Search Results (230)

Smartphones have revolutionized our daily lives, becoming portable pocket computers with easy internet access. India, the second-highest smartphone and internet user, experienced a significant rise in smartphone usage between 2013 and 2024. Prolonged smartphone use, exceeding 20 min at a time, can lead to physical and mental health issues, including psychophysiological disorders. Digital devices and their extended exposure to blue light cause digital eyestrain, sleep disorders and visual-related problems. This research examines the impact of 1 h smartphone usage on visual fatigue among young Indian adults. A portable, low-cost system has been developed to measure visual activity to address this. The developed visual activity measurement system measures blink rate, inter-blink interval, and pupil diameter. Measured eye activity was recorded during 1 h smartphone usage of e-book reading, video watching, and social-media reels (short videos). Social media reels show increased screen variations, affecting pupil dilation and reducing blink rate due to continuous screen brightness and intensity changes. This reduction in blink rate and increase in inter-blink interval or pupil dilation could lead to visual fatigue. Full article

Background/Objectives: In an increasingly pervasive digital environment, trait boredom has been identified as a key psychological factor in the onset and maintenance of problematic digital technology use. This systematic review aims to investigate the role of trait boredom in digital behavioral addictions, including problematic smartphone use, Internet and social media overuse, and gaming addiction, through theoretical models such as the I-PACE model and the Compensatory Internet Use Theory (CIUT). Methods: A systematic literature search was conducted across multiple scientific databases (PsycINFO, Web of Science, PubMed, and Scopus), yielding a total of 4603 records. Following the PRISMA guidelines after duplicate removal and screening based on title and abstract, 152 articles were assessed for full-text eligibility, and 28 studies met the predefined inclusion and exclusion criteria and were included in the final review. Results: Findings reveal that trait boredom functions as both a direct and indirect factor in problematic technology use. It serves as a mediator and moderator in the relationship between psychological vulnerabilities (e.g., depression, alexithymia, vulnerable narcissism) and dysfunctional digital behaviors. Furthermore, as an independent variable, it has an influence on technological variables through Fear of Missing Out (FoMO), loneliness, low self-regulation, and dysfunctional metacognitions, while protective factors such as mindfulness and attentional control mitigate its impact. Conclusions: Boredom represents a central psychological lever for understanding behavioral addictions in the digital age and should be considered a key target in preventive and therapeutic interventions focused on enhancing self-regulation and meaningful engagement with free time. Full article

Current technological development has made the Internet and new technologies increasingly present in people’s lives, expanding their opportunities but also potentially posing risks for dysfunctional use. This study aims to identify psychopathological factors associated with dysfunctional ICT use, extending the evidence beyond the well-established relationships with mood disorders to include personality disorders (i.e., cluster C in particular). A total of 711 participants (75.70% female; Mage = 28.33 years, SD = 12.30) took part in the data collection. Firstly, the results showed positive correlations between higher levels of addictive patterns for the Internet, social networks, smartphones and applications, and video games and higher levels of borderline symptoms as assessed by the Borderline Symptom List 23—Short Version. Moreover, scores reflecting high addictive patterns also positively correlated with general narcissistic traits as indicated by the total score of the Narcissistic Personality Inventory 13—Short Version and those specifically described by its Entitlement/Exploitativeness dimension, as well as with higher levels of almost all the personality traits assessed by the Personality Inventory for DSM 5—Brief Form (i.e., negative affectivity, detachment, disinhibition, and psychoticism). These findings broaden the still scarce body of evidence on the relationship between personality disorders and dysfunctional ICT use, which, however, needs to be further explored. Full article

