Using theories of behaviour to understand transfusion prescribing in three clinical contexts in two countries: Development work for an implementation trial
Bibliographic record
Abstract
BACKGROUND: Blood transfusion is an essential part of healthcare and can improve patient outcomes. However, like most therapies, it is also associated with significant clinical risks. In addition, there is some evidence of overuse. Understanding the potential barriers and enablers to reduced prescribing of blood products will facilitate the selection of intervention components likely to be effective, thereby reducing the number of costly trials evaluating different implementation strategies. Using a theoretical basis to understand behaviours targeted for change will contribute to a 'basic science' relating to determinants of professional behaviour and how these inform the selection of techniques for changing behaviour. However, it is not clear which theories of behaviour are relevant to clinicians' transfusing behaviour. The aim of this study is to use a theoretical domains framework to identify relevant theories, and to use these theories to identify factors that predict the decision to transfuse. METHODS: The study involves two steps: interview study and questionnaire study. Using a previously identified framework, we will conduct semi-structured interviews with clinicians to elicit their views about which factors are associated with waiting and further monitoring the patient rather than transfusing red blood cells. Interviews will cover the following theoretical domains: knowledge; skills; social/professional role and identity; beliefs about capabilities; beliefs about consequences; motivation and goals; memory, attention, and decision processes; environmental context and resources; social influences; emotion; behavioural regulation; nature of the behaviour. The interviews will take place independently in Canada and the UK and involve two groups of physicians in each country (UK: adult and neonatal intensive care physicians; Canada: intensive care physicians and orthopaedic surgeons). We will: analyse interview transcript content to select relevant theoretical domains; use consensus processes to map these domains on to theories of behaviour; develop questionnaires based on these theories; and mail them to each group of physicians in the two countries. From our previous work, it is likely that the theories will include: theory of planned behaviour, social cognitive theory and the evidence-based strategy, implementation intention. The questionnaire data will measure predictor variables (theoretical constructs) and outcome variables (intention and clinical decision), and will be analysed using multiple regression analysis. We aim to achieve 150 respondents in each of the four groups for each postal survey.
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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 | 0.154 | 0.116 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| 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".