Artificial Intelligence (AI) is advancing rapidly in behavioral health, promising high-quality, affordable, and accessible care. These tools are often framed as solutions to longstanding gaps in service access. At the same time, governments in the United States have increasingly turned to litigation and policy tools to regulate technology platforms as public and policy perspectives have shifted toward recognizing potential harms. This tension underscores the need for thoughtful regulatory approaches to AI, yet regulatory systems have struggled to keep pace as AI enters the behavioral health domain. This paper presents a policy case analysis of a state office of artificial intelligence that recently developed initial regulatory guidance for behavioral health. Drawing on first-hand accounts from policy leaders involved in the regulatory process, supplemented by publicly available legislation and guidance documents, the analysis reconstructs key activities, decision points, and tradeoffs underlying the guidance. We discuss three potential regulatory pathways: (1) market-based approaches with minimal regulation, (2) risk-only regulation focused on harm avoidance, and (3) risk-benefit regulation aimed at maximizing benefits while minimizing harm. The paper identifies key questions regulators face, tensions among stakeholder groups, and practical strategies one state used to develop initial regulatory guidance.
This study examines how Black male clinical social workers navigate social media in their professional lives, drawing on focus group data from 21 licensed practitioners across the United States. Using the Black Perspective and mass communication theory as guiding frameworks, the research explores how digital platforms function as spaces of professional connection, advocacy, and community building while also exposing clinicians to racialized scrutiny, emotional burden, and heightened surveillance. Findings reveal that participants strategically use social media to counter professional isolation and access culturally aligned resources, yet they simultaneously manage fears of reputational harm, workplace consequences, and the amplification of racial stereotypes. The study argues that social work education must integrate culturally responsive digital literacy into curricula, preparing practitioners to critically engage online spaces where clients increasingly seek mental health information and support. Specific recommendations address course content, field education, accreditation standards, and continuing education, positioning practitioners as experts whose digital navigation strategies should inform curriculum development.
The COVID-19 pandemic created significant challenges for human services leaders, including a pivot to technology, as public health restrictions disrupted face-to-face service models. These challenges were exacerbated for social enterprise leaders, whose organizations' hybrid nature requires balancing social mission and market-driven operational demands. While the human services organizations' use of technology is documented, less is known about how human services and in particular social enterprise leaders guided technological shifts. Adopting an exploratory qualitative approach, this study draws on semi-structured interviews with ten regional Australian social enterprises leaders and an institutional logics perspective to analyze how they navigated their complex organizational demands and shaped technological choices during the COVID-19 pandemic. The findings reveal heterogeneous responses, where while a minority prioritized a single logic to guide their technological choices of adoption, adaptation, and, in one case, refusal, most were not constrained by the competing demands of their hybrid nature. Instead, the presence of multiple logics served as a framework for action, transforming a disruptive situation of ambiguity into a complex interplay of value-driven technological decisions. By mapping the landscape, the study contributes to a deeper understanding of technological choices and the leadership experience in complex human services settings, particularly within resource-constrained contexts.
Child protection informatics (CPI) is critical in our increasingly digitalized society and social services. This scoping review, following Joanna Briggs Institute (JBI) methodology, mapped CPI research from the last decade within institutional child protection systems. Seven databases were searched for peer-reviewed English articles, identifying 80 studies for analysis using a Health and Human Services Informatics (HHSI) paradigm. Research predominantly focused on the Use of Information and Communication Technology (ICT) (n = 34), encompassing diverse applications from e-services to AI-driven tools. Other HHSI research areas included Steering and Organizing of Information Management in Work Processes (n = 17), Knowledge Management and Informatics Competencies (n = 16), and Data Models and Structures (n = 13). The findings highlight the field's active engagement with technological advancements, particularly in ICT. However, the review also identifies a need for deeper inquiry into foundational CPI principles and broader competency development to enhance the effective and ethical use of information and technology in safeguarding vulnerable children.
This pilot study investigates the feasibility of an AI-enhanced, self-paced Narrative Therapy (NT) training platform designed to address barriers such as cost, availability, and geographic constraints for beginners. The objectives were to evaluate AI-simulated conversations as a learning tool, examine the reliability of AI-based assessments, and assess participant outcomes. A single-group pretest-posttest design was implemented with 35 participants over one week. The platform incorporated AI-generated rubrics, self-report measures, and qualitative feedback. Results indicated that the AI assessments demonstrated substantial reliability and validity. Participants showed moderate to high alignment with NT principles, reported above-average confidence in using NT, showed greater awareness of their strengths, and expressed positive views regarding the AI simulations and feedback. The discussion emphasizes the potential of generative AI in facilitating dialogic learning, supporting reliable skill assessment, and enabling scalable delivery. Findings suggest that this approach may democratize access to NT training and could be extended to other therapeutic modalities through multimodal AI integration.
