Using photo-elicitation to explore health promotion concepts with children and adolescents with disabilities: a rapid scoping review
Bibliographic record
Abstract
PURPOSE: It is important to directly engage children and adolescents with disabilities (CAWD) in health promotion research to ensure their health needs are met. Arts-based research methods may help CAWD better express their ideas; photo-elicitation is one such technique, using self-captured photographs to enhance verbal descriptions of complex concepts. This review 1) summarizes findings from health promotion studies using photo-elicitation with CAWD; 2) explores benefits and challenges of using photo-elicitation; 3) identifies recommended photo-elicitation practices. MATERIALS AND METHODS: A scoping review was conducted using rapid review principles. Four health and social science databases were searched (2009-2019) using terms related to children, adolescents, disability, and photo-elicitation. Articles meeting inclusion criteria were summarized and analyzed thematically. RESULTS: Eight studies met inclusion criteria and explored a range of health promotion topics. Benefits of photo-elicitation included the ability to mediate communication and direct participants' focus. Challenges included difficulty operating a camera and understanding instructions about photograph subject matter. Four recommended practices were identified: 1) brainstorming photograph ideas; 2) photograph-taking training; 3) having CAWD select photographs for discussion; 4) limiting the number of photographs CAWD could capture. CONCLUSIONS: Integrating practices to support CAWD in using photo-elicitation can help researchers more fully understand their health experiences.Implications for RehabilitationThere is a need to directly engage children and adolescents with disabilities to express themselves in health promotion research.The arts-based method of photo-elicitation may help children and adolescents with disabilities convey how they view and experience health.Children and adolescents with disabilities may need supports, including camera training, to participate in photo-elicitation.
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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 | 0.059 | 0.134 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.026 | 0.021 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".