Measuring therapeutic relationship in the care of patients with haemophilia: A scoping review
Bibliographic record
Abstract
OBJECTIVE: We conducted a scoping review of the tools used to measure therapeutic relationship in patients with haemophilia. BACKGROUND: Haemophilia is an inherited bleeding disorder caused by a deficiency of a clotting factor in the blood. Therapeutic relationship is foundational to the management of patients with chronic diseases like haemophilia. A reliable and valid measurement tool for assessing therapeutic relationship is needed to evaluate the quality of care received by these patients, and to rigorously study the association between therapeutic relationship and the outcomes of treatment. METHODS: We adopted the Arksey and O'Malley framework for scoping studies. The following electronic databases were searched for studies that measured a construct related to therapeutic relationships in haemophilia care: MEDLINE, EMBASE, CINAHL, PsycINFO and Scopus. We inventoried these studies, identified the measurement tools used, and described each tool by purpose, content, measurement properties and target population. We identified gaps in the current evidence and directions for future research. RESULTS: There were 253 unique records retrieved in the search, and twenty studies were deemed relevant. Ten measurement tools were identified. None of the tools measured therapeutic relationship as a single entity; however, six tools measured constructs considered part of patient-provider relationship (eg trust, communication, working alliance). There has been little validation testing of these tools in haemophilia patient populations. CONCLUSIONS: There is a need for a validated tool for measuring therapeutic relationship in the care of patients with haemophilia. This review provides a foundation for future research in this area.
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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 | 0.026 | 0.133 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.026 | 0.027 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| 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".