Social work leadership competencies in health and mental healthcare: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Leadership skills are an integral part of effective social work practice in health and mental healthcare settings. Social workers require critical leadership skills to effectively support, treat and advocate for the complex needs of those most vulnerable. Despite an increasing focus on social work leadership within the last decade, there has been a paucity of research on social work leadership competencies within the realm of health and mental health service provision. To bridge this gap, this scoping review will synthesise and map the current literature on social work leadership competencies in health and mental healthcare. METHODS AND ANALYSIS: Arksey and O'Malley's five-stage framework for scoping reviews will guide our search of six academic databases including: PsycINFO, OVID Social Work Abstracts, OVID Medline, Sociological Abstracts, Social Services Abstracts and CINAHL Plus with Full Text. Selected articles that meet inclusion criteria will then be reviewed and charted. Recurrent themes will be reviewed through a qualitative thematic analysis, and reported in both text and figures. ETHICS AND DISSEMINATION: Findings will highlight key social work leadership competencies as they relate to social work practice, team dynamics, and client outcomes within health and mental healthcare. Material retrieved in this scoping review was selected from publicly available sources, and thus as an obtrusive research method, this review does not warrant ethics approval. Findings from this review will be disseminated through published scholarly material, as well as presented at conferences pertaining to social work research, practice and education.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.107 | 0.073 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.027 | 0.021 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.061 | 0.014 |
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".