The predictive value of supervised machine learning models for insomnia symptoms through smartphone usage behavior.

Introduction: Digital phenotyping can be an innovative and unobtrusive way to improve the detection of insomnia. This study explores the correlations between smartphone usage features (SUF) and insomnia symptoms and their predictive value for detecting insomnia symptoms. Methods: In an observational study of a German convenience sample, the Insomnia Severity Index (ISI) and smartphone usage data (e.g., time the screen was active, longest time the screen was inactive in the night) for the previous 7 days were obtained. SUF (e.g., min, mean) were calculated from the smartphone usage data. Correlation analyses between the ISI and SUF were conducted. For the specification of the machine learning models (ML), 80 % of the data was allocated to training, 20 % to testing, and five-fold cross-validation was used. Six algorithms (support vector machine, XGBoost, Random Forest, k-Nearest-Neighbor, Naive Bayes, and Logistic Regressions) were specified to predict ISI scores ≥15. Results: 752 participants (51.1 % female, mean ISI = 10.23, mean age = 41.92) were included in the analyses. Small correlations between some of the SUF and insomnia symptoms were found. In the ML models, sensitivity was low, ranging from 0.05 to 0.27 in the testing subsample. Random Forest and Naive Bayes were the best-performing algorithms. Yet, their AUCs (0.57, 0.58 respectively) in the testing subsample indicated a low discrimination capacity. Conclusions: Given the small magnitude of the correlations and low discrimination capacity of the ML models, SUFs, as measured in this study, do not appear to be sufficient for detecting insomnia symptoms. Further research is necessary to explore whether examining intra-individual variations and subpopulations or employing alternative smartphone sensors yields more promising outcomes.

Problematic social media use in childhood and adolescence.

At the time of writing, about 4.59 billion people use social media with many adolescents using their social media accounts across a myriad of applications and platforms. According to recent statistics, in 2022 individuals spent an average of 151 minutes on social media each day, illustrating the global relevance of social media (Dixon, 2022a,b). One of the pressing questions, internationally, is whether social media use is harmful and/or addictive. This question is of particular importance because many teenagers - and younger adolescents - spend considerable time on these platforms, which have increasingly become an integral part of their lives. Moreover, considering lifespan development, adolescents may be particularly vulnerable to specific features and advertisements shown to them on social media platforms. Growing prevalence of poor mental health in young people has led to recent recommendations in the United States to routinely screen for anxiety in 8-18 year olds, and for depression and suicide risk for adolescents between 12-18 years of age (US Preventive Services Task Force et al., 2022 a,b) - the conditions often accompanying problematic social media use. The present work not only provides insights into the current state of the literature but provides also recommendations.

A Bifactor Evaluation of Self-Report and Clinician-Administered Measures of PTSD in Veterans.

The PTSD Checklist for DSM-5 (PCL-5) and the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5) are two of the most widely used and well-validated PTSD measures providing total and subscale scores that correspond with DSM-5 PTSD symptoms. However, there is little information about the utility of subscale scores above and beyond the total score for either measure. The current study compared the proposed DSM-5 four-factor model to a bifactor model across both measures using a sample of veterans (N = 1,240) presenting to a Veterans Affairs (VA) PTSD specialty clinic. The correlated factors and bifactor models for both measures evidenced marginal-to-acceptable fit and were retained for further evaluation. Bifactor specific indices suggested that both measures exhibited a strong general factor but weak lower-order factors. Structural regressions revealed that most of the lower-order factors provided little utility in predicting relevant outcomes. Although additional research is needed to make definitive statements about the utility of PCL-5 and CAPS-5 subscales, study findings point to numerous weaknesses. As such, caution should be exercised when using or interpreting subscale scores in future research.

On fear of missing out, social networks use disorder tendencies and meaning in life.

