A Study of Magnitude and Psychological Correlates of Smartphone Use in Medical Students: A Pilot Study with A Novel Telemetric Approach

Association of Smartphone Use and Digital Addiction with Mental Health, Quality of Life, Motivation and Learning of Medical Students: A Two-Year Follow-Up Study

Background: Despite studies evaluating the insertion of technology and the use of smartphones in the mental health and learning of medical students, few have investigated these outcomes longitudinally. This study aims to investigate the association between smartphone use and digital addiction with mental health, quality of life, learning, and academic motivation of medical students. Methods: This is a longitudinal study conducted between 2016 and 2018. Socio-demographics, smartphone use, digital dependence (Internet Addiction Test), surface and deep learning approach (Biggs), motivation (Academic Motivation Scale), evaluation of symptoms of depression, anxiety, and stress (DASS- 21) and Quality of Life (WHOQOL-BREF) were assessed. Adjusted regression models were used for data analysis. Results: A total of 269 students were included(51.4% of the total). In the two-year follow-up, despite an increase in the frequency of smartphone use in general and also in the classroom for non-educational activities, no increase in digital dependence was found. In the adjusted models, the frequency of smartphone use and digital dependence were predictors of lower academic motivation and greater surface learning after two years of follow up. However, only digital dependence was a predictor of worse mental health (anxiety, depression, and stress) and worse quality of life. Conclusion: Greater use of smartphones and high addiction scores were associated with worse educational outcomes. Digital dependence was another marker of outcomes in mental health and quality of life. It is important that educators are aware of these negative effects and can guide students on the proper and safe use of these devices.

A scoping review and evaluation of instruments used to measure resilience among post-secondary students

As mental health problems continue to increase among post-secondary populations, the need to develop effective initiatives designed to bolster students' resilience has increasingly been identified as a priority. Therefore, access to valid tools with which to measure the efficacy of these interventions is imperative. To date, a comprehensive assessment of existing instruments used to evaluate the construct of resilience among post-secondary student populations has not been conducted. The purpose of this study was to fill this gap by conducting a scoping review of literature detailing the use of resilience instruments and evaluating their quality based on suitability for use in the post-secondary setting and associated psychometric evidence. We identified a total of 78 records published between 2010 and 2022, extracting a total of 12 instruments. Using detailed criteria frameworks, each instrument was assessed in terms of suitability and quality of associated psychometric evidence for validity and reliability. The results of our study suggest that many of the instruments currently being used to assess resilience among post-secondary students may not be appropriate. The majority of the instruments included in our review were developed for use among general adult populations and not specifically designed for use in the post-secondary setting. Most instruments did not assess resilience in a comprehensive, holistic matter that addressed the ability to bounce back from adversity by drawing upon psychological, social, cultural, and environmental resources, as defined by recent research. Further, no instruments included in our review had published evidence in support of a complete psychometric analysis. The results of our evaluation suggest that the Connor-Davidson Resilience Scale (CD-RISC) is the most suitable instrument for measuring resilience among post-secondary populations due to its suitability, comprehensive assessment of the construct of resilience, and demonstrably strong psychometric properties for both the 25- and 10-item versions of the tool.

Prevalence of smartphone addiction among Asian medical students: A meta-analysis of multinational observational studies

BACKGROUND

High prevalence of smartphone addiction among medical students may contribute to adverse physical and mental health outcomes.

AIM

To estimate the prevalence of smartphone addiction, and explore the influencing factors and related mental health symptoms of smartphone addiction among Asian medical students.

DESIGN

Systematic review and meta-analysis.

METHODS

PubMed (MEDLINE), the Cochrane Central Register of Controlled Trials, and EMBASE were searched for relevant literature from the inception to September 10, 2021. Using Stata software 11.0, the meta-analysis of prevalence and the influencing factors of smartphone addiction were determined with 95% confidence intervals.

RESULTS

Nineteen articles, published between 2014 and 2019, were included, producing medical student studies from seven different Asian countries. The included studies were conducted in India (n = 11) and Malaysia (n = 3), with China, Saudi Arabia, Turkey, Nepal, and Iran each contributing one study. Among a total of 5,497 medical students, the participants included 3,214 females, of whom 2,181 were medical students with smartphone addiction. The prevalence of smartphone addiction among Asian medical students was 41.93% (95% CI [36.24%, 47.72%]). The influencing factors of smartphone addiction among medical students included gender, duration of smartphone use, smartphone function, and marital status. Ten studies (52.63%) explored related mental health symptoms of smartphone addiction among Asian medical students. Smartphone addiction was positively correlated with poor sleep quality (r = .17-.31), stress (r = .30-.40), anxiety, depression, neuroticism, and general health among Asian medical students.

