Behavioral and Social Studies in Mental Health

Predicting Psychological Self-Care Behaviors Based on Psychological Capital and Social Support

Hossein Rahimi ^*

This study aimed to explain the perceived roles of psychological capital and social support in the initiation, organization, and maintenance of psychological self-care behaviors among adults living in Tehran. A qualitative descriptive design using conventional qualitative content analysis was employed. The participants were 18 adults living in Tehran who were recruited through purposive maximum-variation sampling with attention to diversity in gender, age, marital status, educational attainment, and occupational status. Data were collected exclusively through individual semi-structured interviews lasting approximately 45–75 minutes. Interviews continued until theoretical saturation was reached; preliminary saturation occurred after the sixteenth interview, and two additional interviews were conducted to confirm the stability and comprehensiveness of the categories. Interviews were audio-recorded with permission, transcribed verbatim, and analyzed concurrently with data collection. NVivo 14 software was used to organize transcripts, codes, categories, analytic memos, and relationships among concepts. Credibility, dependability, confirmability, and transferability were strengthened through participant validation, peer review of coding decisions, maintenance of an audit trail, maximum-variation sampling, reflexive documentation, and rich description of the research context. Four main categories were identified: “psychological capital as the motivational engine of self-care,” “translation of psychological resources into emotional regulation and healthy boundaries,” “responsive social support as a safe context for self-care,” and “the interactive cycle of personal resources, social relationships, and contextual barriers.” Participants described self-efficacy, hope, realistic optimism, and resilience as resources that enabled them to recognize psychological needs, formulate feasible self-care goals, initiate action, and resume routines after disruption. Emotional, informational, instrumental, and appraisal support reduced isolation, validated psychological needs, facilitated help-seeking, and promoted adherence to self-care routines. In contrast, controlling or mismatched support, role overload, lack of time, financial constraints, and the stigma attached to psychological help-seeking impeded self-care. Psychological self-care emerged as a relational and context-sensitive process rather than an exclusively individual choice. Psychological capital appeared to provide the motivational and self-regulatory capacity required for self-care, whereas responsive social support supplied emotional safety, practical resources, feedback, and accountability. The findings suggest that effective self-care programs should simultaneously strengthen hope, efficacy, resilience, and realistic optimism and improve people’s ability to request, receive, evaluate, and provide appropriate social support.

The Role of Artificial Intelligence in Transforming Psychological Help-Seeking Behaviors: A Social–Behavioral Analysis of User Trust, Acceptance, and Resistance

Maryam Ahmadi , Sina Hosseini ^*

This study aimed to explain how artificial intelligence transforms psychological help-seeking behaviors and to analyze the social and behavioral processes underlying users’ trust, acceptance, and resistance. This qualitative study employed a reflexive thematic analysis approach. Participants were 26 residents of Tehran who had used generative artificial intelligence systems or conversational chatbots at least three times during the previous six months to obtain mental health information, seek emotional support, or decide whether to consult a mental health professional. Purposive maximum-variation sampling was used to ensure diversity in gender, age, educational level, occupational status, and experience with artificial intelligence. Data were collected exclusively through individual semistructured interviews. After obtaining informed consent, the interviews were audio-recorded, transcribed verbatim, and organized and analyzed using NVivo 14. Theoretical saturation was reached during the twenty-third interview, followed by three additional interviews to confirm informational adequacy. Four main categories were identified: “low-friction access and a reduced threshold for help-seeking,” “conditional and evaluative trust,” “instrumental acceptance and preference for a human–AI hybrid model,” and “social–emotional resistance and protection of the uniqueness of human relationships.” Participants perceived continuous availability, anonymity, affordability, immediate responses, and the opportunity to disclose embarrassing concerns without fear of judgment as important facilitators of help-seeking. Nevertheless, trust was provisional and was repeatedly reassessed according to response accuracy, transparency, cultural relevance, privacy protection, consistency, and the system’s ability to recognize its limitations. Most participants accepted artificial intelligence as a resource for psychoeducation, emotional clarification, preliminary support, symptom monitoring, and preparation for professional consultation, but rejected its use as a complete substitute for therapists. Artificial intelligence appears to transform psychological help-seeking from a binary decision to seek or avoid professional care into a gradual, experimental, and multi-resource process. User acceptance does not necessarily indicate complete trust; rather, it reflects a continuing negotiation among convenience, perceived usefulness, vulnerability, risk, and the need for human understanding. Responsible integration of artificial intelligence into mental health services therefore requires transparent communication, culturally and linguistically appropriate design, strong data protection, professional oversight, crisis safeguards, and explicit referral pathways to qualified human professionals.