Much research has been conducted on the association between social networks use disorder tendencies (SNUD; i.e. problematic social media use) and well-being. In more detail, a meta-analysis and further research suggest an inverse association between higher SNUD tendencies and lower well-being. In existing studies on social media use and well-being, this association has often been investigated by asking participants about their life satisfaction and/or emotional well-being. A path that has only recently been used to shed further light on SNUD tendencies is the assessment of meaning in life. Against this background, the present study aimed to investigate both the search for and presence of meaning in life in the context of SNUD tendencies in 955 participants. To the best of our knowledge and beyond what has been mentioned, this study is the first to investigate the links between meaning in life variables and state/trait fear of missing out (FoMO), with FoMO being a critical variable known to be linked to the overuse of digital technologies. In a structural equation model, we observed that associations between FoMO and meaning in life variables was mediated by SNUD tendencies. Although the present study is of cross-cultural nature and cannot establish causality, it might be the case that proneness to FoMO might trigger SNUD tendencies and as a consequence, results in more search for meaning in life, while hindering presence of meaning in life.

Biased processing of game-related information in problematic mobile gaming users.

Background and aims: The present study investigated processing bias for game-related cues in problematic mobile gamers (PMGs) under or above the threshold of conscious awareness. Methods: In Experiment 1, all participants (20 PMGs and 23 casual players (CPs)) finished a masked visual probe task during a brief (17ms) masked exposure condition. In Experiment 2, an unmasked visual probe task was conducted by an additional forty participants (20 PMGs and 20 CPs) at two exposure durations (200 and 500ms). Results: Results showed that PMGs, but not CPs, had an attentional bias for game-related cues which had been presented with two exposure durations (17 and 200ms). Discussion and conclusion: In conclusion, the present study provides evidence that bias in PMGs could be observed both preconsciously and consciously. The results are discussed with reference to incentive sensitization theory and automatic action schema theory.

Emotion dysregulation factors associated with problematic smartphone use severity: The mediating role of fear of missing out.

Based on current theoretical frameworks, there has been increasing research examining psychopathology leading to problematic smartphone use (PSU). However, less is known about the affective and cognitive processes linked to PSU. The present study aimed at analyzing the fear of missing out (FoMO) as a mediator in the association between emotion dysregulation and PSU severity. Participants were 343 U.S. undergraduate students (64.7  % female, Mage = 19.3, SD = 2.51) who completed online measures of emotion dysregulation, FoMO and PSU. A fully latent structural equation model was analyzed. Results indicate greater impulse control dysregulation was associated with heightened PSU via increased FoMO. Our findings present evidence suggesting emotion dysregulation and FoMO as affective and cognitive mechanisms associated with PSU, with FoMO serving a mediating role between impulse control and PSU severity. Clinical implications are discussed.

Predicting Big Five personality traits from smartphone data: A meta-analysis on the potential of digital phenotyping.

OBJECTIVE: Since the first study linking recorded smartphone variables to self-reported personality in 2011, many additional studies have been published investigating this association. In the present meta-analyses, we aimed to understand how strongly personality can be predicted via smartphone data. METHOD: Meta-analytical calculations were used to assess the association between smartphone data and Big Five traits. Because of the lack of independence of many included studies, analyses were performed using a multilevel approach. RESULTS: Based on data collected from 21 distinct studies, extraversion showed the largest association with the digital footprints derived from smartphone data (r = .35), while remaining traits showed smaller associations (ranging from 0.23 to 0.25). For all traits except neuroticism, moderator analyses showed that prediction performance was improved when multiple features were combined together in a single predictive model. Additionally, the strength of the prediction of extraversion was improved when call and text log data were used to perform the prediction, as opposed to other types of smartphone data CONCLUSIONS: Our synthesis reveals small-to-moderate associations between smartphone activity data and Big Five traits. The opportunities, but also dangers of the digital phenotyping of personality traits based on traces of users' activity on a smartphone data are discussed.

Is Nomophobia Problematic or Functional? A Perspective from Bifactor Structure.

