impact of mobile on college students essay

ORIGINAL RESEARCH article

Smartphone use and psychological well-being among college students in china: a qualitative assessment.

• 1 School of Journalism and Communication, Minjiang University, Fuzhou, China
• 2 School of Journalism and Media, University of Kentucky, Lexington, KY, United States
• 3 School of Economics and Management, Minjiang University, Fuzhou, China

Background: Problematic smartphone use is widespread, and college-age youth faces an especially high risk of its associated consequences. While a promising body of research has emerged in recent years in this area, the domination of quantitative inquiries can be fruitfully and conceptually complemented by perspectives informed through qualitative research. Toward that end, this study aimed to interrogate the myriad behavioral, attitudinal, and psychological tendencies as a side effect of college students’ engagement with the smartphone in their everyday lived experience through in-depth interviews.

Methods: We recruited 70 participants from seven college campuses hailing from different geographic regions in China, and conducted semi-structured in-depth virtual interviews via WeChat in November and December 2020. Subjective experiences, personal narratives and individual perceptions in the context of routine interaction with the smartphone were thematically analyzed through a reiterative process in an effort to detect prevailing threads and recurring subthemes.

Results: The smartphone has established a pervasive presence in college students’ everyday life. Time-based use characteristics generated a typology of four distinct user groups: hypo-connected antagonists, balanced majority, hyper-connected enthusiasts, and indulgent zealots. Habitual usage falls on predictable patterns matched onto temporal, locale-based and contextual cues and triggers. Students’ dependency relationships with the smartphone have both functional and emotional dimensions, as prominently manifested in occasions of detachment from the device. Self-regulatory effort in monitoring and limiting use is significantly impacted by mental focus and personal goal setting. Perspectives from our qualitative data suggest the need for taking into account a variety of contextual cues and situational factors in dissecting psychological and emotional outcomes of smartphone use and abuse.

Introduction

The rapid and widespread penetration of mobile technologies into the fabric of everyday life has fundamentally changed the landscape of human communication. This mobile revolution has been amplified by two landmark developments in the 21st century: mobile phone subscription surpassed fixed-line use in 2002 ( Srivastava, 2005 ), and Apple launched its first iPhone in 2007 (followed by Google’s Android devices in 2008). By incorporating multifunctional applications and multifaceted traits into an all-in-one device, smartphones have nourished “an [sic] historical movement toward a personal communication society” ( Campbell and Park, 2008 , p. 381). Thanks to their boundary-spanning nature, portable convenience and all-encompassing affordances, smartphones function as integrated environments of polymedia ( Madianou, 2014 ), and have turned into the “fourth screen” (coming after but emulating the historical role of the cinema, television, and computers) ( Miller, 2014 ).

The pervasiveness of mobile media in general and smartphones in particular with the adolescent population is a hallmark of contemporary youth culture. As “mobile natives,” Vanden Abeele (2016) argues that immersive engagement with the smartphone has engendered heterogeneous “mobile lifestyles” among the current youth generation. Smartphone technology conforms to the Apparatgeist of “perpetual contact” – “the spirit of the machine that influences both the design of the technology as well as the initial and subsequent significance accorded them” ( Katz and Aakhus, 2002 , p. 305). The always-on mode of the smartphone, coupled by its portability and multilayered functionality, has triggered concerns about its addictive potential, especially among the adolescent and youth population. Against this backdrop, an expanding body of academic inquiries in recent years has linked excessive smartphone use to a variety of addiction-like behavioral and psychometric symptoms such as decrease in productivity and daily interruptions ( Duke and Montag, 2017 ), stress, social anxiety and loneliness ( Vahedi and Saiphoo, 2018 ), neuroticism and impulsivity ( Carvalho et al., 2018 ).

The term “smartphone addiction” has been prevalently used and frequently studied in conceptual frameworks commonly adopted for substance abuse and pathological gambling in contextualizing its antecedents as well as myriad negative physical and physiological outcomes and consequences ( Mahapatra, 2019 ; Sahu et al., 2019 ; Yu and Sussman, 2020 ). However, we concur with Panova and Carbonell (2018) that, even though there is mounting evidence to associate smartphone use with various problems and negative outcomes, “addiction” is not an accurate or correct term to diagnose a set of psychological or physical consequences that are not comparable to the severity and/or associated health problems caused by substance addiction. In a similar vein, as De-Sola Gutiérrez et al. (2016) point out, the diversity of perspectives encapsulated in the umbrella term and the failure to differentiate between addiction, problematic use and abuse has caused confusion and muddied comparability of findings.

It is worth noting that different terms – among them smartphone addiction, smartphone use disorder, pathological smartphone use, excessive smartphone use, maladaptive smartphone use, smartphone dependence, and problematic smartphone use – have been used interchangeably or synonymously in most academic literature. We support the call ( De-Sola Gutiérrez et al., 2016 ; Panova and Carbonell, 2018 ) for a more precise conceptualization of terms, which is more constructive in promoting academic deliberations in investigating symptoms and pondering corresponding corrective actions. We therefore adopt the term problematic smartphone use (PSU) in our research, which aims to examine the myriad behavioral, attitudinal, and psychological tendencies as a side effect of college students’ engagement with the smartphone in their lived experience. We resorted to semi-structured in-depth interviews with 70 college students in disentangling the variety of nuanced pathological habitual patterns and psychological predispositions in the context of students’ daily interaction with the smartphone.

Problematic Use of the Smartphone: Psychological and Behavioral Dimensions

By consolidating computing, portability, and mobility into one interface, the smartphone has the potential to fulfill a variety of communication needs from information to entertainment and interaction. The all-in-one nature of smartphone technologies has drastically enhanced the ever-expanding repertoire of available functionalities and applications. However, availability of services is not tantamount to adoption by the end users. As is the case with most other media technologies, usage and adoption of mobile applications and services has been a well-trodden area of academic research in the new millennium (e.g., Park and Chen, 2007 ; Verkasalo et al., 2010 ; Kang and Jung, 2014 ). The continuous advancement of smartphone technologies calls for constant update of this line of research in various national contexts.

Research Question 1: What are the most frequently used smartphone-based apps in college students’ daily routine engagement?

Design of the smartphone succeeds on a variety of habit-forming technologies and compulsive human tendencies ( Eyal, 2014 ). As a result, habitual use of the smartphone has the potential to develop into certain patterns of compulsive behaviors, including repetitive checking (brief sessions of touching), context-dependent triggered acts, and quick access of dynamic content, all of which may induce habit formation on users ( Oulasvirta et al., 2012 ). Psychology of habit theory posits that a variety of cues, exposure to which may be intentional or inadvertent, can trigger habit performance; in the case of substance use, addiction results when motivation shifts from goal-directed (voluntary) to habitual drug use ( Wood and Rünger, 2016 ). It stands to reason that the same process applies to pathological smartphone use, although more research is needed in support of this mechanism. We therefore pose the following research question:

Research Question 2: What are the temporal and venue-based cues and triggers driving patterns of habitual use of the smartphone?

In terms of psychological consequences, a meta-analysis of 30 independent samples by Vahedi and Saiphoo (2018) confirms a positive association between PSU and stress and anxiety. A survey of college students in Turkey by Enez Darcin et al. (2016) found that social anxiety and feeling of loneliness are associated with vulnerability to smartphone addiction. In a similar vein, Yang et al.’s (2020) meta-analytic review of 14 studies points to a significant correlation of PSU with poor sleep quality, depression, and anxiety. Recent research has started to pay attention to NOMOPHOBIA or NO MObile phone PHOBIA, which is a psychological condition caused by the mental disorder over fear of being disconnected from the smartphone ( Yildirim and Correia, 2015 ; Bhattacharya et al., 2019 ). Another behavioral tendency, especially among adolescent and young users, is called “phubbing,” defined as the practice of “an individual halting face-to-face communication with another person to interact with their telephone” ( Erzen et al., 2021 , p. 57). Moreover, problematic smartphone behavior can be exacerbated by FOMO, or Fear of Missing Out – the perceived need to be constantly connected over the apprehension of missing important information, especially that over social networking sites ( Wolniewicz et al., 2018 ; Elhai et al., 2020 ). We are thus interested in finding out:

Research Question 3: What are the college students’ self-reported symptoms and motivating factors with regard to NOMOPHOBIA, Phubbing and FOMO?

There is a growing awareness among the general public about the excessive amount of time the smartphone consumes and its possible negative consequences on personal health and well-being. In response to the concerns of deepening dependency on the smartphones, digital detox has been proposed as one viable solution to promote planned abstinence from electronic devices such as the smartphone. A synthesis of existing evidence from the body of detox scholarship published between 2008 and 2020 as it relates to smartphone use shows mixed results, with no consistent findings between detox interventions and subsequent cognitive and physical performance measures ( Radtke et al., 2021 ). We would like to contribute to this emerging line of research by asking:

Research Question 4a: What detox measures, if any, do students undertake to mitigate smartphone (over)use?

Research Question 4b: What is the efficacy of these detox interventions?

It is worthy to highlight that the majority of the research on smartphone use and addiction has been inspired by quantitative studies. For instance, an extensive review of current research on phubbing by Al-Saggaf and O’Donnell (2019) led them to bemoan the paucity of qualitative studies and prompted them to call for more qualitative interviews in offering rich descriptions on why people phub. What we aim to contribute to the expanding body of literature through our qualitative semi-structured interviews is to supplement and complement the sizable body of quantitative findings with in-depth, personal and situated perspectives to the diverse dimensions of PSU.

Materials and Methods

We recruited university students from seven college campuses in China, hailing from different geographic locations and representing diverse academic disciplines. Interviewees were briefed on the overall purpose of the study as well as the voluntary nature of participation, and these who agreed to proceed were asked to sign an informed consent to take part in the study. Participants were assured of the anonymity of the interview data. We resorted to a semi-structured interview design in an effort to “understand themes of the lived daily world from the subjects’ own perspectives” ( Brinkmann and Kvale, 2018 , p. 14) with regard to their daily encounters with the smartphone. Because the interviews were conducted in November and December 2020 when the Covid-19 pandemic was still a threat, we adapted to a virtual interview modality conforming to the overall strategies and suggestions in Gray et al. (2020) and Khalil and Cowie (2020) from subject recruitment to rapport building to question handling and use of verbal/non-verbal cues, the main rationale of which was driven by concern for the participants’ health and well-being. However, one major difference is that, instead of using Zoom or Skye, we adopted WeChat, the most popular real-time chat app in China, to conduct the interviews. The reason is that all students have a high level of familiarity and comfort with video-chatting on WeChat, a routine engagement in their daily communication. Our overall WeChat interview experience corroborates the observation by Jenner and Myers (2019) , who conclude after comparing Skye and in-person interviews that virtual interviews are conducive to more sharing of personal information, and does not compromise rapport or reduce the efficacy of the interview methods. As a result, we did not sense any loss or inferiority of the data thus obtained.

The questions cover a range of activities and user characteristics, with most of them open-ended in nature so as to capture the nuanced variations and diverse meanings each interviewee might assign while describing their everyday engagement, but all questions maintained a focus on themes pertaining to the various aspects of PSU mentioned in the above literature review. Specifically, we developed a few clusters of questions focusing on topics framed in our research questions, such as most-often used apps (RQ1), patterns of habitual use and responses to situated cues (RQ2), symptoms of NOMOPHOBIA, phubbing behavioral tendencies, how they would respond to leaving their smartphones behind, and FOMO (RQ3), and whether they had taken detox measures (RQ4a), and (if yes) to what effect (RQ4b). Each interview typically took 30 to 40 min to complete, with a few having gone more than 1 h. Follow-up questions were asked whenever necessary for the sake of clarification or data enhancement.

Data were analyzed by following the well-established qualitative content analysis and thematic analysis approaches in dissecting manifest content into categories and latent content into thematic threads ( Guest et al., 2011 ; Vaismoradi et al., 2016 ). Our analysis is also inspired by the grounded theory method through immersing ourselves in the data corpus in pinpointing key concepts via microanalysis of specific topical areas as well as identifying salient patterns and thematic threads at the level of general analysis ( Brinkmann and Kvale, 2018 ). Conforming to the often-adopted practice of processing the data through a reiterative process in analyzing qualitative interview data, we went through multiple rounds of analysis in first detecting core discrete concepts at the local/individual level and then deciphering dominant, tacit thematic alignments regarding broad perspectives from integrating the totality of the data.

Interviewee Demographics and User Typology

The interviewees comprised 52 female and 18 male students. The disproportionate male/female makeup largely reflects the distribution of the gender differences in the disciplines in the host universities, which are dominated by humanities, social and management sciences, although the number is slightly skewed to the female line.

Of necessity, smartphone dependency first manifests itself in the amount of time one engages with the device on a daily basis. We asked each interviewee to offer an estimate on how much time the smartphone consumes them every day by turning on the Screen Time feature on their smartphone. The majority of the students were able to offer pretty precise answers, typically to the hour with some indicating a clear range (e.g., 6–7 h); moreover, about a quarter of the students reported the exact time as revealed on the Screen Time, such as 5 h 36 min on weekdays by one student. Based on their estimations, the average number of hours on the smartphone approximates to about 6 h (5.7 vs. 5.9 along male/female line) per day on weekdays. There is a sizable increase to the weekend hours (7.7 for male and 7.9 for female). There is, however, significant variation among the individuals, as the reported daily smartphone hours ranged from just 50 min to 10 h on an average weekday, and from 20 min to 12 h on weekend days. For the vast majority of students, there is a consistent pattern in the weekday-weekend variation; we therefore arrived at the daily average use amount in terms of hours by adopting the respective mean of weekday and weekend hours for each interviewee. Our tabulation of users in conformity to the daily amount of smartphone engagement yields four types of users, as reported in Table 1 : below average (disciplined) users (less than 4 h on the phone per day); average (balanced) users (spending 4–7 h on the phone per day); above average (heavy) users (being on the phone for 8–9 h every day); and excessive (problematic) users (using 10 h or more for smartphone-related activities).

Table 1. Typology of users.

Among the four individuals (three in the female group and one from the male group) who said they spent less than 4 h on an average day, all indicated the exercise of self-imposed control as an intentional effort to reduce the amount of time on the phone. On the opposing end, the nine students (making up about 12.9% of the total) who reported excessive smartphone use consented to symptoms of problematic or pathological dependency by explicitly admitting an urge to get onto the smartphone whenever possible. The following quote illustrates the all-consuming nature well by one interviewee: “I get onto my phone whenever I am free. Especially when it comes to the weekend, I stay on my phone all the time except for eating meals or taking the bath.”

For ease of cross-type comparison, we summarized time-based pattern of smartphone use in association with psycho-attitudinal responses to the interview questions into four distinct groups, as presented in Table 2 . First, the hypo-connected antagonists (5.7% of the total) recognize the utilitarian aspects of the smartphone, and their engagement is driven by a highly goal-oriented approach in that they mostly know what they are looking for and go directly to the respective app, dominated by informational and social networking needs, accomplished in short sessions. They are also quite cautious about the negative potentials of the smartphone and exercise appropriate self-control. Second, the balanced majority (51.4%) maintain a conspicuous presence on the smartphone by spending 4–7 h on it. Their use is more expansive, as a significant amount of time is consumed in activities such as listening to music, video-sharing, and mobile shopping beyond information-seeking and social networking. They typically spend half to 1 h browsing the phone before bed and display more noticeable tendencies than hypo-connected antagonists symptomatic of NOMOPHOBIA, phubbing, and FOMO.

Table 2. Psycho-attitudinal traits of different user types.

The third user type, which we name hyper-connected enthusiasts , comprises 30% (22.2% male vs. 32.7% female) of the participants. Hyper is indicated by the level of smartphone engagement as measured in the amount of smartphone time (averaging 8–9 h per day), and enthusiasm is embodied in the palpable craving we detected in their interview conversations while discussing smartphone activities as well as their related emotional dispositions therein. Compared with the two previous groups, entertainment use (e.g., watching teledramas, reading online fiction, viewing movies and using TikTok) is an important part of their regular engagement with the smartphone.

The fourth cohort – who we call indulgent zealots – spend almost all their time outside of class and free from other required duties on the smartphone (averaging about 10 h per day). Although amount of time alone should not be the sole criterion, it is one of the most dependable benchmarks in diagnosing PSU in extant research ( Duke and Montag, 2017 ; Vahedi and Saiphoo, 2018 ; Sahu et al., 2019 ). The statistical distribution of this group (12.9%) fits well-nigh the overall estimate by Eichenberg et al. (2021) in evaluating the prevalence rate of PSU at 15.1% in their study of college students in Vienna. Besides the prevailing tendency to stay longer on a variety of activities that the previous groups also engage in, close to one-half of them specifically mention mobile gaming as one of the most frequently accessed apps on their smartphone. Of particular note is that these students consistently display a set of psych-behavioral traits commonly associated with PSU, such as NOMOPHOBIA, FOMO, and worrying about the amount of time consumed by the smartphone.

