The UK national institute for health and clinical excellence public health guidance on behaviour change: A brief introduction
Bibliographic record
Abstract
In October 2007, the National Institute for Health and Clinical Excellence (NICE) published 'Guidelines for Behaviour change at population, community and individual levels' (National Institute of Health and Clinical Excellence. Behaviour change at population, community and individual levels (Public Health Guidance 6), 2007, from http://www.nice.org.uk/Guidance/PH6). This article provides a brief overview of, and introduction to, the guidance focussing on three of its recommendations. First, the guidance outlines skills and competencies required by those involved in the design and evaluation of behaviour change interventions (BCIs). Second, it specifies a series of key psychological change targets which should be considered in interventions intended to change individual behaviour. Third, it highlights the need to plan intervention design and evaluation so that intervention components or techniques are linked directly to causal process which account for change. In addition, the guidance outlines a research agenda. Based on an analysis of the limitations of the available evidence base, research recommendations advise researchers on how to improve the quality of research into BCIs (including evaluations) and thereby advance the science of behaviour change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.036 | 0.064 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.018 | 0.017 |
| Insufficient payload (model declined to judge) | 0.021 | 0.019 |
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".