With the extensive use of mobile phones globally, some people engage in excessive or problematic phone use behaviors. However, little is known regarding the latent structure of problematic mobile phone use. The current study employed the Chinese versions of the Nomophobia Questionnaire, Mobile Phone Addiction Tendency Scale, and Depression-Anxiety-Stress Scale-21 to explore the latent psychological structure of problematic mobile phone use and nomophobia and their associations with mental health symptoms. Results showed that a bifactor latent model best fit nomophobia, which contained a general factor and four unique factors involving the fear of being unable to access information, losing convenience, losing contact, and losing one's Internet connection. Results also showed significant correlations among latent factors of nomophobia, problematic mobile phone use, and mental health symptoms. Through these findings, we can conclude that two problematic mobile phone use behaviors share a common factor concerning excessive use, and nomophobia has independent unique factors concerning usable function. This study clarifies the structure of problematic mobile phone use, and it implies that we can distinguish problematic mobile phone use from functional use; further investigation of problematic mobile phone use is warranted.

Symptoms of internet gaming disorder and depression in Chinese adolescents: A network analysis.

The current study aimed to investigate comorbidity among symptoms of depression and internet gaming disorder (IGD) utilizing symptom network analysis in a sample of Chinese adolescents. A total of 1,362 Chinese adolescents (Mean age = 15.19 ± 1.67; range 13-21; 39.79% female, 56.02% male, 4.19% not disclosed) were recruited from 11 local secondary schools between June and July 2020. Symptoms of depression and IGD were assessed by the 7-item DASS-21 depression subscale and the 9-item Internet Gaming Disorder Scale. We conducted network analysis to estimate network models and the most central symptoms of depression and IGD and computed a combined network model of both depression and IGD symptoms to find bridge symptoms and illustrate the comorbidity between depression and IGD. We found that feeling 'Worthless', 'Meaningless', and 'Down-hearted' were identified as the most central symptoms of depression, whereas 'Preoccupation' and 'Tolerance' were the two most central symptoms of IGD. The bridge symptoms in the combined network model were 'Gaming for escape or mood relief' from the IGD cluster and 'No initiative' and 'Down-hearted" from the depression cluster. The current study was the first to investigate the relationship between depression and IGD symptoms among adolescents utilizing a symptom network perspective. Also, it highlighted key bridge symptoms in understanding how IGD and depression contribute to each other.

Early self-reported post-traumatic stress symptoms after trauma exposure and associations with diagnosis of post-traumatic stress disorder at 3 months: latent profile analysis.

BACKGROUND: Trauma exposure can cause post-traumatic stress symptoms (PTSS), and persistently experiencing PTSS may lead to the development of post-traumatic stress disorder (PTSD). Research has shown that PTSS that emerged within days of trauma was a robust predictor of PTSD development. AIMS: To investigate patterns of early stress responses to trauma and their associations with development of PTSD. METHOD: We recruited 247 civilian trauma survivors from a local hospital emergency department. The PTSD Checklist for DSM-5 (PCL-5) and Acute Stress Disorder Scale (ASDS) were completed within 2 weeks after the traumatic event. Additionally, 3 months post-trauma 146 of these participants completed a PTSD diagnostic interview using the Clinician Administered PTSD Scale for DSM-5. RESULTS: We first used latent profile analysis on four symptom clusters of the PCL-5 and the dissociation symptom cluster of the ASDS and determined that a four-profile model ('severe symptoms', 'moderate symptoms', 'mild symptoms', 'minimal symptoms') was optimal based on multiple fit indices. Gender was found to be predictive of profile membership. We then found a significant association between subgroup membership and PTSD diagnosis (χ2(3) = 11.85, P < 0.01, Cramer's V = 0.263). Post hoc analysis revealed that this association was driven by participants in the 'severe symptoms' profile, who had a greater likelihood of developing PTSD. CONCLUSIONS: These findings fill the knowledge gap of identifying possible subgroups of individuals based on their PTSS severity during the early post-trauma period and investigating the relationship between subgroup membership and PTSD development, which have important implications for clinical practice.