The fact that gaming has been mentioned the most prominently among the indulgent zealots is noteworthy, as gaming has been consistently pinpointed as a primary addictive tendency associated with compulsive smartphone use ( Liu et al., 2016 ; Derevensky et al., 2019 ). However, PSU symptoms are not just limited to indulgent zealots only, as similar patterns (albeit to a slightly lesser extent) can be observed with hyper-connected enthusiasts. With regard to content type, the reported use pattern among our cohorts is highly congruent with research findings linking entertainment use and gaming to problematic smartphone dependency ( Jeong et al., 2016 ; Bae, 2017 ; Park et al., 2021 ).

The overall patterns of differences across the four user categories can be found in Table 2 . Detailed symptomatic manifestations among the interviewees are discussed in the sections that follow along the topical lines of the research questions.

Smartphone Utilities (RQ1)

We asked each participant to name five to six apps that they used the most frequently. Among the most mentioned are a total of about 20 apps encompassing four broad areas of functions and affordances. Ranked in the degree of their popularity, the first category serves to carry out variegated tasks of socializing functions via instant video and text messaging, as seen in WeChat, QQ, and Sina Weibo. The second type of apps pertains to multiple ways of news sharing and information seeking (e.g., WeChat, QQ, Toutiao, Zhihu). Closely aligned with the second type is an assortment of apps – for example, Xiaohongshu, Taobao, Alipay, Elema – that facilitate the delivery of utilitarian transactions and tasks ranging from online shopping, mobile payment, photo-taking, and time-keeping to navigational services. Trailing not far behind, the fourth category of apps cater to students’ entertainment needs, as exemplified by NetEase Cloud Music, QQ Music, blibli, Youku, and mobile games led by King of Glory (also known as Wangzhe Rongyao in Chinese) and Counter-Strike .

Table 3 lists the top 10 apps students reported using the most. Of particular note is the role of WeChat in the routines of everyday communications among the participants. WeChat offers multifunctionalities that crosscut boundaries typically found in the first and second types of apps as mentioned above – its text messaging, audio and video chat features are widely used for one-on-one interpersonal communications, while the group chat and one-to-many broadcast capabilities make it the platform of choice for getting messages out to groups of varying sizes. The latter affordances make WeChat a hugely popular venue for information sharing, as evidenced in the avowed use of WeChat by the students as a major channel of information seeking.

Table 3. Top 10 most often-used smartphone apps.

Along gender lines, we noted a striking difference: male students express an unmistakable appetite for games, whereas female students are much more inclined to use the built-in camera. King of Glory dominates mobile gameplay. Conversely, almost all female students admitted to using the built-in camera as one of their favorite habitual undertakings while only about half male students acknowledged doing this. The most common cited motive for photo-taking is to chronicle daily life, as revealed in this quote: “Shooting pictures is my favorite pastime. I send photos of my every meal to my parents. I will take photos of the scenery or objects I like whenever I take a stroll.”

One notable development in China during the past years has been its quick transformation into a cashless environment enabled by the widespread adoption of mobile payment technology. This is resonated soundly in the interviews, and it comes as no surprise that e-payment via the smartphone is one of the most sought-after features among the students. This is well illustrated by the following statement:

“One cannot be separated from the smartphone nowadays, mainly because it fulfills the daily need of paying bills. Like most everyone else, I used to pocket cash a few years ago. Now that’s no longer necessary thanks to the smartphone. I can almost do any transaction with the phone, such as buying stuff, paying fees and purchasing tickets. So the smartphone is indeed all-capable!”

Indeed, many students specifically mention e-wallet as one of the major causes of their anxiety when asked about how they feel when they don’t have their smartphone with them. This is elaborated in the ensuing discussion on NOMOPHOBIA.

Habituation (RQ2)

As mentioned in the previous literature review, checking behaviors comprise a large part of repetitive habitual use of the smartphone ( Oulasvirta et al., 2012 ), and smartphone-related habits are closely associated with external situations or internal states ( Wood and Rünger, 2016 ; Park et al., 2021 ). Research also indicates that process-oriented smartphone use may develop into habits, which may in turn automatically trigger problem behaviors activated by internal or external cues ( Van Deursen et al., 2015 ). We asked the students about their habitual routines, rituals, and general tendencies in using their smartphones. The following thematic lines stand out across the interviewees.

A clear pattern emerges characterizing students’ interaction with the smartphone: almost all indicated that the time they spent on the phone surges during weekend or holidays; and smartphone is the primary medium of choice when fragments of time are available, such as during intervals between routine tasks, and moments of non-essential or leisure activities. Smartphones are the unrivaled choice for casual browsing, as students typically opt for “swiping” at most chunks of time available. As far as gender is concerned, female students display no significant deviation percentagewise in these behavioral patterns.

The venue that smartphone consumes the most uninterrupted chunk of time is the dorm for most students. The most extensive block of concentrated smartphone time on each day for virtually everyone is the pre-bedtime hours, although the specific amount of time varies from about half an hour to more than 2 h. The next routinized allocation of smartphone time prevalent among the students is the early morning hour, when the students typically idle on bed from 15 min to close to 1 h browsing the smartphone. Besides the difference in length of time, the late-evening and early-morning rituals tend to focus on different tasks and accomplish different purposes. Late-evening smartphone use is primarily entertainment-oriented (e.g., video, online teledramas, music, gossipy tabloid hearsays, gaming), although socializing (e.g., personal communication) maintains a noticeable presence. Early-morning smartphone checking uniformly centers on updating news of the day and attending to personal messages. As result, students mentioned gravitation toward different apps during these two daily periods. It is also worthy of note that the pre-bed period shows a distinct pattern of variation among the different types of users (from below average to excessive users) in the amount of time they expense. Especially among heavy and excessive users, many confess that this has become a basic routine as a necessary precursor to sleep every night. In contrast, the early-morning time immediately after wake-up, which is typically followed with some smartphone browsing, does not vary much with user types, with each student spending anywhere between 10 and 20 min doing this. This is understandable in that morning is not the time for most students to loaf around in bed, as they are rushed to get ready to embark on the errands of the day.

Besides the pre-bed hour, the next block of time of concentrated smartphone use for the students is during meal (i.e., lunch and dinner) time, when casual, entertainment use dominates. This is confirmed both from self-revealed narratives and alleged observations of habitual behaviors by others. This behavior is aided by the design of the smartphone for one-handed holding and swiping, as some students acknowledged. Another favorite way for the students to engage is to place the smartphone on the table and browse content on the smartphone while dining. Ease of single-handed actions such as flicking, tapping and dragging is something that many students fondly describe and have become very adept in doing.

Regarding the question whether they turn their smartphones off while going to sleep at night, only two out of the 70 informants answered positively, while the rest confirmed that they always keep their phone on at night. Of the two who turned their smartphones off, one student indicated doing this as a habit formed years ago, and the other student who turns off the phone at night said she does this due to health concerns:

“I used to turn the phone to airplane mode, but I was told that would not totally eliminate radiation [from the phone]. In order to avoid radiation, I now completely switch the phone off.”

As to why they keep their smartphones on at night, the most-cited reason (by 83% of the students) is to use its alarm and time-keeping function. Ninety percent of the interviewees said they placed the phone within grab distance, while about a quarter of the students mentioned checking the time on the smartphone at night. Psychologically, about a quarter made a point that opening eyes to see the smartphone makes them feel safe.

In response to the question whether they would check on the phone while waking up in the middle of the night, 32 (constituting 45.7% of the total) students admitted doing this. The type of content consumed late into the night varies quite a bit from looking at the current time, checking on friends’ WeChat “Moments” posts and Weibo updates to viewing short videos. When asked whether the late-night smartphone feeds had any negative impact on their sleep quality, 44% said no but 56% answered in affirmation. Similarly, the aftereffect of this midnight smartphone perusing is diametrically perceived by the two groups: the former group claimed that doing this helps sooth them back to sleep whereas the latter group alleged smartphone checking during bed hours often produces some type of arousal effect on them, thus prolonging the time they need to go back to sleep. Some students in the latter group, albeit not specifically acceding to being addicted to the smartphone, alluded to the potential nature as shown in these quotes:

“Checking my smartphone at night affects my sleep. Oftentimes, once flipping the screen on, it keeps me in a state of arousal, and delays my time to go back to sleep.”

“If I get onto sites such as Zhihu [a popular question-and-answer site like Quora] and Weibo, my sleep will suffer, because these sites are highly addictive. Related content through links on these pages is very seductive to thoughtless, mechanical strolling.”

College students’ social life mainly consists of moments such as hanging up with peers during class breaks, meal times, or weekend hours. Smartphone has been invariably cited as the most-sought-for companion for various purposes – kill time, fool around, idle away, or finish fragments of academic assignments. The campus lifestyle dictates a lot of in-transit moments when students move around between the dorm, classroom, cafeteria, and other places in attending to daily tasks and events. Listening to music is a popular activity for these students, as well as some occasional “virtual strolling” into quick informational checking via various apps of personal preferences. Fifty-six percent of the students acknowledged that they are in the habit of checking their smartphones on a regular basis while walking. As corroborating evidence for its popularity, in response to our interview question on what the students saw as the most common behavioral habits among their peers, topping the list was smartphone checking while walking, followed by looking at the smartphone during meal time and holding the smartphone in the hands at all times.

The habit-inducing nature of the variety of features in the design of the smartphone and its apps is duly noted by the students. Many students explicitly pointed out that they are sensitive to all sorts of prompts and hints (e.g., tones, vibrations, flashing signals) from the phone, and have developed a compulsion to check it out, even if this is during class or late at night. Some students conceded to the irresistibility to upgrade at seeing the little red dot reminder that all brands of smartphone products have adopted indicating availability of newer versions of apps or latest system upgrades. Moreover, AI-operated apps to customize content to individual users are particularly powerful in getting users “hooked.” One student expressed both her fascination and trepidation about Zhihu, a Quora type of peer-to-peer Question-and-Answer app this way:

“At the start, I feel at total control. But the more I click on the app, the more I am trapped into it. In the blink of an eye, 20 min or more has flown by without me knowing it. I may feel it is a total waste of my time doing this. But next time I repeat doing the same thing [on the app].”

NOMOPHOBIA, FOMO, and Phubbing (RQ3)

An emerging line of research in recent years has ascertained the association of nomophobia with a number of negative outcomes pertinent to fear, stress, panic, and anxiety due to inability to access the smartphone (aka nomophobia) ( Nie et al., 2020 ; Rodríguez-García et al., 2020 ). College students suffering from symptoms of nomophobia tend to struggle with concentrating in class ( Lee et al., 2017 ) and perform poorly in academic achievement ( Gutiérrez-Puertas et al., 2019 ). In order to contribute to this body of research, we asked questions of interviewees as regards the degree of pervasiveness of nomophobia and its varied symptomatic manifestations through a set of questions about their attitudes and personal experiences of dealing with situations absent of the smartphone. One question pertains to whether they think of their smartphones during class hours. Forty-three (or 61.4%) of the 70 students interviewed said they often or occasionally get distracted by thinking of their phones, with about 43% acknowledging occasionally engaging in quick phone checking during class. The reasons mentioned for the distraction are mostly one of the three (ranked in this order): the class gets uninspiring; there is an anticipation of time-sensitive information; and there is no specific reason other than the phone just pops up in the mind. Another question asked them if it is their habit to regularly check their smartphones while engaging in tasks such as academic homework, reading and exercising. While about half of the students said they can stay focused on these activities, 37.1% admitted to frequent phone checking while doing these things. It should be noted that the lattermost category involves not merely a quick thumbing through or transitory swipe of the smartphone; this rather entails extensive, concomitant use in parallel with other activities.

In response to the question how they feel when the phone is out of sight, approximately 18.6% ( n = 13) said they would stay calm and cool-headed, vis-à-vis the rest of the 81.4% expressing varying levels of anxiety ranging from feeling insecure to panicking and agitation. As summarized in Table 2 , the most common answers are feeling unsafe, disconnected, uneasy, anxious, a sense of loss, and agitated, whose level of severity steadily increases in accordance with the scale of smartphone dependency in the four user groups. Reversely, the percentage of calm-minded students while the phone is out of sight shows a counter trend – 50% for the below-average group, 22.2% for the average-use group, 14.3% for the heavy-use group, and 0% for the excessive-use group. The pattern along level of smartphone use versus frequency of phubbing and phone checking in the middle of the night (see Table 2 for details).

Relatedly, we asked the students whether they had left their smartphones behind when going out for the day in the recent past, and if yes, what they had done. Twenty-seven students answered firmly that they had not left their phone back, and what is striking are the reasons they cited for why this had not happened – the consistent line therein is that the smartphone constitutes such an all-pervasive aspect of their everyday life that it is virtually impossible to go out without the phone. This sentiment is typified in these two remarks:

“I won’t forget my smartphone any day, because whenever I walk out of my dorm, the first thing I look at is my phone. I wouldn’t walk further beyond a few steps on the stairs before I found out that the phone was not with me.”

“The smartphone is more than just a device of communication; it is a part of my body organs. The moment it’s not with me, I will immediately notice. So I won’t go out without my smartphone.”

Of the 43 students who had experience of leaving their smartphones behind, the words that the students used to describe their feelings at that moment are (ranked in frequency): panicking, uneasy, distressful, restless, unsafe, scared, at a loss, detached from the world, bored, strange, and in despair. Interestingly, the key words mentioned by our interviewees bear substantial semblance to those used by undergraduate students in Furst and Evans’s (2021) campus intercept interviews on students’ reactions to temporary loss of possession of the smartphone. On the other end, only two students said they were “feelingless” (emotionless or unmoved). This response is quite typical:

“I remember one time I did not have my smartphone with me. Without it, I didn’t have any sense of safety, and felt very isolated, to the point of despair. The whole world felt strange to me, and I didn’t know what to do.”

As to what they would do next, 26 (60.5%) said adamantly that they must find a way to immediately go back and retrieve the phone, because otherwise they would not know how to make it through the day. Eleven said that they would wait a bit until they finished what was at hand and then find an opportune time to go back and fetch the phone. A common sentiment among these students during the time without the smartphone was that the time passed by unbearably slow, and they felt “strange” and “out of place” while seeing others were on their smartphones. Only six indicated that they could sustain the day without the smartphone, albeit not without any difficulty for everyone. Being away from the smartphone brought about some unanticipated jubilation for a few:

“I initially panicked a bit [being away from the phone]. But after a while, I actually started to feel relieved at the thought of spending the way without the smartphone. It gave me a sense of comfort that this would be a day without the [virtual] crowd, free from messages and updates, a day when I could relax.”

“It felt weird at the beginning. But I got over that quickly, and gained a sense of elation [at not using the smartphone for the day]. I was able to focus my attention on other things and made a good day of it.”

The haptic benefits, portability and personal nature of the smartphone may cultivate relationships beyond its practical and functional use, as users may “experience enhanced psychological comfort from engaging with their device, which allows it to serve as a palliative aid for owners during moments of stress” ( Melumad and Pham, 2020 , p. 251). Over 60% of the interviewees expressed a psychological sentiment of comfort and reassurance while physically holding the smartphone in their hands. The absence of the smartphone from their sight, or an extended period of time (which typically lasts a few minutes for most students) of not checking the phone creates a particular type of anxiety or distress triggered by FOMO among 68.6% of the students. Specific behavioral responses to mitigate FOMO cited by the students vary from constantly keeping an eye on the phone for cues (e.g., audio alert, vibrating notifications, customized prompts) to frequent phone checking to getting up at night hours for an quick updated skimming.

When asked if they would check the smartphone instead of paying attention to their companions during social conversations (phubbing), forty (constituting about 57%) out of the 70 students admitted doing this often or sometimes. The most-cited reasons for opting to do this are (ranked from high to low): to bypass boring conversations; to evade awkward moments with people they do not know well; not to miss important smartphone messages from friends; and others are looking at the smartphone. Close to 30% of the students mentioned phubbing as a social strategy during moments when they do not have anything to say or when they want to avoid speaking, especially in the company of others they do not perceive as intimate friends. Ten percent of the students alleged that they can manage to multitask between conversing with friends and checking the smartphone without affecting either in any negative manner. As a matter of fact, the prevalence of phubbing-related behavior in China in recent years has even led to the coinage of a new word in the Chinese language – ditouzu , or the “Heads-down Generation,” to (derisively) refer to the tendency of people in late teens and early 20s to lower their heads in fixedly staring at the smartphone in social situations or while walking in public spaces.