The Impact of Problematic Social Media Use on Young Adults’ Mental Health: The Mediating Role of Social Comparison and Emotion Regulation

Reza Zare , Neda Safari ^*

پژوهش حاضر با هدف واکاوی تجربه زیسته جوانان از تأثیر استفاده مسئله‌زا از شبکه‌های اجتماعی بر سلامت روان و تبیین نقش واسطه‌ای ادراک‌شده مقایسه اجتماعی و تنظیم هیجان انجام شد. این پژوهش با رویکرد کیفی و روش تحلیل محتوای قراردادی انجام شد. مشارکت‌کنندگان شامل 22 جوان 18 تا 30 ساله ساکن تهران بودند که با روش نمونه‌گیری هدفمند و با رعایت اصل بیشینه تنوع انتخاب شدند. معیارهای ورود شامل استفاده روزانه دست‌کم سه ساعت از شبکه‌های اجتماعی طی شش ماه گذشته، تجربه دشواری در کنترل استفاده و ادراک پیامدهای روان‌شناختی یا کارکردی ناشی از آن بود. داده‌ها صرفاً از طریق مصاحبه‌های نیمه‌ساختاریافته فردی گردآوری شدند. مصاحبه‌ها تا دستیابی به اشباع نظری ادامه یافت؛ اشباع اولیه پس از مصاحبه بیستم حاصل شد و دو مصاحبه تکمیلی ثبات مقوله‌ها را تأیید کرد. داده‌ها پس از پیاده‌سازی کلمه‌به‌کلمه، با استفاده از نرم‌افزار NVivo کدگذاری و تحلیل شدند. برای افزایش اعتبار یافته‌ها از بازبینی مشارکت‌کنندگان، مرور همتایان، یادداشت‌نویسی تأملی و ثبت مسیر تحلیل استفاده شد. تحلیل مصاحبه‌ها به استخراج پنج مقوله اصلی منجر شد: «استفاده تکانه‌ای و نشانه‌محور و از دست رفتن کنترل»، «مقایسه صعودی با تصاویر گزینش‌شده و فرسایش خودارزیابی»، «استفاده از شبکه‌های اجتماعی به‌عنوان راهبرد تنظیم هیجان و گریز دیجیتال»، «تجمع پیامدهای روان‌شناختی و اختلال در عملکرد روزمره» و «خودمراقبتی دیجیتال ناپایدار و بازگشت به الگوی مسئله‌زا». تجربه مشارکت‌کنندگان نشان داد که مواجهه مستمر با بازنمایی‌های آرمانی، احساس عقب‌ماندگی، ناکافی‌بودن و ترس از دست دادن را تقویت می‌کند. همچنین استفاده از شبکه‌های اجتماعی برای کاهش موقت اضطراب، تنهایی، ملال و فشار روانی، در بلندمدت با احساس گناه، نشخوار فکری، اختلال خواب و کاهش تمرکز همراه بود. یافته‌ها بیانگر آن است که رابطه استفاده مسئله‌زا با سلامت روان صرفاً حاصل مدت حضور در شبکه‌های اجتماعی نیست، بلکه به انگیزه استفاده، فقدان کنترل، ماهیت منفعلانه مصرف محتوا، مقایسه صعودی و وابستگی به رسانه برای تعدیل هیجان مربوط می‌شود. نتایج از یک الگوی مفهومی حمایت می‌کنند که در آن مقایسه اجتماعی منفی و تنظیم هیجان ناکارآمد، مسیر ارتباط استفاده مسئله‌زا با آشفتگی روان‌شناختی را توضیح می‌دهند؛ بااین‌حال، ماهیت کیفی پژوهش امکان آزمون آماری میانجی‌گری یا استنباط علی را فراهم نمی‌کند. مداخلات پیشگیرانه باید هم‌زمان بر سواد رسانه‌ای، اصلاح مقایسه‌های غیرواقع‌بینانه، مهارت‌های تنظیم هیجان و مدیریت محرک‌های دیجیتال تمرکز کنند.

