). The mediating effect of EI was 5.64%.

Neuroticism was not significantly associated with EI, b = − 0.22, 95% BCa CI [− 0.53, 0.08], t = − 1.43, p  = 0.153 (R2 = 0.17). Higher neuroticism was significantly associated with lower spontaneous decision-making style even with EI in the model, b = − 0.11, 95% BCa CI [− 0.16, − 0.06], t = − 4.05, p  < 0.001; EI was not significantly associated with spontaneous decision-making style, b = − 0.01, 95% BCa CI [− 0.03, 0.01], t = − 0.71, p = 0.476 (R2 = 0.15). When EI was not in the model, higher neuroticism was significantly associated with lower spontaneous decision-making style, b = − 0.11, 95% BCa CI [− 0.16, − 0.05], t = − 4.01, p  < 0.001 (R2 = 0.15). The mediating effect of EI was 1.49%.

No calculations were done for openness to experience and extroversion personality traits since they were not significantly associated with the spontaneous decision-making style in the bivariate analysis .

Avoidant decision-making style (Table 4 , model 5)

Higher extroversion was significantly associated with higher EI, b = 0.88, 95% BCa CI [0.54, 1.21], t = 5.18, p  < 0.001 (R2 = 0.15). Extroversion was not significantly associated with avoidant decision-making style even with EI in the model, b = − 0.01, 95% BCa CI [− 0.06, 0.05], t = − 0.27, p  = 0.790; higher EI was significantly associated with avoidant decision-making style, b = − 0.04, 95% BCa CI [− 0.06, 0.03], t = − 4.79, p  < 0.001 (R2 = 0.25). When EI was not in the model, extroversion was not significantly associated with avoidant decision-making style, b = − 0.05, 95% BCa CI [− 0.1, 0.08], t = − 1.69, p  = 0.092 (R2 = 0.19).

Higher neuroticism was significantly associated with lower EI, b = − 0.59, 95% BCa CI [− 0.91, − 0.27], t = − 3.60, p < 0.001 (R2 = 0.15). Neuroticism was not significantly associated with avoidant decision-making style even with EI in the model, b = − 0.03, 95% BCa CI [− 0.09, 0.02], t = − 1.34, p  = 0.182; higher EI was significantly associated with lower avoidant decision-making style, b = − 0.04, 95% BCa CI [− 0.06, − 0.03], t = − 4.79, p < 0.001 (R2 = 0.25). When EI was not in the model, neuroticism was not significantly associated with avoidant decision-making style, b = − 0.09, 95% BCa CI [− 0.06, 0.04], t = − 0.33, p  = 0.739 (R2 = 0.19).

No calculations were done for openness to experience, agreeableness, and conscientiousness personality traits since they were not significantly associated with the avoidant decision-making style in the bivariate analysis.

This study examined the relationship between personality traits and decision-making styles, and the mediation role of emotional intelligence in a sample of general medicine students from different medical schools in Lebanon.

Agreeableness is characterized by cooperation, morality, sympathy, low self-confidence, high levels of trust in others and agreeable individuals tend to be happy and satisfied because of their close interrelationships [ 19 , 20 ]. Likewise, dependent decision-making style is characterized by extreme dependence on others when it comes to making decisions [ 1 ]. Our study confirmed this relationship similarly to Wood (2012) [ 41 ] and Bayram and Aydemir (2017) [ 26 ] findings of a positive relationship between dependent decision-making style and agreeableness personality trait and a negative correlation between this same personality trait and spontaneous decision-making style. In fact, this negative correlation can be explained by the reliance and trust accorded by agreeable individuals to their surroundings, making them highly influenced by others opinions when it comes to making a decision; hence, avoiding making rapid and snap decisions on the spur of the moment (i.e. spontaneous decision-making style); in order to explore the point of view of their surrounding before deciding on their own.

Conscientiousness is characterized by competence, hard work, self-discipline, organization, strive for achievement, and goal orientation [ 20 ]. Besides, conscientious individuals have a high level of deliberation making them capable of analyzing the pros and cons of a given situation [ 21 ]. Similarly, rational decision-makers strive for achievements by searching for information and logically evaluating alternatives before making decisions; making them high achievement-oriented [ 20 , 42 ]. This positive relationship between rational decision-making style and conscientiousness was established by Nygren and White (2005) [ 43 ] and Bajwa et al. (2016) [ 25 ]; thus, solidifying our current findings. Furthermore, we found that conscientiousness was positively associated with dependent decision-making; this relationship was not described in previous literature to our knowledge and remained statistically significant after adding EI to the analysis model. This relationship may be explained by the fact that conscientious individuals tend to take into consideration the opinions of their surrounding in their efforts to analyze the pros and cons of a situation. Further investigations in similar populations should be conducted in order to confirm this association. Moreover, we found a positive relationship between conscientiousness and intuitive decision-making that lost significance when EI was removed from the model. Thus, solidifying evidence of the mediating role played by EI between personality trait and decision-making style with an estimated mediation effect of 38%.

Extroversion is characterized by higher levels of self-confidence, positive emotions, enthusiasm, energy, excitement seeking, and social interactions. Similarly, intuitive decision-making is highly influenced by emotions and instinct. The positive relationship between extroversion and intuitive decision-making style was supported by Wood (2012) [ 41 ], Riaz et al. (2012) [ 24 ] and Narooi and Karazee (2015) [ 23 ] findings and by our present study.

Neuroticism is characterized by anxiety, anger, self-consciousness, and vulnerability [ 20 ]. High neurotic individuals have higher levels of negative affect, depression, are easily irritated, and more likely to turn to inappropriate coping responses, such as interpersonal hostility [ 22 ]. Our study results showed a negative relationship between neuroticism and spontaneous decision-making style.

Openness to experience individuals are creative, imaginative, intellectually curious, impulsive and original, open to new experiences and ideas [ 19 , 20 ]. One important characteristic of intuitive decision-making style is tolerance for ambiguity and the ability to picture the problem and its potential solution [ 44 ]. The positive relationship between openness to experience and intuitive decision-making style was established by Riaz and Batool (2012) [ 24 ] and came in concordance with our study findings. Additionally, our results suggest that openness personality trait is negatively associated with dependent decision-making style similar to previous findings [ 23 ]. Openness to experience individuals are impulsive and continuously seek intellectual pursuits and new experiences; hence, they tend to depend to a lesser extent on others’ opinions when making decisions since they consider the decision-making process a way to uncover new experiences and opportunities.

Our study results showed that EI had a significant positive effect on intuitive decision-making style. Intuition can be regarded as an interplay between cognitive and affective processes highly influenced by tactic knowledge [ 45 ]; hence, intuitive decision-making style is the result of personal and environmental awareness [ 46 , 47 , 48 ] in which individuals rely on the overall context without much concentration on details. In other words, they depend on premonitions, instinct, and predications of possibilities focusing on designing the overall plan [ 49 ] and take responsibility for their decisions [ 46 ]. Our study finding supports the results of Khan and al. (2016) who concluded that EI and intuitive decision-making had a positive relationship [ 35 ]. On the other hand, our study showed a negative relationship between EI and avoidant and dependent decision-making styles. Avoidant decision-making style is defined as a continuous attempt to avoid decision-making when possible [ 1 ] since they find it difficult to act upon their intentions and lack personal and environmental awareness [ 50 ]. Similarly to our findings, Khan and al. (2016) found that avoidant style is negatively influenced by EI [ 35 ]. The dependent decision-making style can be regarded as requiring support, advice, and guidance from others when making decisions. In other words, it can be described as an avoidance of responsibility and adherence to cultural norms; thus, dependent decision-makers tend to be less influenced by their EI in the decision-making process. Our conclusion supports Avsec’s (2012) findings [ 51 ] on the negative relationship between EI and dependent decision-making style.

Practical implications

The present study helps in determining which sort of decision is made by which type of people. This study also represents a valuable contribution to the Lebanese medical society in order to implement such variables in the selection methods of future physicians thus recruiting individuals with positively evaluated decision-making styles and higher levels of emotional intelligence; implying better communication skills and positively impacting patients’ experience. Also, the present study may serve as a valuable tool for the medical school administration to develop targeted measures to improve students’ interpersonal skills.

Limitations

Even though the current study is an important tool in order to understand the complex relationship between personality traits, decision-making styles and emotional intelligence among medical students; however, it still carries some limitations. This study is a descriptive cross-sectional study thus having a lower internal validity in comparison with experimental studies. The Scott and Bruce General Decision-Making Style Inventory has been widely used internationally for assessing decision-making styles since 1995 but has not been previously validated in the Lebanese population. In addition, the questionnaire was only available in English taking into consideration the mandatory good English knowledge in all the Lebanese medical schools; however, translation, and cross-language validation should be conducted in other categories of Lebanese population. Furthermore, self-reported measures were employed in the present research where participants self-reported themselves on personality types, decision-making styles and emotional intelligence. Although, all used scales are intended to be self-administered; however, this caries risk of common method variance; hence, cross-ratings may be employed in the future researches in order to limit this variance.

The results suggest that EI showed a significant positive effect on intuitive decision-making style and a negative effect on avoidant and dependent decision-making styles. In addition, our study showed a positive relationship between agreeableness and dependent decision-making style and a negative correlation with spontaneous decision-making style. Furthermore, conscientiousness had a positive relationship with rational and dependent decision-making style and extroversion showed a positive relationship with intuitive decision-making style. Neuroticism had a negative relationship with spontaneous style and openness to experience showed a positive relationship with intuitive decision-making style and a negative relationship with dependent style. Additionally, our study underlined the role of emotional intelligence as a mediation factor between personality traits and decision-making styles namely openness to experience, extroversion, and conscientiousness personality traits with intuitive decision-making style. Personality traits are universal [ 20 ]; beginning in adulthood and remaining stable with time [ 52 ]. Comparably, decision-making styles are stable across situations [ 1 ]. The present findings further solidify a previously established relationship between personality traits and decision-making and describes the effect of emotional intelligence on this relationship.

Availability of data and materials

All data generated or analyzed during this study are not publicly available to maintain the privacy of the individuals’ identities. The dataset supporting the conclusions is available upon request to the corresponding author.

Scott SG, Bruce RA. Decision-making style: the development and assessment of a new measure. Educ Psychol Meas. 1995;55(5):818–31.

Article   Google Scholar  

Capraro V, Everett JA, Earp BD. Priming intuition disfavors instrumental harm but not impartial beneficence. J Exp Soc Psychol. 2019;83:142–9.

Allwood CM, Salo I. Decision-making styles and stress. Int J Stress Manag. 2012;19(1):34.

Rand DG, Brescoll VL, Everett JA, Capraro V, Barcelo H. Social heuristics and social roles: intuition favors altruism for women but not for men. J Exp Psychol Gen. 2016;145(4):389–96.

