eating disorder research papers

Eating disorders

Affiliations.

• 1 Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. Electronic address: [email protected].
• 2 Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; Serviço de Psiquiatria e Saúde Mental, Hospital de Santa Maria, Centro Hospitalar Universitário Lisboa Norte, Lisbon, Portugal.
• 3 Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; South London and Maudsley NHS Foundation Trust, London, UK.
• PMID: 32171414
• DOI: 10.1016/S0140-6736(20)30059-3

Eating disorders are disabling, deadly, and costly mental disorders that considerably impair physical health and disrupt psychosocial functioning. Disturbed attitudes towards weight, body shape, and eating play a key role in the origin and maintenance of eating disorders. Eating disorders have been increasing over the past 50 years and changes in the food environment have been implicated. All health-care providers should routinely enquire about eating habits as a component of overall health assessment. Six main feeding and eating disorders are now recognised in diagnostic systems: anorexia nervosa, bulimia nervosa, binge eating disorder, avoidant-restrictive food intake disorder, pica, and rumination disorder. The presentation form of eating disorders might vary for men versus women, for example. As eating disorders are under-researched, there is a great deal of uncertainty as to their pathophysiology, treatment, and management. Future challenges, emerging treatments, and outstanding research questions are addressed.

Copyright © 2020 Elsevier Ltd. All rights reserved.

Publication types

• Research Support, Non-U.S. Gov't
• Diagnosis, Differential
• Feeding and Eating Disorders* / diagnosis
• Feeding and Eating Disorders* / physiopathology
• Feeding and Eating Disorders* / psychology
• Feeding and Eating Disorders* / therapy
• Nutritional Status

• Open access
• Published: 29 April 2024

Self-reported health related quality of life in children and adolescents with an eating disorder

• A. Wever   ORCID: orcid.org/0000-0002-8877-5876 1 ,
• E. van Gerner 2 ,
• J.C.M Jansen 3 &
• B. Levelink 1  

BMC Psychology volume  12 , Article number:  242 ( 2024 ) Cite this article

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Metrics details

Eating disorders in children and adolescents can have serious medical and psychological consequences. The objective of this retrospective quantitative study is to gain insight in self-reported Health Related Quality of Life (HRQoL) of children and adolescents with a DSM-5 diagnosis of an eating disorder.

Collect and analyse data of patients aged 8–18 years, receiving treatment for an eating disorder. At the start and end of treatment patients completed the KIDSCREEN-52, a questionnaire measuring HRQoL.

Data of 140 patients were analysed. Children diagnosed with Anorexia Nervosa, Bulimia Nervosa, and Other Specified Feeding or Eating Disorder all had lower HRQoL on multiple dimensions at the start of treatment, there is no statistically significant difference between these groups. In contrast, patients with Avoidant Restrictive Food Intake Disorder only had lower HRQoL for the dimension Physical Well-Being. HRQoL showed a significant improvement in many dimensions between start and end of treatment, but did not normalize compared to normative reference values of Dutch children.

The current study showed that self-reported HRQoL is low in children with eating disorders, both at the beginning but also at the end of treatment. This confirms the importance of continuing to invest in the various HRQoL domains.

Peer Review reports

Eating disorders in children and adolescents can have serious medical and psychological consequences and rank 12th on the list of physical and mental conditions amongst woman aged 15–19 years in high-income countries when looking at the global burden of disease [ 1 , 2 ]. The estimated lifetime prevalence of Anorexia Nervosa (AN) in woman is 1–4% and 1–2% for Bulimia Nervosa (BN), and the epidemiology is changing, with increasing rates of eating disorders in younger children, boys and minority groups [ 2 , 3 ].

The past two decades research on health-related quality of life (HRQoL) in patients with an eating disorder has increased [ 4 , 5 , 6 , 7 , 8 ]. HRQoL is a subjective evaluation of the overall health of an individual, as well as the health of underlying subdimensions of physical, psychological and social functioning [ 9 ]. Most studies have been conducted in adults and a recent review and meta-analysis both show that eating disorders are associated with significant impaired HRQoL compared with the healthy population [ 10 , 11 ]. To our knowledge only one other study evaluated the impact of eating disorders on HRQoL in children and adolescents. Jenkins et al. looked at the impact of eating disorders in a group of adolescents seeking treatment for AN, BN or eating disorder not otherwise specified (EDNOS) [ 6 ]. This study reported a poorer HRQoL measured with the SF-36 Health Survey in adolescents with an eating disorder compared with adolescent norms for the Swedish population [ 6 ]. Two studies included both children and adolescents. Weigel et al. examined the association between disorder specific factors, comorbidity and HRQoL in anorexia nervosa in adolescents and adults. HRQoL was measured using the visual analogue scale (EQ-VAS) a generic scale that does not look to different HRQoL domains [ 12 ]. Ackard et al. assessed quality of life in patients diagnosed with an eating disorder, mean age at initial assessment was 20.6 years (SD 5 8.3 years), with a range of 12–53 years. Children were not assessed separatly. Other studies in children and adolescents focused on disordered eating behaviours, but not diagnosed eating disorders [ 4 ]. A review of population-based studies showed that disordered eating attitudes and behaviours were associated with lower HRQoL in children and adolescents [ 9 ]. Herpertz-Dahlmann and colleagues found a poorer HRQoL in adolescents with self-reported disordered eating, and an association between eating disorder symptoms and psychopathology [ 13 ].

Because treating an eating disorder encompasses more than weight gain alone it is important to know the possible impact of an eating disorder on HRQoL [ 14 ]. As there are still few studies on self-reported HRQoL in children and adolescents with a diagnosed eating disorder, the primary aim of this study is to gain more insight in the different domains of self-reported HRQoL in a clinical sample of children and adolescents with a DSM-5 diagnosis of an eating disorder at the beginning of treatment. In addition, changes of HRQoL between start and end of treatment were evaluated to determine whether treatment influences HRQoL and if so which domains.

Participant

Data of patients who were diagnosed conform the Diagnostic and Statistical Manual of Mental Disorders (DSM) -IV-TR/DSM-5 criteria for an eating disorder, and receiving treatment between November 2006 and April 2019 at The Mutsaersstichting were used [ 15 , 16 ]. The Mutsaersstichting is a mental healthcare institute specialised in eating disorders in the Netherlands where children between 0 and 18 years receive both in- and outpatient treatment. At first presentation, every patient received an extensive consultation with a child and youth psychologist, a child and youth psychiatrist and a paediatrician. Based on this information DSM-IV-TR and DSM-5 classification were made. Patients diagnosed before 2014 were rediagnosed using the DSM-5 classification, especially using the new criteria for Avoidant Restrictive Food Intake Disorder (ARFID). Subsequently, a personalized treatment plan was presented to the family. Treatment always consisted of a combination of family-based treatment, individual treatment, group treatment and physical follow-up. Data from patients who met the DSM-5 diagnosis for AN, BN, ARFID, Binge Eating Disorder (BED), or OSFED were considered eligible for analyses. Because the study specifically focused on self-reported HRQoL, only data of children between the ages of 8 and 18 were included, since for younger children the parents completed the HRQoL questionnaire. Children and adolescents who only had HRQoL reports completed by the parents were excluded. Ethical approval was obtained from the medical ethics committee of the Maastricht University Medical Centre.

As part of the Routine Outcome Monitoring the KIDSCREEN-52 questionnaire was sent to every patient who sought treatment for an eating disorder at the Mutsaersstichting. Baseline characteristics and clinical data were collected at the start and end of treatment. At first consultation, patient characteristics including age, sex, underlying diseases, eating attitudes and behaviours, compensatory behaviour and sociodemographic data were obtained. Heart rate and blood pressure were measured with an oscillometric blood pressure machine and evaluated according to the Clinical Practice Guidline of the American Acadamy of Pediatrics [ 17 ]. In addition, a full physical examination was performed. Body Mass Index (BMI) was calculated from measured weight and height [ 18 ]. Growth charts designed by the Dutch organization for applied scientific research (TNO) were used to determine height for age (standard deviation, SD) and weight for height (SD) [ 19 , 20 ]. At the end-evaluation data was collected concerning most recent height, weight, BMI and eating attitudes and behaviours.

The KIDSCREEN-52 is a validated self-report questionnaire for measuring HRQoL in European children between 8 and 18 years old [ 21 , 22 , 23 , 24 , 25 ]. It consists of 52 questions, divided into 10 dimensions: Physical Well-being, Psychological Well-being, Moods and Emotions, Self-Perception, Autonomy, Parent Relations and Home Life, Social Support and Peers, School Environment, Social Acceptance (Bullying), and Financial Resources. The KIDSCREEN-52 uses 5-point Likert scale responses, within each different dimension the results are converted into a Rasch scale. Cronbach–alpha’s vary between 0.77 and 0.89 [ 25 ]. The results are transformed to a t-score, giving the children in the total reference population a mean t-score of 50 with a SD of 10. Specific reference populations are made by country, gender and age groups. The results of this study are compared with the validated normative reference values of Dutch children in the age between 8 and 18 years old [ 25 ]. Ulrike Ravens-Sieberer defined a mean t-score 0.5 SD below the mean t-score of the specific referential population of a country as a low HRQoL and a t-score 0.5 SD above the mean t-score of the referential population as high HRQoL [ 25 ].

Data analysis

All statistical analyses were performed using IBM SPSS Statistics version 25 [ 26 ]. The Mann-Withney U, χ 2 , and fisher exact test were used to determine whether there were statistical differences between all the children and adolescents included in this study and the children who completed the questionnaire at intake and end-evaluation. Paired t test was used to test for statistically significant differences in HRQoL between start- and end of treatment. To test the differences in t-score on the KIDSCREEN-52 stratified for DSM-classification, a one-way ANOVA and Welch test was done, with the Tukey’s Test as a post-hoc analysis. Statistically significance was considered when the result had a p value of < 0.05. Univariate regression analysis was done in the group diagnosed with AN to test whether there is an association between HRQoL and BMI, BMI SD, age, excessive exercise and binge eating. Since purging only occurred in four patients this could not be included in the analysis. Other DSM-5 diagnoses where not included due to small subgroup sample size.

Baseline characteristics

Data of 276 patients were analysed of which 140 were found eligible for this study (Fig.  1 ). Baseline characteristics are presented in Table  1 . The total population consisted primarily of female children and adolescents ( n  = 119; 85%) with a mean age of 15.0 years ranging from 8 to 18 years. Almost half of the population was classified as AN ( n =  68; 48.6%). The mean weight for children with AN ( n  = 67) was 44.1 kg (minimal weight 25 kg– maximal weight 59 kg) with a mean weight SD of -1.6 and mean BMI of 15.9 kg/m 2 (minimal BMI 11.9 kg/m 2 – maximal BMI 19.9 kg/m 2 ). Children with ARFID had a mean weight of 31.9 kg (minimal weight 18 kg– maximal weight 105 kg), mean weight SD– 0.6, mean BMI 15.9 kg/m 2 (minimal BMI 12.1 kg/m 2 – maximal BMI 36.3 kg/m 2 ). Only two patients were diagnosed with BED, this was too small a sample size to be included in results stratified for the DSM-5 criteria. No significant differences were found in the baseline characteristics between children who completed the KIDSCREEN-52 only at the beginning of treatment, and those who completed the questionnaire both at the start and end-evaluation ( n  = 47), except for psychiatric co-morbidities ( X 2 (1) = 4.97; p  = 0.026). Even though the effect size for this finding, Cramer’s V = 0.188, was weak, due to the known association between psychiatric co-morbidities and eating disorder symptoms, a comparison between HRQoL at the beginning and end of treatment was only made within the group of 47 patients that completed both questionnaires [ 13 , 27 , 28 ].

