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All Journal Jurnal Konseling dan Pendidikan Journal of Counseling, Education and Society SCHOULID: Indonesian Journal of School Counseling JRTI (Jurnal Riset Tindakan Indonesia)
Nilma Zola
Center for Educational Neuroscience, Trauma, and Human Behavior, Universitas Negeri Padang
Religion Humanities Education Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Wearable sensing and deep learning for human activity and action recognition in sport and physical activity: a systematic review Nilma Zola; ifdil ifdil; M. Fahli Zatrahadi
Journal of Counseling, Education and Society Vol. 7 No. 1 (2026): 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: 10.29210/08jces693300

Abstract

The fast merging of sensors which can be worn, the interconnected network of things, and the power of artificial intelligence changed the game in measuring movements during sports and physical activity, however, the information on how such systems can detect various athletic activities is still scattered mainly within engineering, sports-science, and health fields. In this systematic review the authors gathered studies which used wearable or vision-based sensors with different forms of machine/deep-learning models to identify human actions and activities during sporting and physical activity scenarios. Scopus, PubMed, and ScienceDirect were searched in compliance with PRISMA 2020 and 658 records were found. After removing 10 duplicates, 648 were screened, 50 full texts were evaluated, and 20 studies were found eligible. These were peer-reviewed English-language publications or reviews published within the last five years (2021 to 2026). Main topics of the research are the combination of inertial and multimodal sensors with the attention-based and hybrid convolutional-recurrent architectures that have yielded a high level of recognition performance for sports actions, together with the trend in research focusing on free-living, edge-deployable, and personal monitoring. The review points to key areas for further research being generalisability, standardised reporting, and athlete-centred validation.
When algorithms read the athlete's mind: a systematic review of artificial intelligence and machine learning for detecting and monitoring athletes' psychological and emotional states Nilma Zola; ifdil ifdil; M. Fahli Zatrahadi
Journal of Counseling, Education and Society Vol. 6 No. 1 (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: 10.29210/08jces693400

Abstract

Athletes are subjected to persistent physiological and psychological stresses; however, it is a challenge to monitor accurately, in real, and at the larger scale their affective and mental conditions. Traditional self-report and clinical instruments are intrusive, retrospective, and prone to reporting bias which have triggered the use of artificial intelligence (AI) and machine learning (ML) in sport psychology. The present systematic review integrates the findings of AI- and ML-based detection, monitoring, and assessment of athletes' psychological and emotional states. APRISMA2020 process was followed to identify six hundred and twenty-five records from a pool of articles obtained via the Scopus database, which were then filtered based on the predefined eligibility criteria. In the end, after the elimination of articles via the title/abstract screening or the full-text article evaluation, 21 empirical studies from the years 2021 to 2025 were the ones to have been identified and included. For the purposes of quality and validity, the articles were judged by Mixed Methods Appraisal Tool and the results were pooled thematically. The research results revealed that when combining various physiological signals with classical ML or deep learning, recognition of emotions, stress, mental fatigue, and mental-health risk can be reached with accuracy above 85%. A major direction for future work and translation of these technologies is real-time wearable-enabled feedback. The critical issues identified were external validation, ecological realism, ethical governance, standardised datasets, longitudinal designs, and transparent and privacy-preserving deployment.
Trauma-informed leadership: a systematic literature review of leadership behaviours, employee well-being, organizational resilience, and psychological recovery Nilma Zola; Ifdil Ifdil; M. Fahli Zatrahadi; Nur Adila Wafiqoh Zulvi
Journal of Counseling, Education and Society Vol. 7 No. 1 (2026): 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: 10.29210/08jces693700

