Should your lips be zipped? How therapist self‐disclosure and non‐disclosure affects clients
Bibliographic record
Abstract
Abstract Is therapist self‐disclosure a therapeutic technique or a therapeutic mistake? Is it useful? Is it ethical? This study attempts to address this controversy among therapeutic modalities by asking clients about their perceptions of self‐disclosure and non‐disclosure. Eighteen people (16 women, two men), currently in therapy in two Canadian cities, generated 157 incidents of both disclosure and non‐disclosure. The incidents were first coded as helpful or unhelpful. Cross‐tabulation of the results showed that disclosures were more than twice as likely to be experienced as helpful; non‐disclosures were twice as likely to be unhelpful (χ2 (3, N=157) = 14.439, p≤0.002). One‐quarter of these incidents was coded by two independent raters; inter‐rater reliability was high (Pearson corr. ranged from 0.755 to 1.0, p≤0.01). The data was then sorted, using the Constant Comparison method, into themes, starting with, but not limited to, the themes suggested by the literature. The greatest single effect was on the therapeutic alliance, both positive and negative. Clients’ perceptions of helpful disclosures and non‐disclosures generally supported therapists’ rationales. There was also some evidence that when clients found disclosures unhelpful, the reasons also supported theoretical rationales against disclosing. Rather than simply supporting either position in the controversy, this study suggests that skill, or lack of it, was the intervening variable that affected the perceptions of both techniques. Further research on the effects of skill on both disclosure and non‐disclosure are warranted. This study has implications for both researchers and practitioners.
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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 | 0.010 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".