HRQoL at the start of treatment

Table  2 shows mean t-scores scored by children and adolescents on the KIDSCREEN-52 at the start of treatment, stratified for the DSM-5 criteria. Children with the diagnosis AN, BN and OSFED all had a lower HRQoL (≤ 0.5 SD of mean score) than the reference population for the dimensions Physical Well-being, Psychological Well-being, Moods and Emotions, Self-Perception, Autonomy, Financial Resources, Peers and Social Support, School Environment and Bullying. There were no statistically significant differences in t-scores between AN, BN and OSFED. This was confirmed with a Turkey’s post hoc test. Compared with the reference population the HRQoL in patients with ARFID was only lower for the dimension Physical Well-Being. For the dimensions Physical Well-being, Psychological Well-being, Moods and Emotions, Self-Perception, Autonomy, Parent Relations and Home Life and School Environment the t-scores of children with ARFID were significantly higher than those of the children who met criteria of all other eating disorders. Social Support and Peers was significantly higher in patients with ARFID compared to AN, but not with BN and OSFED. Univariate regression analysis in the group diagnosed with AN showed a significant association between a higher t-score on the domain Physical Well-being and higher BMI, BMI SD. Other variables were not associated with a higher or lower t-score.

HRQoL change between start and end of treatment

In Table  3 mean t-scores of the KIDSCREEN-52 at the start of treatment are compared with t-scores at the end evaluation. HRQoL showed a significant improvement in mean t-scores before and after treatment for Physical Well-being (t (46) = -4.4, p  < 0.001), Psychological Well-being (t (45) = − 3.0, P  = 0.004), Moods and emotions (t (45) = -3.3, p  = 0.002) Self Perception (t (45) = -3.7, p  = 0.001) and School environment (t (44) = -2.8, p  = 0.008). However, after treatment the HRQoL for these dimensions did not normalize compared to normative reference values of Dutch children. The subgroup sample sizes were too small for findings relating to change in QoL before and after treatment to be stratified by diagnosis.

This study shows that the self-reported HRQoL in children and adolescents receiving outpatient treatment in the Netherlands for an eating disorder is significantly lower on multiple dimensions at the beginning and end of treatment compared with the reference population. Most studies that have been conducted in children and adolescents are population-based studies that focus on disordered eating behaviours, yet they also show a significantly decreased mental HRQoL [ 9 , 13 , 29 , 30 , 31 , 32 , 33 , 34 ]. The study of Jenskins, showed similar results in a group of sixty-seven adolescents seeking treatment for an eating disorder [ 6 ].

The domain physical well-being is significantly lower for all types of eating disorders. This finding replicates that of Winkler et al. in which compared to the controls, adult women with AN had significantly impaired HRQoL as measured by the Eating Disorders Quality of Life (EDQOL) scale including lower physical functioning [ 35 ]. Yet several other studies showed only a significantly lower mental component summary and normal levels in the psychical component summary scored with Short Form-36 Health Survey (SF-36) [ 4 , 6 , 14 , 36 ]. This difference could partially be explained by the use of different questionnaires, where some questionnaires could reflect the physical pathology of eating disorders rather than real physical health. The KIDSCREEN-52 for example specifically asked for fatigue, where other questionnaires ask for the ability to walk the stairs. When diagnosed with AN extensive exercise might be associated with the disease itself. Disease severity and duration of the eating disorder might also influence results. Children and adolescents in our study received one or more previous treatments in 55% of the patients and in 34% had a disease duration of more than one year. To gain more insight a univariate regression analysis was done in the group diagnosed with AN, which showed a significant association between a higher BMI and higher t-score on the domain Physical Well-being, suggesting that the results as shown within this study might be a reflection of real physical health rather than psychopathology.

When comparing AN, BN and OSFED this study does not find statistically significant differences similar as the meta-analysis on quality of life by Winkler et al. suggesting a similarity between these eating disorders with regard to HRQoL [ 35 ]. Notable exception to this are the children and adolescents with ARFID, who only score lower on the item Physical Well-being, unlike the children and adolescents classified with all other eating disorders who have lower scores on almost all HRQoL dimensions. This suggests that HRQoL affects children with ARFID differently. Hay et al. compared adults and adolescents from the age of 15 years with ARFID in the Australian population to other eating disorders and found, unlike the current study, a normal physical HRQoL and a significantly lower mental HRQoL [ 37 ]. A Dutch study by Krom et al., in which children were treated for ARFID in a Diagnostic Centre for Feeding Problems showed that the HRQoL, reported by their parents using TNO-AZL Preschool Children Quality of Life (TAPQOL) was significantly lower on the subscales appetite, lungs, stomach, motor functioning, and positive mood and liveliness, suggesting that both physical and mental HRQoL was affected [ 38 ]. The difference in mental HRQoL between the current study and the study by Krom et al. might be explained by an overestimation by parents of the child’s psychosocial functioning due to parent’s own concerns, and besides that it might be caused by age differences. Another explanation could be that ARFID differs from longer recognised disorders such as anorexia nervosa and bulimia nervosa in that they do not have a core psychopathology of body image disturbance or weight/shape overvaluation. Given that in adolescent and young adult women at least, it is clear that overvaluation of weight/shape is very strongly associated with impairment in quality of life including but not limited to the mental health domain, it is not too surprising that children and adolescents with a diagnosis of ARFID report relatively little impairment in mental HRQoL [ 39 , 40 ]. The lower physical HRQoL that is seen in the current study might be explained by nutritional deficits often seen in children with ARFID [ 41 ].

The HRQoL shows significant improvement after treatment in all dimensions except for Autonomy and Social Support and Peers. However, HRQoL does not normalize compared to the reference population, and stays significantly impaired. This finding is consistent with considerations of other studies, namely that symptom remission alone is not sufficient for improvement in quality of life [ 42 ]. Studies looking at the long-term effects of eating disorders show that the long-term HRQoL after treatment continues to improve but is still not normalized after 8- or 30-years [ 14 , 42 , 43 , 44 ]. Thus follow-up, with paying attention to HRQoL, should continue longer than the initial treatment. Similar to our results, greatest improvement in HRQoL was noted in the physical functioning domain [ 43 , 44 ]. With childhood and adolescence being a critical period of development, the current study underlines the importance of treatment in which the success of the treatment is not based on BMI or amount of food intake alone, but focuses on other quality of life factors, such as psychological well-being, autonomy and social support.

There are limitations to this study. Due to the small subgroup sample size findings in the change in HRQoL before and after treatment could not be stratified by diagnosis. This study enrolled participants during a 14-year period, this longer period could have confounded the results due to changes in the care and treatments. Also, the retrospective nature of this study and the use of a generic HRQoL scale needs to be taken into consideration. Using generic HRQoL scales could give an over or underestimation of the HRQoL, since it does not focus specific on eating disorders, and questions for example about physical wellbeing could be an expression of the eating disorder rather than healthy behaviour. Our patients received both in- and outpatient treatment, which implies a certain disease severity and might not be generalizable to patients in other settings. HRQoL at the start of treatment could be lower or higher depending on the setting. Even though the children who completed the KIDSCREEN-52 only at the beginning of treatment and those who completed the questionnaire both at the start and end-evaluation are comparable, a large number of patients did not fill in the KIDSCREEN-52 at end-evaluation which might influence the outcome of quality of life after treatment, especially if the patients that did recover are the ones that did not fill in the questionnaire.

However, despite the limitations this descriptive study gives insight in the self-reported HRQoL of children and adolescents in the Netherlands treated for an eating disorder. It shows a significant reduction in both mental and physical HRQoL compared to the reference population with the exception of ARFID in which only physical HRQoL is impaired. This study also shows that even after treatment, children do not achieve normal HRQoL, which poses a potential risk to their development. Long-term follow-up of these children seems important, and more research is needed focusing on the effect of using quality of life parameters as most important measurements for recovery.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

Anorexia Nervosa

Avoidant Restrictive Food Intake Disorder

Binge Eating Disorder

Body Mass Index

Bulimia Nervosa

Diagnostic and Statistical Manual of Mental Disorders

Eating Disorders Quality of Life

Eating disorder not otherwise specified

Health-related quality of life

Standard deviation

36-Short Form-36 Health Survey

TNO-AZL Preschool Children Quality of Life

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The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. The authors have no relevant financial or non-financial interests to disclose.

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Department of Primary care, Radboud University Medical Centre, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands

E. van Gerner

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CRediT author statement: A Wever: Writing - Original Draft, E. van Gerner: Formal analysis and Investigation, J.C.M. Jansen: Conceptualization and Writing - Review & Editing, B Levelink: Conceptualization and Writing - Review & Editing.

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Wever, A., van Gerner, E., Jansen, J. et al. Self-reported health related quality of life in children and adolescents with an eating disorder. BMC Psychol 12 , 242 (2024). https://doi.org/10.1186/s40359-024-01684-y

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40 years of research on eating disorders in domain-specific journals: Bibliometrics, network analysis, and topic modeling

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation School of Health Sciences, Universidad Peruana de Ciencias Aplicadas, Lima, Perú

• Carlos A. Almenara

• Published: December 15, 2022
• https://doi.org/10.1371/journal.pone.0278981
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Previous studies have used a query-based approach to search and gather scientific literature. Instead, the current study focused on domain-specific journals in the field of eating disorders. A total of 8651 documents (since 1981 to 2020), from which 7899 had an abstract, were retrieved from: International Journal of Eating Disorders (n = 4185, 48.38%), Eating and Weight Disorders (n = 1540, 17.80%), European Eating Disorders Review (n = 1461, 16.88%), Eating Disorders (n = 1072, 12.39%), and Journal of Eating Disorders (n = 393, 4.54%). To analyze these data, diverse methodologies were employed: bibliometrics (to identify top cited documents), network analysis (to identify the most representative scholars and collaboration networks), and topic modeling (to retrieve major topics using text mining, natural language processing, and machine learning algorithms). The results showed that the most cited documents were related to instruments used for the screening and evaluation of eating disorders, followed by review articles related to the epidemiology, course and outcome of eating disorders. Network analysis identified well-known scholars in the field, as well as their collaboration networks. Finally, topic modeling identified 10 major topics whereas a time series analysis of these topics identified relevant historical shifts. This study discusses the results in terms of future opportunities in the field of eating disorders.

Citation: Almenara CA (2022) 40 years of research on eating disorders in domain-specific journals: Bibliometrics, network analysis, and topic modeling. PLoS ONE 17(12): e0278981. https://doi.org/10.1371/journal.pone.0278981

Editor: Alberto Baccini, University of Siena, Italy, ITALY

Received: February 5, 2021; Accepted: November 27, 2022; Published: December 15, 2022

Copyright: © 2022 Carlos A. Almenara. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data that support the findings of this study are publicly available from the OSF repository: https://osf.io/5yzvd/ (DOI: 10.17605/OSF.IO/5YZVD ).

Funding: Funding for this study was obtained from Universidad Peruana de Ciencias Aplicadas (A-006-2021).

Competing interests: The author has no competing interest to declare.

Introduction

There are a large and growing number of scientific publications on eating disorders (ED) [ 1 – 3 ]. ED are mental disorders characterized by a continuous disturbance in eating behavior, such as Anorexia Nervosa [ 4 ]. ED are usually defined according to manuals like the Diagnostic and Statistical Manual of Mental Disorders (DSM) [ 4 ]. The spectrum of ED can share some symptoms (e.g., fear of fatness ), and these symptoms negatively impact psychosocial functioning and physical health. Due to the complexity of ED like Anorexia Nervosa, scholar literature about them covers different disciplines, such as ED related to: visual arts (e.g., art history) [ 5 ], sociology (e.g., social history) [ 6 ] and even dentistry (e.g., oral health) [ 7 ]. Thus, ED literature has a broad diversity.

