Journal of evidence-based social work (2019)最新文献

Purpose: This study tested the effectiveness of a new kinship and adoption navigator program.

Materials and methods: Prior to implementation, 10 regions of a state were randomized to an intervention group or minimal intervention control group. Kinship and adoptive caregivers seeking program services were assigned to the intervention or control group based on the region in which they lived. Eligible caregivers were enrolled in the effectiveness trial and completed a survey at baseline (n = 1,728), 3 months after their intake (81% retention), and 6 and 12 months after the end of the intervention (78% and 76% retention from baseline respectively).

Results: Multi-level regressions showed that relative to the control group (n = 828), caregivers in the intervention group (n = 900) reported higher levels of satisfaction with the program's services, accessibility of community resources, and resourcefulness to meet their children's needs three months after intake. Six months after the end of services, the intervention group reported lower levels of concrete needs and better caregiver-child relationships. Favorable effects for accessibility of community resources and resourcefulness were sustained 12 months after the end of services. Effect sizes were small (g = .08 to g = .23) but statistically significant (p < .05). There were no differences in child well-being, safety nor permanency outcomes.

Discussion: Findings contribute to the limited knowledge of navigator programs with positive effects on proximal caregiver well-being outcomes for a broad population of informal kinship, formal kinship, and adoptive families.

Purpose: To analyze the knowledge, competences, and challenges of Social Work in addressing loneliness and social isolation among older people, and how these dimensions shape professional practice.

Material and methods: An exploratory mixed-methods study was conducted in Barcelona (Spain) with a total sample of 425 participants: thirty semi-structured interviews with older people, social workers and technical managers (n = 30), a questionnaire administered to practising professionals (n = 351), and four focus groups with older people, professionals and other stakeholders (n = 44). Qualitative data were analyzed inductively and quantitative data descriptively, integrating findings across three dimensions: knowledge, competences, and challenges.

Results: Social workers reported frequent contact with older adults experiencing loneliness or social isolation and demonstrated strong relational and ethical sensitivity. However, 43% felt little or not at all prepared to address these situations, and only 5.1% felt very well prepared. Although 57.3% claimed to differentiate between forms of loneliness, this ability was rarely systematic, and existential loneliness was the least recognized. The most valued competences included respect for diversity, promotion of dignity and self-determination, and support during processes of loss and life transitions. Major challenges involved limited time and resources, excessive caseloads, difficulties in reaching certain groups, insufficient training and systematization, and emotional strain linked to relational work.

Discussion: Findings reveal a gap between relational sensitivity and the lack of methodological and systematic tools for evidence-based practice.

Conclusion: Progressing toward evidence-informed relational practice requires consolidating frameworks, integrating loneliness and aging into professional training, and developing indicators legitimizing accompaniment as a measurable professional intervention.

Purpose: Investigating understudied risk and protective factors for opiate misuse among young adults who were serious violent juvenile offenders may inform prevention and intervention strategies. Young adults misuse opiates at higher rates than other age groups, with a history of serious violent juvenile offending constituting an especially high-risk population.

Materials and method: Our study uses data from the Pathways to Desistance prospective study of serious juvenile offenders, which includes participants from Phoenix, Arizona (n = 549) and Philadelphia, Pennsylvania (n = 483). Participants were enrolled between November 2000 and January 2003 and followed for seven years until April 2010. First, we conducted bivariate analyses using Chi-square analyses and simple logistic regression. Then, we conducted a multiple logistic regression model to determine whether the following variables would influence the odds of young adult opiate misuse (during wave 11) violence exposure and victimization (during wave 8), a PTSD diagnosis (during wave 9), maternal warmth (during wave 1), moral disengagement (during wave 11), identifying as White, Hispanic, and/or male.

Results: We found that young adults exposed to violence and/or victimized (OR = 1.17, p = .029), those with PTSD (OR = 4.18, p = .039), those who were morally disengaged (OR = 8.11, p = 000), those who were White (OR = 7.27, p = .000) and those who were Hispanic (OR = 2.26, p = .024) were more likely to misuse opiates. Maternal warmth did not protect against opiate misuse.

Conclusion: Our study underscores the important role trauma, particularly PTSD, plays in predicting opiate misuse.

Purpose: As generative Artificial Intelligence (AI) expands across academic and professional fields, its integration into human-centered professions like social work remains complex. Limited research explores how social workers engage with these technologies in the United States. This study examines how perceived utility and knowledge influence AI usage among social work students.