Background and Objectives: Excessive social media use is repeatedly linked to negative body image outcomes, yet its association with muscle dysmorphia, especially in athletic youth, remains underexplored. We investigated how social media exposure, comparison behavior, and platform engagement relate to muscle dysmorphia symptomatology in young German athletes. Materials and Methods: An anonymous, web-based cross-sectional survey was conducted (July–October 2024) of 540 individuals (45% female; mean age = 24.6 ± 5.3 years; 79% ≥ 3 h sport/week) recruited via Instagram. The questionnaire comprised demographics, sport type, detailed social media usage metrics, and the validated German Muscle Dysmorphic Disorder Inventory (MDDI-1, 15 items). Correlations (Spearman’s ρ, Kendall’s τ) were calculated; multivariate importance was probed with classification-and-regression trees and CatBoost gradient boosting, interpreted via SHAP values. Results: Median daily social media time was 76 min (IQR 55–110). Participants who spent ≥ 60 min per day on social media showed higher MDDI scores (mean 38 ± 7 vs. 35 ± 6; p = 0.010). The strongest bivariate link emerged between perceived social media-induced body dissatisfaction and felt pressure to attain a specific body composition (Spearman ρ = 0.748, Kendall τ = 0.672, p < 0.001). A CatBoost gradient-boosting model out-performed linear regression in predicting elevated MDDI. The three most influential features (via SHAP values) were daily social media time, frequency of comparison with fitness influencers, and frequency of “likes”-seeking behavior. Conclusions: Intensive social media exposure substantially heightens muscle dysmorphia risk in young German athletes. Machine-learning interpretation corroborates time on social media and influencer comparisons as primary drivers. Interventions should combine social media literacy training with sport-specific psychoeducation to mitigate maladaptive comparison cycles and prevent downstream eating disorder pathology. Longitudinal research is warranted to clarify causal pathways and to test targeted digital media interventions. Full article

Background: Social media represents a unique opportunity to investigate the perspectives of people with eating disorders at scale. One forum alone, r/EatingDisorders, now has 113,000 members worldwide. In less than a day, where a manual analysis might sample a few dozen items, automatic classification using large language models (LLMs) can analyze thousands of posts. Methods: Here, we compare multiple strategies for invoking an LLM, including ones that include examples (few-shot) and annotation guidelines, to classify eating disorder content across 14 predefined themes using Llama3.1:8b on 6850 social media posts. In addition to standard metrics, we calculate four novel dimensions of classification quality: a Category Divergence Index, confidence scores (overall model certainty), focus scores (a measure of decisiveness for selected subsets of themes), and dominance scores (primary theme identification strength). Results: By every measure, invoking an LLM without extensive guidance and examples (zero-shot) is insufficient. Zero-shot had worse mean category divergence (7.17 versus 3.17). Whereas, few-shot yielded higher mean confidence, 0.42 versus 0.27, and higher mean dominance, 0.81 versus 0.46. Overall, a few-shot approach improved quality measures across nearly 90% of predictions. Conclusions: These findings suggest that LLMs, if invoked with expert instructions and helpful examples, can provide instantaneous high-quality annotation, enabling automated mental health content moderation systems or future clinical research. Full article

Objective: This study aimed to investigate the relationship between social media use (SMU) in children diagnosed with major depression (MD) or attention deficit hyperactivity disorder (ADHD) and various psychosocial factors, including familial functioning, parental SMU, and parent-reported internalizing and externalizing symptoms. A healthy control group was included for comparison. Methods: The study included 121 children and adolescents aged 10–18 years (36 with MD, 41 with ADHD, and 44 healthy controls). The Social Media Addiction Scale—Short Form (SMDS) was administered to all participants, while mothers completed the McMaster Family Assessment Scale (FAS), the Social Media Addiction Scale—Adult Form (SMAS-AF), and the Child Behavior Checklist (CBCL). Psychiatric diagnoses were made using the K-SADS-PL DSM-5-T. Correlation and linear regression analyses were used to assess associations among variables. Results: SMU scores were significantly higher in the ADHD group compared to both the depression and control groups. Parental SMU was also higher in the ADHD group. In the depression group, child SMU was significantly associated with internalizing symptoms and impaired family communication. In the ADHD group, child SMU was predicted by poor family problem-solving and communication. Regression analyses showed that internalizing symptoms and family communication predicted SMU in the depression group (R² = 0.335), while family problem-solving and communication predicted SMU in the ADHD group (R² = 0.709). Conclusion: The findings suggest that social media use in children with depression and ADHD is associated with different psychosocial factors. While internalizing symptoms and family communication are more prominent in depressed children, family functioning—particularly problem-solving and communication—plays a larger role in children with ADHD. These results emphasize the need for targeted family-based interventions to mitigate problematic SMU in clinical populations. Full article