Previous bibliometric studies about ED have focused on: identifying the distribution by language, region and country, as well as topics and their trends [ 1 ], productivity trends and collaboration patterns [ 2 ], most cited works in Anorexia Nervosa research [ 8 ], cross-cultural aspects of ED [ 3 ], comparison of citations between types of journals [ 9 ], female authorship [ 10 ], secular trends in the scientific terminology [ 11 , 12 ], the gap between scientific research and clinical practice [ 13 ], the use of keywords [ 14 ], and network analyses of common terms used in the field [ 15 ]. In particular, the current study complements the work by He et al. [ 1 ].

A standard practice of these studies is to retrieve the literature by performing a systematic search in databases like Web of Science or Scopus (i.e., employing a query-based approach), although there are some caveats worth mentioning. As noted elsewhere [ 16 , 17 ], those two databases differ in journal coverage and their use can introduce bias favoring science publications (e.g., biomedicine) in detriment of arts and humanities, other than overrepresenting English-language journals. Second, databases in general (including others like PubMed, Dimensions, JSTOR), differ in their search engine functionality and information retrieval capabilities.

For example, some databases offer a controlled vocabulary like a thesaurus or taxonomy from which to choose the search terms (e.g., the Medical Subject Headings [MeSH] in PubMed), whereas others offer a full text search. Regarding the latter, indexing scanned documents to offer a full text search, requires pre-processing methods like optical character recognition (OCR), known to include typos, and post-OCR processing, both affecting information retrieval accuracy [ 18 – 23 ].

In other words, a query-based approach, although widely used, can be affected by several factors, including: domain expertise to design the most appropriate search strategy, the characteristics of the selected database(s), including indexation accuracy (e.g., due to OCR typos). The former is particularly important because scholars are not always consistent in using the terminology [ 24 ]. In fact, their selection of keywords is not systematic, but rather influenced by factors like their background knowledge and previous experience [ 25 ]. In this regard, within the field of ED, scholars are encouraged to use appropriate terminology [ 26 , 27 ], usually a controlled vocabulary such as the Thesaurus of Psychological Index Terms. This helps to optimize the Knowledge Organization Systems (KOS) of journals and databases, such as a controlled vocabulary for information retrieval [ 14 , 28 ].

In sum, most previous studies have employed a query-based search, being compelled to choose among different databases, search terms, and search strategies [ 29 ]. Nevertheless, this approach not necessarily recognizes the boundaries and limitations of both databases and we as humans interacting with machines, using diverse information retrieval strategies, and dealing with information overload [ 30 , 31 ].

An alternative to the query-based approach is the one proposed in this study: to select a set of specialty journals exclusively devoted to the study of ED. Although this sampling could seem arbitrary, it was adopted: (1) to complement the findings of previous studies [ 1 , 2 ] and (2) because it has in fact a sound base: the intellectual and social structure of knowledge [ 32 – 36 ]. We must recognize that documents need to be understood with regard to "the broader contexts in which they are produced, used, and cited" [ 37 , p. 42]. Thus, the following sections will explain how domain-specific journals are tightly tied to an organized social and disciplinary structure. Moreover, I will explain how this approach does not necessarily exclude all ED literature from non-domain-specific journals, but rather incorporates part of it into their citations. Finally, from a complex systems perspective, I will show how domain-specific journals can be conceived as a specialized subset from the larger and more complex network comprising all ED literature.

Domain-specific journals and its social structure

From a scientometric perspective, science, metaphorically conceived as a knowledge space or knowledge landscapes , can be defined in terms of a network of scholars that produce a network of knowledge [ 35 ]. In the former case, the social function of science has long been recognized (e.g., by Thomas Kuhn): scholars produce and communicate scientific knowledge and this organized activity has the characteristics of a social process [ 36 , 38 ]. More importantly, the patterns of interactions and communication within this social organization are tightly tied, rather than isolated, to the knowledge they produce [ 36 ].

An exemplary case is the role of journal editors as gatekeepers, with studies identifying editorial gatekeeping patterns [ 39 , 40 ]. According with the Network Gatekeeping Theory, inspired by the work of Kurt Lewin, gatekeeping refers to the control in the flow of information [ 41 , 42 ]. In the field of ED, this intellectual and social organization of knowledge can be seen in professional societies like the Academy of Eating Disorder, which since 1981 publishes the most renowned scientific journal: The International Journal of Eating Disorders. Within its editorial board, there are distinguished scholars that can act as gatekeepers to ensure quality control and that manuscripts published by the journal are in line with the aims and scope of it.

In sum, domain-specific journals have the goal of publishing information within the boundaries of their aims and scope, allowing the diffusion of specialized knowledge.

Domain-specific journals and its disciplinary organization

From a network perspective, specialty journals are also indicators of disciplinary organization [ 43 ], which exerts a non-trivial influence at both the global and local level of the network. To be more precise, if we visualize a network [e.g., 2 , 44 , 45 ], the local density of specialty journals evidence emerging patterns such as citation patterns by articles from the same journal or group of journals [ 43 ]. At the author level, these patterns reflect the local influence of specialty journals on scholars who adhere to their research tradition and their contributions help to advance a research agenda [ 46 ].

For example, domain-specific journals on ED often publish curated information from conferences [e.g., 47 ] or special issues about a specialized topic [e.g., 48 ], which commonly include a research agenda [ 48 ], setting the stage for future research. As we mentioned above, similar literature, such as special issues about ED published in other journals [e.g., 49 ], is not necessarily excluded in the analysis of domain-specific journals. Rather, such literature is commonly cited in documents from domain-specific journals and can be included in a citation analysis. Importantly, these citation patterns suggest that the former intellectual and social structure of knowledge constrains what is being studied in the future [ 46 ]. Thus, in the upcoming years, most of this specialized literature is expected to become an active research front [ 32 ], as evidenced by its high number of citations.

Finally, it is worth mentioning that the analysis of these patterns can reveal latent hierarchies and topological properties of journal networks. In fact, domain-specific journals can be identified through the study of the hierarchical organization of journal networks. When hierarchical network analysis is used to identify the capability of journals to spread scientific ideas, multidisciplinary journals are found at the top of the hierarchy, whereas more specialized journals are found at the bottom [ 50 , 51 ]. Similarly, significant articles from a specific domain have unique topological properties that can affect the dynamic evolution of the network [ 52 ]. In sum, it is important to recognize the topological properties of networks and their latent hierarchies, both at the journal level and document level. In our case, focusing on domain-specific journals, it would be like zooming into the most central part (core) of the network topology to analyze its organization and distinctive features. Indeed, this approach is commonly employed, for example, when studying network subsets such as niches or communities in complex systems.

Domain-specific journals and complex adaptive systems

Domain-specific journals can also be comprehended from a complex systems standpoint, as the aggregation of the intellectual, social, and citation patterns outlined above. According to the Structural Variation Theory [ 53 ], the body of scientific knowledge can be conceived as a complex adaptive system (CAS). As such, it can be described and studied as a complex network with a series of characteristics like non-linearity, emergence, and self-organization; and a series of social, conceptual, and material elements that evolve over time [ 46 ]. Ideally, we must study CAS holistically to understand the properties of the system at the macrolevel [ 54 ]. In our case, this would require including all scholar literature on ED, which could be attempted using a query-based approach and employing ad hoc methodologies (e.g., iterative citation expansion) [ 45 ]. However, complex systems emerge from rules and behavior of lower-level components, and there is growing interest in understanding complexity from its simplest and fundamental elements and patterns [ 55 , 56 ]. In our case, this can be accomplished by zooming into domain-specific patterns that emerge from the relational structure and organization of journals and papers [ 46 ], rather than focusing on the whole system which comprises all the scientific literature on ED.

This approach can be described in terms of modularity , a structural property of systems: the local density of specialty journals is indicative of a structural module or subsystem [ 57 ]. This property of complex systems is important because it recognizes, as we did above, the existence of subsets within networks. Indeed, scientometric studies usually attempt to detect communities based on the principle of modularity by grouping similar literature (i.e., clustering) [ 44 , 58 ]. However, in the approach used in this study, rather than using bibliographic connections (e.g., through co-citation analysis) to detect domain-specific literature, we can use logical connections [ 59 ], to identify modules that operate as domain-specific representations [ 60 ]. In other words, domain-specific journals can be seen as clusters of articles that are logically linked because they all pertain to a given domain, which is explicitly stated in the aims and scope of the journals.

This modular organization has some advantages over others such as a hierarchy (e.g., Scimago categorization of journals) or a cluster obtained by literature partitioning algorithms. First, it has the advantage of reducing both complexity bias and hierarchical bias . The former is the tendency to assume and adopt a more complex system (the opposite to Occam’s Razor: prefer the simplest explanation), which means to analyze all ED literature. The latter assumes that behavior is directed in a hierarchical fashion, where a central authority passes instructions to all agents in the system [ 54 ]. Second, although it still recognizes a hierarchical structure composed by diverse classes of subsystems, it assumes heterarchy [ 43 , 61 ], which means that both hierarchical and nonhierarchical elements can be present in a system; holarchy , which means that systems are composed of components that can be recognized as subsystems [ 62 ]; and glocal control , which means that local and global phenomena in a system are achieved by local actions [ 63 ]. In simple words, sampling a set of domain-specific journals reduces complexity without affecting assumptions such as a categorical hierarchy of journals.

The current study

To expand on previous studies [ 1 , 2 ], the current study aims to answer the following research questions:

Which are the most cited documents in this domain-specific corpus of articles?

Which are the most important authors and their collaboration networks?

Which are the most relevant topics in this domain-specific corpus of articles?

How have the identified topics evolved over time (since 1981 to 2020)?

To answer these questions, this study employs a hybrid methodology. First, basic bibliometrics will be performed to identify the most cited documents. Second, network analysis will be employed to identify the most important authors and their networks of collaboration. Third, text mining, natural language processing, and machine learning algorithms will be used to identify the most relevant topics (i.e., topic modeling). Finally, a simple time series analysis will be performed to examine the evolution of these topics over time. The procedure employed for the analyses is detailed in the methods section below (and S5 File ), whereas the dataset and the code to perform the analyses are shared in a public repository ( https://doi.org/10.17605/OSF.IO/5YZVD ), allowing the reproducibility of results [ 64 ].

Data collection

The methodology workflow is presented in Fig 1 .

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0278981.g001

First, in May 2020, a search of journals was performed in Scimago Journal Reports (SJR, https://www.scimagojr.com/ ), using the term “eating disorders”. In this step, the following five journals were identified: International Journal of Eating Disorders (ISSNs: 0276–3478, 1098-108X), European Eating Disorders Review (ISSNs: 1072–4133, 1099–0968), Eating Disorders (ISSNs: 1064–0266, 1532-530X), Eating and Weight Disorders (ISSNs: 1124–4909, 1590–1262), and Journal of Eating Disorders (ISSN: 2050-2974). The official website of each journal was then visited to confirm that the scope of the journal specifically includes the publication of research articles on eating disorders. It should be noted that the journal Advances in Eating Disorders (ISSNs: 2166–2630, 2166–2649) was not included because it was not found in SJR, it was published only between 2013 and 2016, it was incorporated into the journal Eating Disorders , and by the time of writing this article, it was not indexed neither in Scopus ( https://www.scopus.com ) nor in Web of Science ( https://www.webofknowledge.com ).

