“How can we help you?”: results of a scoping review on the perceived needs of people living with chronic pain regarding physiotherapy
Bibliographic record
Abstract
BACKGROUND: Physiotherapy is effective to reduce pain and improve the quality of life of people living with chronic pain. To offer high-quality physiotherapy services, these services must be patient-centred and respond to patients' needs. However, few studies seem to target patients' perceived needs, whereas more studies tend to focus on needs assessed by healthcare experts, which are not always in line with patients' perceived needs. In addition, people living with chronic pain are often faced with several health inequities and may have varied perceived needs depending on their personal conditions. To offer services that truly meet patients' needs, it is therefore crucial to understand these needs. This scoping review aims to identify and map the perceived needs of people living with chronic pain towards physiotherapy services. METHODS: To conduct this review, we followed the six stages framework proposed by Arksey and O'Malley. We searched four databases (Medline, Embase, CINHAL and APA PsycINFO) as well as the grey literature. We included all studies describing the needs, demands, preferences or expectations of adults living with chronic pain towards physiotherapy. We then performed an inductive thematic analysis of the results and discussion sections of these studies to identify the perceived needs. Once those needs were identified, we mapped them into the seven dimensions of the patient-centred healthcare delivery framework. RESULTS: Our review included 96 studies. Various perceived needs were identified through the thematic analysis, such as the needs for an empathetic relationship; for a clear, adapted and supervised exercise program; and for personalized treatment. Our mapping into the patient-centred healthcare delivery framework showed that most studies reported needs associated with the dimensions of interpersonal care, individualized healthcare and professional care. Needs associated with the other dimensions of the framework (access; coordination and continuity; services and facilities; data and information) were less frequently mentioned. CONCLUSIONS: The results of this review have enabled us to identify and better understand multiple needs perceived by people living with chronic pain regarding physiotherapy services. The perceived needs identified through this scoping review were mapped within the seven dimensions of the Patient-centred healthcare delivery framework.
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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 | 0.040 | 0.131 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.029 | 0.028 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".