Materials and methods: A cross-sectional survey exploring attitudes toward AI, perceived utility, knowledge, and frequency of use was administered to students at a southeastern United States university. Principal Components Analysis assessed the factor structure of attitude items, and regression models determined associations with generative AI use.

Results: Principal Component Analysis identified clear dimensions of AI attitudes. Regression models indicated that both perceived utility and AI knowledge were significant predictors of use when controlling for other factors, suggesting emerging social workers engage with AI tools more frequently when they find them useful and feel knowledgeable about AI. Prior knowledge did not moderate the effect of perceived utility.

Discussion: These findings underscore the necessity to design trainings and curricula that highlight AI's practical utility while imparting knowledge on effective and ethical utilization. By fostering responsible engagement with emerging technologies, those training social workers can prepare future practitioners to navigate an evolving digital landscape while upholding core professional values.

Existing research documents that in a technologically connected society, digital media can often shift population-level ideologies surrounding social justice and social work. Additionally, evidence indicates increased digital-media consumption patterns given how marginalized individuals can face greater barriers in physical participation. Based upon such rationale, this conceptual paper investigates how artificial intelligence serving as digital-media creation tools may impact the lived experience of those who face marginalization due to age, gender, race, Indigenous ancestry, rural geography, disability, and socioeconomic status. This paper reports qualitative data from a parent study engaging with marginalized individuals (n = 8) experiencing 1) intersectional statuses associated with stigma and 2) ongoing barriers to participation in formal learning opportunities, to assess how digital media play critical roles in shaping their access to new information, beliefs, and worldviews. Informed by anti-oppressive and trauma-informed principles in social work, the research employed semi-structured interviews guided by a collaboratively developed framework - CATER (Collection, Action, Transformation, Emotion, Recommendation). Participants reported an average of more than three statuses of marginalization, and were invited to share their lived experiences - specifically informing how marginalization impacts their autonomous creation of digital media and engagements with machine-learning technologies. A sevenpart framework of AI in social-work-oriented digital media creation is thus conceptualized to consider: inclusivity in narrative dissemination; financial barriers intersecting with socioeconomic status; dominant versus counternarratives; market influences; and AI's critical shortcomings in terms of visibility and audience receptivity. Implications for social justice and social work with marginalized groups conclude this study.

Purpose: Rural communities often have a high incidence of medical and behavioral health problems along with more limited access to care. This paper describes an innovative approach to providing integrated care in rural school-based health clinics in which graduate students serve as behavioral health interns. The purpose of this manuscript is 1) to describe a model for providing school-based integrated health services in a rural community and 2) to evaluate services provided by graduate interns embedded in school-based clinics.

Materials and methods: Graduate interns completed a session checklist to track services provided in each session and collected data from participating students who received behavioral health services. Students completed the Outcome Rating Scale (ORS) after each session. Repeated measures MANOVAs were used to analyze the data for changes over time.

Results: Services provided most often by interns included assessment, engagement, positive reinforcement, coping skills, goal setting, and clinical intervention. The data suggest that students receiving at least three sessions improved over time on self-reported wellbeing.

Discussion: The results demonstrate the feasibility of providing integrated health care via school-based clinics that rely on graduate internships for behavioral health services. Challenges to implementing and sustaining school-based integrated health clinics are discussed.

Conclusion: The ongoing challenges to meeting the medical and behavioral health needs of rural communities call for innovative approaches to providing integrated care. The clinics described here responded to these challenges through teamwork and strong university-community partnerships.

Purpose: The U.S. leads the world in incarceration, and individuals with incarceration histories have poorer health outcomes. Inflammation has been proposed as a mechanism linking incarceration and chronic disease, but empirical evidence remains limited. This study tested whether inflammation mediates the association between incarceration and chronic health conditions.

Materials and methods: Data were drawn from the Health and Retirement Study (HRS). Incarceration history was assessed via self-report of spending ≥3 consecutive days in jail or prison. Inflammation was measured using C-reactive protein (CRP). Chronic health conditions were assessed as both an index of six diagnoses (heart disease, hypertension, lung disease, diabetes, cancer, stroke) and individual conditions. Regression-based mediation models with bootstrapping were used to examine indirect effects of incarceration through CRP, adjusting for demographic and health behavior covariates. Analyses accounted for the HRS complex survey design.