Mental Health in the Age of Algorithms: Examining the Behavioral Consequences of Human Interaction with Intelligent Digital Platforms

Ali Ahmadi ^*

This study aimed to explain users’ lived experiences of the behavioral and psychological consequences of continuous interaction with intelligent digital platforms and to identify the mechanisms through which algorithmic personalization influences attention, emotion, identity, social relationships, and digital self-regulation. This qualitative study employed an inductive thematic analysis. The participants were 24 adult users residing in Tehran who were selected through purposive maximum-variation sampling and had used platforms incorporating recommendation systems on a daily basis for at least two years. Data were collected exclusively through individual semi-structured interviews. Interviews continued until theoretical saturation was achieved; preliminary saturation occurred during the twenty-first interview, and three additional interviews were conducted to confirm the stability and comprehensiveness of the categories. The interviews were transcribed verbatim and analyzed with the assistance of NVivo software. Analysis involved familiarization with the data, generation of initial codes, development and review of themes, and definition and naming of the final themes. Member checking, peer review, maintenance of an audit trail, maximum-variation sampling, and reflexive documentation were used to enhance credibility and dependability. Five main categories were identified: “algorithmic capture of attention and the development of compulsive use,” “emotional fluctuation, social comparison, and psychological fatigue,” “identity reconstruction in the algorithmic mirror,” “the duality of social connectedness and perceived loneliness,” and “algorithmic awareness, resistance, and restoration of agency.” Participants did not experience themselves as merely passive recipients of technology. Instead, they described a reciprocal feedback cycle in which user behavior trained the algorithm, while algorithmically selected outputs subsequently influenced users’ moods, preferences, decisions, and future behaviors. Intelligent platforms may simultaneously facilitate belonging, learning, identity expression, and access to social or psychological support while threatening mental health through engagement-oriented design, repeated exposure to emotionally arousing content, social comparison, sleep disruption, and reduced perceived control. Therefore, the quality and context of interaction, the nature of recommended content, and users’ degree of transparency and control may be more informative than screen time alone. Algorithmic literacy, well-being-oriented platform design, meaningful user control over recommendations, and digital self-regulation interventions are required to reduce harm while preserving the psychosocial benefits of digital participation.

Applying Behavioral Science to Mental Health Policymaking: From Attitude Change to Behavior Change

Majid Qasemi ^*

This study aimed to explain the mechanisms, capacities, and implementation requirements of behavioral science in mental health policymaking and to identify strategies for translating attitudinal change into sustained behavioral change. A qualitative study using thematic analysis was conducted. The participants were 24 mental health policymakers and administrators, psychiatrists, psychologists, public health specialists, health communication experts, and representatives of nongovernmental organizations working in Tehran, Iran. Participants were selected through purposive maximum-variation sampling, and recruitment continued until theoretical saturation was achieved. Data were collected exclusively through individual semi-structured interviews. The interviews were audio-recorded with consent, transcribed verbatim, and analyzed according to the six-phase thematic analysis procedure using NVivo 14. Member checking, peer debriefing, reflexive memoing, constant comparison, and documentation of the analytic process were used to enhance credibility, dependability, confirmability, and transferability. Five main categories were identified: “reframing mental health and reducing stigma through lived experience,” “reducing behavioral friction in access to care,” “activating social norms and trusted messengers,” “personalizing digital interventions and timely feedback,” and “institutionalizing ethical and evaluable behavioral governance.” Participants maintained that awareness and positive attitudes alone rarely produce help-seeking, treatment initiation, or sustained engagement when services remain costly, fragmented, stigmatizing, difficult to navigate, or insufficiently confidential. Contact-based communication, locally credible social-norm messages, simplified referral pathways, timely reminders, supportive defaults, personalized feedback, and low-friction digital entry points were regarded as useful strategies when integrated with structural reforms. Mental health policy should move beyond one-way information provision toward the systematic design of behavioral environments. Behavioral science is most effective when capability, opportunity, motivation, trust, and institutional context are addressed simultaneously. Behavioral interventions should not be presented as low-cost substitutes for adequate financing, insurance coverage, service development, workforce expansion, or legal protection. Instead, they should complement structural policies by making beneficial actions easier, safer, more socially acceptable, and more sustainable. Ethical safeguards, transparent objectives, public participation, privacy protection, cultural adaptation, and continuous evaluation are necessary for responsible implementation.