Article   PubMed   Google Scholar  

Kobis NC, Verschuere B, Bereby-Meyer Y, Rand D, Shalvi S. Intuitive honesty versus dishonesty: meta-analytic evidence. Perspect Psychol Sci. 2019;14(5):778–96.

Greene JD, Morelli SA, Lowenberg K, Nystrom LE, Cohen JD. Cognitive load selectively interferes with utilitarian moral judgment. Cognition. 2008;107(3):1144–54.

Rand DG. Cooperation, fast and slow: meta-analytic evidence for a theory of social heuristics and self-interested deliberation. Psychol Sci. 2016;27(9):1192–206.

Tremoliere B, Neys WD, Bonnefon JF. Mortality salience and morality: thinking about death makes people less utilitarian. Cognition. 2012;124(3):379–84.

Brown C, George-Curran R, Smith ML. The role of emotional intelligence in the career commitment and decision-making process. J Career Assess. 2003;11(4):379–92.

Clancy C. The importance of emotional intelligence. Nursing Management (2014+). 2014;21(8):15.

Goleman D. Working with emotional intelligence. New York: Bantam; 1998.

Google Scholar  

Cotruş A, Stanciu C, Bulborea AA. EQ vs. IQ which is Most important in the success or failure of a student? Procedia Soc Behav Sci. 2012;46:5211–3.

Alghamdi NG, Aslam M, Khan K. Personality traits as predictor of emotional intelligence among the university teachers as advisors. Educ Res Int. 2017;2017:1–6 https://doi.org/10.1155/2017/9282565 .

Kazdin AE. Encyclopedia of psychology, vol. Vol 8. Washington, DC: American Psychological Association; 2000.

Bleidorn W, Klimstra TA, Denissen JJ, Rentfrow PJ, Potter J, Gosling SD. Personality maturation around the world: a cross-cultural examination of social-investment theory. Psychol Sci. 2013;24(12):2530–40.

Borkenau P, Riemann R, Spinath FM, Angleitner A. Genetic and environmental influences on person× situation profiles. J Pers. 2006;74(5):1451–80.

Hazrati-Viari A, Rad AT, Torabi SS. The effect of personality traits on academic performance: the mediating role of academic motivation. Procedia Soc Behav Sci. 2012;32:367–71.

Proceedings of the international conference on multiple academic disciplines. HanoiISBN: 978–1–943579-61-7 Hai Phong - . . Paper ID: VM714. 18–19, August: Vietnam (MAD17Vietnam Conference); 2017.

McCrae RR, John OP. An introduction to the five-factor model and its applications. J Pers. 1992;60(2):175–215.

McCrae R, Costa P Jr. Personality in adulthood. In: O envelhecimento. Uma abordagem psicológica . New York: Guilford; 1990. p. 2.

Johnson JA. Units of analysis for the description and explanation of personality. In R. Hogan, J. Johnson, & S. Briggs (Eds.) Handbook of personality psychology : Elsevier; 1997. p. 73–93.

Camps J, Stouten J, Euwema M. The relation between supervisors’ big five personality traits and employees’ experiences of abusive supervision. Front Psychol. 2016;7:112.

Article   PubMed   PubMed Central   Google Scholar  

Narooi ZS, Karazee F. Investigating the relationship among personality traits, decision-making styles, and attitude to life (Zahedan branch of Islamic Azad University as case study in Iran). Mediterr J Soc Sci. 2015;6(6 S6):311.

Riaz MN, Riaz MA, Batool N. Personality types as predictors of decision making styles. J Behav Sci. 2012;22(2):100–14.

Bajwa RS, Batool I, Asma M, Ali H, Ajmal A. Personality traits and decision making styles among university students (Pakistan). Pakistan J Life Soc Sci. 2016;14(1):38–41.

Bayram N, Aydemir M. Decision-making styles and personality traits. Int J Recent Adv Organizational Behaviour Decision Sci. 2017;3:905–15.

Dawda D, Hart SD. Assessing emotional intelligence: reliability and validity of the Bar-on emotional quotient inventory (EQ-i) in university students. Personal Individ Differ. 2000;28(4):797–812.

Day AL, Therrien DL, Carroll SA. Predicting psychological health: assessing the incremental validity of emotional intelligence beyond personality, type a behaviour, and daily hassles. Eur J Personality. 2005;19(6):519–36.

Avsec A, Takšić V, Mohorić T. The relationship of trait emotional intelligence with the big five in Croatian and Slovene university student samples. Psihološka obzorja/Horizons Psychol. 2009;18(3):99–110.

Spicer DP, Sadler-Smith E. An examination of the general decision making style questionnaire in two UK samples. J Manag Psychol. 2005;20(2):137–49.

Zeelenberg M, Pieters R. Feeling is for doing: a pragmatic approach to the study of emotions in decision-makingManuscript under review; 2005.

Bechara A, Damasio AR. The somatic marker hypothesis: a neural theory of economic decision. Games Econ Behavior. 2005;52(2):336–72.

Kustubayeva A, Bagayeva E. Emotional intelligence and decision making. RUDN J Psychol Pedagogics. 2011;S5:104–9.

Jaušovec N, Jaušovec K. Sex differences in brain activity related to general and emotional intelligence. Brain Cogn. 2005;59(3):277–86.

Khan E, Riaz M, Batool N, Riaz M. Emotional intelligence as a predictor of decision making styles among university students. J Appl Environ Biol Sci. 2016;6(4S):93–9.

Sarkis A. Hallit S. Hajj A. Lebanese students’ motivation in medical school: does it change throughout the years? A cross-sectional study. BMC Med Educ 20, 94 (2020). https://doi.org/10.1186/s12909-020-02011-w .

John OP, Donahue EM, Kentle RL. The big five inventory—versions 4a and 54. Berkeley: University of California, Berkeley, Institute of Personality; 1991.

Mohapel P. The quick emotional intelligence self-assessment: San Diego City College MESA Program; 2015.

Soueid M, Ghanem S, Hariri Z, Yamout N, Nehme R. Analysis of Lebanon's education sector: BankMed Market & Economic Research Divisionupdated Nov 10; cited 2015 Apr 6; 2014. Available from: http://www.bankmed.com.lb/BOMedia/subservices/categories/News/20150515170635891.pdf . Accessed 17 Jan 2020.

Hayes AF. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression‐Based Approach. New York, NY: The Guilford Press.

Thomas E. Nygren, Rebecca J. White; 2005. Relating Decision Making Styles to Predicting Selfefficacy and a Generalized Expectationof Success and Failure. Article in Human Factors andErgonomics Society Annual Meeting Proceedings 49(3):432–34.

Baiocco R, Laghi F, D'Alessio M. Decision-making style among adolescents: relationship with sensation seeking and locus of control. J Adolesc. 2009;32(4):963–76.

Nygren TE, White RJ. Relating decision making styles to predicting selfefficacy and a generalized expectation of success and failure. Paper presented at: Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 2005.

Bergstrand B. Situating the estimate: naturalistic decision-making as an alternative to analytical decision making in the Canadian forcesunpublished article. n. pag. http://www.cfcsc.dnd.ca/irc/nh/nh9798/0021.html ; 2001. p. 24.

Sinclair M, Ashkanasy NM. Intuition: myth or a decision-making tool? Manag Learn. 2005;36(3):353–70.

Harren VA. A model of career decision making for college students. J Vocat Behav. 1979;14(2):119–33.

Hablemitoglu S, Yildirim F. The relationship between perception of risk and decision making styles of Turkish university students: a descriptive study of individual differences. World Appl Sci J. 2008;4(2):214–24.

Singh R, Greenhaus JH. The relation between career decision-making strategies and person–job fit: a study of job changers. J Vocat Behav. 2004;64(1):198–221.

Miller CC, Ireland RD. Intuition in strategic decision making: friend or foe in the fast-paced 21st century? Acad Manag Perspect. 2005;19(1):19–30.

Phillips SD, Pazienza NJ, Ferrin HH. Decision-making styles and problem-solving appraisal. J Couns Psychol. 1984;31(4):497.

Avsec A. Do emotionally intelligent individuals use more adaptive decision-making styles? Stud Psychol. 2012;54(3):209.

Soldz S, Vaillant GE. The big five personality traits and the life course: a 45-year longitudinal study. J Res Pers. 1999;33(2):208–32.

Download references

Acknowledgements

We would like to thank all students who agreed to participate in this study.

Author information

Rabih Hallit, Sahar Obeid and Souheil Hallit are last co-authors.

Authors and Affiliations

Faculty of Medicine and Medical Sciences, Holy Spirit University of Kaslik (USEK), Jounieh, Lebanon

Radwan El Othman, Rabih Hallit & Souheil Hallit

Department of Pediatrics, Bahman Hospital, Beirut, Lebanon

Rola El Othman

Department of Infectious Disease, Bellevue Medical Center, Mansourieh, Lebanon

Rabih Hallit

Department of Infectious Disease, Notre Dame des Secours University Hospital Center, Byblos, Lebanon

Research and Psychology departments, Psychiatric Hospital of the Cross, P.O. Box 60096, Jal Eddib, Lebanon

Sahar Obeid & Souheil Hallit

Faculty of Arts and Sciences, Holy Spirit University of Kaslik (USEK), Jounieh, Lebanon

Sahar Obeid

INSPECT-LB: Institut National de Santé Publique, Epidémiologie Clinique et Toxicologie – Liban, Beirut, Lebanon

You can also search for this author in PubMed   Google Scholar

Contributions

REO and REO were responsible for the data collection and entry and drafted the manuscript. SH and SO designed the study; SH carried out the analysis and interpreted the results; RH assisted in drafting and reviewing the manuscript; All authors reviewed the final manuscript and gave their consent; SO, SH and RH were the project supervisors.

Corresponding authors

Correspondence to Sahar Obeid or Souheil Hallit .

Ethics declarations

Ethics approval and consent to participate.

The Holy Spirit University of Kaslik – School of Medicine and Medical Sciences ethics committee approved the study protocol. A written consent was obtained from each student.

Consent for publication

Not applicable.

Competing interests

The authors have nothing to disclose.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

El Othman, R., El Othman, R., Hallit, R. et al. Personality traits, emotional intelligence and decision-making styles in Lebanese universities medical students. BMC Psychol 8 , 46 (2020). https://doi.org/10.1186/s40359-020-00406-4

Download citation

Received : 27 January 2020

Accepted : 12 April 2020

Published : 05 May 2020

DOI : https://doi.org/10.1186/s40359-020-00406-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Personality traits
• Decision-making
• Decision-making style
• Emotional intelligence
• Medical students

BMC Psychology

ISSN: 2050-7283

• General enquiries: [email protected]

Personality Development: Michelle Obama Case Study

The term “personality” refers to a sum of character traits in a person. Therefore, personality development implies that the personality traits evolve from the childhood basis to the full development of individual differences in a character of a grown-up. This case study investigates the personality development illustrated by an example of Michelle Obama, First Lady of the United States of America. She was chosen due to her prominent personality features, outstanding life experience and the fact that she is a worthy role model for modern society; consequently, such development can be an interesting example to consider.

