The Validation of Automated Social Skills Training in Members of the General Population Over 4 Weeks: Comparative Study
Bibliographic record
Abstract
BACKGROUND: Social skills training by human trainers is a well-established method of teaching appropriate social and communication skills and strengthening social self-efficacy. Specifically, human social skills training is a fundamental approach to teaching and learning the rules of social interaction. However, it is cost-ineffective and offers low accessibility, since the number of professional trainers is limited. A conversational agent is a system that can communicate with a human being in a natural language. We proposed to overcome the limitations of current social skills training with conversational agents. Our system is capable of speech recognition, response selection, and speech synthesis and can also generate nonverbal behaviors. We developed a system that incorporated automated social skills training that completely adheres to the training model of Bellack et al through a conversational agent. OBJECTIVE: This study aimed to validate the training effect of a conversational agent-based social skills training system in members of the general population during a 4-week training session. We compare 2 groups (with and without training) and hypothesize that the trained group's social skills will improve. Furthermore, this study sought to clarify the effect size for future larger-scale evaluations, including a much larger group of different social pathological phenomena. METHODS: For the experiment, 26 healthy Japanese participants were separated into 2 groups, where we hypothesized that group 1 (system trained) will make greater improvement than group 2 (nontrained). System training was done as a 4-week intervention where the participants visit the examination room every week. Each training session included social skills training with a conversational agent for 3 basic skills. We evaluated the training effect using questionnaires in pre- and posttraining evaluations. In addition to the questionnaires, we conducted a performance test that required the social cognition and expression of participants in new role-play scenarios. Blind ratings by third-party trainers were made by watching recorded role-play videos. A nonparametric Wilcoxson Rank Sum test was performed for each variable. Improvement between pre- and posttraining evaluations was used to compare the 2 groups. Moreover, we compared the statistical significance from the questionnaires and ratings between the 2 groups. RESULTS: Of the 26 recruited participants, 18 completed this experiment: 9 in group 1 and 9 in group 2. Those in group 1 achieved significant improvement in generalized self-efficacy (P=.02; effect size r=0.53). We also found a significant decrease in state anxiety presence (P=.04; r=0.49), measured by the State-Trait Anxiety Inventory (STAI). For ratings by third-party trainers, speech clarity was significantly strengthened in group 1 (P=.03; r=0.30). CONCLUSIONS: Our findings reveal the usefulness of the automated social skills training after a 4-week training period. This study confirms a large effect size between groups on generalized self-efficacy, state anxiety presence, and speech clarity.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".