Harmful and helpful therapy practices with consensually non-monogamous clients: Toward an inclusive framework.
Bibliographic record
Abstract
OBJECTIVE: Drawing on minority stress perspectives, we investigated the therapy experiences of individuals in consensually nonmonogamous (CNM) relationships. METHOD: We recruited a community sample of 249 individuals engaged in CNM relationships across the U.S. and Canada. Confirmatory factor analysis structural equation modeling was used to analyze client perceptions of therapist practices in a number of exemplary practices (affirming of CNM) or inappropriate practices (biased, inadequate, or not affirming of CNM), and their associations with evaluations of therapy. Open-end responses about what clients found very helpful and very unhelpful were also analyzed. RESULTS: Exemplary and inappropriate practices constituted separate but related patterns of therapist conduct. As expected, perceptions of exemplary and inappropriate practices predicted therapist helpfulness ratings and whether participants prematurely terminated their therapeutic relationships. Qualitative results point toward the importance of having/pursuing knowledge about CNM and using affirming, nonjudgmental practices. CONCLUSIONS: Therapists are positioned to either combat or perpetuate the minority stress faced by individuals engaged in CNM. The results of this study highlight the need for additional research, training, and guidelines regarding CNM clients and their therapy experiences. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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 | 0.004 | 0.008 |
| 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 | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".