Next, also in May 2020, the Scopus database was chosen to retrieve the document records from the aforementioned journals. The election was made for no other reason than the capability of Scopus to retrieve several structured information (metadata, such as the abstract), and the file types for download are easy to manage, such as comma-separated values (CSV). Therefore, all document records published by these journals were searched in Scopus using the ISSN as the search term (e.g., ISSN (0276–3478) OR ISSN (02763478) OR ISSN (1098-108X) OR ISSN (1098108X) ). A total of 8651 documents between 1981 and 2020 were retrieved (of which 7899 had an abstract): 4185 (48.38%) from the International Journal of Eating Disorders, 1540 (17.80%) from Eating and Weight Disorders, 1461 (16.88%) from the European Eating Disorders Review, 1072 (12.39%) from Eating Disorders, and 393 (4.54%) from the Journal of Eating Disorders. These 8651 documents included a total of 213,744 references. It should be noted that the International Journal of Eating Disorders is the oldest of these journals, established in 1981. The S7 and S8 Files provide the number of documents per year and per journal. The document records were downloaded from Scopus both as comma separated values (CSV) and as BibTex ( http://www.bibtex.org/ ), and selecting all fields available (i.e., title, author, abstract, etc.). Due to copyright, the full text of all documents was not retrieved but rather their metadata (i.e, title, author, date, abstract), whilst the dataset shared online ( https://doi.org/10.17605/OSF.IO/5YZVD ) is the one obtained after the preprocessing procedures detailed below.

Analyses were performed using open software: R Statistical Software 4.0.3 (Bunny-Wunnies Freak Out) [ 65 ], and Python programming language version 3.9.1 ( https://www.python.org/ ).

Bibliometric analysis and network analysis in R

The biblioshiny application from the R package bibliometrix [ 66 ] was used to preprocess the CSV file. Next, it was used to identify the most cited documents. Local citations (i.e., citations only from documents whithin the dataset), and global citations (i.e., citations made by any document from the whole Scopus database), were computed. Biblioshiny was also used for network analysis as described by Batagelj & Cerinšek [ 67 ], and Aria & Cuccurullo [ 66 ]. Regarding the network, it is defined as a pair of sets: a set of nodes or vertices and a set of edges (link between nodes) [ 68 ]. In this study, when authors were treated as nodes, a link would represent co-authorship or collaboration [see 69 ]. More precisely, the Louvain algorithm for community detection [ 70 ] was used to identify communities within the collaboration network. This algorithm identifies densely connected nodes within the network (i.e., communities) [e.g., 71 ]. It works unconstrained to automatically extract a number of clusters although it requires basic network parameters as input. These network parameters were: up to 100 nodes, a minimum of two edges by node, and the removal of isolated nodes. For network layout visualization, the Fruchterman & Reingold [ 72 ] algorithm was chosen. Finally, common centrality measures were calculated: betweenness, closeness, and PageRank. Betweenness centrality refers to “the frequency that a node is located in the shortest path between other nodes” [ 73 , p. 772]. Closeness centrality refers to nodes that can easily reach others in the network, whilst PageRank , originally created to rank websites [ 74 ], has been used to rank authors because it takes into account the weight of influential nodes [ 75 ].

Topic modeling: Dimensionality reduction and matrix factorization

As can be seen in the workflow ( Fig 1 ), once network analysis was finished, a series of steps (detailed in S5 File ) were necessary to preprocess the dataset prior to topic modeling. Topic modeling refers to applying machine learning techniques to find topics by extracting semantic information from unstructured text in a corpus [ 76 ]. As we explain in S5 File , to this point we end up with a high-dimensional and sparse document-term matrix. In other words, we have many features (columns) each corresponding to a term in our corpus, and for a given document (rows) we have many columns with zero values meaning the term of that column is not in the given document. To deal with sparsity, we can perform dimensionality reduction to obtain a representation that effectively captures the variability in the data. In summary, dimensionality reduction can be categorized in feature extraction and feature selection ; the former combines the original feature space into a new one, whereas the latter selects a subset of features [ 77 ].

As explained in S5 File , the term frequency (TF) and the term frequency-inverse document frequency (TF-IDF) were used as feature extraction for vectorization. Then, the following machine learning algorithms were applied for topic modeling: Latent Dirichlet Allocation (LDA) [ 78 ], Latent Semantic Analysis (LSA or Latent Semantic Indexing) [ 79 ], Hierarchical Dirichlet Process (HDP) [ 80 ], and Non-negative Matrix Factorization (NMF) [ 81 ]. LDA is a generative probabilistic model that decomposes the document-term matrix into a topic-term matrix and a document-topic matrix, and it is commonly used for topic discovering from a corpus [e.g., 82 ]. LSA utilizes a truncated Singular Value Decomposition for decomposition and can work efficiently on TF or TF-IDF sparse matrices. In a fully unsupervised framework, the HDP model is characterized by inferring the number of topics on its own. Finally, NMF is an alternative approach that implements the Nonnegative Double Singular Value Decomposition, an algorithm suitable for sparse factorization [ 83 ].

First, the GENSIM library [ 84 ] was used for topic modeling because it provides a way to calculate topic coherence , an index to compare models based on measures of segmentation, probability estimation, confirmation measure, and aggregation [see 85 ]. Therefore, based on a TF matrix, HDP, LSA, NMF, and LDA were performed in GENSIM and compared in topic coherence. Once identified the topic modeling algorithms with the highest topic coherence, scikit-learn [ 86 ] was used because it provides an Exhaustive Grid Search option for ensemble learning the models (i.e., automatically fine-tuning the parameters to find the most optimal). Finally, once the topics were extracted, a simple time series analysis was performed to visualize the changes over time in the topics found. This analysis consisted of simply plotting the number of documents for each topic across years, from 1981 to 2020.

First, bibliometric analyses were performed to identify the most cited documents. Local citations are presented in Table 1 (and the S1 File ), whereas global citations are in Table 2 (and the S2 File ).

https://doi.org/10.1371/journal.pone.0278981.t001

https://doi.org/10.1371/journal.pone.0278981.t002

Next, a network analysis was performed to identify the most important authors ( Table 3 ) and their collaboration networks ( Fig 2 , see also S3 File , a dataset, and S4 File , an interactive visualization in HTML and JavaScript, also available online: https://osf.io/5yzvd/ ). This collaboration network analysis identified eight clusters with 96 authors: (1) red color, 4 authors; (2) blue, 15 authors; (3) green, 17 authors; (4) purple 21 authors; (5) orange, 2 authors; (6) brown, 18 authors; (7) pink, 2 authors; (8) grey, 17 authors.

https://doi.org/10.1371/journal.pone.0278981.g002

https://doi.org/10.1371/journal.pone.0278981.t003

Regarding the most relevant topics, LDA and NMF were superior to HDP and LSA in topic coherence. Then, when ensemble learning was used for LDA (based on TF) and NMF (based on TF-IDF), NMF provided the most meaningful results, and 10 topics were identified ( Table 4 ).

https://doi.org/10.1371/journal.pone.0278981.t004

The labels for the topics were manually added based on the top 10 keywords and their respective weights. Thus, each topic was manually labeled as follows: (1) risk factors for eating disorders, (2) body image dissatisfaction, (3) Binge Eating Disorder diagnosis, (4) weight loss, weight control, and diet, (5) clinical groups, (6) treatment outcome, (7) family and parent-child, (8) binge and purge episodes, (9) gender and subgroups, (10) EDNOS.

To examine how these topics have evolved over time, a simple time series analysis plot was created ( Fig 3 and S6 File ).

Note . Values in the y-axis are the sum of the weight values from the NMF analysis for topic dominance, per year and per topic. Values go from minimum 0 to maximum 11.2 (see S6 File ).

https://doi.org/10.1371/journal.pone.0278981.g003

This study analyzed 8651 documents between 1981 and 2020 from domain-specific journals in the field of eating disorders. The aims were: to identify the most cited documents, the most important authors and their collaboration networks, and the most relevant topics and their evolution over time. The results expand previous findings of studies that employed a query-based approach and included articles dating back as far as 1900 [ 13 ]. In particular the results expand the studies by Jinbo He et al. (2022) and Juan-Carlos Valderrama-Zurián, et al. (2017), which employed a similar methodology [ 1 , 2 ]. For example, He et al. (2022) created a collaboration network, although it was based on countries rather than authors [ 1 ]. Therefore, the results obtained here (e.g., author centrality measures, author clusters) provide a more fine grained understanding of the relevance and contribution of individual authors and their collaboration networks. Furthermore, He et al. (2022) [ 1 ] identified top authors based on traditional performance metrics (e.g., h-index), and it should be noted that there is some criticism towards their use and a claim to shift towards more responsible metrics of research excellence [ 87 ]. Then, He et al. (2022) [ 1 ] employed LDA for topic modeling, whilst this study employed NMF. Although LDA is largely used, in this study NMF outperformed LDA in interpretability, reproducibility, and as we said above, it suits better for short texts, as is the case of article abstracts used here. Finally, the top journals identified by He et al. (2022) confirmed that the five journals selected for this study are in fact among the most important in the field of eating disorders [ 1 ]. In the case of Valderrama-Zurián, et al. (2017) [ 2 ], they also focused on authors’ productivity trends whereas their social network analysis was focused on network metrics such as the number of nodes and edges over time, which precludes to inspect the social network at the author level. Therefore, this study also expands on the findings of Valderrama-Zurián, et al. (2017) [ 2 ].

Below, we discuss in more detail the results of the analysis employed to answer the four research questions outlined in the introduction.

Bibliometric analysis

The top cited documents were all from the International Journal of Eating Disorders. As noted above, this journal is the oldest one (it started in 1981), and it has the largest number of articles per year, with the exception of the year 2019 when it was outperformed by the Eating and Weight Disorders journal (see S7 and S8 Files). The majority of top cited documents were related to the development of instruments for the assessment of eating disorders or the course and outcome of eating disorders. For example, we can see in the results the most common instruments used for the screening of eating disorders, as well as the evaluation of its core symptoms: Eating Disorder Inventory (EDI), Body Shape Questionnaire (BSQ), Dutch Eating Behavior Questionnaire (DEBQ), and Eating Disorder Examination Questionnaire (EDE-Q). These instruments are widely used to screen the general population, as well as in clinical settings, together with more recent instruments [ 88 ]. It should be noted, however, that in clinical practice settings the use of instruments for the diagnosis and the different phases of the treatment process is not necessarily widespread [ 89 , 90 ]. To reduce this gap, some authors suggest to provide assessment training and/or assessment guidelines for mental health professionals and general practitioners in primary health care [ 91 , 92 ]. This can help obtain a comprehensive clinical assessment, particularly of individuals with higher risk such as young adolescents with restrictive Anorexia Nervosa [ 93 ]. The instruments mentioned above are reliable measures, and they could be used online for a quick screening or session by session for ongoing monitoring, although further research is necessary [e.g., 94 – 96 ].

The rest of most cited documents include important review articles on epidemiology (Hoek & van Hoeken, 2003, in Table 1 ); the course and outcome of eating disorders (Berkman, Lohr & Bulik, 2007; Strober, Freeman & Morrell, 1997; in Table 1 ); and the diagnosis of Binge Eating Disorder (Spitzer et al., 1992, 1993, in Table 1 ). These results are similar to previous studies in which measurement methods (including instrument development), epidemiology, and review articles were the most common type of document [ 8 , 9 ].

Finally, the large number of articles on the diagnosis of Binge Eating Disorder, which was not fully recognized as a mental disorder in the Diagnostic and Statistical Manual of Mental Disorders (DSM) until its fifth edition [ 4 ], reveal that the recognition of Binge Eating Disorder as an own disorder took several years. To reach expert consensus in a shorter time, eating disorder professionals should pay special attention to emerging eating problems, such as Orthorexia Nervosa [ 97 ].

