Profiles of medical services use and health status in sex therapy clients: Associations with therapeutic alliance, attachment and trauma
Bibliographic record
Abstract
Adults with sexual difficulties tend to report poorer health and higher health services utilization than individuals from community samples. Several correlates are related to greater use of health services, such as childhood interpersonal traumas, insecure attachment and level of therapeutic alliance. Although it is documented that clients presenting sexual difficulties and seeking sex therapy are likely to present these risk factors, health status and medical services use have not yet been empirically examined in this population. A total of 220 clients seeking sex therapy completed self-report questionnaires assessing childhood interpersonal traumas, attachment representations, therapeutic alliance, and sexual satisfaction. Five variables were used to identify their health status and medical services use: 1) annual number of medical consultations; 2) annual number of emergency room visits; 3) presence of chronic health problems; 4) frequency of medication intake; and 5) health status self-assessment. Hierarchical clustering analyses were conducted and three distinct profiles were identified according to the clients’ health status and medical services use. The first profile ( n = 106) was characterized by a good health and low use of medication and medical services. Compared to the other profiles, these clients report more secure attachment, stronger therapeutic alliance, and fewer traumas. The second profile ( n = 73) showed the highest frequency of medical and emergency room consultations. These clients all reported a chronic health problem and a high rate of trauma. The third profile ( n = 41) included clients using the most medication, but reporting a globally good health. These clients reported low levels of therapeutic alliance. Results provide a better understanding of the associations between sexual difficulties and health problems.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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 | 0.000 |
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".