Michelle LaVaughn Obama, née Robinson, was born on January 17, 1964, in Calumet Park Illinois, to a family of a water plant worker and a housewife. She is now able to trace the history of her family back to a Friendfield Plantation in Georgetown, S.C. where her great-great-grandfather worked as a slave, while later his descendants moved North and settled in Illinois. However Mrs. Obama has learned of her ancestry only during a presidential campaign of her husband, and this knowledge has had a great impact on her (Murray, 2008, p. 1).

She graduated from school in1981 as a salutatory student and later studied sociology at Princeton University, from which she graduated BoA cum laude. In 1988, she also graduated from Harvard University as Juris Doctor and began her law practice in Harvard Legal Aid Bureau. Later she also worked in various non-profit organizations but reduced her job responsibilities to help her husband, Barak Obama, whom she married in 1992, with his presidential campaign. The couple raises two daughters, and Michelle considers her family the main life priority. Mrs. Obama is regarded as a fashion icon and a trend-setter ( Michelle Obama Biography , n.d., par. 1-21).

For further exploration of Michelle Obama’s personality development, it is important to mention the models, according to which an individual’s personality development can be explained. These models include psychoanalytic and neo-analytic theories, psychosocial theories, trait, evolutionary, genetic/biological approaches, cognitive, behavioral, and social learning theories, and humanistic theories. For the beginning of the analysis, it would be appropriate to use the psychoanalytic / neo-analytic model, as it is one of the most basic and rather comprehensive theories, which can be considered as both advantage and disadvantage because it does not leave much possibility for other explanations.

According to those theories, based on teachings of Sigmund Freud, the parts of psyche, called “id”, “ego” and “superego” are balanced within each individual, but while Freud himself thought ego to be a weak structure, his successors, the neo-analytics, claimed that ego, containing the functions of learning, memory, and cognitive skills is a part that is the strongest from birth. A development, in this case, takes place in solving the so-called “basic conflicts”, which may serve to temper the character, or result in personality problems if such conflicts were not solved.

For Michelle Obama, an example of such conflict would have been an illness that her father suffered, the multiple sclerosis, which, however, did not stop him from pursuing his goals in life and teaching his daughter the same values ( Fraser Robinson III ~ Michelle Obama’s Father , par. 1-16). This probably was also the reason Michelle is often a participant of charity and non-profit organizations – because of her need to help people and treat them with kindness.

The psychosocial theory was first introduced by psychologist Erik Erikson; it suggests that eight stages of development during one’s life, at which the person learns to accept different virtues, such as hope, will, purpose, competence, fidelity, love, care and wisdom. If one of the stages is missing, the value of its virtue may be lost. This theory encompasses the whole life’s development, but the order of the stages is often argued, and it is not always possible to trace the trajectory of a person’s life. According to this theory, Michelle Obama has successfully passed the stages of life involving purpose, competence (her studies), love and fidelity (her family) and at her adulthood she may be learning again how to care and make her life count, in which she definitely succeeds, both in terms of social and family life.

The trait theory, together with evolutionary and biological theories, presumes that a few fundamental units define the individual’s behavior and that these traits are defined by genetics (McLeod, 2014, par. 22-30). Therefore, further development is defined by these innate factors. These theories place emphasis on conducting psychometric tests (McLeod, par. 24), which can give a high level of precision in defining a character, some critics mention, that “traits are often poor predictors of behavior. While an individual may score high on assessments of a specific trait, he or she may not always behave that way in every situation … trait theories do not address how or why individual differences in personality develop or emerge” (Cherry, 2015, par. 16).

For using this theory, it may be important to investigate the family of Michelle Obama, to understand better, what kind of person she is, and how her legacy could influence her personality development. As it may be seen from her family tree, her ancestors were mostly hard-working people, who were proud of what they did and upheld traditional values; they believed that it was important to educate their children and give them a better life, which was one of the reasons the family moved to the north (Murray, 2008, p.2-4). It is clear that Michelle Obama inherited their dutifulness, perfectionism, independence, but also warmth and liveliness. This is how she became who she is now – a First Lady, a renowned philanthropist, and a trend-setter.

The humanistic or existential approach claims another important focus for a psychologist:

Factors that are specifically human, such as choice, responsibility, freedom, and how humans create meaning in their lives. Human behavior is not seen as determined in some mechanistic way, either by inner psychological forces, schedules of external reinforcement, or genetic endowments, but rather as a result of what we choose and how we create meaning from among those choices. (Beneckson, n.d., par. 42)

It means that understanding oneself and thriving to improve one’s personality may lead to healthy development or the so-called “self-actualization.” Existentialists may also add:

It requires active intention to create authenticity … Man is thrown into the world against his will, and must learn how to coexist with nature, and the awareness of his own death … To be healthy, humans must choose a course of action that leads to … the productive orientation. This is defined as working, loving, and reasoning so that work is a creative self-expression and not merely an end in itself. (Beneckson, n.d., par. 47)

This approach allows to take a different look at human’s psyche, disregarding the doctrines of Freudian, biological and behaviorist theories, however, it is often criticized for being too anthropocentric and idealistic.

For Mrs. Obama, the personal development in terms of humanistic theory may be illustrated with her life experiences, such as life within her family and a brother, which taught her how to listen to other people and get along with them. Later she also developed her working skills after she graduated, and her self-actualization lied in the field of law practice until she made a decision to help her husband. Michelle claimed that her family was her highest priority, and her choice was to work along with her husband and give her love to him and their children, all the while being able to satisfy her own need in self-actualization. The balance between these factors allows a person to find a psychological calm and harmony.

To conclude this research, it would be fair to assume, that although various approaches can be used to better understand an individual’s personality development, all of them can be useful for different scenarios. For example, it may be difficult to use the genetic method, when little or nothing is known about a person’s origins and his or her family. An existential approach should also be used with caution, as this is the least conservative and the newest method in psychology, which means some of its ideas may not have enough proof.

Nevertheless, every method has the right of existence however for a comprehensive and thorough understanding a deep and complex structure, that is the human personality, it may be advisable to unite some of the approaches. It would allow to gather more information, and the cross comparison of the results may highlight the features that previously were not noticed. It is highly important for a psychologist to follow the good practice but also to be versatile and flexible with the use of various tools to achieve better results in assessment and research.

Reference List

Beneckson, R. E. (n.d.) Personality Theory. A Brief Survey of the Field Today and Some Possible Future Directions . Web.

Cherry, K. (2015), Trait Theory of Personality. The Trait Approach to Personality . Web.

Fraser Robinson III ~ Michelle Obama’s Father. (n.d.). Web.

McLeod, S. (2014). Theories of personality . Web.

Michelle Obama Biography . (n.d.). Web.

Murray, S. (2008). A Family Tree Rooted In American Soil. The Washington Post. Web.

• Chicago (A-D)
• Chicago (N-B)

IvyPanda. (2022, June 28). Personality Development: Michelle Obama. https://ivypanda.com/essays/personality-development-case-study-michelle-obama/

"Personality Development: Michelle Obama." IvyPanda , 28 June 2022, ivypanda.com/essays/personality-development-case-study-michelle-obama/.

IvyPanda . (2022) 'Personality Development: Michelle Obama'. 28 June.

IvyPanda . 2022. "Personality Development: Michelle Obama." June 28, 2022. https://ivypanda.com/essays/personality-development-case-study-michelle-obama/.

1. IvyPanda . "Personality Development: Michelle Obama." June 28, 2022. https://ivypanda.com/essays/personality-development-case-study-michelle-obama/.

Bibliography

IvyPanda . "Personality Development: Michelle Obama." June 28, 2022. https://ivypanda.com/essays/personality-development-case-study-michelle-obama/.

• "Michelle Obama Calls on You to Serve" Address
• Rhetorical Theory Applied to Michelle Obama’s Speech
• Occupational Asthma: Michelle’s Case
• Ed. Michelle Lee's "Othello" as a Critical Source
• Michelle Kwan: An American Skating Champion
• Michelle Obama’s Remarks on American Dream
• Rasism in "No Telephone to Heaven" by Michelle Cliff
• Michelle Obama American Dream Speech Analysis –
• Story of a Woman: "Becoming" by Michelle Obama
• Self-Actualization: Interpersonal Communication
• Intelligence Theories Critique
• Personality Psychology: Cinderella's Personality
• Study of Values: 'A Scale for Measuring the Dominant Interests in Personality' by G. Allpor
• Heroism Concept and Its Causes
• Criminality and Personality Theory

Taking a Personality Test – A Case Study (And What To Expect)

Have you been asked to complete an assessment for a job? Don’t panic. When designed and administered correctly, objective psychometrics like a personality test can be an incredibly useful tool both for you and your work. We asked a recent candidate their experience taking one of our assessments. Read on to learn what to expect.

Recently I was given the opportunity to take a PeopleFactors’ assessment and received personal feedback from one of their professional business psychologists. I must admit, prior to actually sitting down to face this personality test I was somewhat apprehensive about it. A variety of perceptions and opinions, and many of them rather skeptical, seemed to crowd my thoughts.

What exactly would these assessments reveal about me? How accurate can an online personality test be?

I suppose these feelings that I brought with me to the personality test are likely to be shared with most people. Adults don’t often take assessments or tests, and certainly not those designed to measure their ability and potential. A common response might be that simply doing their job is measurement enough. On the other hand, people do not regularly receive opportunities to truly reveal the sum total of characteristics, talents, and abilities that make them who they are and uncover their potential for greater things.

PeopleFactors markets itself as an organization that creates wealth through people. They support organizations by identifying and nurturing their talent management process. To that end, the PeopleFactors personality tests serve as the primary discovery tool to locate the best and brightest within any business and guide these companies toward making better career development decisions that serve both the business and their employees.

Well, at least that is what I knew of PeopleFactors before diving in. But I was determined to decide for myself while taking their personality test and listening to the feedback they provided based on my results.

I consider myself an intelligent and competitive person. And I understand that these tests are designed to determine the extent to which I possess the skills and personal make-up inherent to successful business leaders.

So with this in mind, my initial approach with the first test was to give them what they wanted.

