Motivation in rehabilitation and acquired brain injury: can theory help us understand it?
Bibliographic record
Abstract
Background: In acquired brain injury (ABI) populations, low motivation to engage in rehabilitation is associated with poor rehabilitation outcomes. Motivation in ABI is thought to be influenced by internal and external factors. This is consistent with Self-determination Theory, which posits that motivation is intrinsic and extrinsic. This paper discusses the benefit of using Self-determination Theory to guide measurement of motivation in ABI.Methods: Using a narrative review of the Self-determination Theory literature and clinical rehabilitation research, this paper discusses the unique role intrinsic and extrinsic motivation has in healthcare settings and the importance of understanding both when providing rehabilitation in ABI.Results: Based on the extant literature, it is possible that two independently developed measures of motivation for ABI populations, the Brain Injury Rehabilitation Trust Motivation Questionnaire-Self and the Motivation for Traumatic Brain Injury Rehabilitation Questionnaire, may assess intrinsic and extrinsic motivation, respectively.Conclusion: Intrinsic and extrinsic motivation in ABI may be two equally important but independent factors that could provide a comprehensive understanding of motivation in individuals with ABI. This increased understanding could help facilitate behavioural approaches in rehabilitation.Implications for RehabilitationConceptualization of motivation in ABI would benefit from drawing upon Self-determination Theory.External factors of motivation such as the therapeutic environment or social support should be carefully considered in rehabilitation in order to increase engagement.Assessing motivation as a dual rather than a global construct may provide more precise information about the extent to which a patient is motivated.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| 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".