Development of a Theory-Based Intervention to Increase Clinical Measurement of Reactive Balance in Adults at Risk of Falls
Bibliographic record
Abstract
BACKGROUND: Effective balance reactions are essential for avoiding falls, but are not regularly measured by physical therapists. Physical therapists report wanting to improve reactive balance assessment, and theory-based approaches are recommended as the foundation for the development of interventions. This article describes how a behavior change theory for health care providers, the theoretical domains framework (TDF), was used to develop an intervention to increase reactive balance measurement among physical therapists who work in rehabilitation settings and treat adults who are at risk of falls. CASE DESCRIPTION: We employed published recommendations for using the TDF-guided intervention development. We identified what health care provider behavior is in need of change, relevant barriers and facilitators, strategies to address them, and how we would measure behavior change. In this case, identifying strategies required selecting both a reactive balance measure and behavior change techniques. Previous research had determined that physical therapists need to increase reactive balance measurement, and identified barriers and facilitators that corresponded to 8 TDF domains. A published review informed the selection of the Balance Evaluation Systems Test (Reactive Postural Responses Section) as addressing the barriers and facilitators, and existing research informed the selection of 9 established behavior change techniques corresponding to each identified TDF domain. OUTCOMES: The TDF framework were incorporated into a 12-month intervention with interactive group sessions, local champions, and health record modifications. Intervention effect can be evaluated using health record abstraction, questionnaires, and qualitative semistructured interviews. SUMMARY: Although future research will evaluate the intervention in a controlled study, the process of theory-based intervention development can be applied to other rehabilitation research contexts, maximizing the impact of this work.Video Abstract is available for more insights from the authors (see Supplemental Digital Content 1, http://links.lww.com/JNPT/A123).
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".