If they wanted a goal-oriented, decision-making leader, that’s exactly how I would tailor my responses, regardless if my answers accurately reflected my opinions or experience. And again, it’s my assumption that many people might do the same. I mean, we all want to appear and be perceived as smart and highly-capable and in possession of great qualities and talents that perhaps have yet to be noticed, right? I do. And because of that, I began my personality test attempting to game my assessment.

Now sure, PeopleFactors does provide timed intelligence assessment tests, which are similar to IQ tests and designed to be as definitive as possible by testing analytic ability and intellect and reasoning. You can’t beat these tests with strategy. It was with the greyer, more ambiguous assessments that queried my motivational values and managerial style that I thought I could out-manoeuvre.

It took me no more than 15 minutes, however, to understand that this tactic wasn’t going to work.

Even as I attempted to provide the answers I felt most characteristic to executive-level managers, the questions I encountered often contained no absolute correct response at all. Moreover, I soon realized that many questions were being posed again and again, each time slightly reworded or positioned from a new vantage. That’s when I really began to appreciate and admire what PeopleFactors was doing. If I couldn’t out-think the test, my only other option was to be honest and answer each question as truthfully as I could. And that’s the point.

As I moved through each test, I found the questions to be exacting, demanding, and often illuminating. Many of my own responses surprised me. And the further I moved away from the idea that I could somehow manipulate my responses to produce a better “score”, the more attentive I became to my own opinions and preferences, and the more I enjoyed responding. I finished the personality test feeling certain that whatever my results revealed, they’d be a very accurate measurement of the person and employee that I am. I couldn’t wait to hear the feedback.

Two days later, I received both a comprehensive analysis report and a telephone call from one of PeopleFactors’ consultants. Together, we examined how my responses to the personality test shaped their findings and I found our conversation to be a helpful pairing to the conclusions made in the report. The consultant was kind and informative and explained how my skill sets and personal qualities might best be applied within an actual work environment. And I was correct – my results were a thoughtful and intimate reflection of who I really am.

The services PeopleFactors offers extend well beyond my assessment experience, but it’s easy to imagine the practicality and effectiveness of their products and services once applied to an entire team or workforce. The assessments themselves are a great tool to establish and maintain a successful organizational development structure and PeopleFactors should be considered experts at helping companies get there.

Thank you Sean Duffy for this wonderful write-up!

To take an assessment for yourself, dive into our on-demand service here.

We use cookies to enhance our website for you. Proceed if you agree to this policy or learn more about it.

• Essay Database >
• Essays Samples >
• Essay Types >
• Case Study Example

Personality Case Studies Samples For Students

112 samples of this type

If you're seeking a viable method to streamline writing a Case Study about Personality, WowEssays.com paper writing service just might be able to help you out.

For starters, you should skim our extensive directory of free samples that cover most various Personality Case Study topics and showcase the best academic writing practices. Once you feel that you've figured out the major principles of content organization and taken away actionable ideas from these expertly written Case Study samples, composing your own academic work should go much smoother.

However, you might still find yourself in a situation when even using top-notch Personality Case Studies doesn't allow you get the job accomplished on time. In that case, you can contact our experts and ask them to craft a unique Personality paper according to your individual specifications. Buy college research paper or essay now!

Randle Mcmurphy In The One Flew Over The Cuckoo's Nest Case Study Samples

Clinical diagnosis and rationale for the diagnosis, case study on the case of kname:institution:course:tutor:date of submission, the case of k, case study on abnormal psychology: charles manson, introduction.

Don't waste your time searching for a sample.

Get your case study done by professional writers!

Just from $10/page

Schizophrenic Spectrum And Other Psychotic Disorders Case Study Samples

Good example of case study on order# 209969004, human resource management, case study on egoism, sample case study on organizational behaviors.

Organizational behavior is the of study that explores the collision that structures, groups and individuals, have on behavior within an organization for the intention of applying such information towards taming an organization's efficiency. It understands the employees’ role and them understanding the manager’s role in the accurate manner without misconception in favor of the organization. In this case study, a retail shop sells teddy bears and Clark the manager determines her personalities in her organization” (Giacobbe, 2009).

Maxine’s Clark’s personality

Example of occupation: singer case study, free case study on gps-to-go takes on garmin.

[Your first name - initial of middle name and last name with titles (like Mr. or Dr.)]

[Your institute/university’s name goes here]

Free personality types and self-evaluation case study example, types of different personalities.

Freud and Fromm studied four different types of personalities possessed by human beings. They are discussed in the following manner from a leadership perspective:

The Erotic Personality

Individuals that possess this personality want to be loved and needed by others all the time. Compared to respect, people in this personality group tend to emphasize more on being liked and loved by others. They want to be known to others and wish to actively socialize with others. In all erotic personality holders are attention seekers and depend on others to make them happy.

The Obsessive Personality

Antisocial personality disorder case study case study, antisocial personality disorder: case study.

Antisocial Personality Disorder (ASPD) is a type of condition that corrupts an individual mind, emotions, thoughts and behavior. The affected person develops behaviors destructive and harmful to others and generally poses as a danger to society. The individuals tend to have long histories of violating peoples’ rights; they are always aggressive, show no remorse and usually do not know the distinction between truths and lie (Barlow and Durand, 2009).

Good Example Of Case Study On Kinaxis Chooses Sales Reps With Personality

What selection methods did bo dolan use for hiring salespeople, factors contributing to juvenile delinquent behaviour: exemplar case study to follow, case study on alan mulally, ceo, ford motor company.

In seeking success, Ford Motor Company entrusts the services of Alan Mulally, as the CEO. Having worked for Boeing, Mulally appears ready for this task as he embarks on undertaking a thorough research at Ford immediately he arrives, in order to study and formulate the best strategy for the company. As Ford Company is geared towards success, Mulally’s style of leadership is analyzed, as well as his personality dimension elements. The methods Mulally introduces at Ford are evaluated for effectiveness, while seeking for evidence of evidence based management at Ford. Furthermore, Mulally’s elements of communication openness are analyzed.

Case Study On Interview Profile

Interview profile, free adulthood case study case study example, introduction, janet's schizophrenic episode case study.

1. What is the precipitating stressor event that probably triggered the onset of Janet's Schizophrenic episode? What other factors may have contributed?

The Reign Of Napoleon Bonaparte Case Study Sample

Borderline personality disorder case study, borderline personality disorder: case study.

Karen’s Case

Karen was admitted in the intensive care unit of West Raymond medical Center after she knowingly took an overdose of sedatives in addition to alcohol in a suicide attempt following a disagreement with her man.

Domestic Violence Case Study Example

Personality case study, case study on personality disorders identification assignment, personality disorders: paranoid, schizoid, schizotypal, histrionic, narcissistic, borderline, antisocial, dependent and obsessive-compulsive.

Donna Donna has histrionic personality disorder. She used dramatic tactics to gain the attention of everyone at the party, such as boasting about being an actress and pretending to faint.

William has schizotypal personality disorder. He expressed beliefs and behaviors that were seen as odd and strange by everyone else, such as talking about negative forces and psychic soul-spot.

Sherry has borderline personality disorder. She suffered from emotional instability, dramatic changes in mood, and impulsive behavior. She also demonstrated para-suicidal behavior as she took aspirin in a weak attempt to harm herself, which is characteristic of this disorder.

Case Study On The Reign Of Napoleon Bonaparte

Free thomas' five general approaches to managing conflict include the following case study sample, management leadership, dora's case study example, marriage and family system case studies examples, good example of the beauty of sorbet case study case study, theoretical framework case studies examples, bss company startup analysis case studies examples, the beauty of sorbet case study case study to use for practical writing help, counselling theory case study, counselling theory, next leader for asia pacific: case study you might want to emulate, good case study about mba 5325, free mental health case study example, methodology case studies example, video game violence and its effects on children, good case study on alzheimers disease, mgmt331: week #8 paper: case study examples, free case study on personality and psychological disorders, personality and psychological disorders, bipolar personality disorders case study examples, the case of angelina jolie, borderline personality disorder case study sample, case study on david parker ray, changing mindset case study analysis: free sample case study to follow, strong hate for public speaking- notably, richard branson does not like standing in front of an audience giving speeches. (anton) case study template for faster writing, free relationship of the conflict experience and the course text case study example, personal case study.

Communication Personal Case Study

Interpersonal Conflict

Exemplar case study on conflict resolution to write after, example of clinical application of theory case study, good case study on motivation in learning and leadership, hr case evaluation #1 case study sample, free personality and development theories case study sample, good example of early onset of alzheimer’s, on alice case study, good example of stress management case study, principles of effective time management violated by chet.

Chet is not managing his time effectively because he is violating two key principles of effective time management: (1) spending some of his time on important tasks and (2) failure to comfortably say NO (Whetten and Cameron 121). From the case study, Chet is violating the first principle because he is spending all his time on urgent tasks. He also violating principle two because he is seen trying to solve everything that is presented to him.

Rules of Efficient Time Management for Managers Violated by Chet

Case study on hotel rwanda, good case study about key individuals, good essentials of psychology case study example, example of case study on green river murders, example of case study on connections to developmental theories, case study on john bio psychosocial profile 4, psychology: case study.

Introduction 3

Initial interview 4 Assessment formulation methods utilized 4 Assessment of John presenting problems and goals 5 Analysis and critique of MMT approach 6 Agreed goals 6 Treatment plan 6 CBT interventions 7 Intervention for cognitions-thoughts records 7 Benefits of the approach 7 Interventions for behavior- activity scheduling/diversion techniques 8 Benefits of the approach/ interaction 8 Interventions for imagery/interpersonal- imagery based exposure 8 Benefit of approach 9 Intervention for sensation- relaxation/ visualization 10 Conclusion 11

APPENDIX 1 13

5-axis diagnosis case study.

Lucy suffers of a major depression or depressive condition. She is getting the attention or medication with the antidepressants. This depressive episode is causing a lot of disturbance in her daily life activities. The medical pain is extreme hence making her to fail going to her workplace.

She is suffering from a personality disorder, which has contributed to the development of the depression. The attempted to commit suicide shaped her condition of depression. Her history of depression is as a result of the medical pain and being diagnosed with fibromyalgia. The personality disorder induces the depressive episode in axis I.

Case Study on Knowledge Management in Marketing

Example of case study on star bucks.

Password recovery email has been sent to [email protected]

Use your new password to log in

You are not register!

By clicking Register, you agree to our Terms of Service and that you have read our Privacy Policy .

Now you can download documents directly to your device!

Check your email! An email with your password has already been sent to you! Now you can download documents directly to your device.

or Use the QR code to Save this Paper to Your Phone

The sample is NOT original!

Short on a deadline?

Don't waste time. Get help with 11% off using code - GETWOWED

No, thanks! I'm fine with missing my deadline

• Bipolar Disorder
• Therapy Center
• When To See a Therapist
• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Guided Meditations
• Verywell Mind Insights
• 2023 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

What Are the Big 5 Personality Traits?

Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Verywell / Catherine Song

• Universality
• Influential Factors

Frequently Asked Questions

Many contemporary personality psychologists believe that there are five basic dimensions of personality, often referred to as the "Big 5" personality traits. The Big 5 personality traits are extraversion (also often spelled extroversion), agreeableness , openness , conscientiousness , and neuroticism .

Extraversion is sociability, agreeableness is kindness, openness is creativity and intrigue, conscientiousness is thoughtfulness, and neuroticism often involves sadness or emotional instability.

Understanding what each personality trait is and what it means to score high or low in that trait can give you insight into your own personality —without taking a personality traits test . It can also help you better understand others, based on where they fall on the continuum for each of the personality traits listed.

An Easy Way to Remember the Big 5

Some use the acronym OCEAN (openness, conscientiousness, extraversion, agreeableness, and neuroticism) to remember the Big 5 personality traits. CANOE (for conscientiousness, agreeableness, neuroticism, openness, and extraversion) is another option.

History of the Big 5 Personality Theory

Trait theories of personality have long attempted to pin down exactly how many traits exist. Earlier theories have suggested various numbers. For instance, Gordon Allport's list contained 4,000 personality traits, Raymond Cattell had 16 personality factors, and Hans Eysenck offered a three-factor theory.

Many researchers felt that Cattell's theory was too complicated and Eysenck's was too limited in scope. As a result, the Big 5 personality traits emerged and are used to describe the broad traits that serve as building blocks of personality .

Several researchers support the belief that there are five core personality traits. Evidence of this theory has been growing for many years in psychology, beginning with the research of D. W. Fiske (1949), and later expanded upon by others, including Norman (1967), Smith (1967), Goldberg (1981), and McCrae & Costa (1987).

The Big 5 Personality Traits

It is important to note that each of the five primary personality traits represents a range between two extremes. For example, extraversion represents a continuum between extreme extraversion and extreme introversion. In the real world, most people lie somewhere in between.

While there is a significant body of literature supporting these primary personality traits, researchers don't always agree on the exact labels for each dimension. That said, these five traits are usually described as follows.

Openness (also referred to as openness to experience) emphasizes imagination and insight the most out of all five personality traits. People who are high in openness tend to have a broad range of interests. They are curious about the world and other people and are eager to learn new things and enjoy new experiences.

People who are high in this personality trait also tend to be more adventurous and  creative . Conversely, people low in this personality trait are often much more traditional and may struggle with abstract thinking.

Very creative

Open to trying new things

Focused on tackling new challenges

Happy to think about abstract concepts

Dislikes change

Does not enjoy new things

Resists new ideas

Not very imaginative

Dislikes abstract or theoretical concepts

Conscientiousness

Among each of the personality traits, conscientiousness is one defined by high levels of thoughtfulness, good impulse control, and goal-directed behaviors. Highly conscientious people tend to be organized and mindful of details. They plan ahead, think about how their behavior affects others, and are mindful of deadlines.

Someone scoring lower in this primary personality trait is less structured and less organized. They may procrastinate to get things done, sometimes missing deadlines completely.

Spends time preparing

Finishes important tasks right away

Pays attention to detail

Enjoys having a set schedule

Dislikes structure and schedules

Makes messes and doesn't take care of things

Fails to return things or put them back where they belong

Procrastinates  important tasks

Fails to complete necessary or assigned tasks

Extraversion

Extraversion (or extroversion) is a personality trait characterized by excitability, sociability, talkativeness, assertiveness, and high amounts of emotional expressiveness. People high in extraversion are outgoing and tend to gain energy in social situations. Being around others helps them feel energized and excited.

People who are low in this personality trait or introverted tend to be more reserved. They have less energy to expend in social settings and social events can feel draining. Introverts often require a period of solitude and quiet in order to "recharge."

Enjoys being the center of attention

Likes to start conversations

Enjoys meeting new people

Has a wide social circle of friends and acquaintances

Finds it easy to make new friends

Feels energized when around other people

Say things before thinking about them

Prefers solitude

Feels exhausted when having to socialize a lot

Finds it difficult to start conversations

Dislikes making small talk

Carefully thinks things through before speaking

Dislikes being the center of attention

Agreeableness

This personality trait includes attributes such as trust,  altruism , kindness, affection, and other  prosocial behaviors . People who are high in agreeableness tend to be more cooperative while those low in this personality trait tend to be more competitive and sometimes even manipulative.

Has a great deal of interest in other people

Cares about others

Feels empathy and concern for other people

Enjoys helping and contributing to the happiness of other people

Assists others who are in need of help

Takes little interest in others

Doesn't care about how other people feel

Has little interest in other people's problems

Insults and belittles others

Manipulates others to get what they want

Neuroticism

Neuroticism is a personality trait characterized by sadness, moodiness, and emotional instability. Individuals who are high in neuroticism tend to experience mood swings , anxiety, irritability, and sadness. Those low in this personality trait tend to be more stable and emotionally resilient .

Experiences a lot of stress

Worries about many different things

Gets upset easily

Experiences dramatic shifts in mood

Feels anxious

Struggles to bounce back after stressful events

Emotionally stable

Deals well with stress

Rarely feels sad or depressed

Doesn't worry much

Is very relaxed

How to Use the Big 5 Personality Traits

Where you fall on the continuum for each of these five primary traits can be used to help identify whether you are more or less likely to have other more secondary personality traits. These other traits are often split into two categories: positive personality traits and negative personality traits.

Positive Personality Traits

Positive personality traits are traits that can be beneficial to have. These traits may help you be a better person or make it easier to cope with challenges you may face in life. Personality traits that are considered positive include:

• Considerate
• Cooperative
• Well-rounded

Negative Personality Traits

Negative personality traits are those that may be more harmful than helpful. These are traits that may hold you back in your life or hurt your relationships with others. (They're also good traits to focus on for personal growth.) Personality traits that fall in the negative category include:

• Egotistical

For example, if you score high in openness, you are more likely to have the positive personality trait of creativity. If you score low in openness, you may be more likely to have the negative personality trait of being unimaginative.

Universality of Primary Personality Traits

McCrae and his colleagues found that the Big 5 personality traits are remarkably universal. One study that looked at people from more than 50 different cultures found that the five dimensions could be accurately used to describe personality.

Based on this research, many psychologists now believe that the five personality dimensions are not only universal but that they also have biological origins. Psychologist David Buss has proposed an evolutionary explanation for these five core personality traits, suggesting that they represent the most important qualities that shape our social landscape.

Factors Influencing Personality Traits

Research suggests that both biological and environmental influences play a role in shaping our personalities. Twin studies suggest that both nature and nurture play a role in the development of each of the five personality traits.

One study of the genetic and environmental underpinnings of the five traits looked at 123 pairs of identical twins and 127 pairs of fraternal twins. The findings suggested that the heritability of each personality trait was 53% for extraversion, 41% for agreeableness, 44% for conscientiousness, 41% for neuroticism, and 61% for openness. 

Longitudinal studies also suggest that these big five personality traits tend to be relatively stable over the course of adulthood. One four-year study of working-age adults found that personality changed little as a result of adverse life events .

Studies show that maturation may have an impact on the five personality traits. As people age, they tend to become less extraverted, less neurotic, and less open to an experience. Agreeableness and conscientiousness, on the other hand, tend to increase as people grow older.

A Word From Verywell

Always remember that behavior involves an interaction between a person's underlying personality and situational variables. The situation that someone finds themselves in plays a role in how they might react . However, in most cases, people offer responses that are consistent with their underlying personality traits.

These dimensions represent broad areas of personality. But personality is also complex and varied. So, a person may display behaviors across several of these personality traits.

The big 5 personality theory is widely accepted today because this model presents a blueprint for understanding the main dimensions of personality. Experts have found that these traits are universal and provide an accurate portrait of human personality.

The big 5 personality model is not a typology system, so there are no specific "types" identified. Instead, these dimensions represent qualities that all people possess in varying amounts. One study found that most people do tend to fall into one of four main types based on the Big 5 traits:  

• Average (the most common type, characterized by high levels of extroversion and neuroticism and low levels of openness)
• Self-centered (high in extroversion and low in conscientiousness, openness, and agreeableness)
• Reserved (low on extroversion, neuroticism, and openness, and high on conscientiousness and agreeableness)
• Role models (high on every big 5 trait other than neuroticism)

Power RA, Pluess M. Heritability estimates of the Big Five personality traits based on common genetic variants . Translation Psychiatry . 2015;5:e604. doi:10.1038/tp.2015.96

Jang KL, Livesley WJ, Vernon PA. Heritability of the big five personality dimensions and their facets: a twin study . J Pers . 1996;64(3):577-91. doi:10.1111/j.1467-6494.1996.tb00522.x

Gerlach M, Farb B, Revelle W, Nunes Amaral LA. A robust data-driven approach identifies four personality types across four large data sets . Nat Hum Behav . 2018;2(10):735-742.

 doi:10.1038/s41562-018-0419-z

Cobb-Clark DA, Schurer S. The stability of big-five personality traits . Econ Letters . 2012;115(2):11–15. doi:10.1016/j.econlet.2011.11.015

Lang KL, Livesley WJ, Vemon PA. Heritability of the big five personality dimensions and their facets: A twin study . J Personal . 1996;64(3):577–591. doi:10.1111/j.1467-6494.1996.tb00522.x

Marsh HW, Nagengast B, Morin AJS. Measurement invariance of big-five factors over the lifespan: ESEM tests of gender, age, plasticity, maturity, and la dolce vita effects . Develop Psychol . 2013;49(6):1194-1218. doi:10.1037/a0026913

McCrae RR, Terracciano A, Personality Profiles of Cultures Project. Universal features of personality traits from the observer's perspective: Data from 50 different cultures . J Personal Soc Psychol. 2005;88:547-561. doi:10.1037/0022-3514.88.3.547

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Module 12: Personality Disorders

Case studies: personality disorders, learning objectives.

• Identify personality disorders in case studies

Case Study: Latasha

Latasha was a 20-year-old college student who lived in the dorms on campus. Classmates described Latasha as absent-minded and geeky because she didn’t interact with others and rarely, if ever, engaged with classmates or professors in class. She usually raced back to her dorm as soon as classes were over. Latasha primarily stayed in her room, did not appear to have any friends, and had no interest in the events happening on campus. Latasha even asked for special permission to stay on campus when most students went home for Thanksgiving break.

Now let’s examine some fictional case studies.