Network analysis

The network analysis identified eight clusters with 96 authors. Previous studies have examined the network of authors in the field in terms of network statistics such as number of edges or network density [ 2 ]. By contrast, this study provides a more fine-grained network analysis, identifying experts and group of experts in the field of eating disorders. As seen in the results section, the majority are distinguished authors with contributions dating back to the early 1980s.

The author with the largest betweenness centrality was Ross D Crosby (Sanford Center for Biobehavioral Research, United States), followed by James E Mitchell (University of North Dakota, United States) which has the largest value in PageRank. Authors with high betweenness centrality can act as both enablers and gatekeepers of information flow between communities [ 75 ]. Moreover, it has been found that authors with high betweenness centrality establish more collaborations than those high in closeness centrality [ 75 ]. In summary, the results of centrality measures can help to identify experts in the field of eating disorders, particularly authors that can quickly reach other authors in the network (high in closeness), act as gatekeepers (high in betweenness), or relate to influential others (high in PageRank).

Regarding the clusters identified by the network analysis, in the same cluster of Ross D Crosby and James E Mitchell are found other renowned authors like Daniel Le Grange (University of California, San Francisco, United States), Stephen A Wonderlich (Sanford Center for Biobehavioral Research, United States), and Carol B Peterson (University of Minnesota, United States). Among the most relevant results of collaboration of this cluster we can find studies on the ecological momentary assessment of eating disorders [ 98 ], the psychometric properties of the EDE-Q [ 99 ], and the diagnosis of Binge Eating Disorder [ 100 ].

The second largest cluster includes authors like Cynthia M Bulik (University of North Carolina at Chapel Hill, United States), Walter H Kaye (University of California, San Diego, United States), and Katherine A Halmi (Weill Cornell Medical College, United States). The results of their collaboration include studies related to the phenotypic characterization of eating disorders, such as the International Price Foundation Genetic Study, a multisite study that included a large sample of patients with eating disorders and their families [e.g., 101 ].

Finally, the third largest cluster includes authors like Janet Treasure (King’s College London, England), Ulrike Schmidt (King’s College London, England), and Tracey D Wade (Flinders University, Australia), which are widely recognized by the Maudsley Model for Treatment of Adults with Anorexia Nervosa (MANTRA) [ 102 , 103 ]. Interestingly, this is the only cluster that includes collaborations with authors from non-English speaking countries, more specifically from Spain. Examples of these collaborations include studies resulting from the Wellcome Trust Case Control Consortium 3 (WTCCC3) and the Genetic Consortium for AN (GCAN) [ 104 ], and other studies with clinical samples in Spain [e.g., 105 ].

On the other hand, the results reveal the importance of multisite studies that strengthen collaboration and originate in relevant outcomes for the prevention and treatment of eating disorders. Research groups could look for opportunities to collaborate in multisite studies and strengthen both their interdisciplinary and transdisciplinary collaboration, and their collaboration with less common partners such as stakeholders and policy makers [ 106 , 107 ]. By establishing these integrative and strategic collaborations we can promote translational research, and thus helping to reach broader public health goals [ 108 ].

Topic modeling

The combination of TF-IDF and NMF provided meaningful results, identifying 10 topics. After labeling these topics based on the first 10 keywords and their respective weights, we can see that most of the research on eating disorders done in the past 40 years has focused on their prevention and treatment. Interestingly, the time trend analysis of these topics revealed a noticeable change in the first lustrum of the 1990s. Whereas during the early 1980s the study of clinical groups (topic 5) was the most dominant topic, from the mid-1990s, this topic was surpassed by the study of risk factors of eating disorders (topic 1). This indicates an increasing interest for the prevention rather than solely the treatment of eating disorders. This result is consistent with the historical shift that occurred in the United States when in 1992 the Institute of Medicine (IOM) Committee on Prevention of Mental Disorders was created [ 109 ]. Then two years later, a report on reducing risk factors for mental disorders and promoting a preventive approach in research was published [ 110 ]. As expected, this shift had echo in several scholars at the time, became a research front, and relevant publications started to include more information on the prevention of eating disorders, including a special issue [ 111 ], book chapters [ 112 ], and progressively entire books [ 113 ]. It is important to note that this historical shift, as well as later others like in 2017 [ 114 ], were favorable, because in other cases like obesity, it took more time to focus on its prevention due to different issues, including the pressure of the weight loss industry and its commercial interest [ 115 ].

Another interesting finding was that the outcome of the treatment of eating disorders (topic 6), is the second most important topic of 2013, and this finding has important aspects to discuss. First, the surge of state-of-the-art machine learning algorithms provide several opportunities to build intelligent systems for precision medicine. Thus, the treatment course and outcome of eating disorders can be more personalized, guided, and enhanced with the help of predictive technologies and intelligent systems [e.g., 116 ]. Second, as suggested elsewhere [ 117 ], the advantages of technology can be particularly relevant for certain age groups like adolescents, and when a digital intervention is employed [ 118 ]. In summary, treatment outcome is currently an important topic, and future studies can deploy digital interventions and machine learning algorithms for a more precise treatment planning.

Limitations and conclusions

Although this study has strengths, such as using data and code that allows the reproducibility of the results, readers should consider some limitations. First, the analysis of most cited documents is for all the time span, and more recent highly cited documents are underrepresented. Moreover, the journal Advances in Eating Disorders was not included due to indexing issues. Nevertheless, this study provides the code and a detailed procedure to allow researcher to perform further analyses, such as document co-citation analysis. Future studies can also evaluate the Mexican Journal of Eating Disorders ( Revista Mexicana de Trastornos Alimentarios , ISSN 2007-1523), which has published articles primarily in Spanish [ 119 ]. Second, the network analysis included close to 100 scholars mostly with a long trajectory in the field, and this can be a limitation in representing more younger scientists or newcomers [ 2 ]. Future studies can focus on a larger number of scholars and apply different techniques in network analysis, such as other community detection techniques [e.g., 120 ]. Finally, the results of topic modeling suggested a solution of 10 topics out of up to 30 topics solution models tested. Although there is not a universally accepted approach to establish the number of topics, this study relied on several strategies, including ensemble learning, to automatically fine-tune the parameters of the machine learning algorithms, stability, and heuristic approaches [ 121 ]. Future studies can try other machine learning algorithms and techniques to retrieve topics [ 121 ].

In conclusion, this study analyzed 40 years of research on eating disorders, identified the most cited articles, networks of collaboration, experts in the field, and the 10 major topics in the field.

Supporting information

S1 file. most local cited documents..

https://doi.org/10.1371/journal.pone.0278981.s001

S2 File. Most global cited documents.

https://doi.org/10.1371/journal.pone.0278981.s002

S3 File. Network statistics.

https://doi.org/10.1371/journal.pone.0278981.s003

S4 File. Network of collaboration including close to one hundred authors.

https://doi.org/10.1371/journal.pone.0278981.s004

S5 File. Data preprocessing and text representation in Python.

https://doi.org/10.1371/journal.pone.0278981.s005

S6 File. Sum of NMF results for topic dominance per year and per topic.

https://doi.org/10.1371/journal.pone.0278981.s006

S7 File. Number of documents per year and per journal.

https://doi.org/10.1371/journal.pone.0278981.s007

S8 File. Trends over time in number of documents per journal.

https://doi.org/10.1371/journal.pone.0278981.s008

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Walter Kaye and the UCSD Eating Disorders Research team have published over 250 papers on the neurobiology of eating disorders. These publications include behavioral, treatment, and cognitive neuroscience studies that have improved understanding of the clinical presentation, genetics, neurotransmitter systems, and neural substrates involved in appetite dysregulation and disordered eating. These studies are guiding the development of more effective, neurobiologically informed interventions.

• Change in motivational bias during treatment predicts outcome in anorexia nervosa
• Sophie R. Abber MS, Susan M. Murray PhD, Carina S. Brown MS, Christina E. Wierenga PhD
• doi: 10.1002/eat.24156. Epub 2024 February 01.
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• The acceptability, feasibility, and possible benefits of a neurobiologically-informed 5-day multifamily treatment for adults with anorexia nervosa
• Christina E. Wierenga, Laura Hill, Stephanie Knatz Peck, Jason McCray, Laura Greathouse, Danika Peterson, Amber Scott, Ivan Eisler, Walter H. Kaye
• oi: 10.1002/eat.22876. Epub 2018 May 2.
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How Disordered Eating Becomes a Concern in the Neurodivergent

Explore the nuances of disordered eating among neurodivergent populations..

Posted April 18, 2024 | Reviewed by Ray Parker

• What Are Eating Disorders?
• Find a therapist to heal from an eating disorder
• Not all unusual eating habits in neurodivergent people are disorders.
• Standard methods for diagnosing eating disorders may not apply to neurodivergent people.
• Treatment for eating disorders in neurodivergent people should consider their neurodivergence.

Research has shown an overlap between neurodivergence and those struggling with eating disorders. Neurodivergence is a term used to describe those whose minds process information differently than what society has deemed the standard, including variations in how they interpret, experience, and absorb their surroundings.

Due to perpetuated stereotypes across media and academic institutions, eating disorder research was previously skewed to focus on Western female populations, giving a false perception of who was struggling with these disorders. However, as research continues to evolve and awareness of the presentation of neurodivergence among marginalized populations is built, we are learning how a diverse range of populations are affected by these disorders, including the neurodivergent community.

There are a multitude of reasons why neurodivergent people may be at an increased risk of developing an eating disorder. They may have increased or decreased sensory sensitivities, for example, or difficulties identifying hunger and fullness cues, or they may experience emotions more intensely.

Many of these differences are exacerbated due to the stress of having to live in a world designed primarily for neurotypical people, which could itself lead to the development of an eating disorder. However, due to differences in how they process the world around them, neurodivergent folks also commonly have their own relationship with food that may appear to a neurotypical person as disordered.

But does someone whose experience of the world is privileged to align with the neurotypical society get to make this judgment call? Is it even possible to make a sweeping definition of what disordered eating looks like in neurodivergent populations?

I’ll do my best to briefly explore the nuances of disordered eating among neurodivergent populations as well as identify some parameters for when disordered eating becomes a concern.

Is Disordered Eating in Neurodivergent Folks a Concern?

As I mentioned, many neurodivergent individuals have a unique relationship with food due to differences in how they interpret the world around them. They may stick to the same foods each day, be fearful of trying new things, struggle with hunger or fullness cues, avoid going out, or forget to eat and then eat a lot at once. But is this disordered?

Disordered is a word that suggests a disruption to a person’s overall functioning. This means for eating to be disordered, it would cause increased challenges to an area of functioning, be it physical, emotional, social, or financial.

Whether or not functioning is impaired for a neurodivergent individual should not be determined through a neurotypical lens. Instead, it should be seen in collaboration with what the individual reports and/or desires to see in their life moving forward.

For many clinicians, this involves pushing against the traditional methods for eating disorder treatment to see things from a more holistic and nuanced perspective because neurodivergence is a piece of the person, not a clinical symptom to treat as if to make it disappear.

Eating Disorder or Disordered Eating?

One distinction between an eating disorder and disordered eating lies in how impactful a person’s eating behaviors are on their overall health, functioning, and quality of life. Diagnostic criteria require that an eating disorder significantly impact a person’s functioning in one or more areas of their life. This means that disordered eating has intensified to the point where a person’s well-being is jeopardized by the illness.

