Development of the social dimensions of health behaviour framework
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite rapid theoretical expansion in conceptualising individual and environmental processes, the examination of social processes associated with health behaviours has a less cohesive theoretical landscape. The purpose of this mapping review and content analysis was to develop a taxonomy of social dimensions applicable to health behaviours. Michie et al. (2014) ‘ABC of Theories of Behaviour Change’ text, which includes 83 behaviour change theories, was used as the data-set, whereby an iterative concurrent content analysis was undertaken with respect to all relational/interpersonal psychological dimensions. The analysis resulted in a social dimensions of health behaviour (SDHB) framework of 10 dimensions, including seven sub-types of social appraisal dimensions and three-sub-types of social identification dimensions. The SDHB revealed that specific dimensions, such as descriptive norm, are prevalent in behavioural theories, while other dimensions have seen less attention. Further, while most social constructs in behavioural theories are represented by only one social dimension in the SDHB, other constructs have complex representation. This version 1.0 of the SDHB framework should assist in specifying the core social dimensions in health behaviour, provide a common lexicon to discuss relational constructs in psychological theories, amalgamate the disparate social constructs literature and identify opportunities for further research to advance theory development and interventions.
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.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it