This study, guided by six research questions and six hypotheses, adopted cross sectional survey research design to investigate the influence of socio-demographic variables on the perception of undergraduates toward the efficacy of cyber counseling platforms in managing mental health. The population of the study included 65,900 undergraduates in the federal and state-owned universities in Cross River State, Nigeria. A sample of 800 students was selected through stratified and simple random sampling techniques. An instrument entitled "Questionnaire on Perceptions towards Cyber Counseling Platforms" (QPCCP) was designed by the researchers for data gathering. The instrument was validated, and had a Cronbach alpha reliability of 0.79. The generated data was analyzed using mean, standard deviation, population t-test, independent t-test, ANOVA and Scheffe's post hoc test. The results of the study indicated that sex, year of study, area of discipline and age of the students had significant influence, while ownership of university showed no significant influence, on the perception of undergraduates toward cyber counseling. It was therefore recommended, amongst others, that considering that undergraduates have positive perception toward cyber counseling, counselors should create awareness, encourage and guide students to utilize cyber counseling platforms in attending to their mental counseling needs.
There is growing interest in using digital technology like welfare technology (WT) to support older adults (aged 75+) to age in place, particularly in Nordic countries. This cross-sectional survey study (n = 414), conducted in 18 Swedish municipalities, used descriptive statistics and binary logistic regression to examine: user experiences related to satisfaction with WT, as well as users' expectations and perceived needs for WT related to safety, independence, activity, and participation. Results indicate that appealing aesthetics, user involvement in WT-related decisions, and confidence in use are central to WT satisfaction, yet remain insufficient for many survey respondents. Survey respondents with poorer health reported lower fulfillment expectations for WT, and those with lower economic status expressed less fulfillment of needs. Moreover, the specific WT acquired by participants provided limited support for older adults' daily activities and participation, pointing to an important area for future research to address. These results reveal a clear misalignment between WT outcomes and Swedish policy objectives, as well as broader digital policy ambitions across the Organisation for Economic Co-operation and Development (OECD) countries. The study highlights the need for targeted improvements to enhance WT's usability and impact, which should be carefully addressed by policymakers, technology developers, and care providers aiming to strengthen aging-in-place strategies.
Cyberbullying is a major concern in youth digital environments. Using PRISMA-guided procedures and Walker and Avant's concept analysis framework, we systematically reviewed definitions of cyberbullying published between 2000 and 2024. Searches across four databases (PubMed, PsycINFO, Web of Science, and Scopus) identified 1,536 records. After duplicate removal and multistage screening, 43 peer-reviewed studies met the final inclusion criteria. Across these studies, eight recurrent attributes were coded: electronic or digital mediation, aggressive behavior, willfulness or intentionality, repetition or persistence, harm, accessibility or ubiquity, anonymity, and power imbalance. The findings show substantial variation in how several attributes, particularly intentionality, repetition, anonymity, and power imbalance, were defined or emphasized across studies. Based on these patterns, this review offers an interpretive refinement of cyberbullying's defining attributes to better reflect contemporary digital environments. By documenting definitional change over time, this study provides a clearer conceptual foundation for future youth-focused research, policy, and practice.
The COVID-19 pandemic has favored the rapid adoption of digital solutions into mental healthcare services. This study investigates the competency of mental healthcare providers delivering eMental Health services in Kosovo, exploring advantages, disadvantages, and factors influencing remote service implementation. Employing a convergent parallel design mixed method, the study involved 197 mental healthcare providers (57% female, 42% male) who responded to demographic questions and the eHealth Competency Scale; and 24 mental healthcare providers (18 psychologists, 6 psychiatrists) who participated in semistructured interviews. Quantitative data were analyzed using IBM SPSS, while inductive thematic analysis identified implications of delivering remote services by categorizing themes extracted from the interviews. The results indicate that mental healthcare providers are competent in delivering remote service. Notably, psychologists and psychiatrists exhibit significant differences in digital tool usage (Z = -3.503; p = .001), as well as females and males in self-efficacy (Z = -2.29; p = .02) and digital tool usage (Z = -3.14; p = .02). Also, 80.1% of study participants reported a lack of guidance for digital tools, and 62.8% noted the absence of established digital care standards. Qualitative analysis yields five major themes: (1) (In) Efficiency, (2) Therapist skills, (3) Relationship with client, (4) Ethical/legal considerations, and (5) (In) capacities to deliver remote services-highlighting the absence of guidelines and standards as the most challenging part of assistance. The implementation of eMental healthcare encounters enduring and significant challenges. Rather than serving as a replacement for face-to-face care, it is imperative to recognize eMental healthcare as a complementary dimension of client/patient care.
