Facilitators and Barriers to the Implementation of iSPRINT: A Sport Injury Prevention Program in Junior High Schools
Bibliographic record
Abstract
OBJECTIVES: Sport injury is the leading cause of hospitalization in Canadian youth and represents a high burden to the health care system. This study aims to describe the facilitators and barriers to implementation of a sport injury prevention program in junior high school physical education (known as iSPRINT), previously shown to reduce the risk of sport-related injury in youth (age, 11-15 years). METHODS: Focus group data were mapped onto constructs from the Consolidated Framework for Implementation Research (CFIR). Four schools that implemented iSPRINT participated in this study. Forty-seven key stakeholders (teachers, students, principals) participated in 9 semistructured focus groups and 4 interviews. The CFIR was used to guide the focus group discussions, data coding, and analysis using a qualitative content analysis approach. RESULTS: Of the 22 applicable CFIR constructs, 16 were identified in the transcripts. The most significant facilitators to successful implementation efforts included evidence strength and quality, adaptability, implementation climate, culture, and having a high level of compatibility facilitated successful implementation efforts. Barriers to implementation included intervention complexity, planning, and readiness for implementation. Constructs that acted as both a facilitator and a barrier, depending on the context, were self-efficacy, execution, and individual identification with the organization. CONCLUSIONS: Participants in this study reported positive attitudes about implementing iSPRINT, citing evidence strength, adaptability, and constructs related to the organizational setting that contributed to successful implementation. Potential improvements include modifying certain program components, decreasing the number of components, and reducing the equipment required.
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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".