Brief online motivational interviewing pre-treatment intervention for enhancing internet-delivered cognitive behaviour therapy: A randomized controlled trial
Bibliographic record
Abstract
While the efficacy of therapist-guided internet-delivered cognitive behaviour therapy (iCBT) for anxiety and depression is well-established, a significant proportion of clients show little to no improvement with this approach. Given that motivational interviewing (MI) is found to enhance face-to-face treatment of anxiety, the current trial examined potential benefits of a brief online MI intervention prior to therapist-guided iCBT. Clients applying to transdiagnostic therapist-guided iCBT in routine care were randomly assigned to receive iCBT with (n = 231) or without (n = 249) the online MI pre-treatment. Clients rated motivation at screening and pre-iCBT and anxiety and depression at pre- and post-treatment and at 13- and 25-week follow-up after enrollment. Clients in the MI plus iCBT group made more motivational statements in their emails and were enrolled in the course for a greater number of days compared to clients who received iCBT only, but did not demonstrate higher motivation after completing the MI intervention or have higher course completion. Clients in both groups, at screening and pre-iCBT, reported high levels of motivation. No statistically significant group differences were found in the rate of primary symptom change over time, with both groups reporting large reductions in anxiety and depression pre- to post-treatment (Hedges' g range = 0.96–1.11). During follow-up, clients in the iCBT only group reported additional small reductions in anxiety, whereas clients in the MI plus iCBT group did not. The MI plus iCBT group also showed small increases in depression during follow-up, whereas improvement was sustained for the iCBT only group. It is concluded that online MI does not appear to enhance client outcomes when motivation at pre-treatment is high.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".