Impact of a photovoice intervention on fall-related psychological variables, participation levels and quality of life in chronic spinal cord injury
Bibliographic record
Abstract
CONTEXT: Falling is common after spinal cord injury (SCI). Falls can cause a fear of falling and reduced participation in activities. Interventions that target falls self-efficacy may change fall-related behaviors, such as reduced participation. OBJECTIVE: The primary objective was to investigate the impact of a photovoice intervention on falls self-efficacy in individuals with chronic SCI. The secondary objectives were to examine the effects of photovoice on participation, quality of life, fear of falling and falls. METHODS: Convergent mixed methods study with 34 adults with chronic SCI; 17 used a wheelchair (WC) and 17 ambulated (AM). The six-week, virtual photovoice intervention focused on fall prevention and consisted of photo-assignments, individual interviews and group meetings facilitated by a peer mentor. The primary measures were questionnaires of falls self-efficacy and falling concern. The secondary measures included questionnaires of participation, quality of life and fear of falling, and number of falls. Quantitative data were compared over time for WC and AM groups separately with a repeated measures ANOVA or Friedman's test. Semi-structured interviews and thematic analysis were used to collect and analyze qualitative data. A joint display merged quantitative and qualitative findings. RESULTS: Scores did not change over time for both groups (p≥0.109) with the exception of participation. The AM group's participation scores were significantly improved three months post-intervention (p≤0.028). Overall, divergence between quantitative and qualitative data was observed, with some participants describing improvements in self-efficacy and quality of life. CONCLUSIONS: ClinicalTrials.gov identifier: NCT04864262.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".