Help-seeking timeline followback for problem drinkers: preliminary comparison with agency records of treatment contacts.
Bibliographic record
Abstract
OBJECTIVE: A pilot study assessed the utility of the Timeline Followback (TLFB) method to collect information on help seeking. METHOD: Using the TLFB method, 34 clients (26 men) who had attended at least one session of an outpatient alcohol treatment program reported on treatment contacts, including any supplemental services (e.g., psychiatric care). TLFB reports of help seeking at that agency were compared with agency records of treatment contacts. RESULTS: Clients reported on their help-seeking behavior for a period of approximately 8 months after they had completed an initial assessment for the outpatient treatment. With regard to the number of outpatient sessions they attended, intraclass correlations and equivalence testing showed that the TLFB data were comparable to the agency records of treatment contacts. Analysis of week-to-week correspondence of the presence or absence of help-seeking episodes showed good agreement between TLFB and the agency records for most participants, although there was substantial variation. Degree of correspondence was not associated with the length of the recall period or individual differences (e.g., drinking pattern). Older participants, however, tended to have lower week-to-week concordance than did younger participants. CONCLUSIONS: These data provide preliminary support for the utility of a help-seeking TLFB instrument to assess addiction- and mental health-related contacts. This instrument may be especially useful in research in which collecting temporal patterns of help seeking is of interest (e.g., in studies examining factors influencing the delay in help seeking after relapse).
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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 | 0.004 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".