Community‐based Participatory Research: Development of an Emergency Department–based Youth Violence Intervention Using Concept Mapping
Bibliographic record
Abstract
OBJECTIVES: Emergency departments (EDs) see a high number of youths injured by violence. In Ontario, the most common cause of injury for youths visiting EDs is assault. Secondary prevention strategies using the teachable moment (i.e., events that can lead individuals to make positive changes in their lives) are ideal for use by clinicians. An opportunity exists to take advantage of the teachable moment in the ED in an effort to prevent future occurrences of injury in at-risk youths. However, little is known about perceptions of youths, parents, and community organizations about such interventions in EDs. The aims of this study were to engage youths, parents, and frontline community workers in conceptualizing a hospital-based violence prevention intervention and to identify outcomes relevant to the community. METHODS: Concept mapping is an innovative, mixed-method research approach. It combines structured qualitative processes such as brainstorming and group sorting, with various statistical analyses such as multidimensional scaling and hierarchical clustering, to develop a conceptual framework, and allows for an objective presentation of qualitative data. Concept mapping involves multiple structured steps: 1) brainstorming, 2) sorting, 3) rating, and 4) interpretation. For this study, the first three steps occurred online, and the fourth step occurred during a community meeting. RESULTS: Over 90 participants were involved, including youths, parents, and community youth workers. A two-dimensional point map was created and clusters formed to create a visual display of participant ideas on an ED-based youth violence prevention intervention. Issues related to youth violence prevention that were rated of highest importance and most realistic for hospital involvement included mentorship, the development of youth support groups in the hospital, training doctors and nurses to ask questions about the violent event, and treating youth with respect. Small-group discussions on the various clusters developed job descriptions, a list of essential services, and suggestions on ways to create a more youth-friendly environment in the hospital. A large-group discussion revealed outcomes that participants felt should be measured to determine the success of an intervention program. CONCLUSIONS: This study has been the springboard for the development of an ED-based youth violence intervention that is supported by the community and affected youth. Using information generated by youth that is grounded in their experience through participatory research methods is feasible for the development of successful and meaningful youth violence prevention interventions.
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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 | 0.077 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".