Stability of the CORE‐OM and the BDI‐I prior to therapy: Evidence from routine practice
Bibliographic record
Abstract
BACKGROUND: It is important to know the stability of standard outcome measures prior to therapy over differing periods of time that map onto the realities of waiting times in routine service settings. METHOD: We studied 1,684 clients who completed one or both the targeted measures Clinical Outcomes in Routine Evaluation-Outcome Measures (CORE-OM) and Beck Depression Inventory-I (BDI-I) two times, at intervals of up to 12 months, prior to beginning psychotherapy. We also selected an additional 1,623 clients who completed the CORE-OM (N=1,623), BDI-I (N=980) or both at referral, but had no records of further contact with the service. RESULTS: There was little change in the mean CORE-OM or BDI-I scores between referral and clinical assessment. The test-retest correlations showed substantial stability on both measures, declining only moderately at the longer intervals studied. CONCLUSION: The high test-retest correlations for periods of up to 6 months suggest that psychological disturbance was both reliably measured by the CORE-OM and the BDI-I, and reasonably stable among clients waiting to be assessed. Implications for routine practice are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.036 | 0.216 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".