Older adults often receive services from multiple organizations, yet a lack of coordination can lead to fragmented care. This study examines how improved data sharing can support more integrated service delivery. Based on interviews with frontline workers in aging-related organizations in Singapore, we identified common service needs and recurring patterns in how client information is exchanged. From these findings, we developed a conceptual framework in the form of an ontology that enables organizations to categorize, structure, and share client data securely and consistently. The framework provides a foundation for improving coordination across diverse actors while protecting client privacy. Although grounded in the context of aging services, the approach has broader relevance for networks seeking to streamline service delivery and strengthen cross-organizational collaboration.
This article provides an analytical approach and model for mapping the integration of artificial intelligence (AI) technologies into clinical supervision (CS) in social work. With a focus on the evolving work roles of clinical supervisors involving AI technologies, this study offers a methodical approach for understanding the current landscape and anticipating the future direction of AI technologies in CS. This article presents an environmental scan of current and emergent AI technologies that are transformative for CS and a use case-based analysis that maps these AI technologies to the evolving work roles of clinical supervisors. Usage descriptions are provided to convey the actual and potential impacts of these AI technologies on the work roles of clinical supervisors. This study aims to support future critical research as the field of social work navigates the evolving entanglements of AI technologies with clinical social work practice. The analytical model offers a foundational resource for advancing future research on the implications of the integration of AI technologies into CS. It is intended to provide a starting point that can be used and updated by researchers in agile ways to map and analyze the evolving interplay of AI technologies and CS in social work.
Social work programs lack systematic methods to align curricula with employer expectations, typically relying on advisory input and alumni surveys rather than direct analysis of workforce requirements. This paper presents a case study demonstrating how one MSW program used artificial intelligence tools to generate organizational intelligence from job posting data for curriculum planning. Using a locally deployed language model, we classified over 40,000 job postings for MSW relevance and alignment with eight practice specializations, then extracted skills, therapeutic modalities, and technology competencies. Interpersonal Practice dominated the employment landscape, followed by Children, Youth, and Families. Clinical Assessment and Case Management emerged as cross-cutting competencies. Macro-level specializations showed co-occurrence patterns among partially aligned positions that largely disappeared among positions requiring MSW credentials specifically. Trauma-informed care appeared in management and evaluation roles, reflecting its expansion from clinical modality to organizational framework. The methodology demonstrates a transferable approach that other programs can adapt for strategic planning, and the findings illustrate the type of intelligence such analysis can yield. The patterns identified entered faculty deliberation as one input among many, interpreted by stakeholders with contextual knowledge no dataset can fully capture.
The mental health and well-being of staff working in healthcare settings (SWHS) is an urgent global public health priority and an issue of significant importance to society. This study assessed the preliminary effectiveness of 'OK Positive', a new personalized mental health and well-being app (MHapp), aimed at improving well-being, psychological flexibility, burnout, secondary traumatic stress, and compassion satisfaction in SWHS. Participants were provided access to the MHapp and prompted to complete online questionnaires every three days, at 30 and 60 days, to evaluate the impact of the MHapp. Out of 119 initial participants, only 22 completed the follow-up measures, yielding a response rate of 18%. SWHS initially self-reported moderate levels of burnout and compassion satisfaction, and low levels of secondary traumatic stress. Descriptive analyses revealed mixed results regarding the MHapp's preliminary effectiveness and acceptability, highlighting challenges in user retention. While the MHapp showed preliminary support for improving well-being among a motivated subset of users, the study's limitations emphasized the need for further research and organizational support. Therefore, future research is required to continue exploring the efficacy of interventions to meet the well-being and mental health needs of a diverse range of SWHS.
The provision of social services to people with intellectual disabilities by information and communication technology is now widespread. Its universal application during the COVID-19 pandemic allowed us to examine the challenges encountered and offer practical strategies and guidelines. Focus group sessions with 17 social workers and 12 carers supporting people with intellectual disabilities were conducted. Qualitative thematic analysis was performed. Three main themes emerged from the analysis. First, there are specific characteristics and needs that require additional training and support should be recognized. Second, sensorimotor stimuli are essential when communicating with people with intellectual disabilities, and thus human resources may be irreplaceable to varying degrees. Finally, the digital community should consider the universal design of information and communication technology software and devices to ensure that they are fully inclusive. This study reveals the complexity of the universal application of information and communication technology in social services for those with intellectual disabilities. Hence, our research team, which is composed of various professionals, thus provided operational recommendations, preventing the risk of 'othering' people with intellectual disabilities. Further research to assess service delivery with a group of digital natives will be useful.