Identifying an eating disorder in neurodivergent folks may be complicated because symptoms don’t always align with the perception of eating disorders that we have from the media or society. Following are some signs that are more specific to neurodivergent individuals:

• Sticking to one type of texture (e.g., soft foods, crunchy foods)
• Avoiding cold foods
• Avoiding hot foods
• Only eating foods of a certain color palette (e.g., only tan foods, only red foods)
• Avoiding foods with a certain smell
• Refusing foods if small changes are made (e.g., new packaging, new brand, new presentation)
• Taking a long time to finish a meal
• Going long periods of time without remembering to eat or feeling hungry
• Eating alone or only in a certain location
• Going long periods of time without the awareness of hunger
• Eating large quantities of food after going long periods of time without awareness of hunger
• Developing a strong fixation on one or a few types of foods for a period of time

As I mentioned, not all these behaviors have to be labeled as disordered in nature. It is more about whether these behaviors lead to impairments to an individual's well-being. For a personal look into this concept and more information on this topic, you can check out this article , where I offered some additional insights.

Reaching Out for Support

Early intervention can be an important factor in recovering from an eating disorder. However, reaching out for support when an individual is neurodivergent may feel more complicated because it can be challenging to find providers who have a background in eating disorder treatment and an understanding of neurodivergence.

For this reason, it can be helpful to schedule consultation calls with providers before committing to working with them. In these calls, you can ask about their experience with neurodivergent individuals and how they work to take a nuanced approach to treatment beyond the traditional eating disorder interventions, which weren’t developed considering neurodivergent experiences.

Adrian G-S, Victoria M-M, Luis B-F. Connecting Eating Disorders and Sensory Processing Disorder: A Sensory Eating Disorder Hypothesis. Glob J Intellect Dev Disabil. 2017; 3(4): 555617

Balasundaram, P., & Santhanam, P. (2022). Eating Disorders. In StatPearls. StatPearls Publishing.

Baron-Cohen, S., Jaffa, T., Davies, S., Auyeung, B., Allison, C., Wheelwright, S. (2013). Do girls with anorexia nervosa have elevated autistic traits? Molecular Autism, 4(24), 2-8.

Biederman, Joseph MD*†; Ball, Sarah W. SCD*; Monuteaux, Michael C. SCD*†; Surman, Craig B. MD*†; Johnson, Jessica L. BS*; Zeitlin, Sarah BA*. Are Girls with ADHD at Risk for Eating Disorders? Results from a Controlled, Five-Year Prospective Study. Journal of Developmental & Behavioral Pediatrics: August 2007 - Volume 28 - Issue 4 - p 302-307 doi: 10.1097/DBP.0b013e3180327917

Morgan Blair, M.A., LPCC , has 17 years of experience living with, studying, and treating eating disorders. She now has her own practice where she treats gender-expansive and neurodivergent individuals recovering from eating disorders.

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Understanding what emotional intelligence looks like and the steps needed to improve it could light a path to a more emotionally adept world.

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• Published: 15 September 2015

Perceptions of the causes of eating disorders: a comparison of individuals with and without eating disorders

• Elizabeth H. Blodgett Salafia 1 ,
• Maegan E. Jones 1 ,
• Emily C. Haugen 1 &
• Mallary K. Schaefer 1  

Journal of Eating Disorders volume  3 , Article number:  32 ( 2015 ) Cite this article

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In this study, we examined perceptions regarding the causes of eating disorders, both among those with eating disorders as well as those without. By understanding the differences in perceived causes between the two groups, better educational programs for lay people and those suffering from eating disorders can be developed.

This study used open-ended questions to assess the beliefs of 57 individuals with self-reported eating disorders and 220 without. Participants responded to the questions, “What do you think was (were) the cause(s) of your eating disorder?” and “What do you think is (are) the cause(s) of eating disorders?”.

A list of possible codes for the causes of eating disorders was created based on a thorough review of the literature. A manually-generated set of eight codes was then created from individuals' actual responses. Frequencies and chi square analyses demonstrated differences in rates of endorsement between those with eating disorders and those without. Participants with eating disorders most frequently endorsed psychological/emotional and social problems, with genetics/biology and media/culture ideals least endorsed. Participants without eating disorders most frequently endorsed psychological/emotional problems and media/culture ideals, with traumatic life events and sports/health least endorsed. There was a difference between groups in the endorsement of the media as a cause of eating disorders, suggesting that those without eating disorders may overly attribute the media as the main cause while those with eating disorders may not be fully aware of the media’s impact. Additionally, while both groups highly endorsed psychological/emotional problems, there was a noticeable stigma about eating disorders among those without eating disorders.

Conclusions

There were noteworthy differences between samples; such differences suggest that there is a need for more education on the topic of eating disorders. Furthermore, despite empirical support for the effects of genetics, sports, and family factors, these were infrequently endorsed as causes of eating disorders by both groups. Our results suggest that there is a need for more education regarding the factors associated with eating disorders, in order to reduce the stigma surrounding these disorders and to potentially aid the treatment process.

Eating disorders have increasingly become the focus of research studies due to their prevalence, especially in Western cultures. Of the adolescent and young adult populations in the United States, for example, between .3 and .9 % are diagnosed with anorexia nervosa (AN), between .5 and 5 % with bulimia nervosa (BN), between 1.6 and 3.5 % with binge eating disorder (BED), and about 4.8 % with eating disorder otherwise not specified (EDNOS) [ 1 – 4 ]. According to the fifth edition of the DSM, individuals that do not fit the criteria for AN, BN or BED are diagnosed with sub-threshold or atypical conditions that fit under other specified feeding or eating disorder (OSFED) [ 5 ]. Due in part to decreased thresholds for the diagnoses of AN, BN or BED in the DSM-V, rates of OSFED have been found to be lower than previous rates of EDNOS, while the rates of AN, BN or BED have stayed the same or slightly increased [ 6 ]. Furthermore, the age at onset is concerning, as most eating disorders originate during adolescence [ 4 ]. Despite the potentially serious health consequences that result from disordered eating [ 7 ], many in the general public believe that issues with eating are due to personal shortcomings [ 8 , 9 ]. This creates a foundation of stigma regarding why individuals develop an eating disorder (e.g., to be “skinny”) and the purpose the disorder serves (e.g., to gain control). Such stigma may dishonor the actual experience of those who have lived with an eating disorder, as people could assume eating disorders are self-inflicted. In turn, those developing unhealthy habits may be discouraged from seeking help [ 10 ].

Previous research has identified biological, psychological, and sociocultural factors related to the development of eating disorders. However, it is important to explore individual narratives to identify similarities and differences among individuals with and without eating disorders. Obtaining such knowledge can help scholars determine the public’s educational needs and better target missing gaps in their knowledge. More accurate information may reduce stigma regarding eating disorders, which may in turn encourage those experiencing symptoms to seek help sooner, as they may no longer fear the negative feedback from peers and family that such stigma causes.

Factors that contribute to eating disorders identified by research

Research has identified many risk factors, ranging from individual to sociocultural, that contribute to the development of eating disorders. Based on empirical literature, we present some of the most salient factors below.

Individual factors

Genetics and biology are individual factors that play a role in the development of eating disorders. Genetic contributions to the development of eating disorders have been suggested by twin studies, with heritability estimates ranging from 0.39 to 0.74, depending on the disorder [ 11 ]. Abnormalities in the regulation of certain neurochemicals, such as 5-Hydroxytryptamine (HT) and the serotonin-transporter-linked polymorphic region (5-HTTLPR), have been closely linked with eating disorders [ 11 – 13 ]. Further, recent research has identified mutations on two specific genes that have been associated with increased risk of developing eating disorders in families: estrogen-related receptor α (ESRRA) and histone deacetylase 4 (HDAC4) [ 14 ]. In addition, early puberty has also been associated with disordered eating behaviors, potentially due to increases or irregularities in circulating sex hormones, especially estrogen [ 15 , 16 ].

Body dissatisfaction has been commonly identified as an influential risk factor for eating disorders. Individuals dissatisfied with their bodies are at an increased risk of engaging in disordered eating behaviors such as bingeing and purging in order to gain satisfaction and move closer to the thin ideal [ 14 , 17 ]. Engaging in dieting behaviors also increases the risk for the occurrence of eating pathology such as binge eating and purging [ 15 , 18 ].

Researchers have recognized perfectionism as a specific risk factor in the development of eating disorders, as this personality trait may lead to a persistent pursuit of the thin ideal [ 15 , 19 , 20 ]. Perfectionism can also be a maintenance factor for disordered eating since it promotes dieting, bingeing, and purging, and enhances eating disorder symptoms, particularly when combined with low self-esteem [ 12 , 15 ]. Similarly, research has shown that negative affect in general, such as high levels of stress, guilt, hostility, anger, anxiety, and depressed mood, is associated with increases in eating disorder symptoms [ 12 , 13 , 17 – 21 ].

Sexual, physical, and emotional abuse have all received empirical support as risk factors for psychiatric difficulties, which can include eating disorders [ 22 ]. Specifically, research has shown that sexual abuse can occur in 29 % of individuals with eating disorders, and physical abuse may occur in 57 % of individuals [ 23 , 24 ]. Additionally, emotional abuse is a significant predictor of eating disorder symptoms among women when other types of abuse are controlled for, suggesting that emotional abuse may be particularly salient [ 12 , 25 ].

Sociocultural factors

Many sociocultural factors affect the development of eating disorders. In families, for example, mothers’ and fathers’ own body dissatisfaction and dieting behaviors have been associated with their children’s eating-related attitudes and behaviors [ 26 , 27 ]. Parental weight-related teasing, negative comments about body shape, pressure to lose weight, and encouragement to diet have also been associated with body dissatisfaction, dieting, disordered eating behaviors, and eating disorders among both females and males [ 12 , 15 , 26 , 28 – 31 ]. Furthermore, parents who engage in high levels of parental control, expressed emotionality, critical comments, hostility, or emotional overinvolvement and negate their child’s emotional needs are more likely to have children who develop eating disorders [ 12 , 32 ].

Peer influences on the development of eating disorders can also be broken down into a variety of factors. Peer pressure to conform to cultural ideals has been consistently identified as an important factor associated with the development of disordered eating behaviors, especially among adolescents [ 29 , 33 ]. In particular, girls may learn attitudes and behaviors from their peers, such as the importance of being thin and dieting behaviors, through modeling, teasing, and conversations about body image and eating [ 12 , 33 ]. Similarly, romantic partners play a significant role in the development of eating disorders through negative comments about appearance and encouragement to lose weight, which can lead to weight concerns, body dissatisfaction, and disordered eating behaviors among both men and women [ 34 , 35 ].

It is also worth mentioning that eating disorders among athletes are common, as there is a large focus not only on being in shape, but on being the fittest and therefore the “best” [ 36 , 37 ]. There is an even greater risk of developing an eating disorder with participation in certain competitive sports that focus on leanness, such as gymnastics [ 38 ]. Athletes who believe that being leaner will increase their performance are more likely to engage in disordered eating [ 39 ]. This belief may be encouraged or reinforced by coaches and instructors, further increasing athletes’ risk for developing disordered habits [ 40 ].

Lastly, the media has an influential, if often controversial, role in the development of eating behaviors due its representation of the thin ideal. There is support that, regardless of the level of internalized thin ideal, women who were warned that a thin media image was altered experienced lower body dissatisfaction in comparison to those who were not warned the image was altered [ 41 ]. A preference for a thin and virtually unattainable body has been associated with the development of eating disorders, particularly AN [ 42 ].

A relatively small number of studies have examined individuals’ perceptions regarding the causes of eating disorders [ 10 , 36 , 43 – 55 ]. Some studies have solely focused on the perceptions of either the general public [ 10 , 43 – 47 ] or those with eating disorders [ 36 , 37 , 50 – 55 ]. Both types of studies have identified a common set of risk factors, with public perceptions and the perceptions of individuals with eating disorders varying slightly [e.g. 48,49]. Overall, both populations have a basic understanding of what eating disorders are and characteristics of each eating disorder [ 10 , 36 , 43 – 55 ]. However, despite this knowledge, many adults without eating disorders may be unsympathetic to those suffering from eating disorders, believe that having an eating disorder would not be distressing, and report that eating disorders are not difficult to treat [ 9 ].