Case Study: The Mad Hatter

The Mad Hatter, from Alice in Wonderland , appears to be living in a forest that is part of Alice’s dream. He appears to be in his mid-thirties, is Caucasian, and dresses vibrantly. The Mad Hatter climbs on a table, walks across it, and breaks plates and teacups along the way. He is rather protective of Alice; when the guards of the Queen of Hearts come, he hides Alice in a tea kettle. Upon making sure that Alice is safe, Mad Hatter puts her on his hat, after he had shrunk her, and takes her for a walk. While walking, he starts to talk about the Jabberwocky and becomes enraged when Alice tells him that she will not slay the Jabberwocky. Talking to Alice about why she needs to slay the Jabberwocky, the Mad Hatter becomes emotional and tells Alice that she has changed.

The Mad Hatter continues to go to lengths to protect Alice; he throws his hat with her on it across the field, so the Queen of Heart’s guards do not capture her. He lies to the Queen and indicates he has not seen Alice, although she is clearly sitting next to the Queen. He decides to charm the Queen, by telling her that he wants to make her a hat for her rather large head. Once the White Queen regained her land again, the Mad Hatter is happy.

Case Study: The Grinch

The Grinch, who is a bitter and cave-dwelling creature, lives on the snowy Mount Crumpits, a high mountain north of Whoville. His age is undisclosed, but he looks to be in his 40s and does not have a job. He normally spends a lot of his time alone in his cave. He is often depressed and spends his time avoiding and hating the people of Whoville and their celebration of Christmas. He disregards the feelings of the people, knowingly steals and destroys their property, and finds pleasure in doing so. We do not know his family history, as he was abandoned as a child, but he was taken in by two ladies who raised him with a love for Christmas. He is green and fuzzy, so he stands out among the Whos, and he was often ridiculed for his looks in school. He does not maintain any social relationships with his friends and family. The only social companion the Grinch has is his dog, Max. The Grinch had no goal in his life except to stop Christmas from happening. There is no history of drug or alcohol use.

• Modification, adaptation, and original content. Authored by : Julie Manley for Lumen Learning. Provided by : Lumen Learning. License : CC BY: Attribution
• Case Studies: The Grinch. Authored by : Dr. Caleb Lack and students at the University of Central Oklahoma and Arkansas Tech University. Located at : https://courses.lumenlearning.com/abnormalpsychology/chapter/antisocial-personality-disorder/ . License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
• The Mad Hatter. Authored by : Loren Javier. Located at : https://www.flickr.com/photos/lorenjavier/4031000212/ . License : CC BY-ND: Attribution-NoDerivatives
• The Grinch. Located at : https://pixy.org/1066311/ . License : CC0: No Rights Reserved

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Psychol Res Behav Manag
• PMC10894521

Research on the Relations Among Personality Traits, Sports Commitment, and Exercise Behavior — A Case Study of Chinese College Students

Zhendong zhang.

1 School of Physical Education, Zhengzhou Sias University, Zhengzhou, People’s Republic of China

Yonghuan Chen

2 Department of Marine Sports, Pukyong National University, Busan, South Korea

3 School of Physical Education (Main Campus), Zhengzhou University, Zhengzhou, People’s Republic of China

4 Department of Sports Science, Jeonbuk National University, Jeonju-si, South Korea

To explore the relations among personality traits, sports commitment, and exercise behavior of Chinese college students. To test whether sports commitment plays an intermediary role in the process of personality traits affecting exercise behavior. To explore the factors that affect Chinese college students’ exercise behavior from the psychological level, to promote college students to actively participate in physical exercise.

A questionnaire survey was conducted on 1200 students from 6 universities using the “Personality Trait Scale”, “Sports Commitment Scale” and “Exercise Behavior Scale”. SPSS was used to analyze the differences between genders and urban and rural areas; and correlation analysis was conducted on the personality traits, sports commitment, and exercise behaviors of college students. Finally, AMOS was used to establish a structural equation model to test the mediating role of sports commitment.

There are significant differences between different genders in each factor of personality traits ( P <0.05); there is no significant difference between different genders in the participation opportunities of sports commitment ( P =0.734), and there are significant differences in other factors. There were significant differences in each factor of exercise behavior ( P <0.05). There were no significant differences in personality traits, sports commitment, and exercise behavior between urban and rural students ( P > 0.05). There was a significant correlation among personality traits, sports commitment, and exercise behavior ( P < 0.01). The direct effect of personality traits on exercise behavior was not significant ( P > 0.05), but there was only the mediating effect of sports commitment.

There is a significant correlation among Chinese college students’ personality traits, sports commitment, and exercise behavior. Sports commitment plays an intermediary role between personality traits and sports commitment. Improving the level of sports commitment can encourage Chinese college students to participate in physical exercise.

Introduction

In recent years China has enacted several policies aimed at improving the physical fitness and health of Chinese university students. According to the survey results of Wang Keping (2021), 45.8% of college students exercise less than 3 times a week, 87% exercise time less than 45 minutes, and 89.9% exercise intensity is moderate or below, showing the characteristics of little exercise frequency, duration, and intensity. 1 Physical exercise is the behavior of individuals to achieve certain exercise goals through physical means. 2 It has a positive effect on promoting physical health, strengthening will, 3 improving self-efficacy, 4 and happiness. 5 It is also a good means of regulating the mind and body. In recent years, many scholars have conducted detailed discussions on the factors affecting physical exercise from different perspectives. In terms of social factors, scholars have discussed it from the perspectives of family sports environment; 6 school sports environment; 7 social stratification theory. 8 In terms of individual factors, scholars have conducted research from the perspectives of college students’ stress levels, health conditions and athletic abilities, 9 genetics and emotional dependence on sports, 10 anxiety, 11 motivation, 12 and sports friendships. 13 In the long-term exploration and research of sports psychologists, the factors that explain and predict people’s exercise behavior have been highly summarized, and now the protective motivation theory, 14 self-determination theory, 15 and the theory of planned behavior have been formed. Theories such as, 16 health belief theory, 17 and social cognitive theory. 18 These theories explain and predict the occurrence of human sports behavior to a certain extent by building models that affect people’s participation in physical exercise behavior. However, the occurrence of human social behavior is a complex mechanism, so there are still many factors that affect the occurrence of exercise behavior that have not attracted the attention of Chinese academic circles, such as personality traits and sports commitment studied in this study.

Since it was put forward, personality traits have been widely concerned by personality psychologists and developed a variety of personality trait theories, including Cattell personality trait theory, Big Five personality trait theory, and so on. On this basis, a large number of sports psychologists and related scholars introduce the theory of personality traits into the field of sports and use empirical studies to show the influence of personality traits on exercise behavior and prove that personality traits as a stable and lasting psychological resource play a certain role in manipulating individual exercise behavior, predicting individual behavior and affecting individual health. 19 Since the theory of sports commitment was put forward in the 1990s, although some researchers have also proved the effectiveness of this theory in promoting people’s exercise behavior through empirical research, it has not caused much response in China. It is also rare to apply this theory to the empirical research of related groups in China. At the same time, there are fewer articles on the relationship between personality traits and sports commitment. A search of WOS with the keywords “personality traits” and “exercise behavior” revealed only two studies conducted by Korean scholars on Korean residents; a search of CNKI with the same keywords revealed only one related article. In addition, the pandemic of the COVID-19 provides a special environment for possible changes in personality traits, sports commitment, and exercise behavior of Chinese college students. Therefore, this study analyzed the relationship between personality traits, sports commitment and exercise behavior among Chinese college students through an empirical investigation. To provide a reference for shaping college students’ positive personalities, promoting college students to participate in physical exercise, and improving their physical and mental health. It also lays the foundation for future researchers to compare the changes in personality traits, sports commitment and exercise behavior of Chinese college students before and after the COVID-19.

Theory and Hypothesis

The relations between personality traits and exercise behavior.

Personality is the dynamic organization in an individual’s internal psychophysical system, which determines a person’s unique behavior and thoughts. A trait is a kind of neural structure with a certain physiological basis. Stimulating this nervous system can make the individual show an equivalent state of function and induce the same form of adaptability and expressive behavior. 20 Albert believes that personality is the product of the combination of individual material body system and non-material spiritual system, with uniqueness and integration, and the ability to promote and guide individual behavior. In terms of external stimulus input, the ever-changing situations of individuals with similar characteristics are regarded as similar; in terms of behavioral output, individuals with different characteristics show different stress and adaptation styles.

Since personality traits were put forward, a variety of personality trait theories have been formed under the research of personality psychologists such as Alport, Carter, Eysenck, and so on. In particular, the proposal of the five-factor personality theory has set off a “revolution” in the field of personality psychology. The five-factor personality theory includes five factors: conscientiousness, neuroticism, openness, agreeableness, and extroversion. Costa and McCrae developed the Big Five Personality Scale 21 according to the definition of five factors of personality traits and long-term research on personality traits. After the introduction of personality trait theory into China, some scholars revised the Personality trait scale because of the differences between Chinese and foreign cultures, to make the revised scale and its sentence expression more prominent the unique personality characteristics of Chinese people. Finally, the Chinese personality scale and the corresponding seven-factor model are formed. Wang Mengcheng also developed a simplified version of the Big Five Personality questionnaire based on the Chinese Big Five Personality questionnaire.

In the existing research, some scholars use the Big Five personality model to do empirical research on college students’ exercise behavior, 22 sports preference, 23 and exercise motivation, 24 and find that personality traits play a significant role. Some studies take the elderly group 25 as the object of investigation, and confirm that personality traits play a significant role in promoting leisure sports activities and improving the cognitive level of the elderly. Some scholars use meta-analysis to investigate the literature related to personality traits 26 and exercise behavior. 27 The results show that personality traits play an important role in promoting the mechanism of exercise behavior. Based on this, the hypothesis is put forward:

H1: College students’ personality traits are significantly correlated with physical exercise behavior.

The Relations Between Sports Commitment and Exercise Behavior

Social psychologists generally believe that in the field of sports, Commitment refers to conditions that help to explain a person’s persistent course of action, or the stability and persistence of a relations. 28 Sports commitment refers to a psychological state of desire and determination to continue to participate in sports. 29 The theoretical model of sports commitment was first put forward by Scanlan and other scholars in 1993. In this study, the theoretical model of sports commitment includes five antecedents: sports fun, Involvement Alternatives, Personal investment, social constraint, and participation opportunity. However, due to errors in the measurement of the “Involvement Alternatives”, only the remaining four variables were finally verified. In subsequent research, Scanlan improved the sport commitment model, added the “social support” variable, and verified the validity of the revised model in the study of the determinants of sport commitment in tennis players. The sport commitment model was developed as a 6-factor. Scanlan used the sports commitment theoretical model twice to measure the commitment level of young athletes through self-reported scales. The final research results showed that sports fun, personal investment, participation opportunities, and physical exercise investment showed a significant positive correlation. However, social constraints and Involvement Alternatives did not show a significant correlation with exercise investment. 28 At the same time, the structural equation model shows that the data fit well ( CFI =0.981). 30 Subsequently, in the tests of athletes in various sports by Guillet (2022), 31 and Zahariadis (2006), 32 it was proved that the athletes’ sports commitment level and exercise behavior were significantly positively correlated.

