Exploring the conceptualization, operationalization, implementation, and measurement of outreach in community settings with hard-to-reach and hidden populations: A scoping review
Bibliographic record
Abstract
Outreach is as a strategy employed by those in health and social services, which generally involves establishing relationships and providing support to people situated in hard-to-reach and hidden populations. However, there is a lack of clarity across the literature on how outreach is conceptualized, the central elements of outreach as a program and practice, and how the 'success' of outreach is empirically measured. Such gaps limit understandings of how outreach can be most effectively implemented and evaluated. The purpose of this scoping review responds to these challenges by systematically examining how outreach has been conceptualized, operationalized, and evaluated in community settings with hard-to-reach and hidden populations. This scoping review approach was undertaken in accordance with the 6-step framework developed by Arksey and O'Malley and advanced by Levac and colleagues. The search was conducted across four databases (CINAHL, MEDLINE, PubMed, and PsycINFO) and included research, review, and non-empirical articles published in English between January 1, 2008 and April 20, 2020.16,238 records were screened by title and abstract, followed by a review of 654 full-text articles and critical appraisal of 67 articles. Forty-two articles were included in the review, including 28 research articles (90%), two review, and two non-empirical. Findings illustrate that there is considerable variation in how outreach is conceptualized, implemented, and evaluated across the literature. Further, outreach is often inadequately defined, and predominantly overlooks the underlying and systemic reasons for clients' "disengagement" from health and social care. Outreach providers and researchers are encouraged to draw on client-led aims, goals, and outcome measures to determine the enactment, evaluation, and measurement of outreach, and to explicitly position outreach as working alongside clients to remove structural barriers to care.
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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 | 0.091 | 0.246 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.029 | 0.033 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.005 | 0.003 |
| 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".