Phubbing points to the increasing susceptibility of individuals to spend more and more time with their smartphones while less and less time engaging with each other, and may cause feelings of social exclusion, degrade interpersonal relationships, and impair personal well-being ( David and Roberts, 2017 ). Responses to our question about the impact of the smartphone on interpersonal relationships are varied and can be thematically classified into four categories. About 45.7% ( n = 32) of the informants answered in the affirmative (i.e., strengthening), because the smartphone has increased both the level of contact and the amount of content they exchange with their loved ones and friends. Many students stressed the affordance of the smartphone to enable constant engagement with their family even though they are separated from one another (living away from their families). On the opposing end, 30% of the interviewees felt that smartphone use has distanced them from their intimate circles, largely thanks to the reduction of face-to-face communications. An often-mentioned scenario is the decrease of conversations among family members while being together, and a few students admitted that the overreliance on the smartphone has impaired their competence to relate to their loved ones. About 12.9% ( n = 9) of them said the smartphone has had no impact on their relationships with family and friends, while 11.4% reported mixed reactions (i.e., weaking some relationships but strengthening others).

Detox and Self-Regulation (RQ4)

With regard to our inquiries on whether the students made any efforts in cutting or controlling the amount of time they spend on the smartphone, thirty-six indicated they were not concerned about their smartphone time, nor had they tried to curtail its use. Eight said they made sporadic attempts to reduce smartphone use, although they were not concerned about the amount of time they spend on the smartphone. Twenty-six (37.1% of the total) students expressed concerns over the amount of time they spend on the smartphone, and adopted measures in monitoring and reducing their screen time.

Among the 34 students who took effort to monitor and limit smartphone use, the most common way of doing this, as reported by 30 students, is to resort to popular apps such as FocusToDo, Plantie, Screen Time, Tomato Timer, Forest, TODO for managing time and forcing users out after extended use. Rate of digital detox app adoption varies substantially across the four groups of users we identified in Table 2 : excessive and below-average users are diametrically disposed to adopt detox apps (66.7% vs. 25%), with average and above-average users in between (50% vs. 42.9%). Excessive users, who face the highest risk of problematic use, have the highest rate of adoption, which reflect the perceived need of this group in resorting to detox app in cutting down use. Additionally, we were interested in the effect of such apps on those who were intent on curtailing smartphone use, and therefore only asked follow-up questions of the 26 interviewees who explicitly professed such goals. Nineteen of the 26 agreed that their measures were effective while seven answered otherwise.

Using app is not the only means to exert self-regulation over smartphone use. What seems at play in the process is individual goal setting and mental focus, a repeated theme we observed across the interviewees. Many students pointed out that the smartphone only becomes the centerpiece of free play and the locus to idle away time when they are unoccupied or unengaged with anything else, or at moments they feel bored. They have therefore devised various strategies to steer themselves away from the smartphone by engaging in these activities as mentioned in the interviews: doing physical exercises, going on outdoor excursions, reading, chatting in person with friends, turning off the phone, or placing the phone away for the time being. In the case that non-smartphone activities are not an option, five students indicated that sleeping it out works to keep them unhooked from the phone.

Finally, although not a specific focus of our research, the role of the smartphone in the college learning environment has come up repeatedly in our interview conversations with the students. In China, like most elsewhere, more and more college campuses embrace the flipped classroom pedagogical approach, which is a learning model that subverts the traditional teacher-centered class instruction into student-focused pre-class knowledge transfer via technology-mediated platforms including smartphone capabilities ( Wei et al., 2020 ). As a result, the smartphone has become an important and pivotal tool in fostering learning through entertaining, mobile gaming, and other creative modalities ( Krouska et al., 2020 ; Troussas et al., 2020 ). More than one-third of the students mentioned the various role of the smartphone in accomplishing academic and course-related tasks such as researching information, communicating about curricular activities, and reading class notes and course materials. To some extent, the smartphone has assumed some functions that used to be fulfilled by personal computers in the college learning environment, as acknowledged in our interviews. In this regard, the amount of smartphone time will be skewed significantly for those who are more dependent on the smartphone for learning purposes, and type of activities, rather than smartphone time, should be a more reliable indicator of problematic use.

Our research set out to interrogate the multifaceted dimensions of PSU among college students in China. Informed by extensive data we gathered from semi-structured in-depth interviews of 70 undergraduate students from seven college campuses, our findings contribute to the expanding body of academic literature related to this area of research in several ways. First of all, the smartphone has established a pervasive presence and has become a defining feature of the everyday lifestyle among college students. The amount of time the smartphone consumes the students is staggering, averaging close to 6 h during weekdays and nearly 8 h during weekend days. Our typology of time-based smartphone use yields four distinct types of users: hypo-connected antagonists, balanced majority, hyper-connected enthusiasts, and indulgent zealots.

In studying employees’ experience with converged multi-functional mobile devices, Matusik and Mickel (2011) identified three types of users based on how they interpret and practice technology use: enthusiastic reaction puts a totally positive spin on the professional experience and perceives no cost; balanced reaction appreciates the benefits but also sees its downsides; and trade-offs reaction recognizes professional benefits but acknowledges significant personal costs with a common feeling of personal conflict and struggle in maintaining control. The smartphone use in our study differs from the previous context in that ours involves student users in a non-employment environment but the previous research includes mobile devices beyond the phone. Nonetheless, we found parallel as well as distinction between our groups and those by Matusik and Mickel. Our hyper-connected enthusiasts bear semblance to the technological enthusiasts as identified by Matusik and Mickel in that there is a noticeable craving for the smartphone among most of these students while discussing their smartphone use. The balanced majority revealed in our study share quite a bit with Matusik and Mickel’s balanced reaction group. Their trade-offs group is divided into two groups on the opposite end in our research, with the hypo-connected antagonists casting a cautious eye on the downside of the smartphone while the indulgent zealots totally embracing the technology in the other direction.

With respect to the utility aspects of the smartphones, it is easy to note that WeChat has taken supremacy as the all-in-one platform for social networking among Chinese users. Since the advent of short message services (SMS), text messaging and voice call have been two of the most prodigiously used features in mobile services ( Ling, 2004 ; Karnowski and Jandura, 2014 ). Our research findings, however, suggest signs of seismic transformations in the smartphone era. Conventional voice calls, albeit still used on a regular basis by all the students, have become secondary in terms of the amount of time expended by most of them in comparison with other affordances available on the smartphones – so much so that voice calling does not even make it to the top ten of the features in consuming everyday time of the students. Text messaging has been sidelined even further, with just a few interviewees mentioning engaging in that occasionally. This is not to suggest, nonetheless, that these students have stayed away from voice communications or text messaging. Rather, the indications are that students have uniformly expressed preferences in embracing the built-in text, voice and video chat features with WeChat. There is a clear displacement effect in which conventional text messaging and voice call functions are migrating to alternative smartphone-enabled venues.

In its over 100 years of research, habitual use of technology has been consistently found to be moderated by mechanisms that automatically trigger repetitive behaviors in response to recurring context cues with varying (intermittent) rewarding outcomes ( Bayer and Larose, 2018 ). It is important to note that habit automaticity is a necessary but not determining condition causing compulsive or addictive behaviors, as many other factors play an essential role in shaping the path to pathology ( Wood and Rünger, 2016 ). Smartphone technologies give primacy to haptics (i.e., making touch an analog of seeing and hearing) ( Parisi and Archer, 2017 ), a feature that is particularly malleable to the design and implantation of habit-forming interfaces and apps ( Stawarz et al., 2015 ). Our research findings have imparted numerous temporal, locale-based and context-derived behavioral tendencies of smartphone use among the students.

Contextual cues and situational factors play a pivotal role in the formation of behavioral habits. Through an online survey, Karnowski and Jandura (2014) deduced three main mobile usage patterns – “Mobile@home” (among known peers in familiar locations); “En route” (on the way among unknown people in unfamiliar surroundings); and “Hanging out with peers” (with peers in unknown locations. Habitual practices are associated the most frequently with the residence (the equivalent of their “home”) by the informants in their interviews. Since all the students we interviewed are on-campus residents, the dorm is tantamount to the home of the employees investigated by Karnowski and Jandura, and their smartphone engagement bears some resemblance in that usage situations are the most dominant across interviewees. The “En route” moments for the students mostly comprise their in-transit time walking between the dorm, the cafeteria, classrooms and other venues on campus, while their “Hanging with peers” hours manifest profusely in the “empty” chunks of varying lengths such as intervals between classes and/or other obligated school activities, meal breaks and off-class hours. Our findings show that students’ smartphone usage has displayed predictable patterns in connection to these various occasions in terms of both app checking and content browsing. One word of caution, however, we should highlight is that same habitual predisposition should not be construed as unidirectional in its consequence. A case in point is smartphone checking during late night hours, which may work toward pacifying some students but arousing others, thus producing very different impact on their sleep quality. While a common finding in quantitative research suggests an association between PSU and poor sleep quality among adolescent and youth populations ( Hale et al., 2019 ; Mac Cárthaigh et al., 2020 ; Yang et al., 2020 ), results in our interview suggest the need for taking into consideration contextual clues and situational factors in order to develop a more nuanced understanding in disentangling causational attributions.

It is probably no surprise that our research has lent evidence to the undisputable presence of widespread nomophobia and FOMO among college youth. This finds testimonial in various manifestations, from thinking about the phone during class, to keeping the phone in sight and within reach, to holding in hand and never having left it behind in the memorable past, the smartphone has assumed a role beyond that of a technical gadget in sustaining students’ emotional and functional stability. Results in our interviews indicate the level of smartphone dependency is positively related to the severity of disturbance while adversely related to the degree of self-imposture in a number of symptomatic manifestations under investigation.

Problematic smartphone use has emerged as an important public health issue in recent years, and both technical and non-technical interventions have been proposed as possible solutions to limit and control smartphone use ( van Velthoven et al., 2018 ). The percentage of screen-time controlling app use in our cohort (42.9%) aligns up very nicely with Schmuck’s (2020) study, which found that 41.7% of the surveyed 500 Australian adults adopted detox apps to limit and control smartphone time. In addition, Schmuck alleges her research evidence shows “for the first time that self-monitoring behavior using digital detox apps may prevent young adults to develop problematic or compulsive smartphone usage patterns due to using SNSs” based on multigroup analysis that “those young adults who used digital detox apps indicated lower levels of perceived PSU and higher levels of well-being in response to the use of SNSs” ( Schmuck, 2020 , p. 26). Findings in our study, however, paint a different and more nuanced picture. That excessive or problematic smartphone users are the most likely to resort to detox apps in exerting self-control cannot be construed as evidence to either refute or confirm the efficacy of these apps or such a mechanism; it is plausible that excessive smartphone dependency tends to lead to self-monitoring through detox apps. Whether it is accomplished through technology-based detox apps or through non-technological approaches, we found strong evidence that mental focus and individual goal setting play a central role in the success or the lack thereof in outcomes of moderating smartphone use. This accords cogently with the core premise that the exercise of free will is “a causal primary ” to effect self-regulation ( Binswanger, 1991 ), and it highlights the critical role of self-monitoring and self-reaction as conceived in the theory of self-control ( Bandura, 1991 ).

Lastly, the results of our research are best understood in the context of its limitations. Due to the qualitative nature of our research design, the number of students we studied, although more than sufficient for in-depth interviews, is a small sample size compared with large-scale quantitative studies. Correspondingly, the perspectives and insight we generated from the data may not be generalizable to the large population of college students in China. The findings we presented in the paper call for corroboration and triangulation from large-scale datasets derived from cross-sectional or even longitudinal surveys. Moreover, differences in national settings are likely contributors to variations in usage patterns; it is therefore useful to make cross-national comparisons in deepening our understanding of PSU among global youth.

Problematic smartphone use is a pervasive phenomenon, and calls for attention from scholars with diverse backgrounds and contribution from multidisciplinary perspectives. Prevalence rate is particularly prominent among college-age population, as the smartphone has established itself as a hallmark of youth lifestyle. From its built-in technical features to the assortment of apps and the rich set of available content, the smartphone is conducive to repetitive, habit-forming patterns of usage. Students’ engagement with the smartphone often displays predictable behavioral proclivities in response to specific temporal, locale-based and contextually driven cues and triggers. While informational use is universally found among all users, problematic use is typically associated with gaming, streaming, entertainment, and social networking gratifications. As smartphone further establishes itself as a viable tool in mediating college learning, time alone should not be used as a sole predictor of problematic use. Both activity type and level of engagement warrant consideration in evaluating PSU. Extensive interaction with the smartphone has led to a special type of attachment to the device that pertains to not just its utilitarian functionalities but also its affective bond, manifested in various symptoms of uneasiness, discomfort and anguish at moments of not being with or seeing the smartphone. While we found evidence of the efficacy of detox apps in curtailing use, mental focus and proactive goal setting seem to be the most productive in attaining self-regulatory goals. Perspectives from our qualitative data suggest the need for a more nuanced approach in taking into consideration contextual cues and situational factors in dissecting psychological and emotional outcomes of smartphone use and abuse.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The studies involving human participants were reviewed and approved by Institute of Scientific Research at Minjiang University. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

CD, ZT, and SN were involved in the conception and design of the study, coordinated work to transcribe, and analyzed the data. ZT wrote the draft of the manuscript. CD and SN arranged and conducted the online interviews. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords : smartphone use disorder, smartphone dependency, mobile lifestyle, problem smartphone use, digital wellbeing

Citation: Dai C, Tai Z and Ni S (2021) Smartphone Use and Psychological Well-Being Among College Students in China: A Qualitative Assessment. Front. Psychol. 12:708970. doi: 10.3389/fpsyg.2021.708970

Received: 17 May 2021; Accepted: 12 August 2021; Published: 09 September 2021.

Reviewed by:

Copyright © 2021 Dai, Tai and Ni. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Zixue Tai, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Essay on Effects Of Mobile Phones On Students

Students are often asked to write an essay on Effects Of Mobile Phones On Students in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.

Let’s take a look…

100 Words Essay on Effects Of Mobile Phones On Students

Introduction.

Mobile phones, once a luxury, have now become a necessity for everyone, including students. While they offer several benefits, they also pose significant challenges. Let’s explore their effects on students.

Learning Tool

Mobile phones can be great learning tools. They provide access to a vast amount of information on the internet. Students can use educational apps, watch educational videos, and even take online courses. This makes learning more interactive and fun.

Communication

Mobile phones make communication easier. Students can connect with their teachers, classmates, and parents anytime, anywhere. This helps in sharing information, discussing projects, and seeking help when needed.

Distraction

On the flip side, mobile phones can be a major source of distraction. Students might spend excessive time on social media, games, and entertainment apps, leading to reduced study time and lower academic performance.

Health Issues

Excessive use of mobile phones can lead to health issues. Staring at the screen for long hours can cause eye strain. Also, it can lead to poor posture and sleep disorders, impacting a student’s overall health.

In conclusion, mobile phones have both positive and negative impacts on students. They can enhance learning and communication but can also lead to distraction and health issues. It’s important for students to use them wisely.

250 Words Essay on Effects Of Mobile Phones On Students

Mobile phones are a big part of our lives today. Most students use them for different things like playing games, chatting with friends, or studying. They can be helpful but also have some bad effects on students.

Positive Effects

Mobile phones can be really useful for students. They can use them to find information on the internet, use educational apps, and even take notes in class. This makes learning easier and more fun. Also, students can stay in touch with their friends and family, which is good for their social life.

Negative Effects

Even though mobile phones can be helpful, they can also cause problems. Students can get addicted to games or social media, which can make them spend less time on their studies. This can lead to poor grades. Also, spending too much time on the phone can lead to health problems like eye strain or poor sleep.

In conclusion, mobile phones have both good and bad effects on students. They can help with learning and staying connected, but can also lead to addiction and health problems. It’s important for students to use their phones wisely. They should try to balance their time between using their phone and doing other important things like studying and spending time with family.

500 Words Essay on Effects Of Mobile Phones On Students

Mobile phones have become an important part of our lives. They are used by people of all ages, including students. Mobile phones have both positive and negative effects on students. This essay will discuss these effects.

