The growing demand for accessible mental health support, compounded by workforce shortages and logistical barriers, has led to increased interest in utilizing Large Language Models (LLMs) for scalable and real-time assistance. However, their use in sensitive domains such as anxiety support remains underexamined. This study presents a systematic evaluation of LLMs (GPT and Llama) for their potential utility in anxiety support by using real user-generated posts from the r/Anxiety subreddit for both prompting and fine-tuning. Our approach utilizes a mixed-method evaluation framework incorporating three main categories of criteria: (i) linguistic quality, (ii) safety and trustworthiness, and (iii) supportiveness. Results show that fine-tuning LLMs with naturalistic anxiety-related data enhanced linguistic quality but increased toxicity and bias, and diminished emotional responsiveness. While LLMs exhibited limited empathy, GPT was evaluated as more supportive overall. Our findings highlight the risks of fine-tuning LLMs on unprocessed social media content without mitigation strategies.

We sought to demonstrate social media's efficacy as a unique data source to gain insights into people's perceptions and beliefs. Leveraging Twitter data, we built a model for identifying language markers of mental illness, including depression, anxiety and stress. We explored associations between student loans, gender, and mental health, and investigated gender-specific differences in emotions and sentiments to understand the emotional toll of these disparities. Findings suggest the need for targeted interventions for those experiencing the coexisting burden of student loan and mental illness. This study highlights social media's potential for studying human emotions and informing social work practices.

Objective. To examine if an association exists between the availability of mental health services and the sentiments expressed on Twitter by people who have social media markers that indicate they have direct experience with mental health disorders. Methods. Pearson’s Correlation was used to test an association between aggregated Twitter sentiments data for three years (2016-2018) and data from Substance Abuse and Mental Health Services Administration (SAMSHA) on the number of mental health services providers.Results. Statistically significant negative association was found between the normalized Twitter sentiments and SAMSHA counts of mental health services reported for each of the 50 States across the three years. Conclusions. Findings indicate that limited access to mental health services manifests itself on Twitter and the value of naturalistic data from Twitter to assist in identifying how people who have direct experience with mental health disorders perceive the availability of mental health services in their communities.

PURPOSE:First-generation college students (FGCS) face a myriad of sociocultural, financial, and emotional challenges that impact their educational journey. With less academic capital and lower odds of obtaining a bachelor's degree than their non-FGCS peers, understanding the factors affecting their academic success is pivotal for social work professionals aiming to provide tailored interventions and support systems. This study delved into the potential differences between these groups concerning physical activities, which are linked to learning, cognition, and overall well-being, and evaluated their influence on degree completion.METHOD:A path model was developed to analyze the relationship between degree completion, physical activities, FGCS status, and background variables, using a sample of 1,625 participants.RESULTS:The model showed a strong fit (CFI = 0.979, RMSEA = 0.055, SRMR = 0.010) and accounted for 29.5% of the variance in degree completion. Walking to school was positively associated with degree attainment. FGCS status was associated with decreased walking to school, reduced degree completion, and increased walking for exercise. An indirect effect suggested that FGCS were less likely to achieve their degree, potentially due to a greater reliance on transportation like buses or cars.DISCUSSION:The findings emphasize the critical role of campus resources for FGCS. Enhancing access to fitness centers and offering affordable housing options nearer to campus may aid FGCSs' academic success. These insights can guide social work practices, highlighting the importance of environmental factors in the academic experiences of FGCS.

Animal-Assisted Interventions (AAIs) are gaining traction in mental health services. AAIs generally involve the inclusion of a trained therapy animal to provide therapeutic comfort. It is known that college students have elevated levels of stress; Classroom Canines, an Animal-Assisted Activity (AAA), which is a type of AAI, was incorporated into a graduate-level social work classroom to reduce stress. The intervention, which included a therapy-dog-in-training, was compared to music therapy. Students in different sections of the same course (n = 36) were asked to complete surveys before and after the interventions. The pre-post scores were compared using Wilcoxon Signed Rank and paired sample t-tests. Students in Classroom Canines did experience a reduction in anxiety from pretest to posttest, however, no strong evidence was found to indicate an impact in either classroom overall. More research is needed to see if AAA can positively impact students with stress.

Anxiety is a common type of mental health condition that affects approximately one-fifth of US adults.Research indicates that the onset of mental illness and certain mental health conditions may trigger problem debt such as delinquency and default.Delinquency and default in student debts are becoming a major problem in the United States with nearly one-quarter of student loan borrowers unable to repay their loans on time.Utilizing data from the 2018 National Financial Capacity Study, the present study examined the associations among financial anxiety, student loan repayment behaviors, and financial knowledge.Results suggested a negative association between financial anxiety and on-time student loan repayment behaviors.Additional analyses showed distinct patterns among associations between financial anxiety, repayment behaviors, and financial knowledge.Findings have implications particularly for vulnerable population groups as they have disproportionately high amounts of debts, lack access to mental health services, and face more repayment issues compared to other socioeconomic groups.