Public perceptions of factors that contribute to eating disorders

The studies to date that have focused on identifying public perceptions of the factors associated with the development of eating disorders have surveyed individuals drawn from communities or schools. Typically, these samples have been quite large, numbering over 100 [ 43 , 44 ] or even several hundred [ 10 , 45 , 46 ], and have included both females and males [ 10 , 43 , 44 , 46 – 48 ]. Despite the importance of large samples, all of these studies have been limited in that the researchers did not ask open-ended questions; rather, participants responded to forced-answer questions where they either had to identify which item was a cause of eating disorders or identify to what degree a particular item was a cause.

The public commonly places blame on individuals with eating disorders, suggesting that they have control over their “self-inflicted” illnesses [ 48 ]. Of the individual factors associated with the development of eating disorders, the majority of people who do not have eating disorders identify psychological explanations such as emotional state, personality, and low self-esteem [ 10 , 43 , 46 – 48 ]. The general public also believes that individuals’ own behaviors and attitudes related to body image such as dieting, a desire to be thin, and body image distortion are important factors in the development of eating disorders [ 43 , 47 , 48 ]. Traumatic events, genetics, and sexual abuse were rarely discussed or, if they were mentioned, rated low on the level of significance in causing eating disorders [ 10 , 47 ].

Although sociocultural factors are less commonly identified as causal factors of eating disorders among the general public, a few factors have received support. Of all the sociocultural factors, family issues were the factors most often identified [ 43 , 46 , 48 , 49 ]. Pressure from friends as well as social isolation and loneliness were also perceived to be factors contributing to eating disorders [ 46 , 47 ]. In one study, the portrayal of thin women in the media was a highly significant cause endorsed by adult women [ 45 ].

Perceptions of individuals with eating disorders regarding causes

In contrast to studies investigating the perceptions of the general public regarding factors associated with the development of eating disorders, most studies we found that focused on individuals with eating disorders used open-ended measures, either via interview or questionnaires. Despite this, one pitfall of the research to date is that it has often involved relatively small sample sizes, ranging from 15 to 36 [ 36 , 37 , 49 – 51 ]. Only two studies have included samples over 50 individuals [ 52 , 53 ]. Additionally, almost all of these studies have focused exclusively on women, with only two including a limited number of men [ 37 , 50 ]. Furthermore, although research has included assessments of individuals with AN [ 36 , 50 , 54 ] and BN [ 53 , 55 ] or both [ 49 , 51 , 52 ], studies have failed to examine if differences existed in the perceptions of those with AN versus BN, or include individuals with other eating disorders such as BED, EDNOS, or OSFED.

Similar to public perceptions of causal factors, people with eating disorders also identify individual and sociocultural factors. Individual factors commonly identified among samples of those who were diagnosed with eating disorders include perfectionism, emotional problems or distress, stress, unhappiness with appearance, high expectations of self, and lack of control [ 36 , 48 , 50 – 54 ]. Behaviors and attitudes related to body image, such as weight loss activities, body image distortion, and a belief that thinness equals happiness, were also frequently identified as factors that related to the development of their disorders [ 48 , 53 , 55 ]. Hereditary factors and sexual abuse were not indicated.

Sociocultural influences identified by individuals with eating disorders included the media, family, peers, and sports. Although rarely mentioned, the media was occasionally identified as playing a role through the importance it places on thinness and self-comparison to the thin ideal [ 36 , 37 ]. Family factors, in contrast, were often cited and included poor parental care, controlling parents, poor relationship with parents, family tension or high amounts of conflict, critical family environment, emotional abuse, and an emphasis on weight [ 36 , 37 , 48 – 51 , 53 , 55 ]. Factors associated with peers and sports were also common and included receiving comments or pressure from friends and coaches about appearance, a need to lose weight for sports performance, and poor relationships with peers [ 36 , 37 , 53 , 55 ].

Comparisons of individuals with and without eating disorders

We could only find two studies that examined the perceptions of both individuals with and without eating disorders. First, Haworth-Hoeppner [ 49 ] interviewed 21 women with an eating disorder (either AN or BN) and 11 without, asking open-ended questions about the development of eating disorders. In this study, no comparisons were made across the two groups, likely due to the qualitative nature of the project as well as the small sample size. Second, Holliday and colleagues [ 48 ] used larger samples of individuals with and without AN and made comparisons across groups regarding the causes of eating disorders and the most important causes. However, this study was limited in that it did not allow participants to describe their own beliefs. Instead, participants responded to a list of eighteen pre-identified causes of eating disorders, which did not allow for individual perspectives and greater depth into the complexity of eating disorders.

The present study

With the prevalence of eating disorders and young age of onset, examining people’s perceptions of the factors contributing to eating disorders is important. Such efforts can enhance public education and potentially decrease the stigma surrounding eating disorders. The present study specifically examined the differences between what people with and without eating disorders perceived to be the causes of eating disorders in order to better understand people’s experiences with eating disorders as well as to better educate the larger population. We also examined differences regarding the causes of eating disorders according to type of eating disorder, including AN, BN, both, and other (e.g., BED, EDNOS, or OSFED). This study strengthens existing research by utilizing qualitative, open-ended responses as opposed to forced-answer questionnaires so that participants could identify causes using their own opinions.

Participants and procedure

This study was reviewed and approved by the university’s Institutional Review Board. Our sample was recruited from flyers and emails distributed at local universities as well as from flyers distributed to local hospitals and clinics in a medium-sized, Midwestern U.S. city. A secure Internet link was provided, which participants used to indicate consent, provide demographic information, and answer several open-ended questions. All participants were first asked, “Do/did you have an eating disorder?” with the answer choices of “yes, currently,” “yes, in the past,” and “no.” Individuals who answered as having an eating disorder, whether past or current, were asked to specify which eating disorder they had/have and for how long.

The total sample consisted of 277 participants: 57 individuals who had a past or current eating disorder and 220 who did not. Consistent with the ethnic composition of the city, most of the sample identified themselves as White (93 %). There were 234 females (84.5 %) and 43 males (15.5 %). The age range of participants was from 18 to 51 (M = 22.39, SD = 5.77).

Sample with eating disorders

Of the 57 individuals who had an eating disorder, 26 had AN (46 %), 12 had BN (21 %), 11 had both AN and BN (19 %), and 8 had another type of eating disorder such as BED or EDNOS/OSFED (14 %). Participants reporting having an eating disorder from between 4 months and 22 years (M = 3.70 years, SD = 4.55 years). Similar to the demographics of the entire sample, 93 % identified as White, and the majority of individuals in this sample were female (96.5 %; n  = 55). Participants ranged in age from 18 to 47 (M = 23.70, SD = 5.84).

Sample without eating disorders

Of the 220 individuals who did not have an eating disorder, 93 % identified as White. In addition, 81 % identified as female ( n  = 179). Participants ranged in age from 18 to 51 (M = 22.05, SD = 5.71). In terms of ethnicity and age, both samples were similar; there were no statistically significant differences between samples ( p  = .80 and p  = .11, respectively). There was, however, a statistically significant difference in gender ( p  = .01).

Survey questions and compensation

After completing a series of demographic questions using the secure Internet link, individuals who had an eating disorder were asked the open-ended question, “What do you think was (were) the cause(s) of your eating disorder?” Individuals who did not have an eating disorder were asked a similar open-ended question, “What do you think is (are) the cause(s) of eating disorders?” These participants were then asked to report why they believed that these were the causes or how they learned about them. All participants were invited to participate in a random drawing for one of four $50 giftcards. Interested individuals were given another secure Internet link to provide their contact information if they wished to enter the drawing; this was done to keep the survey responses anonymous.

Coding of participants’ reponses

We initially created a list of possible codes for the causes of eating disorders commonly specified in previous research articles (as identified by overview articles on the risk factors or causes of eating disorders [e.g., 12, 15]). This provided us with a basic framework for content analysis [ 56 ]. Next, we manually generated a set of codes from actually reading individuals’ responses to the questions, “What do you think was (were) the cause(s) of your eating disorder?” and “What do you think is (are) the cause(s) of eating disorders?” Thus, we were able to identify a unique but relevant set of eight key themes. The eight themes that emerged from the data were: 1) traumatic life events, 2) family problems, 3) social problems, 4) psychological and emotional problems, 5) genetics and biology, 6) media and culture ideals, 7) sports and health, and 8) body image and eating.

Participants’ responses were then grouped under each of these categories. Many participants identified multiple causes of eating disorders, which were therefore grouped under multiple categories. The responses were coded independently by three research assistants, then checked by an additional research assistant and the first author for consistency. This was done to ensure interrater reliability [ 56 ]. When a difference in coding existed, the research team discussed the differences and mutually agreed upon a solution. See Table  1 for sample responses in each category.

Frequencies of individuals reporting each cause

A Chi square test for goodness of fit indicated that the participants in this sample showed significantly different rates of endorsement among the causes of eating disorders, χ 2 (7, n  = 108) = 41.63, p  < .05. Specifically, psychological and emotional ( n  = 30) and social problems ( n  = 22) were most frequently endorsed, with the lowest number of endorsements for genetics and biology ( n  = 2) and media and culture ideals ( n  = 5).

Individuals with AN most commonly indicated psychological and emotional problems as the cause ( n  = 13), followed by body image and eating problems ( n  = 9). Individuals with BN reported psychological and emotional ( n  = 8) and social ( n  = 7) as the primary causes. Those with both AN and BN listed all types of problems as causes, so there was not a clear primary cause, although social ( n  = 5) and psychological and emotional problems ( n  = 4) were slightly more frequently endorsed. Finally, those with other eating disorders most frequently cited psychological and emotional problems ( n  = 5) and traumatic life events ( n  = 3). See Table  2 for a complete listing of the frequencies of individuals citing each causal category.

A Chi square test for goodness of fit indicated that the participants in this sample showed significantly different rates of endorsement among the causes of eating disorders, χ 2 (7, n  = 414) = 326.95, p  < .05. Specifically, psychological and emotional problems ( n  = 141) and media and culture ideals ( n  = 104) were most frequently endorsed, with the lowest number of endorsements for family problems ( n  = 28), genetics and biology ( n  = 18), traumatic life events ( n  = 5), and sports and health ( n  = 4). Clearly, this sample differed from the sample of individuals with eating disorders in what they viewed as the primary causes. See Table  2 for the frequencies.

Differences between samples

Chi square tests for independence indicated that there was not a significant relationship between type of eating disorder (AN, BN, both, or other) and the causes specified. Furthermore, there were no significant relationships among each pairing of eating disorder sub-groups. The lack of statistically significant findings here could be the result of our small sample sizes for each group. See Table  3 for a summary of results from these chi square tests for independence.

Of particular noteworthiness, results from a chi square test of independence indicated that there was a significant relationship between eating disorder versus non-eating disorder groups and the causes specified, χ 2 (7, n  = 522) = 77.96, p  < .05, Phi = .39. This suggests that individuals with and without eating disorders had significantly different views regarding the causes of eating disorders, with each group likely to endorse causes at different rates. In conducting follow-up analyses of each cause separately, we found significant differences in the endorsement of family problems (χ 2 (1, n  = 39) = 7.41, p  < .05), social problems (χ 2 (1, n  = 79) = 15.51, p  < .05), psychological and emotional problems (χ 2 (1, n  = 171) = 72.05, p  < .05), genetics and biology (χ 2 (1, n  = 20) = 12.80, p  < .05), media and culture (χ 2 (1, n  = 109) = 89.92, p  < .05), and body image and eating (χ 2 (1, n  = 71) = 26.04, p  < .05) among those with and without eating disorders. More specifically, individuals with eating disorders more often endorsed family problems, and social problems while individuals without eating disorders more often endorsed psychological and emotional problems, genetics and biology, media and culture, and body image and eating.