Results: Participant history of incarceration associated with higher CRP and higher CRP associated with more chronic conditions. Bootstrapping confirmed significant mediation. Further testing indicated that cancer, stroke, and lung disease may be main drivers of this effect.

Discussion: Findings suggest incarceration associates with chronic disease risk partly through elevated inflammation. While direct effects between incarceration and specific health conditions were inconsistent, the association between incarceration and CRP highlights inflammation as a plausible indirect pathway.

Conclusion: Incarceration may increase the risk for multiple chronic health conditions by elevating inflammation, particularly the risk of cancer, stroke, and lung disease. Addressing carceral healthcare quality and strengthening community supports are critical roles for health professionals and social workers.

Purpose: This study explores how artificial intelligence (AI) can be integrated into social work practice by examining both its potential opportunities and associated challenges. The research aims to determine how AI technologies can support social workers in delivering more effective, accessible, and ethical services, and to identify the professional training needs that may arise from this digital transformation.

Method: Using an interpretative phenomenological approach grounded in human-centered and ethical social work principles, data were collected through semi-structured interviews with 23 social workers from diverse fields in Türkiye and analyzed thematically with MAXQDA.

Findings: Participants identified several advantages of AI integration, including enhanced risk analysis, rapid intervention capacity, improved service quality, cost-effectiveness, and easier access for disadvantaged populations. However, they also emphasized challenges such as the loss of human-centered approaches, ethical and privacy risks, insufficient technological infrastructure, and potential employment concerns.

Originality and contribution: The study contributes to the limited qualitative research on AI in social work by presenting practice-based insights from professionals. It emphasizes the need for comprehensive, ethics-oriented AI education and policy development to ensure technological innovation aligns with the profession's humanistic values. It also highlights the importance of addressing conceptual tensions between technological innovation and human-centered practice, offering insights to inform AI-focused training and education in social work.

Conclusions: While AI offers significant opportunities for innovation and inclusion, its integration must be guided by ethical standards, professional training, and adequate infrastructure to ensure that it complements rather than replaces the relational foundations of social work.

Building upon existing literature on physical barriers experienced by higher-needs patients and marginalized communities, this paper presents a targeted analysis of qualitative data under a parent study on healthy cities. To optimize equity in access to health care as one of the many life opportunities affected by transportation, semi-structured interviews were conducted with community members reflecting diverse statuses of marginalization in addition to both mental and physical health challenges (n = 17), supplemented in dialogue with global policymakers (n = 5). Participant responses reveal how transportation time, costs, and risk strongly determine the actual confines of the world where they experience sufficient autonomy to access life opportunities. How these daily opportunities intersect with research on food deserts, education deserts, childcare deserts, and health care deserts indicates that physical barriers can emerge as a baseline consideration affecting ongoing experiences of socio-structural determinants. Most notably, the act of accessing care in itself, when involving transportation, can also present its own health risks requiring further integrated care services - given the body of evidence on injury, crime-related mental health stressors for marginalized groups, in addition to longitudinal public health concerns related to cardiovascular health and climate change risks. Access to both mental health care and physical health care can both be linked to urban development, intersecting with socioeconomic positionality amidst urban-rural environments - as physical access emerges with significant intersections with social work that is sensitive to the housing and employment needs of families. A four-part framework for integrated health care toward equitable outcomes in social work concludes the study.

The purpose of this introductory article is three-fold: (1) to share with the reader the inspiration for the present special issue; (2) to describe for the reader the array of articles published in this special issue and the organizing logic; and (3) to offer for the readers' consideration a proposed conceptual framework for understanding the ethical role of Artificial Intelligence in the social work profession. In 2024, David Edmonds and a team of leading philosophers published AI Morality. Edmonds identified six emergent themes based on the authored chapters: autonomy; bias; responsibility; privacy and transparency; meaning; and, values and morals. We explore these six themes as a viable complement to the Belmont Report and the National Association of Social Workers (NASW) Code of Ethics for understanding categorical ethical concerns related to the use of AI in social work research, and in this way, evidence-based social work practice and broader society. We thematically grouped the corresponding relationships and used these groupings as an organizing framework: (1) autonomy, power/oppression, and informed consent; (2) bias, discrimination, and social justice; (3) responsibility, harm, and competence; (4) privacy, confidentiality, and transparency; (5) meaning, service, and social need; and, (6) values, morality, and ethical alignment. We identify ethical concerns across these six categories and make respective recommendations before offering final thoughts.