Search Results (7)

Artificial intelligence (AI)-powered mental health chatbots have evolved quickly as scalable means for psychological support, bringing novel solutions through natural language processing (NLP), mobile accessibility, and generative AI. This systematic literature review (SLR), following PRISMA 2020 guidelines, collates evidence from 25 published, peer-reviewed studies between 2020 and 2025 and reviews therapeutic techniques, cultural adaptation, technical design, system assessment, and ethics. Studies were extracted from seven academic databases, screened against specific inclusion criteria, and thematically analyzed. Cognitive behavioral therapy (CBT) was the most common therapeutic model, featured in 15 systems, frequently being used jointly with journaling, mindfulness, and behavioral activation, followed by emotion-based approaches, which were featured in seven systems. Innovative techniques like GPT-based emotional processing, multimodal interaction (e.g., AR/VR), and LSTM-SVM classification models (greater than 94% accuracy) showed increased conversation flexibility but missed long-term clinical validation. Cultural adaptability was varied, and effective localization was seen in systems like XiaoE, okBot, and Luda Lee, while Western-oriented systems had restricted contextual adaptability. Accessibility and inclusivity are still major challenges, especially within low-resource settings, since digital literacy, support for multiple languages, and infrastructure deficits are still challenges. Ethical aspects—data privacy, explainability, and crisis plans—were under-evidenced for most deployments. This review is different from previous ones since it focuses on cultural adaptability, ethics, and hybrid public health incorporation and proposes a comprehensive approach for deploying AI mental health chatbots safely, effectively, and inclusively. Central to this review, symmetry is emphasized as a fundamental idea incorporated into frameworks for cultural adaptation, decision-making processes, and therapeutic structures. In particular, symmetry ensures equal cultural responsiveness, balanced user–chatbot interactions, and ethically aligned AI systems, all of which enhance the efficacy and dependability of mental health services. Recognizing these benefits, the review further underscores the necessity for more rigorous academic research into the development, deployment, and evaluation of mental health chatbots and apps, particularly to address cultural sensitivity, ethical accountability, and long-term clinical outcomes. Full article

Anxiety disorders are among the most prevalent mental health conditions globally, causing significant personal and societal burdens. Traditional therapies, while effective, often face barriers such as limited accessibility, high costs, and the stigma associated with seeking mental health care. The emergence of artificial intelligence (AI) chatbots offers a novel solution by providing accessible, cost-effective, and immediate support for individuals experiencing anxiety. This comprehensive review examines the evolution, efficacy, advantages, limitations, challenges, and future perspectives of AI chatbots in the treatment of anxiety disorders. A methodologically rigorous literature search was conducted across multiple databases, focusing on publications from 2010 to 2024 that evaluated AI chatbot interventions targeting anxiety symptoms. Empirical studies demonstrate that AI chatbots can effectively reduce anxiety symptoms by delivering therapeutic interventions like cognitive-behavioral therapy through interactive and personalized dialogues. The advantages include increased accessibility without geographical or temporal limitations, reduced costs, and an anonymity that encourages openness and reduces stigma. However, limitations persist, such as the lack of human empathy, ethical and privacy concerns related to data security, and technical challenges in understanding complex human emotions. The key challenges identified involve enhancing the emotional intelligence of chatbots, integrating them with traditional therapy, and establishing robust ethical frameworks to ensure user safety and data protection. Future research should focus on improving AI capabilities, personalization, cultural adaptation, and user engagement. In conclusion, AI chatbots represent a promising adjunct in treating anxiety disorders, offering scalable interventions that can complement traditional mental health services. Balancing technological innovation with ethical responsibility is crucial to maximize their potential benefits. Full article

Grief is a natural and self-limited adaptation process to a new reality that emerges after a significant loss (whether real or perceived), with a broad variety of manifestations that exert an impact on a grieving person’s health. The study aim was to synthesize the evidence available about the interventions carried out by Primary Health Care nurses, by means of an individual approach to reduce maladaptive grief or maladaptive grief risk. A scoping review was conducted (November and December 2023) through searches in Medline, Cinahl, Web of Science, ProQuest and Scopus using MeSH terms combined with Booleans. Primary research of any design in adult people undergoing grief situations and receiving professional assistance by nurses in the primary, home and community care contexts published after 2009 in English, Spanish or Portuguese languages were included. Excluded publications were those conducted in in-hospital clinical settings and which did not correspond to research designs or the gray literature. The screening process was carried out by two reviewers using the appropriate JBI critical appraisal tools for each design and discrepancies were resolved by a third reviewer. A total of n = 10 studies were included (n = 4 qualitative, n = 2 RCTs, n = 1 quasi-experimental, n = 2 cross-sectional observational, and n = 2 mixed methods). The qualitative studies identified topics and subtopics of professionals’ and families’ experiences of grief. The observational studies analyzed symptoms and factors associated with the grieving process. Interventions consisted of cognitive–behavioral therapies delivered by psychological specialists who assessed the severity of grief in a range of cultural contexts using different instruments. The evidence retrieved from the studies that address the reduction in maladaptive grief or maladaptive grief risk is not conclusive. There is a need to increase both the number and the methodological quality of studies assessing the effectiveness of Nursing care in Primary Health Care for individuals experiencing maladaptive grief or maladaptive grief risk. Further research should focus on experimental studies, developing specific interventions conducted by nurses to address individual’s grief and prevent maladaptive grief. Full article

