Using self‐determination theory in research and evaluation in primary care
Bibliographic record
Abstract
BACKGROUND: Multimorbidity (the co-existence of two or more long-term conditions within an individual) is a complex management challenge, with a very limited evidence base. Theories can help in the design and operationalization of complex interventions. OBJECTIVE: This article proposes self-determination theory (SDT) as a candidate theory for the development and evaluation of interventions in multimorbidity. METHODS: We provide an overview of SDT, its use in research to date, and its potential utility in complex interventions for patients with multimorbidity based on the new MRC framework. RESULTS: SDT-based interventions have mainly focused on health behaviour change in the primary prevention of disease, with limited use in primary care and chronic conditions management. However, SDT may be a useful candidate theory in informing complex intervention development and evaluation, both in randomized controlled trials and in evaluations of 'natural experiments'. We illustrate how it could be used multimorbidity interventions in primary care by drawing on the example of CARE Plus (a primary care-based complex intervention for patients with multimorbidity in deprived areas of Scotland). CONCLUSIONS: SDT may have utility in both the design and evaluation of complex interventions for multimorbidity. Further research is required to establish its usefulness, and limitations, compared with other candidate theories. PATIENT OR PUBLIC CONTRIBUTION: Our funded research programme, of which this paper is an early output, has a newly embedded patient and public involvement group of four members with lived experience of long-term conditions and/or of being informal carers. They read and commented on the draft manuscript and made useful suggestions on the text. They will be fully involved at all stages in the rest of the programme of research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".