One positive effect of mobile phones on students is that they can be used as learning tools. There are many educational apps and websites that students can access on their phones. These can help them understand difficult subjects, practice skills, and learn new things. For example, language learning apps can help students practice a new language. Also, there are apps for math, science, history, and many other subjects. These resources make learning more interesting and fun for students.

Mobile phones also make it easy for students to communicate with their friends, family, and teachers. They can send messages, make calls, and even have video chats. This can be very helpful, especially when students need help with their homework or projects. They can easily reach out to their classmates or teachers for assistance.

Organization

Mobile phones can also help students stay organized. They can use their phones to set reminders for assignments, tests, and other important dates. They can also use them to take notes and keep track of their tasks. This can help students manage their time better and stay on top of their schoolwork.

On the other hand, mobile phones can also have negative effects on students. One of these is distraction. Many students spend a lot of time on their phones, playing games, chatting with friends, or browsing social media. This can take away time from their studies and can lead to poor academic performance.

Another negative effect of mobile phones is health issues. Spending too much time on a phone can lead to problems like eye strain, poor posture, and even sleep disorders. These can affect a student’s health and well-being.

In conclusion, mobile phones have both positive and negative effects on students. They can be great tools for learning, communication, and organization. But they can also cause distraction and health issues. It’s important for students to use their phones wisely and in a balanced way. This will help them get the most benefits from their phones while avoiding the negative effects.

That’s it! I hope the essay helped you.

If you’re looking for more, here are essays on other interesting topics:

• Essay on Effects Of Media Violence On Children’s Behavior
• Essay on Effects Of Internet Addiction
• Essay on Effects Of Improper Waste Disposal

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current events conversation

What Students Are Saying About How Much They Use Their Phones, and Whether We Should Be Worried

New research challenges assumptions about the negative effects of social media and smartphones on children. We asked teenagers whether their parents should worry about how much time they spend on their devices.

By The Learning Network

Please note: This post is part of The Learning Network’s ongoing Current Events Conversation feature. We invite students to react to the news via our daily writing prompts and, each week, we publish a selection of their comments.

We frequently ask students about their relationship with screens, but a question we posed this week seems to have struck a chord with the teenagers who comment on our writing prompts.

Inspired by the article “ Panicking About Your Kids’ Phones? New Research Says Don’t ,” we asked students: Should the adults in your life be worried by how much you use your phone?

We heard from over 300 teenagers who gave a flurry of nuanced, thoughtful and enlightening responses. In fact, their comments were so good that we decided to feature only this prompt in this week’s Current Events Conversation, instead of the usual three , so we can highlight as many responses as possible.

Some students admitted to spending upward of eight hours a day online, with the majority averaging around two to four hours. Some said their devices were a reasonable escape from the pressures of teenage life, while others explained they were essential for school. And still others raised an insightful question: Why is their “phone addiction” perceived as more harmful than that of the adults in their lives?

As you’ll see below, one thing was crystal clear in their reflections: These teenagers spend a lot of time thinking about their phone usage. And they have a critical lens not only on how much they use their phones, but also on how it affects their education, emotional life and relationships.

Read on for a fuller scope of the comments, but before you do, we want to offer a warm welcome to new classes from Ames High School, Iowa ; Carney ; Florida ; Fort Mill High School ; Georgia ; Hightstown High School, N.J. ; Nelson County High School ; New Berlin, Wis. ; New York ; and Pennsylvania .

Please note: Student comments have been lightly edited for length, but otherwise appear exactly as they were originally submitted.

I know I’m on my phone too much.

I think that I spend a little too much time on my phone per day. And by a little, I mean a lot. I’m not sure my average but I know I could be going to bed a lot earlier and get my work done quicker if I just put it down. I do many things on my phone like text people, snapchat, play games, and so on.

I think it does have a positive benefit on my well being because without it, I would not have friendships and relationships I have today. The negative effects it has on me is time usage and keeping me from doing work and going to bed on time. I am worried about being on my phone too much but I don’t think it interferes with me being social, especially in this day and age.

My average screen time is probably about 12 hours a day. I worry a lot about how much time I spend on my phone. But the way I socialize is through my phone. I use social media to communicate, and I have to use my phone to make calls and text. But whenever I have to study, I pull out my phone and go on it for about an hour …

When it is time to go to sleep, I go on my phone in the dark with dark mode on. My bed has my charger connected to it so I can easily stay up all night. I want to remove it but because I am so addicted to my phone, I do not. One time I fell asleep at 2 am because I was on my phone, and it made me extremely tired (this was on a school night).

— Jessica Chen, J.R. Masterman, Philadelphia, PA

Since I got an iPhone, I have spent more time on my phone because of social media apps. I caught myself on multiple occasions telling myself “only 15 more minutes and then I’ll start my homework,” but then I end up spending 30 minutes on my phone. When I have tried to use my phone less I end up watching tv, so I just go from one type of a screen to the next.

— Allison Ciero, Glenbard West HS Glen Ellyn, IL

I spend too much time on my phone. I sometimes think about how much I am on my phone and I’m disgusted with how much time I feel like I’m wasting. But the truth is, I do a lot more than scroll through social media or watch stupid videos on my phone. My phone is a portable library that carries all of my favorite books on it. And those stupid videos and posts sometimes completely change my day for the better.

— Mason Evans, Hoggard High School Wilmington, NC

On average, I spend about 6 hours a day on my phone. It is spent with me going on social media, playing games, or watching Netflix. Every weekend, a notification pops up showing me how much time I have spent and each week it has gone up. I am starting to become a lot more cautious about how much time I spend on my phone because it is starting to worry me. My phone has become something that I always have to have and it never leaves my side. It has gotten in the way of me studying and spending time with my family which has started to worry me. I believe that parents should know how much time their kid is using their phone but I don’t think that they should act upon it.

— Mark, Hightstown

Teenagers should monitor their own phone use.

I understand a little micromanaging when it comes to technology time. However, by the time we reach high school, we should all be responsible for ourselves in that realm, to turn in homework, to know our time limits. It is time for the parents to release their grasp unless it is absolutely necessary.

It is our job as teenagers to learn what happens when we stay on our phones too long and we don’t get enough sleep or don’t finish a homework assignment, we won’t understand the consequences if we don’t learn for ourselves.

— Josh Reifel, Glenbard West, Glen Ellyn, IL

While I stand by this statement, I would also like to point out that our parents didn’t grow up with this stuff, and they may not know how to handle our usage in the best way. Often times I find my parents using the phone — that they bought for us — as punishment. They threaten to take it away or to throw it out, this only makes out subconscious want it more. Moreover, they make us feel guilty for being born in a world where we do have access to these devices — as if we could help it. They say “when I was a kid we didn’t have to talk to our friends all the time, we would wait to see them the next day at school.” They try us guilt you into not using which once again, will only make us want it more to spite them.

— kenna royce, Glenbard West HS Glen Ellyn, Il

While some parents see it beneficial to limit teens usage on phones, others don’t take any action. For example, my parents have always trusted me to be responsible in my time management, and balancing school, Church, and friends. However, I do understand that my parents pay for my phone, and data usage, and I would willingly comply if they had any restrictions or rules. Phones, however, often rely as a crutch for parents, meaning they often incorrectly blame their child’s issue, or challenges for how much time they spend on their phone.

— Anna Atwood, Bryant High School Arkansas

In observing my friends and classmates, I think that most of us have a handle on what an appropriate amount of screen time is. Social media can be a breeding ground for bullying, which can then lead to depression and anxiety, but I’m not entirely sure that would correlate with simply spending more time on devices. Hopefully, if parents instill the value of limitations while kids are young, they will be able to control themselves appropriately in the future.

— Sarah Song, Ames High School

I feel like I’m extremely in touch with my personal media usage, but it isn’t easy. Apps are designed to keep you on them as long as possible, and sometimes it’s horribly hard to put down a phone after seeing a Snapchat from your friend pop up. After checking just now, I spent an average of 1 hour 58 minutes on my phone last month. Just shy of 2 hours, which is the recommendation maximum time adolescents should spend on non-education related screens. Many of my peers use them 6+ hours daily.

I notice an exact correlation between the amount of time I’m on my phone and how productive I am that given day. If I get out of bed and don’t immediately pick up my phone, I feel like I can get ready faster, and feel more energized and motivated.

Sometimes, if I have a lot of homework one night, I plug my phone in in a separate room, so I won’t think about it. It’s just so easy to forget about the essay you need to write if you unlock your phone and start messing around. They’re excellent distractions.

I couldn’t agree more with the statement that “phones increase anxiety, depression and sleep deprivation among teenagers.” I’ve seen it happen in myself and my peers. In the 3 years I’ve had a phone, there have been too many nights I regret sacrificing sleep for texting to a friend online or getting lost on YouTube. It’s becoming more important to be aware of how our phones affect our lives as they take over more and more aspects of our days.

— Mollie Brinker, Hoggard High School in Wilmington, NC

Who is supervising how much adults use their phones?

I think that in some ways it could be good for adults to monitor how much children are on their phones today. However, who is going to monitor the adults? What I have noticed while growing up in this world of technology, is that so many adults around me are on their phone just as often as the children. I think it can be difficult to stay away from our phones when everyone around you is on their phones. I think we have to accept technology’s role and try to be as responsible with it as we can.

— Kaylee Phillips, Glenbard West HS, Glen Ellyn, IL

Some evenings at my house consists of our family in the same room, each of us on our same devices. Adults should worry about cell phone usage, in both their life and their children’s lives.

A part of the issue is that parents can use their devices just as much as the kids. Adults must realize that they too must change. If they take their kid’s phone away, they should put theirs away too. They should push their child to have real-life experiences, where words can’t be misinterpreted.

— Evan Lippolis, Ames High School

Screens are affecting our mental and physical health.

I feel like phones have a negative effect on the mental stability of most teenagers today. There are so many things we worry about now … “How many snaps have I got this hour?”, “Has he seen my story yet?”, “I wonder if he’s just ignoring me?”

Our phones present us with an ultimatum, Go out and be social, or stay in and get on facetime. It’s not the same, there are certain endorphins your mind releases when you are physically in contact with another person. Human interaction is healthy.

My phone brings me mixed emotions, and I kind of rely on my phone for almost everything. Before I had a phone my life was so easy and I was a social butterfly, now I’m a 17 year old girl who comes home from work and watches a movie on my phone until my eyes physically will not open.

— Brooklyn Harcrow, Lubbock, TX

I usually spend about 3 hours a week on my phone. I grew up in Haiti, so most of the time I am in contact with my friends back home. When we lived in Haiti, FaceTime was a way that I could not only talk to my sister, who was at Iowa State, but we could also see her.

My phone has had negative impacts on my health. I have had chronic migraines that have been affected by my posture, which is aggravated by being hunched over my phone all day. I also find myself in more pain after even a short time on my phone. Social media has also left me feeling left out and more discouraged about my own life. As someone who is in a new atmosphere and environment, when I see on social media my friends’ activities I feel more isolated and alone.

— Kerlande Mompremier, Ames High School

I most definitely see the connection between higher levels of stress and being on your phone for a more than needed amount of time. Scrolling through social media and looking at small square sized snapshots of a person’s “picture perfect life” can really have an effect on both self-esteem and mental health. The world and especially the younger generations must learn to spark creativity and imagination. Those things can only be formed through one’s mind, experiences, and thoughts, not any phone or device on the planet can provide them.

— Sadie Dunne, Hoggard High school in Wilmington, NC

For me personally, I tend to find myself veering away from my phone during stressful times because I feel like all it does is add to it. I have anxiety and have seen that the negative effects from social media only add to that anxiousness. I agree that phone usage and constant usage of social media can definitely increase anxiety and depression, if you allow yourself to get involved so much you can’t return to a normal lifestyle without it. I think that as I feel like I’m starting to feel more anxious and stressed, my phone does not help the situation but makes it worse, so I try to stay away from it during these times.

— Taylor Tomlinson, Lubbock, TX

Social media has made me feel more connected to others, not less.

Speaking personally, I can recall many times in which social media has helped me feel less lonely than I otherwise would have been. I have severe anxiety, so the idea of socializing with people in a less formal setting, such as in a lunchroom, or outside of class is terrifying to me. So, as a result, I am often alone during these periods. I’ll go off and find my own corner, and I sit and have to watch as those around me have fun with their friends and socialize.

I have gone through this process near-daily for ten years, and I am confident that without social media to fall back on, I would have been driven mad. Social media makes me feel as though there are people out there I can talk to, and that I can control the conversation however I like. I can have friends that I respond to at my own pace, leaving me room to better formulate my responses.

— Jackson Bumgarner, Bryant High School, AR

My mom is a really busy woman and she’s not always there for me and my phone has been my shelter since 5th grade. When I came home feeling sad in school, a couple of youtube videos can cheer me up. Smartphones also make contacting friends and families easier making me less lonely during my sad times. The use of phone also opens a new window of opportunities, I learnt how to edit and shoot videos from youtube. There was a time when my mental health was just not great and the internet saved me.

— shirley, fhs

My first friend was an online friend. I was in fifth grade and I was obsessed with Hamilton, and would spend hours reading about and listening to the songs. My family was on vacation in WildWood, and we were living in a small hotel. I was swimming in the pool and a kid came up to me, and I found out we both liked Hamilton a lot, so we started talking. At the end of the vacation the kid told me her email and we started texting on hangouts. We still text to this day. My phone played a big part in letting me stay in touch, and it built my relationship with her.

— Arianna Andriyevsky, Julia R. Masterman

More screen time can be beneficial.

As the life of a teenager continues to increase in its complexity and demands, the resources and tools a smartphone can provide help keep teenagers grounded. So, before adults chastise us for our use of phones (while they’re leveling up in Candy Crush) it’s important to show that phones are very powerful tools, sometimes too powerful.

With how many activities a teenager can be involved in these days, smartphones help make more productive use of their time, keeping up with meetings, get-togethers, and updates. Whether it be communicating with other club members, or simply catching up with friends, these communication tools help bring people closer without necessitating time-consuming travel.

— Sayre S., Ames High School

I am on my phone about three hours a day. The majority of this is spent on social media apps like snapchat or twitter and listening to music. My phone has a positive influence on me. I feel more connected to the world and what is going on and while that is not always a good thing it is nice to be informed and updated on events within seconds.

— Mehdi Sebghati, Ames High School

My average screen time is about 40 minutes per week. I typically look at news, talk with my relatives in China through WeChat, or go on Youtube to watch cooking videos … My phone does help me build my Chinese skills when texting in WeChat. On WeChat, I can also build relationships with my relatives and friends that I cannot meet face-to-face.

However, my parents are still very worried about my time on my phone. That’s because I have glasses, and my eyesight has been worsening every year. They express their concern by speaking my name in a warning tone when they think I’ve been on my phone long enough. I listen to them, because I know that they are trying to do the best for them.

— Daniella Liang, J.R. Masterman

Teenagers shouldn’t be on their phones as much.

I think adults should be worried about how much their child is on their phone. If my child was constantly on their phone I would be mad because it is disrespectful when you are with someone and they won’t get off their phone. I get offended and annoyed when my friends are on their phones instead of talking to me and I wouldn’t want to be that rude to someone so if my parents told me I shouldn’t be on my phone I think that’s a good thing. Parents are supposed to teach their children how to talk, walk, and ride a bike, they should teach them proper manners and to not go be on your phone for too long.

— Anna Diab, Glenbard West HS, Glen Ellyn, IL

The answer to this question is different for me than many of my peers because unlike many “savvy” teens I have a flip phone. When I was fifteen I decided to stick with a flip phone, it solved my basic needs. I’m currently seventeen and have friends. It came down to me seeing kids and people on their phones at dangerous and inappropriate times. They were on their while driving, in school, and at the supper table. When I see somebody on their phone it reminds me that there is more to life. I am on my phone for less than ten minutes a day, still, I have survived. I can call and text people without the hassle of getting social media notifications. I’m not saying smartphones are bad they can be very useful. I just prefer reality.

— Ethan Morton, Ames, Iowa

I hate that I’m one of those teenagers who have a mini heart attack when they don’t feel their phone in their pocket. I know I’m not on my phone nearly as much as some of my peers, but even the time I do spend there I resent. Despite what the article says about technology not having any real negative influence on mental health, I can’t help but feel like it causes other problems.

We text and DM people when we have something to say, leaving behind outdated voice-calling and — gasp — that archaic practice of talking in person. So much of communication is nonverbal. Many today struggle to maintain eye contact, pay full undivided attention to others, and meaningfully interact in person. Screens are our modern-day masks and boy, do we love hiding behind them. While maybe it is true that technology doesn’t directly connect to the rise in mental disease and anxiety, it leads to a host of other problems, most prominent among these being social decay.