Open-source data and tools are lauded as essential for replicable and usable social science, though little is known about their use in resource constrained human service provision. This paper examines the challenges and opportunities of open-source tools and data in human service development by using both to forecast failure to pay eviction filings in Bronx County, NY. We use zip code level data from the Housing Data Coalition, the American Community Survey 5-year estimates, and DeepMaps Model of the Labor Force to forecast rates through July 2021. We employ multilevel (MLM) and exponential smoothing (ETS) models using the R project for Statistical Computing, an oft used open-source statistical software. We compare our results to what happened during the same period, to illustrate the efficacy of the open-source tools and techniques employed. We argue open-source data and software may facilitate rapid analysis of public data - a much-needed ability in human service intervention development under increasingly constrained resources - but find public data are limited by the information they reliably capture, limiting their utility by a non-trivial margin of error. The manuscript concludes by considering lessons for human service organizations with limited analytical resources and a vested interest in low-resourced communities.
This study evaluates an online employment program by an immigrant-serving organization targeting newcomer youth, designed to foster digital marketing skills and support labor market integration through a combination of online training and an internship component. A mixed-methods approach was employed, combining quantitative surveys with program participants and qualitative insights from the program staff interviews. The findings revealed that the program successfully enhanced participants' skills and confidence, resulting in improvements in employability. Staff feedback highlighted the program's accessibility, particularly through its online delivery format, though some technological barriers, including digital literacy and platform compatibility, were identified. The results emphasize the program's positive influence on skill development and integration, while also pointing to areas for improvement in digital infrastructure and participant engagement. These findings have broader implications for similar programs in the settlement sector targeting youth, suggesting that while such programs can significantly contribute to youth integration, careful attention to digital accessibility and engagement strategies is essential for maximizing their effectiveness.
Youth in foster care have poor health outcomes related to fragmented care and lack of information sharing. Automated data exchange can improve information sharing between systems, such the healthcare system and the child welfare system. While the benefits of information exchange for youth in foster care have been previously described, this qualitative study of healthcare staff, youth, and caregivers sought to understand the implications of automated data sharing on privacy. Healthcare staff, youth, and caregivers recognized the benefits of information sharing to improve healthcare delivery and health outcomes, as long as data was accurate and timely, but also recognized the risk to privacy when information was broadly shared. Caregivers and youth worried about the possibility of generating bias by sharing social history and the invasion of privacy for sensitive topics, such as sexual and reproductive healthcare. Further research is needed to better understand the best approach to protecting privacy while pursuing the benefits of information sharing.
The emergence of interactive "digital copies" of the deceased, made possible by generative artificial intelligence, poses significant ethical and practical questions for the human services sector. This study investigates the attitudes of 404 Moscow university undergraduates (61% female; ages 18-27) toward these technologies. Through a survey conducted in Spring 2024, data were analyzed using factor and cluster analysis to identify key attitude patterns. Results reveal substantial resistance to digital immortality practices, with cluster analysis classifying 73.6% of students as "Intolerant" toward these technologies. Religiosity and death acceptance emerged as significant protective factors against adoption, while interpersonal relationships and death anxiety showed more variable associations. These findings signal that digital immortality is not a neutral tool but a potentially distressing intervention, raising critical ethical concerns for its use in human services. The widespread skepticism underscores the need for proactive policy development and practitioner guidelines to navigate this new frontier in bereavement support.
Ongoing challenges in accessing mental health services in the Philippines, such as stigma, financial constraints, transportation issues, and lack of awareness, prompted this study to explore whether Filipino adults would consider mental health chatbots as a supplementary solution to traditional counseling. A cross-sectional predictive research design was used, involving 503 Filipino adults selected through purposive sampling. Validated scales from the Unified Theory of Acceptance and Use of Technology (UTAUT) were applied to assess performance expectancy, effort expectancy, social influence, and barriers to accessing mental health services. Data were analyzed using regression analysis and the PROCESS Macro to identify predictors of behavioral intention to use chatbots. Performance expectancy was the strongest predictor, indicating that perceived effectiveness drives interest. Although interaction effects were relatively small, female millennials showed the highest openness to chatbot use. Barriers increased behavioral intention, especially among those with limited previous experiences with AI chatbots. In contrast, individuals with more and particularly negative experiences showed weaker intention. These findings suggest that mental health chatbots have potential as supportive tools for Filipino adults, but their impact depends on previous experience and perceived usefulness.
