Self-efficacy and alcohol consumption: Are efficacy measures confounded with motivation?
Bibliographic record
Abstract
Recent research has suggested self-efficacy measures (i.e., I can) are confounded with motivation (i.e., I will). The study tested whether two measurement conditions can disentangle motivation from self-efficacy in relation to alcohol consumption. Specifically, the study compared a standard self-efficacy measurement condition with a motivation held constant (i.e., including “If I really wanted to” in self-efficacy measures) and a vignette condition (i.e., clarifying the definition of “can” before self-efficacy measurements). A randomized posttest-only design was used. A sample of 259 university students were allocated to one of three conditions (standard; motivation held constant; vignette) and completed measures of self-efficacy and alcohol consumption. Greater self-efficacy towards both consuming and refraining from alcohol was found in the vignette (d = 0.58 & 0.74) and motivation held constant (d = 0.34 & 0.58) conditions. Heavy drinkers in the vignette (d = 1.48) and motivation held constant (d = 0.93) conditions reported greater self-efficacy for refraining from alcohol than the standard condition. Self-efficacy towards refraining from alcohol in the standard condition (r = −.55) was more highly correlated with alcohol behaviour than self-efficacy in the vignette condition (r = −.06). The study adds to the evidence that standard measures of self-efficacy are confounded with motivation. Providing a vignette clarifying the meaning of self-efficacy and including “If I really wanted to” in self-efficacy measures can overcome self-efficacy confounding.
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 | 0.014 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".