The Concept of Patient Motivation
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The purpose of this work was to investigate how stroke rehabilitation professionals understand the concept of motivation and the ways that they use this concept in their clinical practice. METHODS: This qualitative study used semistructured, in-depth interviews with the professionals working in the stroke unit of an inner-city teaching hospital in the UK. RESULTS: Motivation was a frequently used concept and was described as an important determinant of rehabilitation outcome. Motivation was attributed to patients on the basis of their demeanor (proactivity was equated with motivation, passivity with lack of motivation) and their compliance with rehabilitation (compliance was seen as indicative of motivation, noncompliance as a lack of motivation). These criteria were found to have blurred boundaries. The determinants of motivation were located partly in personality factors but also in social factors. Central among the social factors were aspects of the professionals' own behavior taken to positively and negatively affect motivation. Some professionals reported treating unmotivated patients differently from motivated ones, especially if these unmotivated patients were elderly. Motivation was described as a potentially dangerous label. CONCLUSIONS: Professionals are wary of the concept of motivation yet commonly use it in their clinical practice. The blurred boundaries of the criteria used to identify motivation mean that patients must strike a delicate balance between proactivity and compliance to avoid being categorized as unmotivated. The way the concept of motivation is used in clinical practice might have negative implications for patient care, eg, when reticent yet motivated patients are labeled unmotivated.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.020 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".