A multifaith spiritually based intervention for generalized anxiety disorder: a pilot randomized trial
Bibliographic record
Abstract
This pilot trial evaluated the efficacy of a multifaith spiritually based intervention (SBI) for generalized anxiety disorder (GAD). Patients meeting DSM-IV criteria for GAD of at least moderate severity were randomized to either 12 sessions of the SBI (n=11) delivered by a spiritual care counselor or 12 sessions of psychologist-administered cognitive-behavioral therapy (CBT; n=11). Outcome measures were completed at baseline, post-treatment, and 3-month and 6-month follow-ups. Primary efficacy measures included the Hamilton Anxiety Rating Scale, Beck Anxiety Inventory, and Penn State Worry Questionnaire. Data analysis was performed on the intent-to-treat sample using the Last Observation Carried Forward method. Eighteen patients (82%) completed the study. The SBI produced robust and clinically significant reductions from baseline in psychic and somatic symptoms of GAD and was comparable in efficacy to CBT. A reduction in depressive symptoms and improvement in social adjustment was also observed. Treatment response occurred in 63.6% of SBI-treated and 72.3% of CBT-treated patients. Gains were maintained at 3-month and 6-month follow-ups. These preliminary findings are encouraging and suggest that a multifaith SBI may be an effective treatment option for GAD. Further randomized controlled trials are needed to establish the efficacy of this intervention.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".