PURPOSE:The review had two purposes. The first was to examine the nature and extent of published literature on student loan and the second was to systematically review the literature on student loans and mental health. MATERIALS AND METHODS:Data from academic databases (1900-2019) were analyzed using two methods. First, topic modeling (a text-mining tool that utilized Bayesian statistics to extract hidden patterns in large volumes of texts) was used to understand the topical coverage in peer-reviewed abstracts (n = 988) on student debt. Second, using PRISMA guidelines, 46 manuscripts were systematically reviewed to synthesize literature linking student debt and mental health. RESULTS:A model with 10 topics was selected for parsimony and more accurate clustered representation of the patterns. Certain topics have received less attention, including mental health and wellbeing. In the systematic review, themes derived were categorized into two life trajectories: before and during repayment. Whereas stress, anxiety, and depression dominated the literature, the review demonstrated that the consequences of student loans extend beyond mental health and negatively affect a person's wellbeing. Self-efficacy emerged as a potential solution. DISCUSSION AND CONCLUSION:Across countries and samples, the results are uniform and show that student loan burdens certain vulnerable groups more. Findings indicate diversity in mental health measures has resulted into a lack of a unified theoretical framework. Better scales and consensus on commonly used terms will strengthen the literature. Some areas, such as impact of student loans on graduate students or consumers repaying their loans, warrant attention in future research.

We examined patterns and sociodemographic correlates of financial characteristics and behaviors among emerging and young (18-34-year-old) student loan borrowers. Employing latent class regression modeling on a subset of the 2018 National Financial Capability Study (N =1,490), we explored a heterogeneous constellation of patterns in these borrowers' financial characteristics and behaviors. Results indicated four distinct classes of financial characteristics and behaviors: financially strained (20.8%), financially balanced (29.2%), financially capricious (20%), and financially vulnerable (30.1%). Gender, race, and education were found to be consistently correlated with financial characteristics and behavior patterns. Marital status, income, employment, and welfare services use were found to be associated with some but not all latent classes. Findings have implications for financial planners and counselors and can help them detect distinct patterns of financial characteristics and behaviors among young student loan borrowers and customize their intervention programs to mitigate the negative consequences of student loan delinquency and default.

PURPOSE:The primary objective of this study was to identify patterns in users' naturalistic expressions on student loans on two social media platforms. The secondary objective was to examine how these patterns, sentiments, and emotions associated with student loans differ in user posts indicating mental illness.MATERIAL AND METHOD:Data for this study were collected from Reddit and Twitter (2009-2020, n = 85,664) using certain key terms of student loans along with first-person pronouns as a triangulating measure of posts by individuals. Unsupervised and supervised machine learning models were used to analyze the text data.RESULTS:Results suggested 50 topics in reddit finance and 40 each in reddit mental health communities and Twitter. Statistically significant associations were found between mental illness statuses and sentiments and emotions. Posts expressing mental illness showed more negative sentiments and were more likely to express sadness and fear.DISCUSSION AND CONCLUSION:Patterns in social media discussions indicate both academic and non-academic consequences of having student debt, including users' desire to know more about their debts. Interventions should address the skill and information gaps between what is desired by the borrowers and what is offered to them in understanding and managing their debts. Cognitive burden created by student debts manifest itself on social media and can be used as an important marker to develop a nuanced understanding of people's expressions on a variety of socioeconomic issues. Higher volumes of negative sentiments and emotions of sadness, fear, and anger warrant immediate attention of policymakers and practitioners to reduce the cognitive burden of student debts.

AbstractBackground and Objectives: The present study is a systematic scoping review to determine the extent and nature of the peer-reviewed research concerning financial exploitation of older adults in the United States (U.S.). The rising population of older adults means financial exploitation is a major challenge that will grow in the future. Recent estimates suggest that older adults already lose billions of dollars in personal wealth every year.Research Design and Methods: The review was structured by the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol (PRISMAP). Five academic databases - Web of Science, EBSCO, PyscINFO, Social Services Abstracts, and PubMed - as well as Google Scholar were searched using variations of the phrases “financial exploitation AND older adults”.Results: Fifty-two peer-reviewed papers were identified and categorized into nine subject areas: (1) profiles of older adults who experienced financial exploitation, (2) measuring financial exploitation, (3) profiles of perpetrators, (4) impacts of financial exploitation, (5) prevalence estimates, (6) racial, ethnic, and cultural differences, (7) conceptual models and frameworks, (8) stakeholders’ perceptions, and (9) legal and non-legal services.Discussion and Implications: The review found a limited number of peer-reviewed papers focused on financial exploitation of older adults (n=52), which were spread across a large number of subject areas (n=9). Yet critical gaps remained in the literature, including a lack of research about the effectiveness of legal and non-legal services, the potential role of systemic racism, and financial exploitation via technology.

