The Theory of Planned Behavior: Some Measurement Issues Concerning Belief‐Based Variables
Bibliographic record
Abstract
The theory of planned behavior presents clear operational definitions of attitudes, subjective norm, perceived behavioral control, and each of their corresponding belief‐based measures. Theoretically, the direct and indirect measures of a given construct must be closely correlated. Empirical results, however, indicate that this is not always the case. In the present study, 2 of the factors that could be responsible for this situation‐namely, the scaling of the variables defining each belief‐based construct and the adequacy of using an expectancy‐value model within the belief‐based measures‐were verified among a data set of 16 studies concerned with the application of the theory of planned behavior to the field of health. The results indicate that the scaling method used affected the correlation coefficients between indirect and direct measures. However, the face validity of these scaling methods must be demonstrated. The results also support the idea that, in most cases, using the expectancy‐value model is no better than using only one arm of the belief‐based measure.
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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 | 0.074 | 0.183 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".