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Effectiveness of multi-session mindfulness-based interventions on sport performance and competitive anxiety in competitive athletes: a systematic review of controlled trials Ifdil Ifdil; Nur Adila Wafiqoh Zulvi; M. Fahli Zatrahadi
Journal of Counseling, Education and Society Vol. 6 No. 2 (2025): Journal of Counseling, Education and Society
Publisher : Indonesian Institute for Counseling, Education and Theraphy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/08jces693900

Competitive athletes perform under evaluative pressure, and competitive anxiety threatens sport performance. Mindfulness-based interventions (MBIs) are increasingly adopted in applied sport psychology, yet controlled evidence on their effects on performance and anxiety remains fragmented. This review synthesised controlled trials examining whether structured multi-session MBIs improve performance and reduce competitive anxiety in competitive athletes, and which programme characteristics accompany favourable outcomes. The review followed the PRISMA 2020 statement and a PICOS framework. Scopus was searched with a Boolean string combining mindfulness, athlete or sport, and performance or competitive anxiety terms, limited to English-language open-access journal articles published between 2016 and 2025, yielding 521 records. Eligible studies were randomised or non-randomised controlled trials of multi-session MBIs reporting objective or observer-rated sport performance or competitive or sport anxiety; single-session, uncontrolled, and non-athlete studies were excluded. Seventeen studies met the criteria. Most reported performance gains, particularly in precision and endurance tasks such as free throws, shooting, and rowing, whereas anxiety effects were less consistent and sometimes matched by psychological skills training. Sport-specific programmes lasting six to eight weeks appeared most promising. The findings support MBIs as a complementary performance tool, while larger preregistered trials with follow-up and objective outcomes are needed.

Virtual reality-based psychological counseling and psychotherapy for mental health conditions: a systematic review of randomized controlled trials on applications and therapeutic effectiveness ifdil ifdil; Nur Adila Wafiqoh Zulvi; M. Fahli Zatrahadi
SCHOULID: Indonesian Journal of School Counseling Vol. 10 No. 2 (2025): SCHOULID: Indonesian Journal of School Counseling
Publisher : Indonesian Counselor Association (IKI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23916/086864011

Virtual reality (VR) has moved from laboratory prototypes into clinical counseling, yet its therapeutic value relative to conventional approaches remains debated. This systematic review mapped the counseling and psychotherapeutic applications of VR evaluated in randomized controlled trials and appraised their effectiveness against conventional or control conditions. Following PRISMA 2020 and a PICOS-structured strategy, Scopus was searched with Boolean combinations of VR and counseling or psychotherapy terms, yielding 981 records. Eligible studies were English-language, open-access, final-stage journal articles published between 2016 and 2025 that randomized people with mental health conditions to a VR-based psychological intervention; protocols, reviews, non-randomized designs, and non-psychotherapeutic uses of VR were excluded. After removing 14 duplicates and 542 records outside the search limiters, 425 records were screened and 17 trials were included. Applications clustered into depression, anxiety and fear, substance use, trauma, and transdiagnostic stress. VR consistently outperformed usual care or no-VR conditions, whereas comparisons with active conventional therapies mostly indicated equivalence or non-inferiority. VR therefore appears to extend rather than replace established counseling models. Future research should prioritize adequately powered comparative trials, longer follow-up, and implementation studies in counseling settings.

Reading the unspoken: a systematic review of multimodal artificial intelligence for detecting psychological and affective states from nonverbal cues Ifdil Ifdil; Nur Adila Wafiqoh Zulvi; M. Fahli Zatrahadi
JRTI (Jurnal Riset Tindakan Indonesia) Vol. 10 No. 3 (2025): JRTI (Jurnal Riset Tindakan Indonesia)
Publisher : IICET (Indonesian Institute for Counseling, Education and Therapy)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/30036998000

The psychological assessment is limited to only relying on the patients' self-reports, as they may not even understand or have the desire or capacity to express the distress they show with their body language such as facial movements, voice, gaze, posture, and physiology. This systematic literature review brings together the findings of multimodal artificial intelligence (AI), mainly the use of such a system in detecting psychological and affective states from nonverbal cues and examines whether it is ready for mental-health and counseling applications. Using PRISMA 2020, we identified the records from a Scopus search, then screened them by the predefined eligibility criteria and evaluated them with the tool for Mixed-Method Appraisal. The original list of 669 articles was reduced first by removing the duplicates to 665 screened articles, and among them, we selected 20 articles released in 2024, 2025 that fulfilled the criteria. The themes identified in the five modality Channels facial & micro expression, speech & acoustic, text & linguistic, physiologic, and body movement together with their amalgamation were compared against the target states which were mainly depression, general emotion, and concealed affect. Multimodal approach generally yielded better results than unimodal methods and recognized concealed distress and suicidality, but the research is limited in scope, data sets being very small, external validation is missing and ethical precautions are not even considered yet.