Additionally, there were significant relations between each individual type of eating disorder versus non-eating disorder and the causes specified. See Table  3 for these results. This suggests, for example, that individuals without eating disorders had different levels of endorsement for each cause than the group of individuals with AN. The same was true for the sub-groups of BN, both, and other, when compared to individuals without eating disorders.

This is the only known study that assessed subjective perceptions of the causes of eating disorders among a relatively large sample of individuals with and without eating disorders. The results support differences between the general public and individuals suffering from eating disorders, which hopefully can be used to provide proper education. Specifically, the general public largely believed that the media causes eating disorders, a perception that is not shared among individuals with an eating disorder. Similarly, sports, body image, and traumatic events were listed less frequently by participants without eating disorders than participants with eating disorders. However, psychological and emotional problems were highly endorsed by all. Together, these findings indicate differences in opinion regarding the causes of eating disorders between those who have an eating disorder and those who do not.

The open-ended questions used in the present study enabled us to gain insight into individuals’ personal opinions regarding factors associated with the development of their disorders, ultimately providing a greater understanding for both clinicians and lay people. Psychological and emotional problems were the most frequently reported causes for those with an eating disorder, supporting the need for greater availability of support systems. In considering the perspectives of individuals who had an eating disorder, it is difficult to know if their perceptions align accurately with the actual causes. However, professionals working with these individuals could help assess the discrepancy between perceived and actual causes. For many postmodern therapists, understanding the perception of the eating disorder from the client perspective and helping him or her make meaning of the experience is more important than determining the actual cause of the disorder [ 57 , 58 ]. This, therefore, provides reinforcement for the role of psychologists and family therapists within the field of eating disorders, yet many currently lack sufficient training to address eating disorders and instead must refer clients to specialists, who are often expensive and not widely located.

The role of the media

Our findings revealed a definite contrast between how people with and without eating disorders perceive media as a risk factor for developing an eating disorder. A large percentage of people without eating disorders identified media as a cause (47 %), but only five total participants with eating disorders did. There is a clear separation in the experience of those with eating disorders and with society’s conceptualization of them [ 36 , 37 ]. Thus, it seems that lay individuals may overemphasize the role of the media as one of the main causes of eating disorders, while those with eating disorders may not be fully aware of the potential impact of the media [ 50 ]. Whereas specific media variables such as depiction of the thin ideal and unrealistic body standards may be correlated with eating disorders [ 42 ], they do not fully explain disordered behaviors. Our findings should be used to educate consumers of media on the complexity of eating disorders, and as evidence for the need to change the types of messages regarding body image ideals that are currently available in the media.

• Psychological and emotional problems

Psychological and emotional problems were one of the highest named causes of eating disorders by both groups, which is consistent with prior research [ 43 , 46 , 48 ]. However, upon close examination of the data, we noticed a contrast between the written answers of those who had eating disorders and those who did not. More specifically, individuals with eating disorders listed personal reasons, such as “a bad relationship that caused a lot of low self-esteem,” or simple statements such as “stress, depression.” In contrast, there was a negative stigma surrounding some of the answers from participants without eating disorders. These answers included phrases such as “no self-confidence” and “mental disabilities.” This difference is worth noting, because it demonstrates a stigma towards those with eating disorders, which may result in a fear of judgment from others that often prevents those suffering from eating disorders to seek help [ 59 ]. Reduction of this stigma through educational programs could encourage individuals who are developing disordered eating habits to speak up, as well as encourage friends and family to begin a non-judgmental, supportive dialogue with individuals about their habits.

Other factors

Traumatic life events were only listed by 2 % of the non-eating disorder group, versus 23 % of those with eating disorders. This once again emphasizes the need for education geared towards the general public. However, there is also a need for better education for those with eating disorders, as the number of people listing traumatic events was quite low. Many individuals may not make the connection between a traumatic event, such as sexual assault, and the beginning of their disorder, despite empirical support for the effects of abuse [ 22 ].

Similar to previous studies, genetics as a cause of disordered eating was only listed by two participants with eating disorders and eight participants without eating disorders [ 10 , 47 ], making it the least endorsed cause. This indicates a need for the dissemination of information regarding the genetic component of eating disorders, as this could potentially help with the negative stigma surrounding eating disorders [ 60 ].

Similarly, and in line with previous studies, only twelve participants with eating disorders and 28 participants without listed family problems as a cause of disordered eating [ 43 , 46 , 48 , 49 ]. There are numerous studies, however, that show the impact that mothers, fathers, and siblings can have on the development of disordered eating in an individual (e.g., [ 26 , 27 ]). If education efforts could help improve understanding of how eating disorders develop within families, parents and siblings can take steps towards preventing the occurrence of these issues and can work towards developing healthier habits for themselves as well.

Sports and health were also listed more frequently as causes by those with eating disorders (19 %), whereas only 2 % of those without eating disorders mentioned them. However, these numbers are both still low. The general public, and specifically coaches, need to be aware of how an intense focus on the body can lead to negative outcomes and strive to support healthy methods of getting and staying in shape.

Body image was listed as a cause of eating disorders by 26 % of participants without an eating disorder, and 25 % of those with experience with disorder eating; these numbers represent a substantial portion of participants. Poor body image often provides a foundation for the development of an eating disorder [ 15 , 17 ], and understanding what issues underlie an eating disorder can help not only those struggling to recover, but those trying to assist them.

Another highly-endorsed cause of eating disorders was social problems, as 26 % of those without eating disorders and 39 % of those with eating disorders listed them. While these numbers are considerably higher than other groups, only one fourth of those without eating disorders acknowledged social problems as a cause, while a much larger number of those with eating disorders indicated social problems as a cause. However, many individuals may not realize the effect that external events can have on their internal belief systems, once again indicating the need to incorporate this finding into general education, as well as into the treatment process as a way of lessening the blame that those suffering may place on themselves.

Summary of findings

This study provides insight into the educational resources needed to inform the lay audience regarding eating disorders as well as some factors to consider in the education or prevention of eating disorders among those affected. There is a clear difference between perceived causes of eating disorders from those who have experienced them and those who have not. Those who had not struggled with an eating disorder were more likely to believe that media and cultural ideals influenced eating disorders. For those who had lived with an eating disorder, this was one of the least likely perceived causes. Social problems, in contrast, were frequently listed by participants with eating disorders and less frequently listed by participants without. Genetics and traumatic events were listed most infrequently by both groups, and there were also relatively low levels of endorsement for traumatic life events, sports and health, and family problems among both groups. Both groups listed body image as a fairly frequent cause, and although both groups highly endorsed psychological and emotional problems as causes, there was a clear negative stigma surrounding psychological and emotional problems when listed by non-disordered participants. Improved educational programs should seek to give those who are uninformed a greater understanding of how psychological, social, and relational factors influence those with eating disorders. Increased opportunities for those who have lived with eating disorders to share their stories and perspectives are also needed. With the opportunity to provide first-hand knowledge, these individuals can be an excellent asset for researchers, professionals, and lay people.

Limitations

Our sample was a relatively homogenous group in terms of gender and ethnicity, so separate analyses could not be conducted examining differences among men and women or among various ethnic groups. Thus, care should be taken when generalizing the results to males and non-white individuals. Furthermore, in order to utilize open-ended questions, no measurement scales were used to determine eating disorder pathology. Therefore, eating disorder status was determined solely by self-report and may not be clinically accurate. In retrospect, it may have been useful to at least provide participants with a self-report survey to assess their eating disorder symptomatology. However, we do note that our sample was recruited not only from local universities but directly from hospitals and clinics that included eating disorder treatment facilities. As a result, we hope that participants were able to appropriately reflect on the nature of their symptomatology. Further, our type of questioning allowed for only two groups of samples, those with eating disorders and those without; individuals who have subclinical symptoms or undiagnosed eating disorders may have been inaccurately placed in the category of non-eating disorder due to their own assessment. Similarly, those who identified themselves as having an eating disorder may have been self-diagnosed, and therefore may not technically meet clinical standards for a disorder.

Additionally, two different questions were asked of participants. Specifically, we asked participants with an eating disorder: “What do you think was (were) the cause(s) of your eating disorder?”, and we asked participants without an eating disorder: “What do you think is (are) the cause(s) of eating disorders?” This allows individuals to add a personal dimension to their analysis of the causes of eating disorders. As such, they may believe that the cause of their disorder is very different than the cause of someone else’s disorder. Similarly, individuals with an eating disorder may have focused more on life events or recent triggers without a reflection on more general risk factors.

Lastly, because this study was completed online, it could be considered relatively impersonal, whereas in-person interviews would have most likely been more in depth. However, because the main interest of the study was to examine participants’ instinctive reactions to eating disorders, the completely anonymous online survey was the most beneficial means of execution.

Despite limitations, this study contributes to the field in a variety of ways. The sample size of those with eating disorders ( n  = 57) is somewhat larger than samples currently in the literature. Furthermore, while many studies focus only on AN or BN, this study included those with self-reported AN, BN, BED and EDNOS/OSFED, allowing for more inclusive results. It also allowed us to separately assess perceived causes of eating disorders according to the type of eating disorder. For example, individuals with AN most frequently indicated psychological and emotional problems as well as body image and eating problems; individuals with BN often reported psychological and emotional problems as well as social problems; individuals with both AN and BN listed all types of problems; and individuals with BED, EDNOS, or OSFED primarily cited psychological and emotional problems as well as traumatic life events. Although these differences in perceptions were not statistically significant, it may suggest that each type of disorder is unique, with potentially unique causes attributed to the disorder. Future research should continue to examine these differences, and education should focus on the unique nature of each type of eating disorder.

The use of an open-ended qualitative assessment allowed for a complete picture of individuals’ perceptions of the causes of eating disorders. It also allowed individuals to write about more than one perceived cause of the disorders, which is not always possible with close-ended questions with limited answer options. An additional strength of this study is that it contributes to the relatively small pool of current literature discussing perceptions of eating disorders. Within this limited research, most examine perceptions of the general public or perceptions of those with eating disorders separately. Our study is also one of very few studies to examine differences between these two groups.

Overall, it appears that all individuals would benefit from learning more about eating disorders and their causes. Knowing this could be particularly helpful for individuals going through eating disorder treatment, especially for therapists to use when educating those close to someone struggling with an eating disorder. This could help facilitate greater support and connection between family members and friends, and help to end the stigma surrounding these problems and allow those in trouble to seek help.

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Acknowledgements

We thank our undergraduate and graduate research assistants at the North Dakota State University Eating Disorders and Body Image Lab for their assistance with coding the data.

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Elizabeth H. Blodgett Salafia, Maegan E. Jones, Emily C. Haugen & Mallary K. Schaefer

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EHBS conceived of and designed the study, developed codes for and analysed the data, and wrote the manuscript. MEJ co-wrote and formatted the manuscript. ECH coded data and co-wrote the manuscript. MKS coded data and co-wrote the manuscript. All authors read and approved the final manuscript.

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Blodgett Salafia, E.H., Jones, M.E., Haugen, E.C. et al. Perceptions of the causes of eating disorders: a comparison of individuals with and without eating disorders. J Eat Disord 3 , 32 (2015). https://doi.org/10.1186/s40337-015-0069-8

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Received : 13 April 2015

Accepted : 04 September 2015

Published : 15 September 2015

DOI : https://doi.org/10.1186/s40337-015-0069-8

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