Activity Trackers in Physical Therapy for People With Chronic Obstructive Pulmonary Disease in the Netherlands: Cross-Sectional Study on Current Use and Implementation Determinants
Bibliographic record
Abstract
Background: In the Netherlands, 545,900 people experienced chronic obstructive pulmonary disease (COPD) in 2022. Physical therapy following the Royal Dutch Society for Physiotherapy (Koninklijk Nederlands Genootschap voor Fysiotherapie) guidelines for COPD treatment is a proven effective treatment for people with COPD. The revised guidelines include a new recommendation: a patient's physical activity level should be assessed with an activity tracker (AT). Literature shows that the implementation of eHealth in clinical practice, in this case, ATs, is challenging. Objective: This study aims (1) to assess how and why ATs are currently used in physical therapy in patients with COPD and (2) to determine which barriers and facilitators are of relevance for optimal implementation of ATs during the clinical reasoning process of physical therapists in patients with COPD. Methods: A cross-sectional study was used to evaluate the implementation of ATs in physical therapy. Included participants were physical therapists who were affiliated with Chronisch ZorgNet and had a specialization in COPD treatment. The survey content was based on the Consolidated Framework for Implementation Research, the theory of planned behavior, the framework "experiences of patients with commercially available ATs," and the Koninklijk Nederlands Genootschap voor Fysiotherapie guidelines for COPD. Physical therapists were questioned via a digital survey. Results: In total, 211 completed surveys were analyzed. Of the 211 participating physical therapists, 108 (51.2%) used ATs, whereas most of them (n=82, 75.9%) already used ATs before it was advised in the guidelines. Physical therapists indicated that the most important reason to use ATs is that they experience it as an added health care value. Both users and nonusers indicated that the most important reason why they do not use ATs is because their patients do not want to use an AT. The second reason was a lack of knowledge in the nonuser group. Moreover, both users and nonusers indicated that the implementation of ATs was not prepared and planned for within their center. Conclusions: Overall, these results show that ATs are not yet fully implemented in the Dutch general physical therapy practice in patients with COPD, as recommended by current evidence-based guidelines. Physical therapists need guidance for the successful implementation of ATs. This could be accomplished by providing training for physical therapists, integrating ATs into the education of (future) physical therapists, and providing support during the implementation process of ATs for both the physical therapists and management.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".