Perceptions of health care social workers in Ontario: challenges and facilitators to reflective practice
Bibliographic record
Abstract
Background: Reflective practice in health care social work ensures that social workers provide effective and efficient services to clients as well as maintaining their mental and physical health. In this study, we aim to determine how health care social workers engage in and describe reflective practice and challenges related to their reflective practice in their work in the health care system.Methods: We used the Reflective Dialogue Rating Scale (RDRS) developed by Marion Bogo et al. to structure qualitative face-to-face interviews with 23 health care social workers employed in a hospital in a large urban area in Ontario, Canada.Results: Findings illustrated that all participants regularly engaged in reflective practice in order to carry out everyday social work activities, promote ethical practice, and to enhance the provision of services to their clients. The social worker participants consistently agreed that as a profession they faced challenges maintaining their knowledge of current research due to few opportunities for professional development, workload competing with educational opportunities, and a work climate that is not conducive to gaining professional development, thereby challenging reflective practice. Supportive working environments include: peer supervision, safe and private spaces to talk to colleagues, a supportive supervisor, and an overall positive organizational culture.Discussion and conclusion: Reflective practice is a key component in health care social work. All 23 social workers stated that they used reflective techniques (such as peer supervision and debriefing) to deal with their own reactions and operated in a purposeful and intentional manner to form therapeutic relationships with clients. As such, participants stated that lifelong learning was paramount in providing quality care to clients.
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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 | 0.018 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.015 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".