Abstract

Trauma is practically built into modern work now. Employees in healthcare, education, child welfare, policing, and social care routinely face stress, vicarious traumatization, and outright adversity. This review pulls together the evidence on what trauma-informed leadership actually does to leader behaviours, staff well-being, organizational resilience, and psychological recovery. The search followed PRISMA 2020, and Scopus was queried across trauma-informed practice, leadership, and workforce outcomes. That search returned 101 records. Once duplicates were removed and the full screening was done, 15 studies made it through. Four findings came out of the synthesis. First, trauma-informed leadership works as a relational, self-regulating practice rooted in trauma neurobiology, not as some managerial technique you can just bolt on. Second, when leadership is built on safety, trustworthiness, choice, collaboration, and empowerment, well-being improves, affective commitment goes up, and burnout drops. Third, that kind of leadership strengthened resilience during crises, COVID-19 being the clearest case. Fourth, psychological recovery turns out to be a collective process, one that leadership enables rather than directs. The review extends servant and transformational leadership theory, and it gives a practical foundation for trauma-informed leadership development, policy, and workforce mental-health strategies. What is still missing is longitudinal, multi-sector, causal research, and that is where future work should point.
Digital grief and bereavement in the social media era: a systematic literature review of psychological adaptation, online mourning, and counseling interventions Nilma Zola; Ifdil Ifdil; M. Fahli Zatrahadi; Nur Adila Wafiqoh Zulvi
Journal of Counseling, Education and Society Vol. 7 No. 1 (2026): 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: 10.29210/08jces693800

Abstract

Death, loss, and mourning are universal experiences, yet contexts of grief have been transformed by social media and digital technologies. This systematic literature review synthesized evidence on digital grief and bereavement, focusing on online mourning, adaptation, and technology-mediated counseling. Following PRISMA 2020, a Scopus search identified 633 records; 622 were screened after exclusions, 61 full texts assessed, and 10 studies retained for synthesis, supported by 50 sources. Thematic synthesis addressed three research questions and bibliometric analysis. Three findings emerged. First, online spaces offer accessible, anonymous, and asynchronous support for stigmatized losses such as suicide, perinatal loss, and infertility-related grief. Second, digital mourning has ambivalent effects, providing social support and continuing bonds while potentially exposing mourners to distress contagion, harmful content, and isolation. Third, internet-based self-help, cognitive therapy, and co-designed resources show acceptability and feasibility, although effectiveness evidence remains limited. Future research should emphasize controlled trials, longitudinal designs, diversity, and safeguarding.
Beyond self-report: a systematic review of wearable and multimodal digital biomarkers for detecting psychological, affective, and fatigue states in athletes Nilma Zola; Ifdil Ifdil; M. Fahli Zatrahadi
SCHOULID: Indonesian Journal of School Counseling Vol. 10 No. 1 (2025): SCHOULID: Indonesian Journal of School Counseling
Publisher : Indonesian Counselor Association (IKI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23916/086862011

Abstract

Subjective, retrospection-based questionnaires of self-reports are not sufficient sources for early signs of psychological and fatigue conditions in athletes which opens the possibility of digital biomarkers. The review is on the basis of the PRISMA 2020 framework of the 799 records initially found through Scopus, of which 2 duplicates were excluded resulting in 797, among whom, 44 were considered for the inclusion of 16 and the rest were the exclusion of abstract titles. Papers in English describing sensor-based detection of psychological, affective, or fatigue states in sport or exercise were selected. Electrocardiograpy was the main modality used alongside heartbeat rate variability with the most studies focusing on the detection of fatigue and stress states, and there was an overall increase in the use of deep and machine-learning classifiers with some studies having classification accuracy beyond 90%. Multimodal fusion gave better results compared to the single-signal method. The limitations to the actual implementation of these systems were mainly the use of small sample sizes, weak external validation, inconsistent labelling of the reference signal. This review presents modalities and stresses the importance of standardized protocols, ecological validity, and transparent reporting both for researchers and practitioners.
The digital counselor in sport: a systematic review of AI-mediated psychological counseling, emotional support, and mental health care for athletes Nilma Zola; Ifdil Ifdil; M. Fahli Zatrahadi; Nur Adila Wafiqoh Zulvi
SCHOULID: Indonesian Journal of School Counseling Vol. 11 No. 1 (2026): SCHOULID: Indonesian Journal of School Counseling
Publisher : Indonesian Counselor Association (IKI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23916/086863011