Objective: The present study explores the cross-cultural validation of neuropsychological assessments and their clinical applications in cognitive behavioral therapy (CBT), focusing on culturally adapted CBT (CA-CBT) across diverse populations and settings. Methods: Following the PRISMA guidelines, a comprehensive search was conducted in multiple academic databases, including PubMed, PsycINFO, Scopus, and Web of Science. Keywords related to cognitive behavioral therapy, cultural adaptation, and specific populations were used. The inclusion criteria encompassed randomized controlled trials (RCTs) and pilot studies that assessed CA-CBT for various mental health conditions. Results: The review included studies involving Chinese Americans, Latino caregivers, Syrian refugees, Jordanian children, Malaysian Muslims, Afghan refugees, Iraqi women, Japanese children and adolescents, and Tanzanian and Kenyan children. CA-CBT demonstrated significant effectiveness in reducing symptoms of depression, anxiety, PTSD, and psychosis. For instance, research has shown that CA-CBT is more effective than standard CBT in reducing depressive symptoms among Chinese Americans and in significantly lowering PTSD symptoms in Syrian refugee women. This method has been well-received and is feasible for use in diverse populations, such as Jordanian children and Afghan refugees. The long-term benefits are promising, with sustained improvements being reported in various studies. Additionally, digital and remote delivery methods have demonstrated potential for expanding the accessibility of CA-CBT. Conclusions: CA-CBT is a valuable and effective intervention for diverse cultural populations, significantly improving mental health outcomes. However, future research must address limitations such as small sample sizes, short follow-up periods, and variability in assessment tools. Future studies should include larger and more diverse sample sizes, longer follow-up periods, rigorous control groups, and comprehensive outcome measures to further validate and enhance the application of CA-CBT across different cultural contexts. Full article

Human-computer interaction (HCI) has contributed to the design and development of some efficient, user-friendly, cost-effective, and adaptable digital mental health solutions. But HCI has not been well-combined into technological developments resulting in quality and safety concerns. Digital platforms and artificial intelligence (AI) have a good potential to improve prediction, identification, coordination, and treatment by mental health care and suicide prevention services. AI is driving web-based and smartphone apps; mostly it is used for self-help and guided cognitive behavioral therapy (CBT) for anxiety and depression. Interactive AI may help real-time screening and treatment in outdated, strained or lacking mental healthcare systems. The barriers for using AI in mental healthcare include accessibility, efficacy, reliability, usability, safety, security, ethics, suitable education and training, and socio-cultural adaptability. Apps, real-time machine learning algorithms, immersive technologies, and digital phenotyping are notable prospects. Generally, there is a need for faster and better human factors in combination with machine interaction and automation, higher levels of effectiveness evaluation and the application of blended, hybrid or stepped care in an adjunct approach. HCI modeling may assist in the design and development of usable applications, and to effectively recognize, acknowledge, and address the inequities of mental health care and suicide prevention and assist in the digital therapeutic alliance. Full article

Aims: Previous research has shown the efficacy of culturally adapted Cognitive Behavioral Therapy (CA-CBT) in reducing depression, yet its effect on increasing sexual satisfaction is not well documented. In this study, an embedded randomized controlled trial design was used to examine the effect of group and individual CA-CBT on depression and sexual satisfaction among perimenopausal women. Method: A total of 64 depressed Iranian perimenopausal women were randomly assigned to two formats of treatments; sixteen sessions of group CA-CBT and eight sessions of individual CA-CBT, as well as a waitlist control group. Depression and sexual satisfaction were measured using BDI-II and ENRICH, respectively, at T1 (pre-treatment), T2 (post-treatment) and T3 (follow-up). Results: Repeated measures ANOVA indicated that the women who underwent both group and individual CA-CBT had effectively reduced depression and increased sexual satisfaction between pre-treatment and post-treatment, and it was sustained after six months of follow-ups with large effect sizes of significant differences (p < 0.001), but the control group did not. Conclusion: The results showed promising evidence for the efficacy of both treatment groups of CA-CBT for depression and sexual satisfaction among perimenopausal women. The population mental health burden among perimenopausal women may likely be reduced by propagating this effective treatment. Full article

Background: Globally, paternal depression is a neglected and under-researched area. Aims: To feasibility test Learning Through Play Plus Dads (LTP+ Dads), a group parenting psychoeducation program adapted for depressed Pakistani fathers of children under 3 years of age. Methods: Fathers with depression were recruited in Karachi, Pakistan, for a pre-post feasibility study. Ten sessions of group LTP+ Dads were offered over three months. Clinical assessments were administered at baseline, three (end of intervention), and six (follow-up) months and included the Edinburgh Postnatal Depression Scale, 17-item Hamilton Depression Rating Scale, Brief Disability Questionnaire, Multidimensional Scale of Perceived Social Support, Euro-Qol-5 Dimensions, Rosenberg Self-esteem Scale, Parenting Stress Index, and Knowledge, Attitude and Practices questionnaire. Results: Of the 78 fathers approached, 34 consented to screening and 18 were eligible to participate. Participants had a mean age of 33 years, with a mean of 3.61 children. Most were unemployed and were from low-income households with low education backgrounds. The intervention was feasible and acceptable based on a recruitment rate of 100% of eligible participants and a 100% attendance rate for five of the 10 sessions. Fathers showed, on average, a reduction in depressive symptoms, an increase in most areas of knowledge, and positive attitudes about child development. Perceived social support, self-esteem, and functioning scores also increased. Conclusions: A low-cost, culturally adapted group intervention was found to be feasible and acceptable. Changes in depression, parenting-related, and other outcomes are promising and inform a future larger trial. Trial Registration: The trial was registered on Clinicaltrials.gov on 9 December 2020 (identifier: NCT04660253). Full article