Digital Mindfulness-Based Interventions and Their Psychosocial Mental Health Outcomes

Hossein Jalali ^* , Zahra Nourian

This study aimed to explain users’ lived experiences of digital mindfulness-based interventions and identify their perceived psychological and social health outcomes. This qualitative study was conducted using conventional content analysis. The participants were 20 residents of Tehran who had used a mindfulness mobile application, web-based program, or synchronous online mindfulness course for at least eight weeks. Purposive maximum-variation sampling was applied to achieve diversity in age, gender, marital status, education, occupational status, intervention format, and duration of use. Data were collected exclusively through individual semi-structured interviews. Conceptual and theoretical saturation was reached after the eighteenth interview, followed by two confirmatory interviews. The interviews were audio-recorded with permission, transcribed verbatim, and analyzed inductively using NVivo version 14. Meaning units were identified, condensed, coded, compared, and organized into subcategories and main categories. Credibility and trustworthiness were enhanced through participant checking, peer review, maximum-variation sampling, reflexive memoing, prolonged engagement with the data, and maintenance of an audit trail. Five main categories were identified: reduced psychological arousal and improved emotional regulation; enhanced self-awareness, cognitive distancing, and self-compassion; improved interpersonal interactions and social connectedness; accessibility, autonomy, and integration of mindfulness into everyday life; and fragile engagement due to digital fatigue, limited human feedback, privacy concerns, insufficient personalization, and difficulty managing intense experiences. Participants described reductions in stress, repetitive negative thinking, impulsive emotional reactions, and interpersonal conflict. They also reported greater listening capacity, empathy, boundary awareness, and purposeful social participation. Nevertheless, inconsistent practice, technological distractions, feelings of isolation during self-guided practice, and uncertainty about the accuracy or safety of digital content limited perceived benefits. Digital mindfulness interventions may promote psychosocial mental health by strengthening present-moment attention, acceptance, emotional regulation, self-compassion, and deliberate interpersonal responding. Their flexibility and accessibility make them potentially valuable as preventive, complementary, and low-threshold mental health resources. However, they should not be regarded as universal substitutes for professional assessment or treatment. Persian-language, culturally responsive programs that combine autonomous practice with optional human guidance, privacy protection, risk screening, crisis referral, personalization, and engagement-support features are likely to be safer and more sustainable.

Evaluating the Effectiveness of Social Media–Based Interventions in Reducing Mental Health Stigma: A Qualitative Study in Tehran

Ali Qasem Abadi ^* , Sara Sadeghi , Amir Salehi Nejad

This study aimed to explain users’, people with lived experience, family members’, and mental health professionals’ perceptions of the mechanisms, outcomes, and limitations of social media–based interventions intended to reduce mental health stigma. A qualitative descriptive-interpretive design was employed. The participants were 24 residents of Tehran who were selected through purposive maximum-variation sampling. They included 12 individuals with lived experience of mental health problems, 7 mental health professionals or professional content creators, and 5 family members or social advocates. Data were collected exclusively through individual semi-structured interviews. Interviews continued until theoretical saturation was reached; preliminary saturation occurred after the twenty-first interview, followed by three additional interviews to ensure informational adequacy. All interviews were transcribed verbatim and analyzed through inductive thematic analysis using NVivo version 14. Credibility and trustworthiness were enhanced through participant checking, peer review, documentation of the analytical process, maximum-variation sampling, and maintaining an audit trail. Four main categories emerged: “improving mental health literacy and cognitively reconstructing stigma,” “digital social contact and humanization of mental health experiences,” “empowerment for controlled disclosure, peer support, and help-seeking,” and “fragility of intervention effects in the face of distrust, trivialization, and platform-related risks.” Participants believed that accessible scientific information, authentic recovery narratives, and opportunities for reciprocal communication could challenge stereotypes, reduce fear, and decrease desired social distance. Nevertheless, misinformation, commercialized or performative portrayals of mental disorders, stigmatizing comments, privacy concerns, algorithmic repetition, and discontinuous exposure restricted intervention effectiveness. Social media–based interventions can contribute to reducing public stigma and facilitating help-seeking when they are scientifically credible, culturally appropriate, sustained over time, connected to professional services, and designed with meaningful participation from people with lived experience. However, social media interventions should not be considered substitutes for structural policies, face-to-face education, or accessible mental health services. Multilevel intervention design, professional content governance, active moderation, and assessment of long-term behavioral outcomes are required to achieve sustainable stigma reduction.

