A Knowledge Translation Intervention Designed and Implemented by a Knowledge Broker Improved Documented Use of Gait Speed: A Mixed-Methods Study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Although outcome measures are a valuable part of physical therapy practice, there is a gap in routine outcome measurement use by physical therapists (PTs). Knowledge brokers (KBs) are individuals who can collaborate with PTs to facilitate outcome measure use. The purpose of this study was to determine whether an intervention tailored by an external KB, cocreated with the PTs and supported by the supervisor, would increase the use of gait speed by PTs working at an inpatient subacute rehabilitation hospital. METHODS: A mixed-methods study was conducted with 11 PTs. The 2-month intervention included education, documentation changes, audit and feedback, goal setting, and organizational support. Use of the 4-meter walk test was measured through chart audits and was self-assessed with the Goal Attainment Scale. Proportions were calculated to determine the number of times gait speed was documented by the PTs both at initial examination (IE) and at discharge. A repeated-measures analysis of variance was used to determine significant differences from baseline (3-month retrospective chart audit), 0 to 2, 2 to 4, 4 to 6, and 6 to 8 months. A Wilcoxon signed rank test was used to determine significant differences in self-reported use on the Goal Attainment Scale month 0 to month 2. Focus groups immediately following the intervention (month 2) and at follow-up (month 9) were used to determine barriers to measuring gait speed and perceptions of the intervention. Open coding was used to identify key themes. A comparison group of per diem PTs was trained by the supervisor between months 4 and 8, using the approach developed by the KB. The comparison group was included as their training may have influenced the experimental groups' outcome. Chart audit data for the comparison group from months 0 to 2, 2 to 4, 4 to 6, and 6 to 8 were reported descriptively. RESULTS AND DISCUSSION: Documentation of the 4-meter walk test significantly improved from the 3-month retrospective chart audit at baseline (0% IE, 0% discharge) to months 0 to 2 at IE (mean = 71%, SD = 31 %, F = 9.30, P < .001) and discharge (mean = 66%, SD = 30%, F = 14.16, P < .001) and remained significantly higher at months 6 to 8 follow-up for IE (mean= 63%, SD 21%) and discharge (mean=59%, SD 32%). Eleven PTs participated in the focus group at month 2 and reported that the knowledge translation strategies including documentation changes, environmental cues, and social support helped facilitate their behavior change. Lack of space and the patient's activity limitations were barriers. The PTs significantly improved self-reported use of gait speed using the Goal Attainment Scale from month 0 to month 2 at IE: -2 to 0 (0% use to 50%) (Z = -2.842, P = .004) and discharge: -2 to 1 (0% use to 75%) (Z = -2.448, P = .014). The comparison group increased documented use of gait speed from 0% to 25% at IE and 47% at discharge between months 6 and 8. CONCLUSION: The KB, with supervisor support, successfully collaborated with the PTs to tailor an intervention to address local barriers to consistently use the 4-meter walk test. The PTs significantly improved the documented use of gait speed following the intervention. The PTs reported that the intervention facilitated outcome measure use although barriers to using gait speed remained.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".