Exploring the operationalisation and implementation of outreach in community settings with hard-to-reach and hidden populations: protocol for a scoping review
Bibliographic record
Abstract
INTRODUCTION: Outreach is regularly identified as an effective strategy to engage underserved, hard-to-reach and hidden populations with essential life-sustaining health services. Despite the increasing expansion of outreach programmes, particularly in HIV prevention and health promotion with youth, sex workers, people living with mental health and substance use challenges, and those affected by homelessness, there has been limited synthesis of the evidence concerning the core components of outreach programming or indicators of its successful implementation. Without this understanding, current outreach programmes may be limited in achieving the desired aims. The aim of this scoping review is to explore how outreach has been operationalised and implemented in various community settings with people underserved in current healthcare contexts. Understanding the state of knowledge pertaining to outreach as programming and as practice involving the engagement of people considered hard-to-reach will enable the identification of promising trends and limitations in the field. METHODS AND ANALYSIS: This scoping review follows the Arksey and O'Malley's framework. CINAHL, MEDLINE, PsycINFO and PubMed databases will be searched for peer-reviewed references focused on outreach with hard-to-reach and hidden groups from 1 January 2008 to 30 April 2020. Guided by explicit inclusion and exclusion criteria, three reviewers will independently assess references in two successive stages. Titles and abstracts will be reviewed followed by full-text assessment of papers meeting the review criteria. A descriptive overview, tabular and/or graphical summaries and a thematic analysis will be carried out on extracted data. ETHICS AND DISSEMINATION: Ethics approval was not required as the only data source was peer-reviewed documents. Outreach knowledge users who are members of the project team will participate in all aspects of study design, implementation and result dissemination strategies.
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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 | 0.140 | 0.123 |
| Meta-epidemiology (narrow) | 0.007 | 0.006 |
| Meta-epidemiology (broad) | 0.015 | 0.019 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.060 | 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".