CONCLUSION

Smartphone addiction is highly prevalent among Asian medical students. Smartphone addiction may adversely affect mental health, resulting in sleep disturbance, stress, anxiety, depression, and neuroticism. It is necessary to take appropriate precautionary actions and interventions to prevent smartphone overuse among medical students.

A systematic review and meta-analysis of discrepancies between logged and self-reported digital media use

There is widespread public and academic interest in understanding the uses and effects of digital media. Scholars primarily use self-report measures of the quantity or duration of media use as proxies for more objective measures, but the validity of these self-reports remains unclear. Advancements in data collection techniques have produced a collection of studies indexing both self-reported and log-based measures. To assess the alignment between these measures, we conducted a pre-registered meta-analysis of this research. Based on 106 effect sizes, we found that self-reported media use correlates only moderately with logged measurements, that self-reports were rarely an accurate reflection of logged media use and that measures of problematic media use show an even weaker association with usage logs. These findings raise concerns about the validity of findings relying solely on self-reported measures of media use.

Smartphone Addiction and Quality of Sleep among Indian Medical Students

Background: Smartphone is an indispensable miracle of artificial intelligence in the hands of global netizens. Medical students overburdened and sleep-deprived due to the curricular demands can have serious health effects due to further sleep deprivation caused by problematic smartphone use, affecting their work proficiency as practicing physicians. This study aimed to evaluate the association of smartphone addiction and quality of sleep among medical students across all semesters, along with other background variables.Methodology: This cross-sectional study was conducted on 224 medical students of a tertiary care teaching hospital in North India using a self-administered questionnaire with four parts -Socio-demographic characteristics, General health questionnaire (GHQ-12), Smartphone addiction scale-short version (SAS-SV), and Pittsburgh sleep quality index (PSQI).Results: The prevalence of smartphone addiction is was found out to be 33.33% in females and 46.15% in males. In the study, 63.39% were poor sleepers as assessed by their PQSI scores, and 62.05% reported poor health status as per their GHQ scores. There was a positive correlation between overall PQSI scores and smartphone use duration per day, SAS-SV scores, and GHQ scores.Conclusion: The high prevalence of excessive smartphone usage among medical students is a cause for concern and is detrimental to their health and sleep quality. The research addresses current lacunae in correlating smartphone addiction with smartphone usage before sleeping and right after waking up. Risky behavior adoption and pervasive mood changes associated with excessive smartphone use are addressed with equal representation across semesters. The study recommends increasing self-awareness for help-seeking to regulate smartphone usage and providing counseling services for students in their formative years.

The association between the Big Five personality traits and smartphone use disorder: A meta-analysis

BACKGROUND AND AIMS

Personality is one of the most frequently investigated variables to shed light on the putatively addictive use of the smartphone. By investigating associations between personality and individual differences in addictive smartphone use, researchers aim to understand if some personality traits predispose technology users to develop addictive behaviors. Here, based on existing empirical literature, we aimed at determining the strength of associations between Big Five personality traits and smartphone use disorder (SmUD) by a meta-analytic approach.

METHOD

For each Big Five personality trait, we performed a meta-analysis of correlations representing their association with SmUD. We also investigated possible publication bias and the moderating effects of age, gender, nationality, length of personality assessments, and time of publication.

RESULTS

We found n = 26 eligible studies. In line with both the Interaction of Person-Affect-Cognition-Execution (I-PACE) model and the framework on problematic mobile-phone use by Billieux, we observed a positive association between Neuroticism and SmUD (r = 0.25), while the association between Extraversion and SmUD was not significant. Partially in line with the aforementioned theoretical frameworks, Conscientiousness was negatively associated with SmUD (r = -0.16). Remaining traits showed smaller associations. No significant publication bias emerged. Moderator analyses showed that time of publication moderated the link between Conscientiousness and SmUD. Moreover, Agreeableness and Conscientiousness showed a heightened inverse association with SmUD among older samples.

CONCLUSIONS

The present meta-analysis provides robust empirical evidence that Big Five personality traits can help to understand individual differences in SmUD, supporting the usefulness of their assessment when planning and targeting interventions aimed at at-risk individuals.

Passive objective measures in the assessment of problematic smartphone use: A systematic review

Research focussing on problematic smartphone use has predominantly employed psychometric tests which cannot capture the automatic processes and behaviours associated with problematic use. The present review aimed to identify passive objective measures that have been used or developed to assess problematic smartphone use. A systematic search was conducted using Web of Science, Scopus, PsychInfo and PubMed databases to identify passive objective measures that have been employed to assess problematic smartphone use, resulting in 18 studies meeting the inclusion criteria. Objective data that were monitored predominantly focussed on general screen usage time and checking patterns. Findings demonstrate that passive monitoring can enable smartphone usage patterns to be inferred within a relatively short timeframe and provide ecologically valid data on smartphone behaviour. Challenges and recommendations of employing passive objective measures in smartphone-based research are discussed.

