Evaluating a Web-Based Social Anxiety Intervention Among Community Users: Analysis of Real-World Data
Bibliographic record
Abstract
BACKGROUND: Social anxiety is both harmful and prevalent. It also currently remains among the most undertreated major mental disorders, due, in part, to socially anxious individuals' concerns about the stigma and expense of seeking help. The privacy and affordability of computer-aided psychotherapy interventions may render them particularly helpful in addressing these concerns, and they are also highly scalable, but most tend to be only somewhat effective without therapist support. However, a recent evaluation of a new self-guided, 7-module internet-delivered cognitive behavioral therapy intervention called Overcome Social Anxiety found that it was highly effective. OBJECTIVE: The initial evaluation of Overcome Social Anxiety revealed that it led to significant reductions in symptom severity among university undergraduates. The aim of this study was to extend the results of the initial study and investigate their generalizability by directly evaluating the intervention's effectiveness among a general community sample. METHODS: While signing up for Overcome Social Anxiety, users consented to the usage of their anonymized outcome data for research purposes. Before and after completing the intervention, users completed the Fear of Negative Evaluation Scale (FNE), which we employed as the primary outcome measure. Secondary outcome measures included the Depression Anxiety Stress Scales (DASS) and 2 bespoke questionnaires measuring socially anxious thoughts (Thoughts Questionnaire) and avoidance behaviors (Avoidance Questionnaire). RESULTS: Participants who completed the intervention (102/369, 27.7%) experienced significant reductions in the severity of their symptoms on all measures employed, including FNE (P<.001; Cohen d=1.76), the depression subscale of DASS (P<.001; Cohen d=0.70), the anxiety subscale of DASS (P<.001; Cohen d=0.74), the stress subscale of DASS (P<.001; Cohen d=0.80), the Thoughts Questionnaire (P<.001; Cohen d=1.46), and the Avoidance Questionnaire (P<.001; Cohen d=1.42). CONCLUSIONS: Our results provide further evidence that Overcome Social Anxiety reduces the severity of social anxiety symptoms among those who complete it and suggest that its effectiveness extends to the general community. The completion rate is the highest documented for a fully automated intervention for anxiety, depression, or low mood in a real community sample. In addition, our results indicate that Overcome Social Anxiety reduces the severity of symptoms of depression, physiological symptoms of anxiety, and stress in addition to symptoms 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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".