Relations between anxiety sensitivity's cognitive concerns and anxiety severity: brooding and reflection as serial multiple mediators.

The outbreak of COVID-19 has caused a major impact on productivity and life functioning, and also led to adverse emotional reactions. In the face of this public health event, increased anxiety is one of the most common emotional reactions. Previous studies have shown that anxiety sensitivity, rumination and anxiety are closely related. Various dimensions of anxiety sensitivity have different effects on anxiety. Also, rumination can be divided into brooding and reflection. To explore the relationships among anxiety sensitivity's cognitive concerns, anxiety and different types of rumination, we conducted an online survey during the outbreak of coronavirus (February 17-25, 2020), using the Anxiety Sensitivity Scale-3 (ASI-3), Ruminative Responses Scale (RSS), and Depression Anxiety Stress Scale-21 (DASS-21). The results showed significant positive correlations among anxiety sensitivity's cognitive concerns, anxiety, brooding and reflection. Furthermore, brooding and reflection had a chain mediation effect between cognitive concerns and anxiety, and the mediation effect of reflection was even stronger. Results suggest that anxiety sensitivity's cognitive concerns may not only affect anxiety directly, but also affect anxiety through rumination, especially reflection.

Attentional bias to threat is modulated by stimulus content: an fNIRS study.

People are evolutionarily predisposed to associate threat relevant stimuli with fear or aversiveness and show an attentional bias toward threat. Attentional bias modification (ABM) has been shown to reduce threat biases, while quantitative reviews assessing the effectiveness of bias modification yielded inconsistent results. The current study examined the relationship between the training effect of attentional bias to threat and the type of threatening stimuli. Twenty-two participants performed a modified dot-probe task while undergoing functional near-infrared spectroscopy (fNIRS) imaging. Results indicated that there was a strong pattern of attentional avoidance among individuals in an animal but not human threat condition. Furthermore, findings from fNIRS confirmed that the influence from type of threatening stimulus would be modulated by cortical activation patterns, especially in the ventrolateral prefrontal cortices (vlPFC) and angular gyrus. Overall, these results suggest that stimulus-specific may play a major role in personalization of specific psychological interventions.

The Effect of Cognitive-Affective Factors on PTSD and Alcohol Use Symptoms: An Investigation on Rumination, Suppression, and Reappraisal.

Background: Posttraumatic stress disorder (PTSD) and alcohol use disorder (AUD) are mental health conditions that often co-occur. The complexity of this comorbidity is well-documented, though the role of malleable cognitive-affective factors in PTSD/AUD warrants further study. Specifically, attaining a more comprehensive understanding of the role of malleable cognitive-affective factors in individuals with symptoms of PTSD/AUD may have important implications for future research, such as in treatment-seeking individuals. Extant examinations of cognitive-affective factors have demonstrated unique associations of cognitive reappraisal, expressive suppression, and rumination in PTSD symptom severity, though these effects had yet to be explored in subgroups of comorbid PTSD/AUD.Methods: In a sample of trauma-exposed individuals (n = 334) recruited to participate through an internet labor market, we first empirically examined latent subgroups of PTSD/AUD symptoms using latent profile analysis, then included expressive suppression, cognitive reappraisal, and four dimensions in the model to elucidate their role in specific profile patterns of PTSD/AUD symptom typologies.Results: Our results support a four-class model of PTSD/AUD symptoms, with unique predictive effects of expressive suppression, problem-focused thoughts, repetitive thoughts, and anticipatory thoughts on latent profile status.Conclusions: These findings may have important implications for future research focused on examining cognitive-affective patterns as they apply to intervention techniques in treatment-seeking individuals with symptoms of PTSD/AUD.