Prevalence and Correlates of Excessive Smartphone Use among Medical Students: A Cross-sectional Study

BACKGROUND

Increasing smartphone use has led to the introduction of smartphone addiction as a behavioral addiction with detrimental effects on health. This phenomenon has not been widely studied in the Indian context. This study assessed the rate of smartphone addiction in a sample of medical students, with a focus on its correlation with sleep quality and stress levels.

METHODS

A cross-sectional study was conducted between November 2016 and January 2017 in 195 medical students. Their smartphone use, level of smartphone addiction, sleep quality, and perceived stress levels were measured using the Smartphone Addiction Scale-Short Version (SAS-SV), the Pittsburgh Sleep Quality Index (PSQI), and the Perceived Stress Scale (PSS-10), respectively.

RESULTS

Of the 195 students, 90 (46.15%) had smartphone addiction as per the scale. A self-reported feeling of having smartphone addiction, use of the smartphone right before sleeping, PSS scores, and PSQI scores were found to be significantly associated with the SAS-SV scores. Significant positive correlations were observed between the SAS-SV and PSS-10 scores, and the SAS-SV and PSQI scores.

CONCLUSIONS

There is a high magnitude of smartphone addiction in medical students of a college in Western Maharashtra. The significant association of this addiction with poorer sleep quality and higher perceived stress is a cause for concern. The high self-awareness among students about having smartphone addiction is promising. However, further studies are required to determine whether this self-awareness leads to treatment seeking. Further studies are required to explore our finding of the association of smartphone addiction with using the smartphone before sleeping.

Transitions in smartphone addiction proneness among children: The effect of gender and use patterns

OBJECTIVES

This study assessed the incidence of transitions in smartphone addiction proneness (SAP) among children and examined the effects of gender, use patterns (social networking sites (SNSs) use and smartphone gaming) and depression on smartphone addiction transitions.

METHODS

A representative sample of 2,155 children from Taipei completed longitudinal surveys in both 2015 (5th grade) and 2016 (6th grade). Latent transition analysis (LTA) was used to characterize transitions in SAP and to examine the effects of gender, use patterns and depression on SAP transitions.

RESULTS

LTA identified four latent statuses of SAP: about half of the children were in non-SAP status, one-fifth were in tolerance status, one-sixth were in withdrawal status, and one-seventh were in high-SAP status. Both boys and girls had a higher prevalence of high-SAP and tolerance in 6th grade than in 5th grade, whereas in both grades boys had a higher prevalence of high-SAP and withdrawal, and girls had a higher prevalence of non-SAP and tolerance. Controlling for parents' education, family structure, and household income, higher use of SNSs by children, increasing use of mobile gaming and higher levels of depression were individually associated with increased odds of being in one of the three SAP statuses other than non-SAP. When all three covariates were jointly entered into the model, usage of SNSs and depression remained significant predictors.

CONCLUSION

Both boys and girls tended to transition to tolerance or high-SAP statuses, while children's depression and their usage of SNSs increased the risk of smartphone addiction.

An Innovative, Unobtrusive Approach to Investigate Smartphone Interaction in Nonaddicted Subjects Based on Wearable Sensors: A Pilot Study

Background and objectives: Smartphones are playing a pivotal role in everyday life, due to the opportunity they grant in terms of simplifying communication, entertainment, education and many other daily activities. Against such positive characteristics, smartphone interaction can result, in particular cases, in dangerous smartphone addiction patterns, possibly leading to several long-term detrimental psychophysiological conditions. Therefore, this pilot aims at assessing the feasibility of using an innovative approach, based on unobtrusive wearable sensors, used for the first time in this specific topic, and psychological questionnaires, to investigate the links between stress and emotions in a group of young, nonaddicted individuals performing smartphone interaction. Materials and methods: 17 volunteers were enrolled for the present study. The study protocol was divided into three phases, with an initial resting state (baseline) of three minutes, a smartphone interaction session (task) of the same length, and a final resting state (recovery), lasting three minutes. In the overall procedure, electrocardiogram (ECG) and galvanic skin response (GSR) measurements, both monitored by wearable sensors, were acquired in order to assess the functioning of the autonomic nervous system (ANS). Results: A significant decrease was seen in pNN50 during the smartphone interaction with respect to the baseline (Z = −2.675, p = 0.007), whereas the Low-to-High Frequency (LF/HF) ratio at task was somewhat correlated with phubbing behaviors (r = 0.655, p = 0.029), assessed through dedicated questionnaires. Conclusions: Taken together with the slight changes in GSR data, such results suggest the feasibility of this approach to characterize the ANS activation during smartphone interaction among young individuals. Further studies should enlarge the study population and involve smartphone-addicted subjects in order to increase the scientific and clinical relevance of such findings.