Abstract

Difficulties that affect mental health among athletes are now more widely understood, but issues such as the stigma, limited resources, and constraints due to schedule all these factors prevent a regular psycho-support being provided to the athletes. Artificial intelligence (AI) and other digital technologies have appeared as alternative avenues for providing counseling, emotional support, and mental-health care for athletes, although supporting evidence in this area is currently limited and scattered. This article is an up-to-date review of literature which focuses on understanding how AI and various digital technologies are developed and used for providing mental support to athletes and the results, as well as the design factors and gaps that either promote the usage or limit its adoption. Records were taken by searching Scopus, PubMed, and ScienceDirect for studies and then a filtering was done based on predefined criteria of inclusion for eligibility. Of the 164 records that were retrieved first, 15 were marked as duplicates, 149 were checked by title, abstract, or keywords, 41 full texts were reviewed, which culminated in the final selection of 21 papers. Methodological Quality was checked using the Mixed Methods Appraisal Tool. The findings are related to a few categories such as the Chatbots and Large LanguageModel-based Advisors as counselors, e-mental health adoption, assessment and emotion regulation through artificial intelligence (AI) and AI training.
From sensing to self-regulation: a systematic review of biofeedback and neurofeedback interventions for mental health and stress regulation in athletes Nilma Zola; Ifdil Ifdil; M. Fahli Zatrahadi; Nur Adila Wafiqoh Zulvi
JRTI (Jurnal Riset Tindakan Indonesia) Vol. 11 No. 1 (2026): 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: 10.29210/30036997000

Abstract

Competitive sport puts a lot of stress on both the body and mind, and biofeedback and neurofeedback techniques are new ways to help with stress regulation and athlete mental health support by using sensors and tailoring a personal plan. This systematic review is summarizing the research evidence from these areas that show the impact on mental health aspects and psychophysiological stress regulation. Alongside modalities like HRV biofeedback and modalities of psychological indicators were also examined in the study. By applying the guidelines of a PRISMA systematic review, a Scopus database search 2015, 2026 revealed 629 records. Only one duplicate was removed, 628 titles and abstracts were checked, 31 full papers were critically reviewed, leading to 18 studies that were purely data based. The quality of those included studies was assessed by means of the Mixed Methods Appraisal Tool and their results were thematically combined. HRV biofeedback was the most commonly used technique (7 studies), followed by peripheral multi-modal biofeedback (6), combination HRV-EEG method (2), EEG/scpneurofeedback (2), and paced breathing (1). The most common positive changes were stress and cortisol levels (8), anxiety (5), attention/cognition (5), autonomic regulation (4), and recovery-stress balance (3). In general, the interventions demonstrated good results, such as the lowering of anxiety and perceived stress and the enhancement of autonomic flexibility. Nevertheless, the small number of participants, the different nature of the methods, and very few trials of this type with an active control make one cautious. Well-designed clinical trials with random allocation, appropriate sample sizes, and validated outcome measures are required.
Explainable artificial intelligence in mental health assessment: a systematic review of interpretability techniques, trust, and clinical adoption Nilma Zola; Ifdil Ifdil; M. Fahli Zatrahadi; Nur Adila Wafiqoh Zulvi
Jurnal Konseling dan Pendidikan Vol. 13 No. 4 (2025): JKP
Publisher : Indonesian Institute for Counseling, Education and Therapy (IICET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/1228100

Abstract

Machine learning is now woven into mental health assessment, and the predictive models it produces are impressively accurate. Yet the black-box nature of those models keeps raising the same worries: transparency, clinician trust, and whether they can be adopted safely in practice. Explainable AI, or XAI, is often proposed as the answer, though the evidence on where it helps and how much is still scattered. We ran a systematic review following PRISMA 2020 to pull that evidence together. A structured search of Scopus turned up 403 records. After 18 duplicates were removed, 385 went into screening; 75 full texts were assessed, and 15 studies, all published between 2021 and 2025, made it into the final pool. Study design, mental health condition, modality, XAI technique, interpretability, trust, and clinical utility were all captured and synthesised thematically. Three things stood out. First, SHAP and other post-hoc feature-attribution techniques dominated the field, appearing across work on depression, suicide risk, stress, and anxiety alike. Second, explanation quality did shape trust and acceptance, but remarkably few studies actually involved human participants. Third, heterogeneity, small samples, geographic bias, and a lack of standardised metrics all limited how far the results could be compared or translated into practice. Where should the field go next? Priorities include clinician-in-the-loop evaluation, standardised reporting of explanation quality, and equitable external validation.
Co-Authors Ifdil Ifdil M. Fahli Zatrahadi Nur Adila Wafiqoh Zulvi