ABSTRACT
The advent of artificial intelligence (AI) has revolutionised various aspects of our lives, including mental health nursing. AI-driven tools and applications have provided a convenient and accessible means for individuals to assess their mental well-being within the confines of their homes. Nonetheless, the widespread trend of self-diagnosing mental health conditions through AI poses considerable risks. This review article examines the perils associated with relying on AI for self-diagnosis in mental health, highlighting the constraints and possible adverse outcomes that can arise from such practices. It delves into the ethical, psychological, and social implications, underscoring the vital role of mental health professionals, including psychologists, psychiatrists, and nursing specialists, in providing professional assistance and guidance. This article aims to highlight the importance of seeking professional assistance and guidance in addressing mental health concerns, especially in the era of AI-driven self-diagnosis.
Subject(s)
Mental Disorders , Psychiatric Nursing , Humans , Mental Health , Artificial Intelligence , Mental Disorders/diagnosis , Health PersonnelABSTRACT
BACKGROUND: University students with depression and anxiety do not easily receive or seek treatment; therefore, internet-based interventions have been suggested to be a promising way to improve treatment accessibility and availability. However, it has not been examined whether a guided, culturally adapted, transdiagnostic, internet-based intervention is effective for treating symptoms of depression, anxiety, or both among university students in Indonesia. OBJECTIVE: This study aims to investigate the feasibility (acceptability and satisfaction, usability, and uptake) of a guided, culturally adapted, transdiagnostic, internet-based intervention among university students with symptoms of depression, anxiety, or both in Indonesia. METHODS: Students from Universitas Gadjah Mada, Yogyakarta, Indonesia, were screened for symptoms of depression, anxiety, or both, and filled online informed consent, demographic questionnaires, and a quality of life measure at pretreatment assessment (T0). Subsequently, the participants started the intervention. Seven weeks after T0, the primary outcomes of this feasibility study were analyzed at posttreatment assessment (T1) using the 8-item Client Satisfaction Questionnaire (CSQ-8) and the System Usability Scale (SUS). Mean and SDs for the CSQ-8 and SUS were calculated to examine feasibility. Within-group secondary outcomes (depression, anxiety, and quality of life) were inspected for outliers and normal distribution. Paired-sample t tests were used to investigate differences between time points of secondary outcomes. A mixed-method approach of quantitative and qualitative analyses was adopted. Both the primary and secondary outcomes were additionally explored with an individual semistructured interview and synthesized descriptively. RESULTS: A total of 50 participants completed the intervention. We found a moderate to high level of satisfaction and acceptability, a slightly below-average level of desirable usability (≥70), and an adherence rate of 52% which was higher than expected given the novelty of the intervention. Results for the secondary outcomes indicated a decrease in depression and anxiety. For depression, the overall mean difference between the 2 time points for depression was 3.92 (95% CI 2.75-5.1; Hedges g 1.15; P<.001). For anxiety, the overall mean difference between the 2 time points was 3.34 (95% CI 2.06-4.61; Hedges g 1.02; P<.001). Further, a moderate effect in improving quality of life was found (g=0.50). Overall, participants were positive about the online intervention and ECoaches (online guidance), and they found the intervention to be culturally appropriate. CONCLUSIONS: A culturally adapted, transdiagnostic, internet-based intervention appears to be acceptable and feasible for reducing symptoms of depression, anxiety, or both, and increasing quality of life in university students in Indonesia. Future studies should include a randomized controlled trial to assess the effectiveness of such interventions as they may supplement existing counseling services in universities, reduce the treatment costs, and maximize treatment accessibility in low-resourced settings. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1016/j.invent.2018.11.002.
ABSTRACT
BACKGROUND: There is an increasing prevalence of mental health problems among university student populations. In Indonesia, treatment rates are low among university students because of the high cost of treatment, stigma and the limited availability of mental care services. Internet-based interventions have been found to be effective in treating anxiety and depression in Western countries. However, little is known about the effectiveness of Internet-based interventions in low- and middle-income countries (LMICs) such as Indonesia. In this paper, we describe how we culturally adapted an Internet-based intervention to meet the needs of Indonesian students with depression and anxiety based on the theoretical framework of Barrera et al. (2013). METHOD: We culturally adapted a Western Internet-based student intervention for depression and anxiety. This intervention consists of 8 guided online sessions. 50 students from Universitas Gadjah Mada Yogyakarta who have mild to moderate depression or anxiety as assessed with the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7), will participate in a feasibility study in which we will test participants' satisfaction, system usability and uptake. Secondary outcomes include assessment of participants' depression, anxiety and quality of life. Outcomes will be measured pre and post intervention. DISCUSSION: The present paper presents the protocol of a pilot study aimed at assessing the feasibility and acceptability of a culturally adapted intervention for Indonesian university students with depression and anxiety. The results from the feasibility study will further guide the development of the intervention and may inform the protocol of a future randomized controlled trial (RCT) examining the effectiveness of the Internet-based intervention.