Statistical data demonstrate a concurrent rise in smoking prevalence and mental disorders, such as depression and anxiety, which may be attributed to contemporary lifestyle factors, including social media and recent global events. This indicates a potential correlation between these trends, as individuals with mental disorders may engage in smoking as a form of self-medication to alleviate anxiety. However, smoking is harmful and increases the risk of many diseases. Therefore, smoking cessation strategies are increasingly being considered. Nicotine is a naturally produced alkaloid in plants that makes smoking so addictive. Unfortunately, the public’s lack of understanding of the effects of nicotine leads to misleading claims in the public and media about its biological effects. Thus, current narrative literature review is focused on the examination of the biological effects of organic nicotine from various angles, considering the psychological aspects of addiction and the immune system. Analysis of recent data showed that nicotine not only causes addiction but also has therapeutic benefits in certain diseases (depression, anxiety, schizophrenia) and has anti-inflammatory properties (autoimmunity, neurodegenerative diseases), and a deeper understanding and a broader approach to its effects is needed. Full article

Identifying when and which adolescents are at increased risk of developing problematic social media use (PSMU) is critical for effective prevention and early intervention. Previous research has examined risk and protective factors using theory-driven (confirmatory-explanatory) approaches, such as regression models. However, few studies have simultaneously considered personal, peer, and parent characteristics to assess their relative contributions, and none have explored how these factors are structurally interrelated using data-driven (inductive–exploratory) approaches. To address these gaps, this study combines logistic regression and psychological network analysis to examine which personal, parent, and peer factors are most relevant in identifying at-risk/problematic social media use among adolescents. Using three waves of data analyzed cross-sectionally from N = 2441 secondary school students, adolescents were classified as normative (0–1 symptoms) or at-risk/problematic (2+ symptoms) users based on the Social Media Disorder Scale. Logistic regression showed that fear of missing out, impulsivity, depressive symptoms, intensity of meeting with friends, and reactive parental rules uniquely predicted at-risk/problematic use. Psychological network analysis identified self-esteem, attention problems, impulsivity, depressive symptoms, and life satisfaction as central, highly interconnected nodes. These findings show that theory- and data-driven approaches illuminate different aspects of PSMU risk, and that network analysis can generate novel hypotheses about underlying processes. Full article

Mental illness has emerged as a significant global health crisis, inflicting immense suffering and causing a notable decrease in productivity. Identifying mental health disorders at an early stage allows healthcare professionals to implement more targeted and impactful interventions, leading to a significant improvement in the overall well-being of the patient. Recent advances in Artificial Intelligence (AI) have opened new avenues for analyzing medical records and behavioral data of patients to assist mental health professionals in their decision-making processes. In this study performance of four Randomized Neural Networks (RandNNs) such as Board Learning System (BLS), Random Vector Functional Link Network (RVFLN), Kernelized RVFLN (KRVFLN), and Extreme Learning Machine (ELM) are explored for detecting the type of mental illness a user may have by analyzing the random text of the user posted on social media. To improve the performance of the RandNNs during handling the text documents with unbalanced class distributions, a hybrid feature selection (FS) technique named as TOPSIS-ModCHI is suggested in the preprocessing stage of the classification framework. The effectiveness of the suggested FS with all the four randomized networks is assessed over the publicly available Reddit Mental Health Dataset after experimenting on two benchmark multiclass unbalanced datasets. From the experimental results, it is inferred that detecting the mental illness using BLS with TOPSIS-ModCHI produces the highest precision value of 0.92, recall value of 0.66, f-measure value of 0.77, and Hamming loss value of 0.06 as compared to ELM, RVFLN, and KRVFLN with a minimum feature size of 900. Overall, utilizing BLS for mental health analysis can offer a promising avenue toward improved interventions and a better understanding of mental health issues, aiding in decision-making processes. Full article

Background/Objectives: Adolescent levels of psychological distress are strongly influenced by community, individual, social, and family factors. Family functioning, social media use, and community disorder have shown high predictive value for psychological distress during this critical stage of development. However, these relationships are not always direct and are often mediated by individual-level variables, such as intolerance of uncertainty. Adolescent psychological well-being is not solely determined by contextual factors; the coping skills developed during this critical stage also play a significant role. Our study aims to analyze how these factors are directly and indirectly related by developing a predictive model of psychological distress in adolescents. Methods: The study included 908 adolescents (46.9% female) aged between 14 and 21 years (M = 16.29, SD = 1.5). Participants completed self-administered questionnaires in a school setting. Structural equation modeling was used to estimate total, direct, and indirect effects. Results: The model showed a good fit to the data. Social media disorder and family functioning showed statistically significant direct and indirect effects on psychological distress. Social media disorder was associated with higher psychological distress, while positive family functioning was protective. Community social disorder was only indirectly linked to higher psychological distress through the increase of intolerance of uncertainty. Conclusions: Intolerance of uncertainty is a critical predictor of adolescent distress, often overlooked despite its significant mediating role. Direct effects of family functioning and social media use also strongly influence distress levels. Impaired family functioning and community disorder interact bidirectionally, creating a cycle that exacerbates distress. Adolescents in these contexts face compounded negative effects from these reinforcing environments. Full article

