Converting from a web-based teaching tool to a teaching modality for social anxiety
Bibliographic record
Abstract
A Web-based teaching tool called WebCAPSI was modified and tested as an online treatment for social anxiety. Two-Hundred and Seventy-Seven Introductory Psychology students at the University of Manitoba participated in the study. Twenty-eight participants were excluded from the study, resulting in 121 participants in the control group and 128 in the treatment group used for the final analysis. All participants received written materials on treatment for social phobia via WebCAPSI; however, the material was broken down into discrete units with assigned study questions for participants in the treatment condition. Participants in the treatment condition answered specific questions within the WebCAPSI program whereas participants in the control condition answered questions unrelated to the content of the materials. Further, participants in the treatment condition were given the opportunity to serve as peer reviewers. Results of this study indicated significant differences in post-treatment anxiety scores on two anxiety measures between groups, higher treatment expectancy scores in the treatment group, and higher baseline anxiety scores predicting greater reduction in anxiety post-treatment. Peer review did not appear to have a significant effect on post-treatment anxiety scores. These results indicate that the WebCAPSI program may be a useful tool to present information on the treatment of social anxiety.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".