Introducing multidimensional item response modeling in health behavior and health education research
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
When measuring participant-reported attitudes and outcomes in the behavioral sciences, there are many instances when the common measurement assumption of unidimensionality does not hold. In these cases, the application of a multidimensional measurement model is both technically appropriate and potentially advantageous in substance. In this paper, we illustrate the usefulness of a multidimensional approach to measurement using an empirical example taken from the Behavior Change Consortium. Data from the Treatment Self-Regulation Questionnaire have been analyzed to investigate whether self-regulation can be regarded as a single construct, or if it has multiple dimensions based on the type of regulation or motivation that participants say helps them consider an improvement in healthy behavior. Comparison with consecutive analyses shows the advantages of multidimensional measurement for interpreting participant-reported data.
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 | 0.035 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it