An environmental scan of studies reporting current practices for the conduct of environmental scans
Bibliographic record
Abstract
Objective: The objective of this environmental scan is to synthesize the published, peer-reviewed literature specific to the term ‘environmental scan’ to determine how it is currently being used in health research and to propose some promising practices. Background: Environmental scans are becoming increasingly popular in synthesizing information on emergent topics and describing practice and research scope. Despite the growing use of environmental scans in health research, including nursing and rehabilitation, limited attention is given to methodological best practices. It is essential that we develop knowledge in this area to assist researchers, trainees, healthcare professionals, educators, and decision-makers with the use and reporting of environmental scans. Study design and methods: This environmental scan included a search of four health databases: CINAHL, Embase, MEDLINE, and PsycINFO. We included peer-reviewed studies published between 2000-2024 in English using two key terms, ‘environmental scan’ and ‘health’. Studies were included that described methods used in conducting an environmental scan. Results: We identified 56 studies describing methods for conducting environmental scans. A synthesis of these studies revealed four promising practices: 1) consider environmental/contextual influences, 2) use of multiple data sources and approaches, 3) engage stakeholders to ensure relevance/need and increase uptake, and 4) use of outcomes to address knowledge or service gap to optimise impact. Conclusion: The findings of this environmental scan are among the first to examine methodological studies to determine promising practices for conducting environmental scans across health disciplines. Implications for research, policy, and practice: The findings of this novel environmental scan are beneficial for health professionals, researchers, trainees, educators, and decision-makers in informing research, practice, and policy change What is already known about the topic? The use of environmental scans is becoming increasingly popular in health research, including nursing and rehabilitation. There is a lack of consistency in the use and reporting of environmental scans across health disciplines. What this paper adds This environmental scan is among the first to contribute foundational knowledge and innovation in promising best practices for the conduct of environmental scans in health research. The novel findings will assist in promoting consistency in the use and reporting of environmental scans.
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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 | 0.299 | 0.706 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.084 | 0.080 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.013 | 0.020 |
| Open science | 0.007 | 0.014 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".