— Grace Robertson, Hoggard High School Wilmington, NC

Phones are not the problem.

Basically I have always had really bad anxiety way before I got a phone. Once I got to middle school and I started to mature it got worse because I was finally able to see all the bad in the world that my parents had protected me from. Which I believe is one of the leading factors of my depression. But once I got a phone I was so happy because I was always able to communicate with my friends no matter where I was. Then when I was given social media I really felt connected because I was able to get updates on what everyone was doing and what was going on in the world, but then when my parents found out about my depression they complete ignored the fact that they had sheltered me my entire life and blamed it all on my phone so now I do not have social media and I still feel the same way but I feel less connected and more isolated.

I guess what I’m trying to say is that I don’t think that phones have ruined a generation I think it’s the parents, they don’t realize that sheltering us is hurting us …

— Caleb, America

I feel like the anxiety, stress, and depression are not the result of my phone but from the expectations from parents and teachers, how unsafe I feel in my school, from the medication making me “normal and calm,” and from the news where nothing good is heard. I don’t think my phone stops me from socializing or from sleeping, and I am constantly trying to put down my phone. My parents will warn me once or twice but they are on it as much as me.

But I believe that adults try to use phones as a scapegoat instead of admitting that there are bigger issues, such as global warming, political divisions etc. that teens face or the problems that they themselves cause with high expectations.

— Lilian, Hoggard High School in Wilmington, NC

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Bans may help protect classroom focus, but districts need to stay mindful of students’ sense of connection, experts say

Students around the world are being separated from their phones.

In 2020, the National Center for Education Statistics reported that 77 percent of U.S. schools had moved to prohibit cellphones for nonacademic purposes. In September 2018, French lawmakers outlawed cellphone use for schoolchildren under the age of 15. In China, phones were banned country-wide for schoolchildren last year.

Supporters of these initiatives have cited links between smartphone use and bullying and social isolation and the need to keep students focused on schoolwork.

77% Of U.S. schools moved to ban cellphones for nonacademic purposes as of 2020, according to the National Center for Education Statistics

But some Harvard experts say instructors and administrators should consider learning how to teach with tech instead of against it, in part because so many students are still coping with academic and social disruptions caused by the pandemic. At home, many young people were free to choose how and when to use their phones during learning hours. Now, they face a school environment seeking to take away their main source of connection.

“Returning back to in-person, I think it was hard to break the habit,” said Victor Pereira, a lecturer on education and co-chair of the Teaching and Teaching Leadership Program at the Graduate School of Education.

Through their students, he and others with experience both in the classroom and in clinical settings have seen interactions with technology blossom into important social connections that defy a one-size-fits-all mindset. “Schools have been coming back, trying to figure out, how do we readjust our expectations?” Pereira added.

It’s a hard question, especially in the face of research suggesting that the mere presence of a smartphone can undercut learning .

Michael Rich , an associate professor of pediatrics at Harvard Medical School and an associate professor of social and behavioral sciences at the Harvard T.H. Chan School of Public Health, says that phones and school don’t mix: Students can’t meaningfully absorb information while also texting, scrolling, or watching YouTube videos.

“The human brain is incapable of thinking more than one thing at a time,” he said. “And so what we think of as multitasking is actually rapid-switch-tasking. And the problem with that is that switch-tasking may cover a lot of ground in terms of different subjects, but it doesn’t go deeply into any of them.”

Pereira’s approach is to step back — and to ask whether a student who can’t resist the phone is a signal that the teacher needs to work harder on making a connection. “Two things I try to share with my new teachers are, one, why is that student on the phone? What’s triggering getting on your cell phone versus jumping into our class discussion, or whatever it may be? And then that leads to the second part, which is essentially classroom management.

“Design better learning activities, design learning activities where you consider how all of your students might want to engage and what their interests are,” he said. He added that allowing phones to be accessible can enrich lessons and provide opportunities to use technology for school-related purposes.

Mesfin Awoke Bekalu, a research scientist in the Lee Kum Sheung Center for Health and Happiness at the Chan School, argues that more flexible classroom policies can create opportunities for teaching tech-literacy and self-regulation.

“There is a huge, growing body of literature showing that social media platforms are particularly helpful for people who need resources or who need support of some kind, beyond their proximate environment,” he said. A study he co-authored by Rachel McCloud and Vish Viswanath for the Lee Kum Sheung Center for Health and Happiness shows that this is especially true for marginalized groups such as students of color and LGBTQ students. But the findings do not support a free-rein policy, Bekalu stressed.

In the end, Rich, who noted the particular challenges faced by his patients with attention-deficit disorders and other neurological conditions, favors a classroom-by-classroom strategy. “It can be managed in a very local way,” he said, adding: “It’s important for parents, teachers, and the kids to remember what they are doing at any point in time and focus on that. It’s really only in mono-tasking that we do very well at things.”

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The impact of smartphone use on learning effectiveness: A case study of primary school students

Jen chun wang.

1 Department of Industry Technology Education, National Kaohsiung Normal University, 62, Shenjhong Rd., Yanchao District, Kaohsiung, 82446 Taiwan

Chia-Yen Hsieh

2 Department of Early Childhood Education, National PingTung University, No.4-18, Minsheng Rd., Pingtung City, Pingtung County 900391 Taiwan

Shih-Hao Kung

Associated data.

The datasets generated during and/or analysed during the current study are available from the corresponding author upon request.

This study investigated the effects of smartphone use on the perceived academic performance of elementary school students. Following the derivation of four hypotheses from the literature, descriptive analysis, t testing, one-way analysis of variance (ANOVA), Pearson correlation analysis, and one-way multivariate ANOVA (MANOVA) were performed to characterize the relationship between smartphone behavior and academic performance with regard to learning effectiveness. All coefficients were positive and significant, supporting all four hypotheses. We also used structural equation modeling (SEM) to determine whether smartphone behavior is a mediator of academic performance. The MANOVA results revealed that the students in the high smartphone use group academically outperformed those in the low smartphone use group. The results indicate that smartphone use constitutes a potential inequality in learning opportunities among elementary school students. Finally, in a discussion of whether smartphone behavior is a mediator of academic performance, it is proved that smartphone behavior is the mediating variable impacting academic performance. Fewer smartphone access opportunities may adversely affect learning effectiveness and academic performance. Elementary school teachers must be aware of this issue, especially during the ongoing COVID-19 pandemic. The findings serve as a reference for policymakers and educators on how smartphone use in learning activities affects academic performance.

Introduction

The advent of the Fourth Industrial Revolution has stimulated interest in educational reforms for the integration of information and communication technology (ICT) into instruction. Smartphones have become immensely popular ICT devices. In 2019, approximately 96.8% of the global population had access to mobile devices with the coverage rate reaching 100% in various developed countries (Sarker et al., 2019 ). Given their versatile functions, smartphones have been rapidly integrated into communication and learning, among other domains, and have become an inseparable part of daily life for many. Smartphones are perceived as convenient, easy-to-use tools that promote interaction and multitasking and facilitate both formal and informal learning (Looi et al., 2016 ; Yi et al., 2016 ). Studies have investigated the impacts of smartphones in education. For example, Anshari et al. ( 2017 ) asserted that the advantages of smartphones in educational contexts include rich content transferability and the facilitation of knowledge sharing and dynamic learning. Modern students expect to experience multiple interactive channels in their studies. These authors also suggested incorporating smartphones into the learning process as a means of addressing inappropriate use of smartphones in class (Anshari et al., 2017 ). For young children, there are differences in demand and attributes and some need for control depending upon the daily smartphone usage of the children (Cho & Lee, 2017 ). To avoid negative impacts, including interference with the learning process, teachers should establish appropriate rules and regulations. In a study by Bluestein and Kim ( 2017 ) on the use of technology in the classroom they examined three themes: acceptance of tablet technology, learning excitement and engagement, and the effects of teacher preparedness and technological proficiency. They suggested that teachers be trained in application selection and appropriate in-class device usage. Cheng et al. ( 2016 ) found that smartphone use facilitated English learning in university students. Some studies have provided empirical evidence of the positive effects of smartphone use, whereas others have questioned the integration of smartphone use into the academic environment. For example, Hawi and Samaha ( 2016 ) investigated whether high academic performance was possible for students at high risk of smartphone addiction. They provided strong evidence of the adverse effects of smartphone addiction on academic performance. Lee et al. ( 2015 ) found a negative correlation between smartphone addiction and learning in university students. There has been a lot of research on the effectiveness of online teaching, but the results are not consistent. Therefore, this study aims to further explore the effects of independent variables on smartphone use behavior and academic performance.

The COVID-19 pandemic has caused many countries to close schools and suspend in-person classes, enforcing the transition to online learning. Carrillo and Flores ( 2020 ) suggested that because of widespread school closures, teachers must learn to manage the online learning environment. Online courses have distinct impacts on students and their families, requiring adequate technological literacy and the formulation of new teaching or learning strategies (Sepulveda-Escobar & Morrison, 2020 ). Since 2020, numerous studies have been conducted on parents’ views regarding the relationship of online learning, using smartphones, computers, and other mobile devices, with learning effectiveness. Widely inconsistent findings have been reported. For instance, in a study by Hadad et al. ( 2020 ), two thirds of parents were opposed to the use of smartphones in school, with more than half expressing active opposition ( n  = 220). By contrast, parents in a study by Garbe et al. ( 2020 ) agreed to the school closure policy and allowed their children to use smartphones to attend online school. Given the differences in the results, further scholarly discourse on smartphone use in online learning is essential.

Questions remain on whether embracing smartphones in learning systems facilitates or undermines learning (i.e., through distraction). Only a few studies have been conducted on the impacts of smartphone use on academic performance in elementary school students (mostly investigating college or high school students). Thus, we investigated the effects of elementary school students’ smartphone use on their academic performance.

Literature review

Mobile technologies have driven a paradigm shift in learning; learning activities can now be performed anytime, anywhere, as long as the opportunity to obtain information is available (Martin & Ertzberger, 2013 ).

Kim et al. ( 2014 ) focused on identifying factors that influence smartphone adoption or use. Grant and Hsu ( 2014 ) centered their investigation on user behavior, examining the role of smartphones as learning devices and social interaction tools. Although the contribution of smartphones to learning is evident, few studies have focused on the connection between smartphones and learning, especially in elementary school students. The relationship between factors related to learning with smartphones among this student population is examined in the following sections.

Behavioral intentions of elementary school students toward smartphone use

Children experience rapid growth and development during elementary school and cultivate various aspects of the human experience, including social skills formed through positive peer interactions. All these experiences exert a substantial impact on the establishment of self-esteem and a positive view of self. Furthermore, students tend to maintain social relationships by interacting with others through various synchronous or asynchronous technologies, including smartphone use (Guo et al., 2011 ). Moreover, students favor communication through instant messaging, in which responses are delivered rapidly. However, for this type of interaction, students must acquire knowledge and develop skills related to smartphones or related technologies which has an impact on social relationships (Kang & Jung, 2014 ; Park & Lee, 2012 ).

Karikoski and Soikkeli ( 2013 ) averred that smartphone use promotes human-to-human interaction both through verbal conversation and through the transmission of textual and graphic information, and cn stimulate the creation and reinforcement of social networks. Park and Lee ( 2012 ) examined the relationship between smartphone use and motivation, social relationships, and mental health. The found smartphone use to be positively correlated with social intimacy. Regarding evidence supporting smartphone use in learning, Firmansyah et al. ( 2020 ) concluded that smartphones significantly benefit student-centered learning, and they can be used in various disciplines and at all stages of education. They also noted the existence of a myriad smartphone applications to fulfill various learning needs. Clayton and Murphy ( 2016 ) suggested that smartphones be used as a mainstay in classroom teaching, and that rather than allowing them to distract from learning, educators should help their students to understand how smartphones can aid learning and facilitate civic participation. In other words, when used properly, smartphones have some features that can lead to better educational performance. For example, their mobility can allow students access to the same (internet-based) services as computers, anytime, anywhere (Lepp et al., 2014 ). Easy accessibility to these functionalities offers students the chance to continuously search for study-related information. Thus, smartphones can provide a multi-media platform to facilitate learning which cannot be replaced by simply reading a textbook (Zhang et al., 2014 ). Furthermore, social networking sites and communication applications may also contribute to the sharing of relevant information. Faster communication between students and between students and faculty may also contribute to more efficient studying and collaboration (Chen et al., 2015 ). College students are more likely to have access to smartphones than elementary school students. The surge in smartphone ownership among college students has spurred interest in studying the impact of smartphone use on all aspects of their lives, especially academic performance. For example, Junco and Cotton ( 2012 ) found that spending a fair amount of time on smartphones while studying had a negative affect on the university student's Grade Point Average (GPA). In addition, multiple studies have found that mobile phone use is inversely related to academic performance (Judd, 2014 ; Karpinski et al., 2013 ). Most research on smartphone use and academic performance has focused on college students. There have few studies focused on elementary school students. Vanderloo ( 2014 ) argued that the excessive use of smartphones may cause numerous problems for the growth and development of children, including increased sedentary time and reduced physical activity. Furthermore, according to Sarwar and Soomro ( 2013 ), rapid and easy access to information and its transmission may hinder concentration and discourage critical thinking and is therefore not conducive to children’s cognitive development.

To sum up, the evidence on the use of smartphones by elementary school students is conflicting. Some studies have demonstrated that smartphone use can help elementary school students build social relationships and maintain their mental health, and have presented findings supporting elementary students’ use of smartphones in their studies. Others have opposed smartphone use in this student population, contending that it can impede growth and development. To take steps towards resolving this conflict, we investigated smartphone use among elementary school students.

In a study conducted in South Korea, Kim ( 2017 ) reported that 50% of their questionnaire respondents reported using smartphones for the first time between grades 4 and 6. Overall, 61.3% of adolescents reported that they had first used smartphones when they were in elementary school. Wang et al. ( 2017 ) obtained similar results in an investigation conducted in Taiwan. However, elementary school students are less likely to have access to smartphones than college students. Some elementary schools in Taiwan prohibit their students from using smartphones in the classroom (although they can use them after school). On the basis of these findings, the present study focused on fifth and sixth graders.

Jeong et al. ( 2016 ), based on a sample of 944 respondents recruited from 20 elementary schools, found that people who use smartphones for accessing Social Network Services (SNS), playing games, and for entertainment were more likely to be addicted to smartphones. Park ( 2020 ) found that games were the most commonly used type of mobile application among participants, comprised of 595 elementary school students. Greater smartphone dependence was associated with greater use of educational applications, videos, and television programs (Park, 2020 ). Three studies in Taiwan showed the same results, that elementary school students in Taiwan enjoy playing games on smartphones (Wang & Cheng, 2019 ; Wang et al., 2017 ). Based on the above, it is reasonable to infer that if elementary school students spend more time playing games on their smartphones, their academic performance will decline. However, several studies have found that using smartphones to help with learning can effectively improve academic performance. In this study we make effort to determine what the key influential factors that affect students' academic performance are.

Kim ( 2017 ) reported that, in Korea, smartphones are used most frequentlyfrom 9 pm to 12 am, which closely overlaps the corresponding period in Taiwan, from 8 to 11 pm In this study, we not only asked students how they obtained their smartphones, but when they most frequently used their smartphones, and who they contacted most frequently on their smartphones were, among other questions. There were a total of eight questions addressing smartphone behavior. Recent research on smartphones and academic performance draws on self-reported survey data on hours and/or minutes of daily use (e.g. Chen et al., 2015 ; Heo & Lee, 2021 ; Lepp et al., 2014 ; Troll et al., 2021 ). Therefore, this study also uses self-reporting to investigate how much time students spend using smartphones.

Various studies have indicated that parental attitudes affect elementary school students’ behavioral intentions toward smartphone use (Chen et al., 2020 ; Daems et al., 2019 ). Bae ( 2015 ) determined that a democratic parenting style (characterized by warmth, supervision, and rational explanation) was related to a lower likelihood of smartphone addiction in children. Park ( 2020 ) suggested that parents should closely monitor their children’s smartphone use patterns and provide consistent discipline to ensure appropriate smartphone use. In a study conducted in Taiwan, Chang et al. ( 2019 ) indicated that restrictive parental mediation reduced the risk of smartphone addiction among children. In essence, parental attitudes critically influence the behavioral intention of elementary school students toward smartphone use. The effect of parental control on smartphone use is also investigated in this study.