Objectives: Persistent symptoms following COVID-19 may adversely impact the general mental health of people with chronic pain, and psychological flexibility may buffer these impacts. However, it remains unclear whether such lasting implications of COVID-19 differ between people with and without chronic pain. This study investigated the relationships between persistent symptoms post-COVID-19, psychological flexibility, and general mental health among people with and without persistent pain during the COVID-19 pandemic in the UK. Methods: A total of 204 adults living in the UK were recruited via social media and completed an online survey, including measures of persistent symptoms, depression (Patient Health Questionnaire-9), anxiety (General Anxiety Disorder-7), insomnia (the Insomnia Severity Index), and psychological flexibility (the Multidimensional Psychological Flexibility Inventory), and were included in the analyses. Results: Participants with persistent pain (n = 70) experienced more-persistent symptoms, poorer general mental health, and a higher level of psychological inflexibility compared with participants without persistent pain (n = 133). Overall, the relationships between persistent physical symptoms, general mental health, and psychological (in)flexibility showed similar patterns in the two groups. Participants with more-persistent physical symptoms experienced significantly poorer general mental health. Furthermore, people with higher levels of psychological inflexibility reported worse general mental health. There was little evidence that psychological (in)flexibility could “buffer” the association between persistent physical symptoms and general mental health. Conclusions: People with chronic pain appear more vulnerable to persistent symptoms and reduced general mental health compared with people without pain. Treatments that reduce psychological inflexibility, such as ACT, may improve outcomes for people with persistent symptoms post-COVID-19. Full article

Background/Objectives: Despite the growing awareness of nutrition and the popularity of healthy lifestyles among adolescents, disordered eating behaviors—such as anorexia nervosa, bulimia nervosa, binge eating disorder (BED), and avoidant/restrictive food intake disorder (ARFID)—remain significant public health concerns. ARFID, officially recognized only in 2013, is still poorly understood among youth. This study aimed to assess the relationship between adolescents’ nutritional knowledge, emotional regulation, media influence, and eating behaviors. Methods: A cross-sectional study was conducted in 2024 among 120 students aged 15–17 attending W. Reymont Secondary School No. II in Ostrów Wielkopolski, Poland. Participants completed a custom-designed, paper-based questionnaire consisting of 30 single-choice questions and demographic items. The instrument assessed knowledge of eating disorders, body satisfaction, social media impact, and the emotional determinants of food choices. The tool was developed with expert input but has not undergone formal psychometric validation. While many adolescents demonstrated basic nutritional knowledge—such as awareness of BMI norms and food group distribution—they often failed to apply this knowledge to their dietary behaviors. Results: Significant gender differences were observed: girls were more likely to restrict food intake, report emotional eating, and engage in slimming behaviors, while boys were less emotionally reactive and less influenced by social media. Most participants reported eating one meal daily with family but rarely discussed nutrition at home. Emotional involvement in eating, particularly among girls, emerged as a key factor, more influential than social media in shaping dietary behaviors. Conclusions: The findings highlight a clear gap between nutritional knowledge and actual behavior among adolescents, driven in part by emotional dysregulation and body image concerns. School-based interventions should incorporate not only nutritional education but also emotional regulation strategies and media literacy to effectively support healthy eating behaviors in youth. Full article

Background/Objectives: Parkinson’s disease (PD) is a neurodegenerative disorder with a prolonged prodromal phase and progressive symptom burden. Traditional monitoring relies on clinical visits post-diagnosis, limiting the ability to capture early symptoms and real-world disease progression outside structured assessments. Social media provides an alternative source of longitudinal, patient-driven data, offering an opportunity to analyze both pre-diagnostic experiences and later disease manifestations. This study evaluates the feasibility of using Facebook to analyze PD-related discourse and disease timelines. Methods: Participants (N = 60) diagnosed with PD, essential tremor, or atypical parkinsonism, along with caregivers, were recruited. Demographic and clinical data were collected during structured interviews. Participants with Facebook accounts shared their account data. PD-related posts were identified using a Naïve Bayes classifier (recall: 0.86, 95% CI: 0.84–0.88, AUC = 0.94) trained on a ground-truth dataset of 6750 manually labeled posts. Results: Among participants with PD (PwPD), Facebook users were significantly younger but had similar Movement Disorder Society-United Parkinson’s Disease Rating Scale scores and disease duration compared to non-users. Among Facebook users with PD, 90% had accounts before diagnosis, enabling retrospective analysis of pre-diagnostic content. PwPD maintained 14 ± 3 years of Facebook history, including 5 ± 6 years pre-diagnosis. On average, 3.6% of all posts shared by PwPD were PD-related, and 1.7% of all posts shared before diagnosis were PD-related. Overall, 69% explicitly referenced PD, and 93% posted about PD-related themes. Conclusions: Facebook is a viable platform for studying PD progression, capturing both early content from the premorbid period and later-stage symptoms. These findings support its potential for disease monitoring at scale. Full article

