North American open-label 16-week trial of the MindShift smartphone app for adult anxiety
Bibliographic record
Abstract
Evidence-based treatments can effectively address anxiety and related conditions. However, new resources are needed to make psychological interventions accessible to the substantial and increasing North American population affected by anxiety and related psychopathology. The present study evaluated whether use of the MindShift app (Anxiety Canada) may help reduce anxiety symptoms and related depressive symptoms, quality-of-life, and functional impairment among adults 18 years of age and older. Adults ages 18 to 80 (N=380) participated in an online open-label trial to evaluate change in anxiety and related distress while using the MindShift smartphone app. Inclusion criteria: residence in Canada or the USA and self-identification of anxiety or anxious distress to address during the study. Participants reported the severity of four primary outcomes at baseline and 2-, 4-, 8-, 12-, and 16-weeks after they began using the MindShift app. All four primary outcomes improved over the 16-week period: participants reported reduced anxiety and depressive symptoms; reduced functional impairment; and improved quality-of-life. Improvements were unrelated to the frequency with which participants used the MindShift app. Effect sizes indicated moderate change in anxiety symptoms (d=0.61, p<0.0001), depressive symptoms (d=0.50, p<0.0001), functional impairment (d=0.55, p<0.0001), and quality-of-life (d=0.31, p<0.0001) at the end of the 16-week intervention; improvements were consistent with response to treatment but not remission. Overall, the MindShift app may provide a ready to scale low-cost resource to assist in meeting the mental health needs of adults across North America, particularly those who report mild or moderate symptom severity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".