Another important question related to student smartphone use is self-control. Jeong et al. ( 2016 ) found that those who have lower self-control and greater stress were more likely to be addicted to smartphones. Self-control is here defined as the ability to control oneself in the absence of any external force, trying to observe appropriate behavior without seeking immediate gratification and thinking about the future (Lee et al., 2015 ). Those with greater self-control focus on long-term results when making decisions. People are able to control their behavior through the conscious revision of automatic actions which is an important factor in retaining self-control in the mobile and on-line environments. Self-control plays an important role in smartphone addiction and the prevention thereof. Previous studies have revealed that the lower one’s self-control, the higher the degree of smartphone dependency (Jeong et al., 2016 ; Lee et al., 2013 ). In other words, those with higher levels of self-control are likely to have lower levels of smartphone addiction. Clearly, self-control is an important factor affecting smartphone usage behavior.

Reviewing the literature related to self-control, we start with self-determination theory (SDT). The SDT (Deci & Ryan, 2008 ) theory of human motivation distinguishes between autonomous and controlled types of behavior. Ryan and Deci ( 2000 ) suggested that some users engage in smartphone communications in response to perceived social pressures, meaning their behavior is externally motivated. However, they may also be  intrinsically  motivated in the sense that they voluntarily use their smartphones because they feel that mobile communication meets their needs (Reinecke et al., 2017 ). The most autonomous form of motivation is referred to as intrinsic motivation. Being intrinsically motivated means engaging in an activity for its own sake, because it appears interesting and enjoyable (Ryan & Deci, 2000 ). Acting due to social pressure represents an externally regulated behavior, which SDT classifies as the most controlled form of motivation (Ryan & Deci, 2000 ). Individuals engage in such behavior not for the sake of the behavior itself, but to achieve a separable outcome, for example, to avoid punishment or to be accepted and liked by others (Ryan & Deci, 2006 ). SDT presumes that controlled and autonomous motivations are not complementary, but “work against each other” (Deci et al., 1999 , p. 628). According to the theory, external rewards alter the perceived cause of action: Individuals no longer voluntarily engage in an activity because it meets their needs, but because they feel controlled (Deci et al., 1999 ). For media users, the temptation to communicate through the smartphone is often irresistible (Meier, 2017 ). Researchers who have examined the reasons why users have difficulty controlling media use have focused on their desire to experience need gratification, which produces pleasurable experiences. The assumption here is that users often subconsciously prefer short-term pleasure gains from media use to the pursuit of long-term goals (Du et al., 2018 ). Accordingly, self-control is very important. Self-control here refers to the motivation and ability to resist temptations (Hofmann et al., 2009 ). Dispositional self-control is a key moderator of yielding to temptation (Hofmann et al., 2009 ). Ryan and Deci ( 2006 ) suggested that people sometimes perform externally controlled behaviors unconsciously, that is, without applying self-control.

Sklar et al. ( 2017 ) described two types of self-control processes: proactive and reactive. They suggested that deficiencies in the resources needed to inhibit temptation impulses lead to failure of self-control. Even when impossible to avoid a temptation entirely, self-control can still be made easier if one avoids attending to the tempting stimulus. For example, young children instructed to actively avoid paying attention to a gift and other attention-drawing temptations are better able to resist the temptation than children who are just asked to focus on their task. Therefore, this study more closely investigates students' self-control abilities in relation to smartphone use asking the questions, ‘How did you obtain your smartphone?’ (to investigate proactivity), and ‘How much time do you spend on your smartphone in a day?’ (to investigate the effects of self-control).

Thus, the following hypotheses are advanced.

• Hypothesis 1: Smartphone behavior varies with parental control.
• Hypothesis 2: Smartphone behavior varies based on students' self-control.

Parental control, students' self-control and their effects on learning effectiveness and academic performance

Based on Hypothesis 1 and 2, we believe that we need to focus on two factors, parental control and student self-control and their impact on academic achievement. In East Asia, Confucianism is one of the most prevalent and influential cultural values which affect parent–child relations and parenting practice (Lee et al., 2016 ). In Taiwan, Confucianism shapes another feature of parenting practice: the strong emphasis on academic achievement. The parents’ zeal for their children’s education is characteristic of Taiwan, even in comparison to academic emphasis in other East Asian countries. Hau and Ho ( 2010 ) noted that, in Eastern Asian (Chinese) cultures, academic achievement does not depend on the students’ interests. Chinese students typically do not regard intelligence as fixed, but trainable through learning, which enables them to take a persistent rather than a helpless approach to schoolwork, and subsequently perform well. In Chinese culture, academic achievement has been traditionally regarded as the passport to social success and reputation, and a way to enhance the family's social status (Hau & Ho, 2010 ). Therefore, parents dedicate a large part of their family resources to their children's education, a practice that is still prevalent in Taiwan today (Hsieh, 2020 ). Parental control aimed at better academic achievement is exerted within the behavioral and psychological domains. For instance, Taiwan parents tightly schedule and control their children’s time, planning private tutoring after school and on weekends. Parental control thus refers to “parental intrusiveness, pressure, or domination, with the inverse being parental support of autonomy” (Grolnick & Pomerantz, 2009 ). There are two types of parental control: behavioral and psychological. Behavioral control, which includes parental regulation and monitoring over what children do (Steinberg et al., 1992 ), predict positive psychosocial outcomes for children. Outcomes include low externalizing problems, high academic achievement (Stice & Barrera, 1995 ), and low depression. In contrast, psychological control, which is exerted over the children’s psychological world, is known to be problematic (Stolz et al., 2005 ). Psychological control involves strategies such as guilt induction and love withdrawal (Steinberg et al., 1992 ) and is related with disregard for children’s emotional autonomy and needs (Steinberg et al., 1992 ). Therefore, it is very important to discuss the type of parental control.

Troll et al. ( 2021 ) suggested that it is not the objective amount of smartphone use but the effective handling of smartphones that helps students with higher trait self-control to fare better academically. Heo and Lee ( 2021 ) discussed the mediating effect of self-control. They found that self-control was partially mediated by those who were not at risk for smartphone addiction. That is to say, smartphone addiction could be managed by strengthening self-control to promote healthy use. In an earlier study Hsieh and Lin ( 2021 ), we collected 41 international journal papers involving 136,491students across 15 countries, for meta-analysis. We found that the average and majority of the correlations were both negative. The short conclusion here was that smartphone addiction /reliance may have had a negative impact on learning performance. Clearly, it is very important to investigate the effect of self-control on learning effectiveness with regard to academic performance.

Smartphone use and its effects on learning effectiveness and academic performance

The impact of new technologies on learning or academic performance has been investigated in the literature. Kates et al. ( 2018 ) conducted a meta-analysis of 39 studies published over a 10-year period (2007–2018) to examine potential relationships between smartphone use and academic achievement. The effect of smartphone use on learning outcomes can be summarized as follows: r  =  − 0.16 with a 95% confidence interval of − 0.20 to − 0.13. In other words, smartphone use and academic achievement were negatively correlated. Amez and Beart ( 2020 ) systematically reviewed the literature on smartphone use and academic performance, observing the predominance of empirical findings supporting a negative correlation. However, they advised caution in interpreting this result because this negative correlation was less often observed in studies analyzing data collected through paper-and-pencil questionnaires than in studies on data collected through online surveys. Furthermore, this correlation was less often noted in studies in which the analyses were based on self-reported grade point averages than in studies in which actual grades were used. Salvation ( 2017 ) revealed that the type of smartphone applications and the method of use determined students’ level of knowledge and overall grades. However, this impact was mediated by the amount of time spent using such applications; that is, when more time is spent on educational smartphone applications, the likelihood of enhancement in knowledge and academic performance is higher. This is because smartphones in this context are used as tools to obtain the information necessary for assignments and tests or examinations. Lin et al. ( 2021 ) provided robust evidence that smartphones can promote improvements in academic performance if used appropriately.

In summary, the findings of empirical investigations into the effects of smartphone use have been inconsistent—positive, negative, or none. Thus, we explore the correlation between elementary school students’ smartphone use and learning effectiveness with regard to academic performance through the following hypotheses:

• Hypothesis 3: Smartphone use is associated with learning effectiveness with regard to academic performance.
• Hypothesis 4: Differences in smartphone use correspond to differences in learning effectiveness with regard to academic performance.

Hypotheses 1 to 4 are aimed at understanding the mediating effect of smartphone behavior; see Fig.  1 . It is assumed that smartphone behavior is the mediating variable, parental control and self-control are independent variables, and academic performance is the dependent variable. We want to understand the mediation effect of this model.

Model 1: Model to test the impact of parental control and students’ self-control on academic performance

Thus, the following hypotheses are presented.

• Hypothesis 5: Smartphone behaviors are the mediating variable to impact the academic performance.

Effects of the COVID-19 pandemic on smartphone use for online learning

According to 2020 statistics from the United Nations Educational, Scientific and Cultural Organization (UNESCO), since the start of the COVID-19 pandemic, full or partial school closures have affected approximately 800 million learners worldwide, more than half of the global student population. Schools worldwide have been closed for 14 to 22 weeks on average, equivalent to two thirds of an academic year (UNESCO, 2021 ). Because of the pandemic, instructors have been compelled to transition to online teaching (Carrillo & Flores, 2020 ). According to Tang et al. ( 2020 ), online learning is among the most effective responses to the COVID-19 pandemic. However, the effectiveness of online learning for young children is limited by their parents’ technological literacy in terms of their ability to navigate learning platforms and use the relevant resources. Parents’ time availability constitutes another constraint (Dong et al., 2020 ). Furthermore, a fast and stable Internet connection, as well as access to devices such as desktops, laptops, or tablet computers, definitively affects equity in online education. For example, in 2018, 14% of households in the United States lacked Internet access (Morgan, 2020 ). In addition, the availability and stability of network connections cannot be guaranteed in relatively remote areas, including some parts of Australia (Park et al., 2021 ). In Japan, more than 50% of 3-year-old children and 68% of 6-year-old children used the Internet in their studies, but only 21% of households in Thailand have computer equipment (Park et al., 2021 ).

In short, the COVID-19 pandemic has led to changes in educational practices. With advances in Internet technology and computer hardware, online education has become the norm amid. However, the process and effectiveness of learning in this context is affected by multiple factors. Aside from the parents’ financial ability, knowledge of educational concepts, and technological literacy, the availability of computer equipment and Internet connectivity also exert impacts. This is especially true for elementary school students, who rely on their parents in online learning more than do middle or high school students, because of their short attention spans and undeveloped computer skills. Therefore, this study focuses on the use of smartphones by elementary school students during the COVID-19 pandemic and its impact on learning effectiveness.

Participants

Participants were recruited through stratified random sampling. They comprised 499 Taiwanese elementary school students (in grades 5 and 6) who had used smartphones for at least 12 months. Specifically, the students advanced to grades 5 or 6 at the beginning of the 2018–2019 school year. Boys and girls accounted for 47.7% and 52.3% ( n  = 238 and 261, respectively) of the sample.

Data collection and measurement

In 2020, a questionnaire survey was conducted to collect relevant data. Of the 620 questionnaires distributed, 575 (92.7%) completed questionnaires were returned. After 64 participants were excluded because they had not used their smartphones continually over the past 12 months and 14 participants were excluded for providing invalid responses, 499 individuals remained. The questionnaire was developed by one of the authors on the basis of a literature review. The questionnaire content can be categorized as follows: (1) students’ demographic characteristics, (2) smartphone use, (3) smartphone behavior, and (4) learning effectiveness. The questionnaire was modified according to evaluation feedback provided by six experts. Exploratory and confirmatory factor analyses were conducted to test the structural validity of the questionnaire. Factor analysis was performed using principal component analysis and oblique rotation. From the exploratory factor analysis, 25 items (15 and 10 items on smartphone behavior and academic performance as constructs, respectively) were extracted and confirmed. According to the results of the exploratory factor analysis, smartphone behavior can be classified into three dimensions: interpersonal communication, leisure and entertainment, and searching for information. Interpersonal communication is defined as when students use smartphones to communicate with classmates or friends, such as in response to questions like ‘I often use my smartphone to call or text my friends’. Leisure and entertainment mean that students spend a lot of their time using their smartphones for leisure and entertainment, e.g. ‘I often use my smartphone to listen to music’ or ‘I often play media games with my smartphone’. Searching for information means that students spend a lot of their time using their smartphones to search for information that will help them learn, such as in response to questions like this ‘I often use my smartphone to search for information online, such as looking up words in a dictionary’ or ‘I will use my smartphone to read e-books and newspapers online’.

Academic performance can be classified into three dimensions: learning activities, learning applications, and learning attitudes. Learning activities are when students use their smartphones to help them with learning, such as in response to a question like ‘I often use some online resources from my smartphone to help with my coursework’. Learning applications are defined as when students apply smartphone software to help them with their learning activities, e.g. ‘With a smartphone, I am more accustomed to using multimedia software’. Learning attitudes define the students’ attitudes toward using the smartphone, with questions like ‘Since I have had a smartphone, I often find class boring; using a smartphone is more fun’ (This is a reverse coded item). The factor analysis results are shown in the appendix (Appendix Tables ​ Tables10, 10 , ​ ,11, 11 , ​ ,12, 12 , ​ ,13 13 and ​ and14). 14 ). It can be seen that the KMO value is higher than 0.75, and the Bartlett’s test is also significant. The total variance explained for smartphone behavior is 53.47% and for academic performance it is 59.81%. These results demonstrate the validity of the research tool.

KMO and Bartlett's Test

Total variance explained of smartphone behavior

Total variance explained of academic performance

Factor loading of smartphone behavior

Factor loading of academic performance

In this study, students were defined as "proactive" if they had asked their parents to buy a smartphone for their own use and "reactive" if their parents gave them a smartphone unsolicited (i.e. they had not asked for it). According to Heo and Lee ( 2021 ), students who proactively asked their parents to buy them a smartphone gave the assurance that they could control themselves and not become addicted, but if they had been given a smartphone (without having to ask for it), they did not need to offer their parents any such guarantees. They defined user addiction (meaning low self-control) as more than four hours of smartphone use per day (Peng et al., 2022 ).

A cross-tabulation of self-control results is presented in Table ​ Table2, 2 , with the columns representing “proactive” and “reactive”, and the rows showing “high self-control” and “low self-control”. There are four variables in this cross-tabulation, “Proactive high self-control” (students promised parents they would not become smartphone addicts and were successful), “Proactive low self-control” (assured their parents they would not become smartphone addicts, but were unsuccessful), “Reactive high self-control”, and “Reactive low self-control”.

Cross-tabulation of self-control ability

Regarding internal consistency among the constructs, the Cronbach's α values ranged from 0.850 to 0.884. According to the guidelines established by George and Mallery ( 2010 ), these values were acceptable because they exceeded 0.7. The overall Cronbach's α for the constructs was 0.922. The Cronbach's α value of the smartphone behavior construct was 0.850, whereas that of the academic performance construct was 0.884.

Data analysis

The participants’ demographic characteristics and smartphone use (expressed as frequencies and percentages) were subjected to a descriptive analysis. To examine hypotheses 1 and 2, an independent samples t test (for gender and grade) and one-way analysis of variance (ANOVA) were performed to test the differences in smartphone use and learning effectiveness with respect to academic performance among elementary school students under various background variables. To test hypothesis 3, Pearson’s correlation analysis was conducted to analyze the association between smartphone behavior and academic performance. To test hypothesis 4, one-way multivariate ANOVA (MANOVA) was employed to examine differences in smartphone behavior and its impacts on learning effectiveness. To test Hypothesis 5, structural equation modeling (SEM) was used to test whether smartphone behavior is a mediator of academic performance.

Descriptive analysis

The descriptive analysis (Table ​ (Table1) 1 ) revealed that the parents of 71.1% of the participants ( n  = 499) conditionally controlled their smartphone use. Moreover, 42.5% of the participants noted that they started using smartphones in grade 3 or 4. Notably, 43.3% reported that they used their parents’ old smartphones; in other words, almost half of the students used secondhand smartphones. Overall, 79% of the participants indicated that they most frequently used their smartphones after school. Regarding smartphone use on weekends, 54.1% and 44.1% used their smartphones during the daytime and nighttime, respectively. Family members and classmates (45.1% and 43.3%, respectively) were the people that the participants communicated with the most on their smartphones. Regarding bringing their smartphones to school, 53.1% of the participants indicated that they were most concerned about losing their phones. As for smartphone use duration, 28.3% of the participants indicated that they used their smartphones for less than 1 h a day, whereas 24.4% reported using them for 1 to 2 h a day.