Temporal trends in health worker social media communication during the COVID-19 pandemic.

During the COVID-19 pandemic, healthcare professionals are exposed to extreme hazards and workplace stressors. Social media postings by physicians and nurses related to COVID-19 from January 21 to June 1, 2020 were obtained from the Reddit website. Topic modeling via Latent Dirichlet Allocation (LDA) using a machine-learning approach was performed on 1723 documents, each posted in a unique Reddit discussion. We selected the optimal number of topics using a heuristic approach based on examination of the rate of perplexity change (RPC) across LDA models. A two-step multiple linear regression was done to identify differences across time and between nurses versus physicians. Prevalent topics included excessive workload, positive emotional expression and collegial support, anger and frustration, testing positive for COVID-19 and treatment, use of personal protective equipment, impacts on healthcare jobs, disruption of medical procedures, and general healthcare issues. Nurses' posts initially reflected concern about workload, personal danger, safety precautions, and emotional support to their colleagues. Physicians posted initially more often than nurses about technical aspects of the coronavirus disease, medical equipment, and treatment. Differences narrowed over time: nurses increasingly made technical posts, while physicians' posts increasingly were in the personal domain, suggesting a convergence of the professions over time.

Examining relationships between posttraumatic stress disorder severity and types of media/technology usage.

OBJECTIVE: Psychopathology, cyberpsychology, and mass media theories link psychological symptoms, such as posttraumatic stress disorder (PTSD), to increased media and technology usage (MTU). Given limited research in this area, we uniquely examined if specific MTU facets were associated with PTSD symptom severity. METHOD: A sample of 404 socioeconomically diverse adults (Mage = 35.89; 57.4% female) was recruited from Amazon's Mechanical Turk and completed the Life Events Checklist for DSM-5, Posttraumatic Stress Disorder Checklist for DSM-5, Media and Technology Usage and Attitudes Scale, and Patient Health Questionnaire-9. RESULTS: Hierarchical multiple regression analyses indicated that, controlling for depression severity, greater frequency of TV viewing (p = .004) and media sharing (p = .040) and greater quantity of online friendships (p = .006) were associated with greater PTSD symptom severity. CONCLUSION: Study findings suggest that the extent of MTU behaviors (especially extent of TV use, media sharing, and online friendships) are important to examine in trauma-exposed individuals with PTSD symptoms. Results generalize to trauma-exposed community members and are considered within the context of current MTU theories. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The relationship between adolescent emotion dysregulation and problematic technology use: Systematic review of the empirical literature.

Background and aims: We aimed to systematically identify, evaluate and summarize the research on adolescent emotion dysregulation and problematic technology use. We critically appraise strengths and limitations and provide recommendations for future research. Methods: We followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and conducted a systematic review of published original reports on adolescent emotion dysregulation and problematic technology use published until March 1, 2022. A thorough search preceded the selection of studies matching prespecified criteria. Strengths and limitations of selected studies, regarding design and reporting, were identified based on current best practices. Results: 39 studies met inclusion criteria. All of these studies provided on the relationship between adolescent emotion dysregulation and problematic technology use severity based on self-report data. Discussion: There was a positive correlation between adolescent emotion dysregulation and the severity of problematic technology use. Beyond this, other variables (such as anxiety, depression, self-esteem, etc.) were also closely related to emotion dysregulation and problematic technology use. Such studies are of importance to better understand cause-effect relations regarding both variables.

DSM-5 Posttraumatic Stress Disorder Symptoms in Nonclinical Samples of Chinese and Pakistani Trauma-Exposed Adults: Factor Structure and Invariance Across Culture.