Beyond what people say: a systematic review of artificial intelligence-based detection of psychological non-disclosure and hidden mental states in counseling and mental health care Ifdil Ifdil; Nur Adila Wafiqoh Zulvi; M. Fahli Zatrahadi
JRTI (Jurnal Riset Tindakan Indonesia) Vol. 10 No. 4 (2025): JRTI (Jurnal Riset Tindakan Indonesia)
Publisher : IICET (Indonesian Institute for Counseling, Education and Therapy)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/30036999000

Not revealing psychologically distressing thoughts, symptoms, and experiences, that is, psychological non-disclosure, contributes to the failure of detection and treatment in many cases of mental illness. Since diagnostic methods mostly depend on self-reporting, such states often remain unrecognized. This article is a literature review and it summarizes the research on how AI and computational methods can be applied to detect psychological non-disclosure and secret states. According to PRISMA 2020, literature was searched using three databases: Scopus, PubMed, and ScienceDirect; only eligible sources were selected and the Mixed Methods Appraisal Tool was used for evaluating. After excluding duplicates only 791 records remained with 20 of those (2020-2025) being included. Six methods are mentioned: language and text analysis; speech and acoustic biomarkers; facial micro-expressions and physiological signals; large language model conversational systems; predictive machine learning; and disclosure augmentation. The study shows that multimodal AI can identify hidden distress, self-injury, and suicidal states although the knowledge is still not fully developed, validation is not enough, and safeguards against misuse remain weak. A framework mapping the different modalities to possible targets was suggested as well the article highlights the need for more thorough validation, transparent reporting, and privacy-preserving use of AI.

How psychological trauma shapes human decision-making: a systematic literature review of cognitive, emotional, and behavioral mechanisms Ifdil Ifdil; Nur Adila Wafiqoh Zulvi; M. Fahli Zatrahadi
Jurnal Konseling dan Pendidikan Vol. 14 No. 1 (2026): JKP
Publisher : Indonesian Institute for Counseling, Education and Therapy (IICET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/1227900

sychological trauma is a public-health concern that cuts across emotional well-being and everyday decision-making. Both trauma and decision-making have been studied extensively, yet the mechanisms that connect adverse experiences to altered choice remain scattered across neuroscience, clinical psychology, and behavioral science. In this systematic literature review, we synthesize recent evidence on how trauma shapes human decision-making through cognitive, emotional, and behavioral pathways. The review follows PRISMA 2020. A structured Scopus search targeted English-language research articles published between 2022 and 2026. The search returned 886 records. After full-text assessment of 88 reports, 10 studies met the eligibility and quality criteria. Three convergent findings stand out. First, trauma disrupts value-based and reinforcement learning, which reduces behavioral flexibility and alters feedback sensitivity and belief updating. Second, greater threat appraisal, stronger stress reactivity, and impaired emotion regulation push decisions toward uncertainty avoidance and negative outcomes. Third, these shifts appear in risk-taking, substance-related choices, suicidality, and aggression. Overall, the evidence supports integrative models and trauma-informed, decision-focused clinical care.

Ai-enabled wearable and digital biomarkers for stress and mental health monitoring: a systematic literature review Ifdil Ifdil; Nur Adila Wafiqoh Zulvi; M. Fahli Zatrahadi
Jurnal Konseling dan Pendidikan Vol. 14 No. 2 (2026): JKP
Publisher : Indonesian Institute for Counseling, Education and Therapy (IICET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/1228000

Stress, anxiety, depression, and post-traumatic stress disorder (PTSD) carry a heavy burden. Yet the usual way we assess them still leans on episodic, self-reported instruments, which don't always reflect real life. Now wearable biosensors, smartphones, and artificial intelligence (AI) are opening the door to digital biomarkers. In this systematic literature review, we looked at how AI takes physiological and behavioural signals from wearables and smartphones to detect, predict, and monitor stress and mental-health conditions. We followed PRISMA 2020. A Scopus search turned up 403 records. After 14 duplicates were removed, 389 records went into screening. From there, 88 full texts were assessed, and 15 studies published between 2018 and 2026 made the final cut. Each eligible study combined digital sensing with AI or machine learning and linked those signals to outcomes. Three main themes came out of the synthesis. Heart-rate variability remains the dominant biomarker. Multimodal signals, combining electrodermal, cardiac, and electroencephalographic data, tend to improve classification. And smartphone phenotyping pushes monitoring further into depression, social anxiety, and trauma. The reported performance is promising, but small samples, device heterogeneity, and limited interpretability still hold these models back. Future work needs to prioritise larger cohorts, standardised reporting, explainability, and proper clinical validation.

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