Descriptive analysis results

Smartphone behavior varies with parental control and based on students' self-control

We used the question ‘How did you obtain your smartphone?’ (to investigate proactivity), and ‘How much time do you spend on your smartphone in a day?’ (to investigate the effects of students' self-control). According to the Hsieh and Lin ( 2021 ), and Peng et al. ( 2022 ), addition is defined more than 4 h a day are defined as smartphone addiction (meaning that students have low self-control).

Table ​ Table2 2 gives the cross-tabulation results for self-control ability. Students who asked their parents to buy a smartphone, but use it for less than 4 h a day are defined as having ‘Proactive high self-control’; students using a smartphone for more than 4 h a day are defined as having ‘Proactive low self-control’. Students whose parents gave them a smartphone but use them for less than 4 h a day are defined as having ‘Reactive high self-control’; students given smart phones and using them for more than 4 h a day are defined as having ‘Reactive low self-control’; others, we define as having moderate levels of self-control.

Tables ​ Tables3 3 – 5 present the results of the t test and analysis of covariance (ANCOVA) on differences in the smartphone behaviors based on parental control and students' self-control. As mentioned, smartphone behavior can be classified into three dimensions: interpersonal communication, leisure and entertainment, and information searches. Table ​ Table3 3 lists the significant independent variables in the first dimension of smartphone behavior based on parental control and students' self-control. Among the students using their smartphones for the purpose of communication, the proportion of parents enforcing no control over smartphone use was significantly higher than the proportions of parents enforcing strict or conditional control ( F  = 11.828, p  < 0.001). This indicates that the lack of parental control over smartphone use leads to the participants spending more time using their smartphones for interpersonal communication.

Significant independent variables (Parental control and Self-control) in the first dimension (interpersonal communication) of smartphone use

*** p  < .001

Independent variables (Parental control and Self-control) in the third dimension (information searches) of smartphone behavior

SD standard deviation

For the independent variable of self-control, regardless of whether students had proactive high self-control, proactive low self-control or reactive low self-control, significantly higher levels of interpersonal communication than reactive high self-control were reported ( F  = 18.88, p  < 0.001). This means that students effectively able to control themselves, who had not asked their parents to buy them smartphones, spent less time using their smartphones for interpersonal communication. However, students with high self-control but who had asked their parents to buy them smartphones, would spend more time on interpersonal communication (meaning that while they may not spend a lot of time on their smartphones each day, the time spent on interpersonal communication is no different than for the other groups). Those without effective self-control, regardless of whether they had actively asked their parents to buy them a smartphone or not, would spend more time using their smartphones for interpersonal communication.

Table ​ Table4 4 displays the independent variables (parental control and students' self-control) significant in the dimension of leisure and entertainment. Among the students using their smartphones for this purpose, the proportion of parents enforcing no control over smartphone use was significantly higher than the proportions of parents enforcing strict or conditional control ( F  = 8.539, p  < 0.001). This indicates that the lack of parental control over smartphone use leads to the participants spending more time using their smartphones for leisure and entertainment.

Significant independent variables (Parental control and Self-control) in the second dimension (leisure and entertainment) of smartphone behavior

For the independent variable of self-control, students with proactive low self-control and reactive low self-control reported significantly higher use of smartphones for leisure and entertainment than did students with proactive high self-control and reactive high self-control ( F  = 8.77, p  < 0.001). This means that students who cannot control themselves, whether proactive or passive in terms of asking their parents to buy them a smartphone, will spend more time using their smartphones for leisure and entertainment.

Table ​ Table5 5 presents the significant independent variables in the dimension of information searching. Significant differences were observed only for gender, with a significantly higher proportion of girls using their smartphones to search for information ( t  =  − 3.979, p  < 0.001). Parental control and students' self-control had no significance in the dimension of information searching. This means that the parents' attitudes towards control did not affect the students' use of smartphones for information searches. This is conceivable, as Asian parents generally discourage their children from using their smartphones for non-study related activities (such as entertainment or making friends), but not for learning-related activities. It is also worth noting that student self-control was not significant in relation to searching for information. This means that it makes no difference whether or not students have self-control in their search for learning-related information.

Four notable results are presented as follows.

First, a significantly higher proportion of girls used their smartphones to search for information. Second, if smartphone use was not subject to parental control, the participants spent more time using their smartphones for interpersonal communication and for leisure and entertainment rather than for information searches. This means that if parents make the effort to control their children's smartphone use, this will reduce their children's use of smartphones for interpersonal communication and entertainment. Third, student self-control affects smartphone use behavior for interpersonal communication and entertainment (but not searching for information). This does not mean that they spend more time on their smartphones in their daily lives, it means that they spend the most time interacting with people while using their smartphones (For example, they may only spend 2–3 h a day using their smartphone. During those 2–3 h, they spend more than 90% of their time interacting with people and only 10% doing other things), which is the fourth result.

These results support hypotheses 1 and 2.

Pearson’s correlation analysis of smartphone behavior and academic performance

Table ​ Table6 6 presents the results of Pearson’s correlation analysis of smartphone behavior and academic performance. Except for information searches and learning attitudes, all variables exhibited significant and positively correlations. In short, there was a positive correlation between smartphone behavior and academic performance. Thus, hypothesis 3 is supported.

Pearson’s correlation analysis of smartphone use and academic performance

** p  < .01

Analysis of differences in the academic performance of students with different smartphone behaviors

Differences in smartphone behavior and its impacts on learning effectiveness with regard to academic performance were examined through. In step 1, cluster analysis was conducted to convert continuous variables into discrete variables. In step 2, a one-way MANOVA was performed to analyze differences in the academic performance of students with varying smartphone behavior. Regarding the cluster analysis results (Table ​ (Table7), 7 ), the value of the change in the Bayesian information criterion in the second cluster was − 271.954, indicating that it would be appropriate to group the data. Specifically, we assigned the participants into either the high smartphone use group or the low smartphone use group, comprised of 230 and 269 participants (46.1% and 53.9%), respectively.

Cluster analysis results

BIC Bayesian information criterion

The MANOVA was preceded by the Levene test for the equality of variance, which revealed nonsignificant results, F (6, 167,784.219) = 1.285, p  > 0.05. Thus, we proceeded to use MANOVA to examine differences in the academic performance of students with differing smartphone behaviors (Table ​ (Table8). 8 ). Between-group differences in academic performance were significant, F (3, 495) = 44.083, p  < 0.001, Λ = 0.789, η 2  = 0.211, power = 0.999. Subsequently, because academic performance consists of three dimensions, we performed univariate tests and an a posteriori comparison.

Multivariate analysis of variance results

Df degrees of freedom

Table ​ Table9 9 presents the results of the univariate tests. Between-group differences in learning activities were significant, ( F [1, 497] = 40.8, p  < 0.001, η 2  = 0.076, power = 0.999). Between-group differences in learning applications were also significant ( F [1, 497] = 117.98, p  < 0.001, η 2  = 0.192, power = 0.999). Finally, differences between the groups in learning attitudes were significant ( F [1, 497] = 23.22, p  < 0.001, η 2  = 0.045, power = 0.998). The a posteriori comparison demonstrated that the high smartphone use group significantly outperformed the low smartphone use group in all dependent variables with regard to academic performance. Thus, hypothesis 4 is supported.

Univariate analysis results

SS sum of squares; df degrees of freedom; MS mean square

Smartphone behavior as the mediating variable impacting academic performance

As suggested by Baron and Kenny ( 1986 ), smartphone behavior is a mediating variable affecting academic performance. We examined the impact through the following four-step process:

• Step 1. The independent variable (parental control and students' self-control) must have a significant effect on the dependent variable (academic performance), as in model 1 (please see Fig.  1 ).

Model 2: Model to test the impact of parental control and students’ self-control on smartphone behavior

Model 3: Both independent variables (parental control and student self-control) and mediators (smartphone behavior) were used as predictors to predict dependent variables

• Step 4. In model 3, the regression coefficient of the independent variables (parental control and student self-control) on the dependent variables must be less than in mode 1 or become insignificant.

As can be seen in Fig.  1 , parental control and student self-control are observed variables, and smartphone behavior is a latent variable. "Strict" is set to 0, which means "Conditional", with "None" compared to "Strict". “Proactive high self-control” is also set to 0. From Fig.  1 we find that the independent variables have a significant effect on the dependent variable. The regression coefficient of parental control is 0.176, t = 3.45 ( p  < 0.01); the regression coefficient of students’ self-control is 0.218, t = 4.12 ( p  < 0.001), proving the fit of the model (Chi Square = 13.96**, df = 4, GFI = 0.989, AGFI = 0.959, CFI = 0.996, TLI = 0.915, RMSEA = 0.051, SRMR = 0.031). Therefore, the test results for Model 1 are in line with the recommendations of Baron and Kenny ( 1986 ).

As can be seen in Fig.  2 , the independent variables have a significant effect on smartphone behaviors. The regression coefficient of parental control is 0.166, t = 3.11 ( p  < 0.01); the regression coefficient of students’ self-control is 0.149, t = 2.85 ( p  < 0.01). The coefficients of the model fit are: Chi Square = 15.10**, df = 4, GFI = 0.988, AGFI = 0.954, CFI = 0.973, TLI = 0.932, RMSEA = 0.052, SRMR = 0.039. Therefore, the results of the test of Model 2 are in line with the recommendations of Baron and Kenny ( 1986 ).

As can be seen in Fig.  3 , smartphone behaviors have a significant effect on the dependent variable. The regression coefficient is 0.664, t = 10.2 ( p  < 0.001). The coefficients of the model fit are: Chi Square = 91.04**, df = 16, GFI = 0.958, AGFI = 0.905, CFI = 0.918, TLI = 0.900, RMSEA = 0.077, SRMR = 0.063. Therefore, the results of the test of Model 3 are in line with the recommendations of Baron and Kenny ( 1986 ).

As can be seen in Fig.  4 , the regression coefficient of the independent variables (parental control and student self-control) on the dependent variables is less than in model 1, and the parental control variable becomes insignificant. The regression coefficient of parental control is 0.013, t = 0.226 ( p  > 0.05); the path coefficient of students’ self-control is 0.155, t = 3.07 ( p  < 0.01).

Model 4: Model three’s regression coefficient of the independent variables (parental control and student self-control) on the dependent variables

To sum up, we prove that smartphone behavior is the mediating variable to impact the academic performance. Thus, hypothesis 5 is supported.

This study investigated differences in the smartphone behavior of fifth and sixth graders in Taiwan with different background variables (focus on parental control and students’ self-control) and their effects on academic performance. The correlation between smartphone behavior and academic performance was also examined. Although smartphones are being used in elementary school learning activities, relatively few studies have explored their effects on academic performance. In this study, the proportion of girls who used smartphones to search for information was significantly higher than that of boys. Past studies have been inconclusive about gender differences in smartphone use. Lee and Kim ( 2018 ) observed no gender differences in smartphone use, but did note that boys engaged in more smartphone use if their parents set fewer restrictions. Kim et al. ( 2019 ) found that boys exhibited higher levels of smartphone dependency than girls. By contrast, Kim ( 2017 ) reported that girls had higher levels of smartphone dependency than boys did. Most relevant studies have focused on smartphone dependency; comparatively little attention has been devoted to smartphone behavior. The present study contributes to the literature in this regard.

Notably, this study found that parental control affected smartphone use. If the participants’ parents imposed no restrictions, students spent more time on leisure and entertainment and on interpersonal communication rather than on information searches. This is conceivable, as Asian parents generally discourage their children from using their smartphones for non-study related activities (such as entertainment or making friends) but not for learning-related activities. If Asian parents believe that using a smartphone can improve their child's academic performance, they will encourage their child to use it. Parents in Taiwan attach great importance to their children's academic performance (Lee et al., 2016 ). A considerable amount of research has been conducted on parental attitudes or control in this context. Hwang and Jeong ( 2015 ) suggested that parental attitudes mediated their children’s smartphone use. Similarly, Chang et al. ( 2019 ) observed that parental attitudes mediated the smartphone use of children in Taiwan. Our results are consistent with extant evidence in this regard. Lee and Ogbolu ( 2018 ) demonstrated that the stronger children’s perception was of parental control over their smartphone use, the more frequently they used their smartphones. The study did not further explain the activities the children engaged in on their smartphones after they increased their frequency of use. In the present study, the participants spent more time on their smartphones for leisure and entertainment and for interpersonal communication than for information searches.

Notably, this study also found that students’ self-control affected smartphone use.

Regarding the Pearson’s correlation analysis of smartphone behavior and academic performance, except for information searches and learning attitudes, all the variables were significantly positively correlated. In other words, there was a positive correlation between smartphone behavior and academic performance. In their systematic review, Amez and Beart ( 2020 ) determined that most empirical results provided evidence of a negative correlation between smartphone behavior and academic performance, playing a more considerable role in that relationship than the theoretical mechanisms or empirical methods in the studies they examined. The discrepancy between our results and theirs can be explained by the between-study variations in the definitions of learning achievement or performance.

Regarding the present results on the differences in the academic performance of students with varying smartphone behaviors, we carried out a cluster analysis, dividing the participants into a high smartphone use group and a low smartphone use group. Subsequent MANOVA revealed that the high smartphone use group academically outperformed the low smartphone use group; significant differences were noted in the academic performance of students with different smartphone behaviors. Given the observed correlation between smartphone behavior and academic performance, this result is not unexpected. The findings on the relationship between smartphone behavior and academic performance can be applied to smartphone use in the context of education.

Finally, in a discussion of whether smartphone behavior is a mediator of academic performance, it is proved that smartphone behavior is the mediating variable impacting academic performance. Our findings show that parental control and students’ self-control can affect academic performance. However, the role of the mediating variable (smartphone use behavior) means that changes in parental control have no effect on academic achievement at all. This means that smartphone use behaviors have a full mediating effect on parental control. It is also found that students’ self-control has a partial mediating effect. Our findings suggest that parental attitudes towards the control of smartphone use and students' self-control do affect academic performance, but smartphone use behavior has a significant mediating effect on this. In other words, it is more important to understand the children's smartphone behavior than to control their smartphone usage. There have been many studies in the past exploring the mediator variables for smartphone use addiction and academic performance. For instance, Ahmed et al. ( 2020 ) found that the mediating variables of electronic word of mouth (eWOM) and attitude have a significant and positive influence in the relationship between smartphone functions. Cho and Lee ( 2017 ) found that parental attitude is the mediating variable for smartphone use addiction. Cho et al. ( 2017 ) indicated that stress had a significant influence on smartphone addiction, while self-control mediates that influence. In conclusion, the outcomes demonstrate that parental control and students’ self-control do influence student academic performance in primary school. Previous studies have offered mixed results as to whether smartphone usage has an adverse or affirmative influence on student academic performance. This study points out a new direction, thinking of smartphone use behavior as a mediator.

In brief, the participants spent more smartphone time on leisure and entertainment and interpersonal communication, but the academic performance of the high smartphone use group surpassed that of the low smartphone use group. This result may clarify the role of students’ communication skills in their smartphone use. As Kang and Jung ( 2014 ) noted, conventional communication methods have been largely replaced by mobile technologies. This suggests that students’ conventional communication skills are also shifting to accommodate smartphone use. Elementary students are relatively confident in communicating with others through smartphones; thus, they likely have greater self‐efficacy in this regard and in turn may be better able to improve their academic performance by leveraging mobile technologies. This premise requires verification through further research. Notably, high smartphone use suggests the greater availability of time and opportunity in this regard. Conversely, low smartphone use suggests the relative lack of such time and opportunity. The finding that the high smartphone use group academically outperformed the low smartphone use group also indicates that smartphone accessibility constitutes a potential inequality in the learning opportunities of elementary school students. Therefore, elementary school teachers must be aware of this issue, especially in view of the shift to online learning triggered by the COVID-19 pandemic, when many students are dependent on smartphones and computers for online learning.

Conclusions and implications

This study examined the relationship between smartphone behavior and academic performance for fifth and sixth graders in Taiwan. Various background variables (parental control and students’ self-control) were also considered. The findings provide new insights into student attitudes toward smartphone use and into the impacts of smartphone use on academic performance. Smartphone behavior and academic performance were correlated. The students in the high smartphone use group academically outperformed the low smartphone use group. This result indicates that smartphone use constitutes a potential inequality in elementary school students’ learning opportunities. This can be explained as follows: high smartphone use suggests that the participants had sufficient time and opportunity to access and use smartphones. Conversely, low smartphone use suggests that the participants did not have sufficient time and opportunity for this purpose. Students’ academic performance may be adversely affected by fewer opportunities for access. Disparities between their performance and that of their peers with ready access to smartphones may widen amid the prevalent class suspension and school closure during the ongoing COVID-19 pandemic.

