Resilience support to enhance positive health outcomes for police officers in five Anglosphere nations: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Law enforcement involves exposure to threatening situations and traumatic events that place police officers at risk for negative physical and mental health outcomes. Resilience support, among other elements of training, may help mitigate these risks, yet little is known about which aspects of resilience support help officers achieve better health and quality of life outcomes. METHODS AND ANALYSIS: This review will consider all literature that examines the links between resilience support, physical/mental health and quality of life outcomes for police officers in five Anglosphere nations: Canada, the USA, Australia, New Zealand and the UK. This review will include all literature (including those that show null or negative links) involving any public policing agency that has a formal rank structure and includes a localized, uniformed emergency response function. Resilience support may include, but is not limited to: tools, policies, models, frameworks, programmes and organizational features that seek to promote positive, physical/mental health and quality of life outcomes at three levels of resilience: (1) readiness and preparedness, (2) response and adaptation, (3) recovery and adjustment. Peer reviewed and grey literature examining resilience support since 2000 that focuses on police officers are eligible for inclusion. Databases/sources to be searched will include: PsycINFO, Academic Search Premier, CINAHL, Public Affair Index, Campbell Collaboration, ProQuest Dissertations and Theses Global, Business Source Complete, Scopus and Google. Retrieval of full-text, English-language studies (and other literature), data extraction, data synthesis and data mapping will be performed independently by two reviewers, following Joanna Briggs Institute methodology. ETHICS AND DISSEMINATION: Ethics approval is not required for this scoping review, and the literature search will start in November 2020 or upon acceptance of this protocol. The findings of the scoping review will be available [April 2021] and will be published in a peer reviewed journal.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".