Community Paramedicine Supporting Community Needs: A Scoping Review
Bibliographic record
Abstract
Health and social needs exist along a dynamic continuum. Recognising that health status is inextricably impacted by social determinants of health, community paramedicine has opportunities and a responsibility to reduce inequities. The objective of this scoping review was to investigate the peer‐reviewed and grey literature to explore how community paramedicine supports community needs along a health and social continuum. We conducted a scoping review of the English language literature using the JBI Scoping Review methodology. We searched CINAHL, EMBASE, MEDLINE, Google Scholar, and organisational websites. 30 peer‐reviewed and 13 grey literature articles met the inclusion criteria. The findings describe the ways community paramedicine models evolved from minimising system pressures on emergency health services to addressing health and social needs. A key recommendation across the literature was the need to meaningfully engage communities early in the program development to understand how best to implement and codesign integrated service models addressing specific community needs although there was a lack of evidence to guide this approach. There is a notable lack of evidence pertaining to optimising technologies in the program design and implementation. The results highlight opportunities to determine the best practices for conducting holistic community needs assessments that include equitable stakeholder engagement and enhancing education to prepare paramedics for expanded roles. Community paramedicine provides opportunities to better meet the needs of structurally marginalised communities. There is a social responsibility and opportunity to engage communities to codesign service delivery, advance paramedic education, and enhance interprofessional collaboration to better support community needs and generate upstream solutions for individuals and communities.
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 | 0.026 | 0.106 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.024 | 0.023 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".