Due to the rapid development of China’s economy, the current situation of fishing villages in the southeastern coastal areas is spatial disorder caused by changes in population composition and industrial transformation. This study analyses the differences between the clan structure and the multi-stakeholder engagement model in traditional fishing villages. The main aim is to illustrate contemporary issues that fishing villages’ spaces need to deal with in governance and decision making. With the development of information technology, social media has become an important platform through which stakeholders can communicate and make decisions. The aims of this paper were as follows: (1) Identify the stakeholders involved in the governance of fishing villages; (2) explore how stakeholders participate in the planning and governance of fishing villages through social media; (3) examine the mechanisms of social media and its impact on the spatial planning of fishing villages. Through qualitative research methods such as field surveys and in-depth interviews, the following results were obtained: (1) Social media subverts the traditional fishing village governance model, and the scope of the governance subject is expanded; (2) spatial changes in fishing villages are affected by the joint influence of people, the environment, and the economy, and a social network acts as an intermediary to compensate for the deficiencies that existed in previous fishing village governance processes. Full article

Background/Objectives: There is scientific evidence showing that body- and/or body weight-related blaming, guilting, and shaming continue to be both promoted and tolerated in many societal contexts, including schools and healthcare settings. A deeply ingrained belief still prevails among many individuals that inducing these negative emotions can serve as a motivator for children and adolescents to engage in obesity treatment. Therefore, the aim of this systematic review is to examine these emotions (blame, guilt, shame) in relation to body weight and their impact on psychological functioning within the pediatric population affected by overweight and obesity. Methods: Articles were searched up using PubMed and Web of Science in June 2023 and March 2025. The search was conducted without limiting the years of publication. The inclusion criteria included the following: (1) pediatric samples, (2) full text available, and (3) original research articles. Articles were excluded if they were editorials, letters, replies from authors, review articles, and articles without a full text. Results: The initial search returned 199 results. A total of 16 articles were included in the study. Analysis of the collected records revealed associations between body- or weight-related blame, guilt, and shame and various aspects of psychological functioning in the pediatric population such as (a) interpersonal context (e.g., social stigma, bullying, teasing history, social connectedness, weight-related language used by parents in conversations with children and adolescents; (b) intrapsychic context—relationship with eating and food (e.g., binge eating, dietary restraint, emotional eating, and the risk of developing eating disorders); (c) intrapsychic context—self-perception (e.g., self-esteem, feelings of worthlessness, self-compassion, self-efficacy, perceived control); (d) intrapsychic context—emotional functioning (e.g., emotional distress, anxiety, depression, emotion regulation strategies); and (e) intrapsychic context—additional psychological factors (e.g., mindfulness, quality of life, willingness to seek help, and motivation for both help-seeking and sustaining successful lifestyle changes). Conclusions: Understanding the dynamics of body- and/or weight-related blame, guilt, and shame among children and adolescents with overweight and obesity is essential for developing effective support systems that enhance their well-being and psychological resilience in both the prevention and treatment of obesity. Further research is needed to explore the relationships between body- and weight-related blame, guilt, and shame and psychological functioning in pediatric populations with overweight and obesity, including the dynamics of child–parent–healthcare provider interactions, the context of parenting skills and attitudes that support the child during obesity treatment, the long-term consequences of body- and weight-related blame, guilt, and shame, the relationship between healthcare providers’ tendencies to engage in body- and weight-related shaming or blaming and their communication skills and mental well-being (e.g., levels of professional burnout, emotion regulation skills, and personality traits), as well as the influence of social media on body- and weight-related shame, guilt, and blame. Full article