After the sports commitment theory was introduced into China, Chen Shanping (2005) 33 tested the sports commitment of some Chinese students. The results showed that sports commitment and exercise conditions can better explain and predict college students’ physical exercise behavior (R2=0 0.819), and it is more reliable to use the sports commitment theoretical model to explain and predict the path of college students’ exercise behavior (r=0.908). Chen Shanping 34 proposed a cognitive decision-making model with sports commitment as the core in 2006. This model takes sports commitment as the core explains its generation mechanism, and considers individual factors, social factors, and behavioral characteristics as factors that influence individual cognition. Motivational orientation, effect evaluation, and self-efficacy are regarded as the psychological decision-making process that affects sports commitment, and it is believed that effect evaluation has the greatest impact on college students’ sports commitment. Then, by testing the relations among sports commitment, exercise motivation, and exercise behavior, some scholars proved that there was a significant correlation among exercise motivation, exercise effectiveness, and sports commitment. Therefore, if we want to improve the willingness of college students to participate in physical exercise consciously, we need to first enhance their psychological dependence on physical exercise, that is, to improve their sports commitment level. Based on this, the hypothesis is put forward:

H2: There is a significant correlation between college students’ sports commitment and physical exercise behavior.

The Relations Between Personality Traits and Sports Commitment

Regarding the research on the relations between personality traits and sports commitment, Korean scholar Huang Sunhuan (2018) 35 studied the relations between personality traits, sports commitment, and exercise addiction across fitness participants. After analyzing 219 participants, it was found that personality traits are one of the important variables affecting sports commitment and exercise addiction. At the same time, there are differences in the impact of personality traits on sports commitment and exercise addiction. Participants with high levels of extraversion and agreeableness showed stronger sports commitment; participants with high levels of extraversion and neuroticism showed stronger sports commitment. Participants showed higher levels of exercise addiction; participants with high levels of agreeableness showed lower levels of exercise addiction. There are currently few academic studies on the relations between personality traits and sports commitment, but some scholars have studied personality traits and exercise motivation and believe that the traits of extraversion, conscientiousness, and agreeableness have a significant positive impact on exercise motivation; neurotic personality Indirectly influencing exercise motivation through trait mindfulness. 36 Sports motivation can also be reflected through sports commitment. However, there are few studies on the relations between personality traits and sports commitment. The biggest advantage of sports commitment is that it can reflect the latent psychological state of the individual to a certain extent, and reflect the correlation between the individual’s psychological state and exercise, as well as the psychological comprehensiveness of observing the occurrence of individual exercise behavior. Therefore, the hypothesis is put forward:

H3: There is a significant correlation between college students’ personality traits and sports commitment.

H4: Sports commitment has a mediating effect between personality traits and physical exercise behavior.

Based on the above theories and hypotheses, this study selected college students’ personality traits as the independent variable, physical exercise behavior as the dependent variable, and sports commitment as the mediating variable.

Materials and Methods

Samples and procedures.

This study adopted strict procedural controls. In the design of the questionnaire, the item numbers of the sports commitment and personality traits scale were rearranged, and the reverse scoring items designed by the original scale were retained. Then, according to the ranking of universities in Henan Province in 2023 released by Soft Science China, the students of Zhengzhou University, Henan University of Technology, Nanyang Normal University, Luoyang Institute of Technology, Pingdingshan College, and Zhengzhou Institute of Engineering and Technology were selected by isometric sampling. Questionnaires were issued between June 6, 2023, and June 30, 2023. The survey was conducted through the “Questionnaire Star”, and students from the target institution were asked to assist in distributing and explaining the content of the survey, and a cover letter explaining the purpose of the survey was included on the front page of the questionnaire so that each participant could understand the content of the survey. Finally, 1269 questionnaires were collected, and 1200 valid questionnaires were obtained after eliminating invalid questionnaires (due to missing items or an insufficient response time). Among the students surveyed, 292 were from Zhengzhou University (24.33%), 221 from Henan University of Technology (18.42%), 179 from Nanyang Normal University (14.92%), 153 from Luoyang Institute of Technology (12.75%), 159 from Pingdingshan College (13.25%) and 196 people (16.33%) from Zhengzhou Institute of Engineering and Technology. In terms of gender, there were 598 boys (49.83%) and 602 girls (50.17%). In terms of grade distribution, the number of freshmen is 316 (26.33%), the number of sophomores and juniors is 220 (18.33%), and the number of seniors and graduate students is 222 (18.50%). There were 562 (46.83%) from urban areas and 638 (53.17%) from rural areas.

Research Tool

Personality traits scale.

This study adopts the simplified version of the personality questionnaire developed by Wang Mengcheng and Dai Xiaoyang (2011) 37 according to the Chinese Big Five Personality questionnaire. This questionnaire has 8 measurement items for each personality type, so there are 40 measurement items in total. In terms of scoring method, a 6-point Likert scoring method was used, ranging from “completely inconsistent” represented by the number 1 to “completely consistent” represented by the number 6. Cronbach coefficient showed that neuroticism Cronbach’sα= 0.815, conscientious Cronbach’sα=0.801, agreeable Cronbach’sα= 0.725, open Cronbach’sα= 0.808, extroverted Cronbach’sα= 0.820, indicating good reliability. Confirmatory factor analysis was carried out on the personality scale, the results showed that X ²= 186.992, X ²/ df=1.851, GIF =0.956, AGIF =0.955, CFI =0.937, RMSEA =0.017, indicating that the fit degree of the model was acceptable.

Sports Commitment Scale

This paper uses the sports commitment scale revised by Chen Shanping (2012) 38 for college students in the context of exercise. In the scoring method, the scale uses Likert’s 6-point scoring method. From the number 1 represents “totally disagree” to the number 6 represents “complete agreement”. In terms of content, the scale is composed of six commitment determinants. Cronbach coefficient showed that satisfaction Cronbach’sα=0.762, social constraint Cronbach’sα= 0.746, Involvement Alternatives Cronbach’sα=0.931, social support Cronbach’sα= 0.800, Personal investment Cronbach’sα=0.829, participation opportunity Cronbach’sα=0.752. Confirmatory factor analysis was performed on the sports commitment scale, the results showed that X ²= 198.358, X ²/df=1.338, GIF =0.931, AGIF =0.939, CFI =0.944, RMSEA =0.021, indicating that the fit degree of the model was acceptable.

Exercise Behavior Scale

Measures of exercise behavior included exercise intensity, exercise time, exercise frequency, and exercise persistence. Cronbach coefficient shows that Cronbach’sα of exercise behavior is 0.762, indicating good reliability. Confirmatory factor analysis was performed on the exercise behavior scale, and the results showed that X ²=173.938 ( P =0.000), X 2 /df=1.479, GIF =0.949, AGIF =0.952, CFI =0.935, RMSEA =0.029, indicating that the fit degree of the model was acceptable.

Data Analysis

After preprocessing the collected data, SPSS21.0 was used for descriptive statistics; an independent sample T -test was used to analyze the differences between gender and urban and rural areas; the Pearson correlation test was used to analyze the correlation; finally, AMOS was used to establish a structural model to test the mediating effect of sports commitment between personality traits and exercise behavior.

Common Method Deviation

To avoid the deviation of common methods, this study carried out strict program control and a series of tests. In the design of the questionnaire, the question numbers of the personality traits and sports commitment scale were rearranged, and the reverse score questions of the scale were retained; when the questionnaire was sent to the respondents, the client was asked to emphasize the anonymity of the questionnaire, the confidentiality of the information and the authenticity of the content. The collected data are tested by a common method deviation test with SPSS. The results show that a total of 14 common factors are extracted by principal component analysis before rotation, of which the first factor explains only 18.241% of all variants, which is less than the standard of 40% critical value. Then, using AMOS, further using single-factor confirmatory analysis to verify. After comparing the fitting indexes of the single-factor model and the original model, the results show that the model fitness of the single-factor model does not meet the requirements, in which X ²/ df=20.507, GFI=0.633, AGFI=0.520, CFI =0.567, RMSEA =0.180. It means that compared with the original model, the fitting index of the single-factor model is very poor, so it can be determined that the common method of the data used in this study does not have a serious deviation.

Difference Analysis

An Independent sample T -test was used to test whether there were significant differences in personality traits, sports commitment, and exercise behavior between different genders. The results are shown in Table 1–3 . In terms of personality traits, the P values of independent samples of personality traits of different genders are all less than 0.05, indicating that there are significant differences in all factors of personality traits between boys and girls. In terms of sports commitment, except for the P value of “participation opportunity”, which shows that there is no significant difference between boys and girls in “participation opportunity”, the P values of other factors are less than 0.05, indicating that there are significant differences between boys and girls in these factors. In terms of exercise behavior, the P values of all factors of exercise behavior between boys and girls are less than 0.05, indicating that there is a significant difference.

Differences in Personality Traits Between Genders

Differences in Sports Commitment Between Genders

Differences in Exercise Behavior Between Genders

Subsequently, an independent samples T -test was used to test whether there are significant differences in personality traits, sports commitment, and exercise behavior between students from urban and rural areas. The test results are shown in Table 4 . The P values of the three variables of personality traits, sports commitment, and exercise behavior are all greater than 0.05 in the place of origin, indicating that urban or rural household registration is not the main factor affecting college students’ personality traits, sports commitment, and exercise behavior.

