Perceived Barriers and Facilitators Regarding the Implementation of Gamification to Promote Physical Activity in the Neighborhood: Interview Study Among Intermediaries
Bibliographic record
Abstract
BACKGROUND: In the Netherlands, neighborhood sport coaches (NSCs) play an important role as intermediaries in promoting physical activity (PA) in the neighborhood. Gamification is the use of game elements in nongame contexts; it can be implemented with or without technology and holds promise for promoting PA. NSCs infrequently make use of this option. OBJECTIVE: This study aims to understand barriers to, and facilitators of, using gamification to promote PA, as perceived by NSCs. METHODS: A total of 25 semistructured interviews were conducted with NSCs in the Netherlands. The interviews were audiotaped, transcribed, and analyzed by means of thematic analysis using ATLAS.ti (version 22; ATLAS.ti Scientific Software Development GmbH) software. The deductive coding was informed by the capability, opportunity, motivation, behavior model and the theoretical domains framework, complemented by inductive coding. RESULTS: Barriers and facilitators identified as factors influencing the implementation of gamification were related to 7 themes. NSCs required technical, creative, and promotion skills; knowledge about existing gamification tools; and social support from their employer and professional network. Financial costs were identified as a barrier to the successful implementation of gamification. Lack of clarity regarding stakeholders' responsibility to implement gamification could further hamper implementation. In general, NSCs were positive about investing time in implementing gamification and expected positive effects from implementing it. CONCLUSIONS: To overcome identified barriers, a clear overview of tools, best practices, and available subsidies must be created, a gamification network must be established, the responsibility of NSCs must be clarified, and guidance must be offered on the promotion of gamification.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".