Who Uses Bibliotherapy and Why? A Survey from an Underserviced Area
Bibliographic record
Abstract
OBJECTIVE: To assess which mental health therapists use bibliotherapy, their reasons for doing so, and rationale for recommending specific titles. To review the book selected most often in several categories, using prepublished criteria for reviewers of self-help books. METHOD: We sent a survey to all therapists in a Northern Ontario community requesting information on therapist demographics, the respondent's practice, the use of bibliotherapy, and details of the book most often prescribed in various categories. RESULTS: Of 112 surveys, 62 were returned, for a response rate of 55%. Sixty-eight percent of respondents indicated that they used bibliotherapy. The most common reason for recommending books was to encourage self-help. There was a significant relation between greater counselling experience and increased use of bibliotherapy. Three of the 5 books reviewed were based on empirical theory; only 1 met all the guidelines. CONCLUSION: Most therapists recommend books to their clients, but there is little empirical evidence of efficacy. Counsellors should review the books recommended and discuss them with the client. Client opinion should be solicited and effectiveness measured.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".