Analysis of Differences in Personality Traits, Sports Commitment, and Exercise Behavior Between Urban and Rural Students

Correlation Analysis

To understand whether there is a correlation between personality traits, sports commitment, and exercise behavior. Variables were analyzed using Pearson’s correlation test. The results are shown in Table 5–8 . There were significant correlations between personality traits, sports commitment, and exercise behavior ( P <0.01). Therefore, H1, H2, and H3 were confirmed. Then the factors of the variable were analyzed. Neuroticism was negatively correlated with exercise time, exercise frequency, exercise intensity, and exercise persistence ( P < 0.01). Extroversion, openness, and exercise behavior showed a significant positive correlation ( P < 0.01). There is no significant correlation between agreeableness and all factors of exercise behavior. Conscientiousness was positively correlated with exercise time ( P < 0.05) and exercise persistence ( P < 0.01), but not with exercise frequency and intensity. There was a significant positive correlation between satisfaction, participation opportunity, Personal investment, and exercise behavior ( P < 0.01). There was a significant negative correlation between social constraints and exercise behavior ( P < 0.01). In terms of participation selection, except that there was no significant correlation between exercise time and exercise persistence, there was a significant negative correlation with other factors of exercise behavior ( P < 0.01). Social support had a significant positive correlation with exercise time and exercise persistence ( P < 0.01) and a significant negative correlation with exercise frequency ( P < 0.01), but no significant correlation with exercise intensity. Neuroticism was positively correlated with social constraints and Involvement Alternatives in sports commitment (P < 0.01), but not with social support, but negatively correlated with other factors (P < 0.01). There was a significant positive correlation between conscientiousness and social support, satisfaction, and participation opportunities of sports commitment (P < 0.01), but there was no significant correlation between conscientiousness and Personal investment and Involvement Alternatives . There was a significant negative correlation between conscientiousness and social constraints (P < 0.01). There was a significant positive correlation between agreeableness and Personal investment, participation opportunities, and social support (P < 0.01), there was no significant correlation between agreeableness and Involvement Alternatives, and there was a significant negative correlation between conscientiousness and social constraints (P < 0.01). Openness was not significantly correlated with social constraints of sports commitment, but negatively correlated with Involvement Alternatives and social support (P < 0.01), and positively correlated with other factors (P < 0.01). Extroversion has no significant correlation with satisfaction of sports commitment, Involvement Alternatives, and Personal investment, but has a significant negative correlation with social constraints (P < 0.01), and a significant positive correlation with other factors (P < 0.01).

Correlation Analysis of Personality Traits, Sports Commitment, and Exercise Behavior of Chinese College Students

Note : ** P < 0.01.

Correlation Analysis of Personality Traits and Exercise Behavior of Chinese College Students

Notes : ** P < 0.01. * P <0.05.

Correlation Analysis of Various Factors of Sports Commitment and Exercise Behavior of Chinese College Students

Correlation Analysis of Personality Traits and Sports Commitment Factors of Chinese College Students

Note : **P< 0.01.

Intermediary Test

This study adopts the Bootstrap testing process proposed by Wen Zhonglin. 39 There are five steps in this process: the first step is to test whether the coefficient c is significant. If it is significant, it is based on the mediation effect; if it is not significant, it is based on the masking effect. But regardless of whether the coefficient c is significant, subsequent tests should continue. The second step is to test whether coefficients a and b are significant in turn. If both coefficients a and b are significant, which means there is a significant indirect effect, then the subsequent test will proceed directly to the fourth step; if either coefficient a or b is insignificant, proceed to the third step. The third step is to use the Bootstrap method to test H0: ab=0. If it is significant, it means that there is a significant indirect effect, then proceed to the fourth step; if it is not significant, it means that the indirect effect is not significant, and subsequent analysis will be stopped. The fourth step is to test the coefficient c’. If it is not significant, it means that the direct effect is not significant, which means that there is only a mediating effect; if it is significant, it means that the direct effect is significant, then proceed to the fifth step. The fifth step is to compare whether ab and c’ have both positive or negative signs. If the signs are the same, it indicates the existence of a mediating effect, and the proportion of the mediating effect to the total effect ab/c is reported; if the signs are different, it is judged to be a masking effect, and the absolute value of the proportion of the mediating effect to the direct effect is reported |ab/c’|.

Model Fit Test

First, the model fitting degree of the structural equation model of personality traits, sports commitment, and exercise behavior was tested. Only when the model fitting degree meets the requirements, the subsequent analysis will be meaningful. If the model fitting degree does not meet the requirements, the model can be optimized by limiting, adding, or deleting paths without violating the principles assumed by the model to make the model structure reasonable. 40 After modifying and optimizing the model, the values of each adaptation index of the standardized model can be seen in Table 9 . The chi-square value is 123.315 ( P <0.05), X 2 / df =1.475; GIF =0.912; AGIF =0.955; CFI = 0.979; RMSEA =0.051. Based on the above fitting index, the model fit after optimization and correction is better. Subsequently, a structural equation model of personality traits, sports commitment, and exercise behavior was established. The results are shown in Table 10 and Figure 1 . The standardized estimates of the three coefficients are a=0.734, b=0.752, and c’=0.076. The coefficients a and b reach a significant level, but the coefficient c’ is not significant, which means that the direct effect of personality traits on exercise behavior is not significant. It turns out that there is only the mediating effect of sports commitment. Therefore H4 was confirmed.

Summary Table of Mediation Model Fit

Abbreviations : X 2 , Chi-Square; X 2 /df, Chi-Square/Degrees of freedom; GFI, Goodness of Fit Index; AGFI, Adjusted Goodness-of-Fit Index; CFI, Comparative Fit Index; RMSEA, Root Mean Square Error of Approximation.

Summary of Model Standardized Regression Coefficients

Note : *** P <0.001.

Abbreviations : S.E, Standard Error; C.R, Regression Weight/Standard Errors.

Structural Equation Modelling of Personality Traits, Sports Commitment and Exercise Behaviour.

In terms of the differences between men and women in personality traits, there are significant differences in personality traits among college students of different genders in Henan Province. Among them, the average scores of neuroticism, conscientiousness, and agreeableness of girls were higher than those of boys, while the scores of openness and extroversion of boys were higher than those of girls. The results are also consistent with the commonly believed personality differences between boys and girls: girls are more sensitive, more careful, and more sociable, while boys are more open-minded. More likely to participate in social activities. 41 Some researchers also found that there is a correlation between personality traits and gender, and boys and girls show differences in different factors of personality traits. 42 In terms of the difference between men and women in sports commitment, only the participation opportunity factor did not show gender differences, and in other factors, the average level of satisfaction and Personal investment of boys was higher than that of girls, indicating that boys were stronger in internal participation motivation, and the sense of satisfaction achieved by motivation prompted them to invest more resources to participate in sports. 43 The average value of girls is higher than that of boys in terms of social constraints, Involvement Alternatives, and social support, which is due to the low internal motivation of girls to participate in physical exercise under the pressure of social constraints 44 and the lack of professional guidance in the process of physical exercise. 45 As a result, girls will give up participating in sports when they have other alternative recreational activities and thus need more encouragement and support from others. This is also similar to Ren Zhuoran’s research results. 46 In terms of exercise behavior, college students show significant differences between men and women, and the average values of exercise time, frequency, and intensity and the total amount of exercise for boys are higher than those for girls. Comprehensive related research, the reasons include physiological, 47 psychological, 48 social 49 and cultural, 50 and so on. Boys are generally stronger than girls in physical qualities such as strength, speed, and endurance, and the motivation of boys to participate in sports is generally higher than that of girls. At the same time, in the human social environment and culture, men are always expected to become strong, resolute, and resilient people, while women are expected to be educated, gentle, and virtuous people. 51 The influence of this social culture is reflected in all aspects, as well as in the differences between boys and girls in sports. Urban or rural students have no significant difference in college students’ personality traits, sports commitment, and exercise behavior, which indicates that although the growth environment of urban or rural areas has an impact on human development, however, human development and growth are affected comprehensively in many aspects, while the impact of urban or rural on college students is limited. 52

In terms of correlation, there is a significant correlation among college students’ personality traits, sports commitment, and exercise behavior. A large number of previous studies have proved that personality traits are related to exercise behavior, sports commitment, and exercise behavior. Although there are few studies on the relations between personality traits and sports commitment, it also shows that there is a correlation between personality traits and sports commitment. In this study, the test and analysis of different people at different times and places also confirmed the relations between the three again. This is consistent with previous studies. In the correlation analysis of personality traits and exercise behavior factors, only neuroticism had a significant negative correlation with exercise behavior, while openness and extroversion had a significant positive correlation with exercise behavior factors. Therefore, the exercise behavior of college students can be promoted by reducing the level of neuroticism and improving the level of openness and extroversion. In the correlation between sports commitment and exercise behavior, only social constraints and exercise behavior factors have a significant negative correlation; Personal investment, satisfaction, participation opportunities, and exercise behavior factors show a significant positive correlation. Therefore, we should pay more attention to how to increase students’ Personal investment, enhance their sense of satisfaction, increase their Participation opportunities in physical exercise, and reduce their social constraints.

It can be known by constructing the structural equation model of personality traits, sports commitment and exercise behavior. The direct effect of personality traits on exercise behavior is not significant, indicating that there is only the mediating effect of sports commitment. At the same time, compared with sports commitment, personality trait is a more stable neuropsychological characteristic. Therefore, improving the level of sports commitment to encourage college students to participate in exercise is a more efficient way of psychological intervention.

There were significant gender differences in personality traits, sports commitment, and exercise behaviors, but there were no significant differences between students from urban areas or students from rural areas. Personality traits, sports commitment, and exercise behavior are significantly correlated, but each factor shows different correlations. The direct effect of personality traits on exercise behavior is not significant, indicating that there is only the mediating effect of sports commitment in the constructed model.

Limitations and Future Directions

The survey target group is relatively single. This study only takes some college students in China as the survey subjects. College students are a group of young people who are about to enter society. Their personalities are in a mature period and their mental health and physical fitness are facing a more severe situation, which has great research value. However, other groups such as middle-aged and elderly people and children also deserve attention, and future research should focus on investigating these groups.

Geographical limitations of data sources. The survey subjects of this study are only college students from some universities in Henan Province, and the sample’s source area is limited. Future research should expand the geographical scope of the survey respondents or add more sample sizes to verify the relations between personality traits, sports commitment, and exercise behavior among college students in other regions.

There is a lack of in-depth qualitative research. The results of this study only show the differences and whether there is a correlation between college students’ personality traits, sports commitment, and exercise behavior, and the level of the mediating effect of sports commitment. That is, through survey analysis, the specific relations results between college students’ personality traits, sports commitment, and exercise behavior are shown, but no more in-depth qualitative research methods are used to explore why this result occurs.

The influencing factors explored were limited. This study only explored the mediating role of sports commitment, but many psychological factors affect college students’ exercise behavior, such as trait mindfulness, social adaptability, positive psychological quality, body self-esteem, etc. Whether there is a connection between sports commitment and these psychological factors or whether there is a chain mediation effect to influences college students’ exercise behavior still requires more in-depth research in the future.

Funding Statement

No funding was received to assist with the preparation of this manuscript.

Statement of Human and Animal Rights

The present work did not involve human participants and/or animals.

Data Sharing Statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics Statement

This study was conducted in accordance with the Declaration of Helsinki. This study was approved by the Ethics Committee of Zhengzhou Sias University. Informed consent was obtained from all participants included in this study.

Consent for Publication

All authors had reviewed the final manuscript and gave consent for submission and publication.

Zhendong Zhang and Yonghuan Chen are co-first authors for this study. The authors declare that they have no conflicts of interest in this work.

• Study Guides
• Homework Questions

Case Study 2