A Mixed-Methods Examination of the Role of Social Work in Primary Care Teams in Ontario, Canada
Bibliographic record
Abstract
Context: In primary care teams in Ontario, Canada, social workers are important members involved in the provision of mental health support through early identification, treatment, counselling, follow-up, and recovery. Social workers also bring a biopsychosocial perspective that recognizes the importance of the social determinants of health on patient care. The COVID-19 pandemic significantly impacted social work practice due to expanding complexities of patients, transitioning to virtual care, adapting in-person services, and increasing burnout to provider well-being. Examining the daily practice of social work practice in primary care teams will enable social workers to better meet the robust mental health and complex patient needs, as well as how social workers contribute to interprofessional collaborations. Objective: To describe the current state of the role of social work practice and recommend how to optimize input of social workers in primary care Study Design: Mixed-methods study consisting of a cross-sectional, online survey with open and closed-ended questions, as well as descriptive qualitative focus groups. Eligible participants were Ontario social workers working in primary care teams. Results: We conducted 10 focus groups with 57 participants; and our survey had 170 respondents. Participants noted a preference for in-person interactions with their teams while also recognizing the importance of maintaining virtual communication to support team collaboration. Participants highlighted the need to enhance tracking of social work contributions and acknowledge time required to complete non-clinical work, like documentation and case consultations. Increase in case complexities and mental health needs among patients resulted in higher demand for social work services which can further be optimized. Many social workers provide informal leadership and participants expressed the need for more formal leadership opportunities and recognition of leadership work. Participants also shared the importance of feeling valued through access to supervision, fair compensation, and work flexibility. Conclusions: Social workers in primary care had a crucial role during the COVID-19 pandemic in leading and contributing to addressing increased patient needs and enhanced team collaboration. It will be important to optimize the role of social work and address ongoing challenges related to retention of social workers in primary care teams.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".