Qualitative Modeling of the Effect of Perceived Social Deprivation on Depressive Symptoms: The Mediating Role of Loneliness and the Moderating Role of Social Support

Majid Ahmadi Pourian ^* , Shirin Hasani

This study aimed to develop an explanatory model of how perceived social deprivation contributes to the emergence and intensification of depressive symptoms, with particular emphasis on loneliness as an intervening mechanism and social support as a protective moderating condition among adults living in Tehran. This qualitative study was conducted using thematic analysis. The participants were 24 adults residing in Tehran who reported experiences of perceived social deprivation, loneliness, and depressive symptoms. Participants were recruited through purposive maximum-variation sampling based on gender, age, marital status, educational level, and employment status. Recruitment continued until theoretical and meaning saturation was achieved. Data were collected exclusively through individual semi-structured interviews lasting approximately 45–75 minutes. Following informed consent, the interviews were audio-recorded, transcribed verbatim, anonymized, and imported into NVivo. Data analysis involved repeated familiarization with the transcripts, initial coding, constant comparison of codes, organization of related codes into preliminary categories, refinement of category boundaries, and development of an integrated explanatory model. Credibility was enhanced through prolonged engagement with the data, peer review of coding decisions, participant checking of selected interpretations, and maintenance of an audit trail. Five main categories were identified: “accumulated experiences of exclusion and social invisibility,” “loneliness as the internalization of social deprivation,” “erosion of self-worth and expansion of depressive symptoms,” “social support as a conditional protective buffer,” and “the self-reinforcing cycle of deprivation, loneliness, and depression.” Perceived social deprivation became psychologically harmful when participants interpreted restricted opportunities, exclusion, unequal treatment, or unresponsive relationships as evidence that they were unworthy, unwanted, or socially insignificant. Loneliness translated these experiences into persistent emotional pain, rumination, withdrawal, hopelessness, anhedonia, fatigue, and reduced motivation. Emotional, instrumental, and informational support attenuated this process when it was reliable, respectful, nonjudgmental, and responsive to the participant’s actual needs. Loneliness appears to constitute a central explanatory pathway through which perceived social deprivation is transformed into depressive symptomatology. Social support can weaken this pathway, although its protective value depends more on perceived quality, accessibility, and relational safety than on the mere number of social contacts. Effective prevention should therefore combine individual psychological interventions with community-based and structural strategies that strengthen belonging, reduce exclusion and stigma, and provide meaningful and context-sensitive support.

Behavioral and Social Studies in Mental Health

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Applying Behavioral Science to Mental Health Policymaking: From Attitude Change to Behavior Change

Digital Mindfulness-Based Interventions and Their Psychosocial Mental Health Outcomes

Evaluating the Effectiveness of Social Media–Based Interventions in Reducing Mental Health Stigma: A Qualitative Study in Tehran

Qualitative Modeling of the Effect of Perceived Social Deprivation on Depressive Symptoms: The Mediating Role of Loneliness and the Moderating Role of Social Support

The Impact of Health-Oriented Leadership on Employees’ Psychological Well-Being: The Mediating Role of Psychological Safety

Designing a Primary Prevention Framework for Mental Disorders Based on the Social Determinants of Health

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Predicting Psychological Self-Care Behaviors Based on Psychological Capital and Social Support

The Role of Artificial Intelligence in Transforming Psychological Help-Seeking Behaviors: A Social–Behavioral Analysis of User Trust, Acceptance, and Resistance

The Impact of Problematic Social Media Use on Young Adults’ Mental Health: The Mediating Role of Social Comparison and Emotion Regulation

Mental Health in the Age of Algorithms: Examining the Behavioral Consequences of Human Interaction with Intelligent Digital Platforms

Applying Behavioral Science to Mental Health Policymaking: From Attitude Change to Behavior Change

Digital Mindfulness-Based Interventions and Their Psychosocial Mental Health Outcomes

Evaluating the Effectiveness of Social Media–Based Interventions in Reducing Mental Health Stigma: A Qualitative Study in Tehran

Qualitative Modeling of the Effect of Perceived Social Deprivation on Depressive Symptoms: The Mediating Role of Loneliness and the Moderating Role of Social Support