This study has laid down the basic foundations for future studies concerning the influence of smartphones on student academic performance in primary school as the outcome variable. This model can be replicated and applied to other social science variables which can influence the academic performance of primary school students as the outcome variable. Moreover, the outcomes of this study can also provide guidelines to teachers, parents, and policymakers on how smartphones can be most effectively used to derive the maximum benefits in relation to academic performance in primary school as the outcome variable. Finally, the discussion of the mediating variable can also be used as the basis for the future projects.

Limitations and areas of future research

This research is significant in the field of smartphone functions and the student academic performance for primary school students. However, certain limitations remain. The small number of students sampled is the main problem in this study. For more generalized results, the sample data may be taken across countries within the region and increased in number (rather than limited to certain cities and countries). For more robust results, data might also be obtained from both rural and urban centers. In this study, only one mediating variable was incorporated, but in future studies, several other psychological and behavioral variables might be included for more comprehensive outcomes. We used the SEM-based multivariate approach which does not address the cause and effect between the variables, therefore, in future work, more robust models could be employed for cause-and-effect investigation amongst the variables.

Acknowledgements

The authors would like to express their gratitude to the school participants in the study.

Appendix 1 Factor analysis results

Author contributions.

Kung and Wang conceived of the presented idea. Kung, Wang and Hsieh developed the theory and performed the computations. Kung and Hsieh verified the analytical methods. Wang encouraged Kung and Hsieh to verify the numerical checklist and supervised the findings of this work. All authors discussed the results and contributed to the final manuscript.

The work done for this study was financially supported by the Ministry of Science and Technology of Taiwan under project No. MOST 109–2511-H-017–005.

Data availability

Declarations.

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Publisher's note

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

Contributor Information

Jen Chun Wang, Email: wt.ude.unkn@gnawcj .

Chia-Yen Hsieh, Email: wt.ude.utpn@anudnab .

Shih-Hao Kung, Email: wt.moc.oohay@1-hsg .

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Social Media Addiction and Its Impact on College Students' Academic Performance: The Mediating Role of Stress

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• Volume 32 , pages 81–90, ( 2023 )

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• Lei Zhao   ORCID: orcid.org/0000-0002-7337-3065 1 , 2  

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Social media use can bring negative effects to college students, such as social media addiction (SMA) and decline in academic performance. SMA may increase the perceived stress level of college students, and stress has a negative impact on academic performance, but this potential mediating role of stress has not been verified in existing studies. In this paper, a research model was developed to investigate the antecedent variables of SMA, and the relationship between SMA, stress and academic performance. With the data of 372 Chinese college students (mean age 21.3, 42.5% males), Partial Least Squares, Structural Equation Model was adopted to evaluate measurement model and structural model. The results show that use intensity is an important predictor of SMA, and both SMA and stress have a negative impact on college students’ academic performance. In addition, we further confirmed that stress plays a mediating role in the relationship between SMA and college students’ academic performance.

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This study is supported by the Planning Subject for the 14th Five-year Plan of National Education Sciences (Grant No. EIA210425).

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Zhao, L. Social Media Addiction and Its Impact on College Students' Academic Performance: The Mediating Role of Stress. Asia-Pacific Edu Res 32 , 81–90 (2023). https://doi.org/10.1007/s40299-021-00635-0

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Essay on Mobile Phone: Mobile Phone is often also called “cellular phone”. It is a device mainly used for a voice call. Presently technological advancements have made our life easy. Today, with the help of a mobile phone we can easily talk or video chat with anyone across the globe by just moving our fingers. Today mobile phones are available in various shapes and sizes, having different technical specifications and are used for a number of purposes like – voice calling, video chatting, text messaging or SMS, multimedia messaging, internet browsing, email, video games, and photography. Hence it is called a ‘Smart Phone’. Like every device, the mobile phone also has its pros and cons which we shall discuss now.

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5) Mobile Banking

Nowadays mobiles are even used as a wallet for making payments. Money could be transferred almost instantly to friends, relatives or others by using mobile baking in the smartphone. Also, one can easily access his/her account details and know past transactions. So it saves a lot of time and also hassle-free.

Disadvantages of Mobile Phones

1)  Wasting Time

Now day’s people have become addicted to mobiles. Even when we don’t need to mobile we surf the net, play games making a real addict. As mobile phones became smarter, people became dumber.

2) Making Us Non- communicable

Wide usage of mobiles has resulted in less meet and talk more. Now people don’t meet physically rather chat or comment on social media.

3) Loss of Privacy

It is a major concern now of losing one’s privacy because of much mobile usage. Today anyone could easily access the information like where you live, your friends and family, what is your occupation, where is your house, etc; by just easily browsing through your social media account.

4) Money Wastage

As the usefulness of mobiles has increased so their costing. Today people are spending a lot amount of money on buying smartphones, which could rather be spent on more useful things like education, or other useful things in our life.

A mobile phone could both be positive and negative; depending on how a user uses it. As mobiles have become a part of our life so we should use it in a proper way, carefully for our better hassle-free life rather using it improperly and making it a virus in life.

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Should college essays touch on race? Some feel the affirmative action ruling leaves them no choice

CHICAGO — When she started writing her college essay, Hillary Amofa told the story she thought admissions offices wanted to hear. About being the daughter of immigrants from Ghana and growing up in a small apartment in Chicago. About hardship and struggle.

Then she deleted it all.

“I would just find myself kind of trauma-dumping,” said the 18-year-old senior at Lincoln Park High School in Chicago. “And I’m just like, this doesn’t really say anything about me as a person.”

When the Supreme Court ended affirmative action in higher education, it left the college essay as one of few places where race can play a role in admissions decisions. For many students of color, instantly more was riding on the already high-stakes writing assignment. Some say they felt pressure to exploit their hardships as they competed for a spot on campus.

Amofa was just starting to think about her essay when the court issued its decision, and it left her with a wave of questions. Could she still write about her race? Could she be penalized for it? She wanted to tell colleges about her heritage but she didn’t want to be defined by it.

In English class, Amofa and her classmates read sample essays that all seemed to focus on some trauma or hardship. It left her with the impression she had to write about her life’s hardest moments to show how far she’d come. But she and some of her classmates wondered if their lives had been hard enough to catch the attention of admissions offices.

“For a lot of students, there’s a feeling of, like, having to go through something so horrible to feel worthy of going to school, which is kind of sad,” said Amofa, the daughter of a hospital technician and an Uber driver.

This year’s senior class is the first in decades to navigate college admissions without affirmative action . The Supreme Court upheld the practice in decisions going back to the 1970s, but this court’s conservative supermajority found it is unconstitutional for colleges to give students extra weight because of their race alone.

Still, the decision left room for race to play an indirect role: Chief Justice John Roberts wrote universities can still consider how an applicant’s life was shaped by their race, “so long as that discussion is concretely tied to a quality of character or unique ability.”

“A benefit to a student who overcame racial discrimination, for example, must be tied to that student’s courage and determination,” he wrote.

Scores of colleges responded with new essay prompts asking about students’ backgrounds. Brown University asked applicants how “an aspect of your growing up has inspired or challenged you.” Rice University asked students how their perspectives were shaped by their “background, experiences, upbringing, and/or racial identity.”

WONDERING IF SCHOOLS 'EXPECT A SOB STORY'

When Darrian Merritt started writing his essay, he knew the stakes were higher than ever because of the court’s decision. His first instinct was to write about events that led to him going to live with his grandmother as a child.

Those were painful memories, but he thought they might play well at schools like Yale, Stanford and Vanderbilt.

“I feel like the admissions committee might expect a sob story or a tragic story,” said Merritt, a senior in Cleveland. “And if you don’t provide that, then maybe they’re not going to feel like you went through enough to deserve having a spot at the university. I wrestled with that a lot.”

He wrote drafts focusing on his childhood, but it never amounted to more than a collection of memories. Eventually he abandoned the idea and aimed for an essay that would stand out for its positivity.

Merritt wrote about a summer camp where he started to feel more comfortable in his own skin. He described embracing his personality and defying his tendency to please others. The essay had humor — it centered on a water gun fight where he had victory in sight but, in a comedic twist, slipped and fell. But the essay also reflects on his feelings of not being “Black enough” and getting made fun of for listening to “white people music.”

“I was like, ‘OK, I’m going to write this for me, and we’re just going to see how it goes,’” he said. “It just felt real, and it felt like an honest story.”

The essay describes a breakthrough as he learned “to take ownership of myself and my future by sharing my true personality with the people I encounter. ... I realized that the first chapter of my own story had just been written.”

A RULING PROMPTS PIVOTS ON ESSAY TOPICS

Like many students, Max Decker of Portland, Oregon, had drafted a college essay on one topic, only to change direction after the Supreme Court ruling in June.

Decker initially wrote about his love for video games. In a childhood surrounded by constant change, navigating his parents’ divorce, the games he took from place to place on his Nintendo DS were a source of comfort.

But the essay he submitted to colleges focused on the community he found through Word is Bond, a leadership group for young Black men in Portland.

As the only biracial, Jewish kid with divorced parents in a predominantly white, Christian community, Decker wrote he constantly felt like the odd one out. On a trip with Word is Bond to Capitol Hill, he and friends who looked just like him shook hands with lawmakers. The experience, he wrote, changed how he saw himself.

“It’s because I’m different that I provide something precious to the world, not the other way around,” he wrote.

As a first-generation college student, Decker thought about the subtle ways his peers seemed to know more about navigating the admissions process . They made sure to get into advanced classes at the start of high school, and they knew how to secure glowing letters of recommendation.

If writing about race would give him a slight edge and show admissions officers a fuller picture of his achievements, he wanted to take that small advantage.

His first memory about race, Decker said, was when he went to get a haircut in elementary school and the barber made rude comments about his curly hair. Until recently, the insecurity that moment created led him to keep his hair buzzed short.

Through Word is Bond, Decker said he found a space to explore his identity as a Black man. It was one of the first times he was surrounded by Black peers and saw Black role models. It filled him with a sense of pride in his identity. No more buzzcut.

The pressure to write about race involved a tradeoff with other important things in his life, Decker said. That included his passion for journalism, like the piece he wrote on efforts to revive a once-thriving Black neighborhood in Portland. In the end, he squeezed in 100 characters about his journalism under the application’s activities section.

“My final essay, it felt true to myself. But the difference between that and my other essay was the fact that it wasn’t the truth that I necessarily wanted to share,” said Decker, whose top college choice is Tulane, in New Orleans, because of the region’s diversity. “It felt like I just had to limit the truth I was sharing to what I feel like the world is expecting of me.”

SPELLING OUT THE IMPACT OF RACE

Before the Supreme Court ruling, it seemed a given to Imani Laird that colleges would consider the ways that race had touched her life. But now, she felt like she had to spell it out.

As she started her essay, she reflected on how she had faced bias or felt overlooked as a Black student in predominantly white spaces.

There was the year in math class when the teacher kept calling her by the name of another Black student. There were the comments that she’d have an easier time getting into college because she was Black .

“I didn’t have it easier because of my race,” said Laird, a senior at Newton South High School in the Boston suburbs who was accepted at Wellesley and Howard University, and is waiting to hear from several Ivy League colleges. “I had stuff I had to overcome.”

In her final essays, she wrote about her grandfather, who served in the military but was denied access to GI Bill benefits because of his race.

She described how discrimination fueled her ambition to excel and pursue a career in public policy.

“So, I never settled for mediocrity,” she wrote. “Regardless of the subject, my goal in class was not just to participate but to excel. Beyond academics, I wanted to excel while remembering what started this motivation in the first place.”

WILL SCHOOLS LOSE RACIAL DIVERSITY?

Amofa used to think affirmative action was only a factor at schools like Harvard and Yale. After the court’s ruling, she was surprised to find that race was taken into account even at some public universities she was applying to.

Now, without affirmative action, she wondered if mostly white schools will become even whiter.

It’s been on her mind as she chooses between Indiana University and the University of Dayton, both of which have relatively few Black students. When she was one of the only Black students in her grade school, she could fall back on her family and Ghanaian friends at church. At college, she worries about loneliness.

“That’s what I’m nervous about,” she said. “Going and just feeling so isolated, even though I’m constantly around people.”

The first drafts of her essay focused on growing up in a low-income family, sharing a bedroom with her brother and grandmother. But it didn’t tell colleges about who she is now, she said.

Her final essay tells how she came to embrace her natural hair . She wrote about going to a mostly white grade school where classmates made jokes about her afro. When her grandmother sent her back with braids or cornrows, they made fun of those too.

Over time, she ignored their insults and found beauty in the styles worn by women in her life. She now runs a business doing braids and other hairstyles in her neighborhood.

“I stopped seeing myself through the lens of the European traditional beauty standards and started seeing myself through the lens that I created,” Amofa wrote.

“Criticism will persist, but it loses its power when you know there’s a crown on your head!”

Ma reported from Portland, Oregon.

The Associated Press’ education coverage receives financial support from multiple private foundations. AP is solely responsible for all content. Find AP’s standards for working with philanthropies, a list of supporters and funded coverage areas at AP.org .

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AT&T says a data breach leaked millions of customers’ information online. Were you affected?

FILE - The sign in front of an AT&T retail store is seen in Miami, July 18, 2019. The theft of sensitive information belonging to millions of AT&T’s current and former customers has been recently discovered online, the telecommunications giant said Saturday, March 30, 2024. In an announcement addressing the data breach, AT&T said that a dataset found on the dark web contains information including some Social Security numbers and passcodes for about 7.6 million current account holders and 65.4 million former account holders. (AP Photo/Lynne Sladky, File)

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NEW YORK (AP) — The theft of sensitive information belonging to millions of AT&T’s current and former customers has been recently discovered online, the telecommunications giant said this weekend.

In a Saturday announcement addressing the data breach, AT&T said that a dataset found on the “dark web” contains information including some Social Security numbers and passcodes for about 7.6 million current account holders and 65.4 million former account holders.

Whether the data “originated from AT&T or one of its vendors” is still unknown, the Dallas-based company noted — adding that it had launched an investigation into the incident. AT&T has also begun notifying customers whose personal information was compromised.

Here’s what you need to know.

WHAT INFORMATION WAS COMPROMISED IN THIS BREACH?

Although varying by each customer and account, AT&T says that information involved in this breach included Social Security numbers and passcodes — which, unlike passwords, are numerical PINS that are typically four digits long.

Full names, email addresses, mailing address, phone numbers, dates of birth and AT&T account numbers may have also been compromised. The impacted data is from 2019 or earlier and does not appear to include financial information or call history, the company said.

HOW DO I KNOW IF I WAS AFFECTED?

Consumers impacted by this breach should be receiving an email or letter directly from AT&T about the incident. The email notices began going out on Saturday, an AT&T spokesperson confirmed to The Associated Press.

WHAT ACTION HAS AT&T TAKEN?

Beyond these notifications, AT&T said that it had already reset the passcodes of current users. The company added that it would pay for credit monitoring services where applicable.

AT&T also said that it “launched a robust investigation” with internal and external cybersecurity experts to investigate the situation further.

HAS AT&T SEEN DATA BREACHES LIKE THIS BEFORE?

AT&T has seen several data breaches that range in size and impact over the years .

While the company says the data in this latest breach surfaced on a hacking forum nearly two weeks ago, it closely resembles a similar breach that surfaced in 2021 but which AT&T never acknowledged, cybersecurity researcher Troy Hunt told the AP Saturday.

“If they assess this and they made the wrong call on it, and we’ve had a course of years pass without them being able to notify impacted customers,” then it’s likely the company will soon face class action lawsuits, said Hunt, founder of an Australia-based website that warns people when their personal information has been exposed.

A spokesperson for AT&T declined to comment further when asked about these similarities Sunday.

HOW CAN I PROTECT MYSELF GOING FORWARD?

Avoiding data breaches entirely can be tricky in our ever-digitized world, but consumers can take some steps to help protect themselves going forward.

The basics include creating hard-to-guess passwords and using multifactor authentication when possible. If you receive a notice about a breach, it’s good idea to change your password and monitor account activity for any suspicious transactions. You’ll also want to visit a company’s official website for reliable contact information — as scammers sometimes try to take advantage of news like data breaches to gain your trust through look-alike phishing emails or phone calls.

In addition, the Federal Trade Commission notes that nationwide credit bureaus — such as Equifax, Experian and TransUnion — offer free credit freezes and fraud alerts that consumers can set up to help protect themselves from identity theft and other malicious activity.

AP Reporter Matt O’Brien contributed to this report from Providence, Rhode Island.