Photography is routinely used to expose the dark side of mental illness and mental health care. Even when the intentions are good, the voyeuristic results portray patients and their settings as alien or frightening. In contrast, we use photography to reflect successful treatment, a theme too often absent from the discourse about mental health care and nearly unseen in the 125 plus years of photography related to mental illness. A sample of patients and staff who participated in a study funded by the National Institute of Mental Health (NIMH, R34 MH074640-01A2) was photographed by the two authors. The purpose of the photographs was to create a visual record of the positive outcomes experienced by the patients receiving services at community mental health agencies (CMHAs). Portraits and quotes from the photo sessions offer a counter perspective to the broadly negative impression the general public has of mental health services.

We compare African-American and White clients receiving services at 13 rural and semi-rural community mental health agencies (CMHAs) and the impact of Medicaid on the use of crisis and outpatient services. SEM was utilized to model the indirect effect of crisis services between the association of Medicaid and total hours of outpatient services. We modeled the moderating effects of race using mixture modeling and latent class. The base model showed a non-significant indirect effect between having Medicaid and total hours of services through the use of crisis services (Indirect effect = 0.01, p = .98). African-American clients who received Medicaid were more likely to use crisis services ([Formula: see text], which was associated with increased hours of outpatient services ([Formula: see text]. In general, Medicaid was not related to increase service or crisis service usage. However, African-American clients access crisis services significantly more than White clients.

Summary While the scholarly literature is abound with discussions of technology and its proliferation in different social work domains, evidence about what types of technologies are being used in various social work practice domains remains limited. The present study aimed to identify the larger trends in how technology has permeated the profession. The study sample comprised of 892 articles from a journal known for its contribution in publishing research on technology use in human services. Two methods were used—topic modeling and human-assisted analyses. Topic modeling was performed using MALLET, a machine learning tool which employs latent Dirichlet allocation over a fixed vocabulary for the corpus of text. Human-assisted analyses were performed using QDA Miner and MS-Excel to assist in the manual analyses. Findings In all, 29 topics in social work and 27 topics in technology domains were obtained. Social work education and mental health and clinical social work appeared as two of the top five social work domains in both topic modeling and human-assisted analyses. Management information system, communication technology, generic technology usage, and education technology were the top common topics in both types of analyses. Applications The present study findings have two applications. First, the descriptive analysis of technology adoption across diverse social work areas of research provides the first concrete evidence of how technology has been spread throughout social work. Second, the patterns of technology adoption across social work practice fields indicate some fields have limited research regarding technology.

Every year between 2.2% and 6.6% of older adults in the United States fall prey to different forms of financial exploitation (Deane, 2018). According to estimates, older adults lose approximately 2...

Perinatal depression among impoverished mothers adds an enormous burden to their family responsibilities, which are often further stressed by living in high-crime communities. Thirty impoverished mothers of color living with depression were interviewed about the difficulties they face raising their children. Qualitative interviews about living with depression revealed four themes: recognizing their own depression, feeling isolated, experiencing violence, and living with depression. This article examines how neighborhood and relationship violence, intermittently involved fathers, and isolation contribute to the mothers' depression. Social workers working with depressed, low-income mothers of color can benefit from understanding the mothers' lived experience and the barriers the mothers face while trying to achieve well-being for themselves and their children. This study fits within the "Close the Health Gap" area of the Grand Challenges for Social Work.

BACKGROUND:Primary health care is the key to achieve universal health coverage and health for all. The role of general practitioner is now more important than ever. Gaps exist between primary care doctors' needs and available resources. Primary care professionals everywhere in the world are expected to provide basic standard of care and fulfill the unmet needs of the population. "Needs assessment" is essential in order to develop plans that reflect clinical priorities, educational needs, patient-centered care, and effective and efficient utilization of resources. MATERIALS AND METHODS:A blend of qualitative (28 in-depth interviews) and quantitative (315 survey respondents) research helped to identify the educational gaps of general practitioners in the Asia Pacific (APAC) countries. Our in-depth methodology assessed perceived needs in order to inform educational tactics that will engage physicians and drive changes in clinical practice. Barriers to change and best practices were identified so that those barriers may be addressed by the educational strategy. RESULTS:Key findings include a strong need for education for chronic conditions such as mental illness, skin problems, diabetes, hypertension, and others. The majority of physicians indicated that they prefer education in all aspects of the disease, from screening and diagnosis to maintenance or referral. Most clinicians prefer live presentations and small groups over Internet-based formats. Sub-analysis based on demographic factors showed little differences in the perceived needs, but significant differences in barriers to best practices. CONCLUSION:"Needs assessment" gives an insight into barriers, interest, and necessity related to education and skills in primary care and the best ways to deliver it.

Informed by the Network-Episode Model, 26 African-American men with serious mental illness and 26 members of their kinship networks completed in-depth qualitative interviews about their experiences with the mental health care system to better understand racial differences in mental health care. The aim was to better understand communication among kin networks, clients, and treatment agencies with a focus on the opportunities for kinship involvement. Although kin were involved in clients' everyday lives, they were largely excluded from the community mental health agency (CMHA) and treatment decisions. In addition to incorporating family resources, enhanced efforts by CMHAs to collaborate with kin may increase knowledge about mental illness and mental health care in the African-American community, removing an impediment to service access and client retention.