ABSTRACT: The purpose of the current study was to examine the latent structure and cross-cultural measurement validity of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) posttraumatic stress disorder (PTSD) symptoms assessed by the PTSD Checklist for DSM-5. Participants comprised trauma-exposed Chinese and Pakistani undergraduate students (N = 495 and N = 186, respectively). Confirmatory factor analysis (CFA) indicated that a seven-factor hybrid model involving intrusion, avoidance, negative affect, anhedonia, externalizing behaviors, anxious arousal, and dysphoric arousal factors provided good fit in both samples. This model fit significantly better than three alternative models including the DSM-5 four-factor model and six-factor anhedonia and externalizing behaviors models. The subsequent multigroup CFA showed that the best-fitting hybrid model demonstrated cross-cultural measurement invariance. Our findings provide further empirical support for the seven-factor PTSD hybrid model and its cross-cultural invariance, and have implications for understanding and application of DSM-5's PTSD symptoms.

Exploring subtypes and correlates of internet gaming disorder severity among adolescents during COVID-19 in China: A latent class analysis.

The WHO recently included Gaming Disorder as a psychiatric diagnosis. Whether there are distinct groups of adolescents who differ based on severity of gaming disorder and their relationships with other mental health and addictive behavior outcomes, including problematic smartphone use (PSU), remains unclear. The current study explored and identified subtypes of Internet Gaming Disorder (IGD) severity and estimated the association between these subtypes and other disorders. Participants completed online questionnaires assessing the severity of IGD, PSU, depression, and anxiety during COVID-19. We conducted a latent class analysis of IGD symptoms among 1,305 Chinese adolescents (mean age = 15.2; male = 58.5%) from 11 secondary schools in Macao (SAR), China. Multinomial logistic regression estimated correlates of latent class membership and PSU. A 4-class model adequately described the sample subgroups. Classes were labeled as normative gamers (30.9%), occasional gamers (42.4%), problematic gamers (22.7%), and addictive gamers (4.1%). Relative to normative gamers, PSU severity, depression, and being male were significantly higher among problematic gamers, addictive gamers, and occasional gamers. Only problematic gamers showed significant positive associations with anxiety severity compared to the other groups. The study revealed the differences in severity of gaming disorder and its association with psychopathology outcomes. Application in screening for IGD and comorbidity is discussed. Supplementary Information: The online version contains supplementary material available at 10.1007/s12144-022-03133-8.

Hyperinsulinemia Associated Depression.

Hyperinsulinemia promotes fat accumulation, causing obesity. Being an inflammatory state, obesity can induce further inflammation and is a risk factor for HPA (hypothalamic pituitary axis) dysregulation through hypercortisolism-related hyperglycemia. In another hypothesis, the sympathetic nervous system (SNS) plays a significant role in the regulation of hormone secretion from the pancreas such as an increase in catecholamines and glucagon as well as a decrease in plasma insulin levels, a disruption on SNS activity increases insulin levels, and induces glycogenolysis in the liver and lipolysis in adipose tissue during hypoglycemia. Hyperglycemia-hyperinsulinemia exacerbates inflammation and increases the oxidative stress along with regulating the levels of norepinephrine in the brain sympathetic system. Increased inflammatory cytokines have also been shown to disrupt neurotransmitter metabolism and synaptic plasticity which play a role in the development of depression via inhibiting serotonin, dopamine, melatonin, and glutamate signaling. An increased level of plasma insulin over time in the absence of exercising causes accumulation of lipid droplets in hepatocytes and striated muscles thus preventing the movement of glucose transporters shown to result in an increase in insulin resistance due to obesity and further culminates into depression. Further hyperinsulinemia-hyperglycemia condition arising due to exogenous insulin supplementation for diabetes management may also lead to physiological hyperinsulinemia associated depression. Triple therapy with SSRI, bupropion, and cognitive behavioral therapy aids in improving glycemic control, lowering fasting blood glucose, decreasing the chances of relapse, as well as decreasing cortisol levels to improve cognition and the underlying depression. Restoring the gut microbiota has also been shown to restore insulin sensitivity and reduce anxiety and depression symptoms in patients.