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Compatibility Matching on Age and Gender in Predicting Psychotherapy Outcomes
Sabine Lehane1, Luigi Medoro1, Adrian B Kelly1
1School of Psychology and Counselling, Faculty of Health, Queensland University of Technology, Kelvin Grove, Australia.
Objective:
This study investigated whether specific client-therapist age and gender pairings increase compatibility and bolster psychotherapy outcomes and engagement. Identifying influential relational factors may inform compatibility-based, data-driven matching processes in clinical practice.
Method:
Analyses were conducted using historical questionnaire data from a large sample of 1044 community clients (68.6% female; M = 31.6 years, SD = 12.8; aged 18-76) and 138 provisionally registered student therapists (79.7% female; M = 30.1 years, SD = 8.2; aged 21-57) at a university-affiliated community psychology clinic. Moderated multiple regression examined whether age differential (therapist age-client age), gender combinations (four-level moderator: female-female, male-male, female-male and male-female) or their interaction predicted treatment outcomes, controlling for treatment length (n = 886) (Analysis 1), and hierarchical logistic regression examined the influence on early dropout within three sessions (n = 1004) (Analysis 2). Outcomes were assessed via the Outcome Questionnaire-45 (OQ-45), which measures symptom distress, interpersonal relations and social role functioning.
Results:
A greater age differential, with an older therapist, revealed a small but significant improvement in outcomes, namely, in symptom distress and social role OQ-45 subscales. For female clients, older male therapists decreased early dropout compared to older female therapists.
Conclusions:
Findings suggest a 'perceived expertise' effect, where older therapists, relative to the client, may be viewed as more competent, enhancing client outcomes. For female clients, gendered experiences and expectations influence the impact of age differential on early dropout. These results underscore the potential value of considering relational demographic dynamics in clinical matching processes.
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