Personalised psychotherapy in primary care: evaluation of data-driven treatment allocation to cognitive–behavioural therapy versus counselling for depression
Background Various effective psychotherapies exist for the treatment of depression; however, only approximately half of patients recover after treatment. In efforts to improve clinical outcomes, research has focused on personalised psychotherapy – an attempt to match patients to treatments they are...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2023-03-01
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| Series: | BJPsych Open |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2056472422006287/type/journal_article |
| _version_ | 1811156865727332352 |
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| author | Clarissa Bauer-Staeb Emma Griffith Julian J. Faraway Katherine S. Button |
| author_facet | Clarissa Bauer-Staeb Emma Griffith Julian J. Faraway Katherine S. Button |
| author_sort | Clarissa Bauer-Staeb |
| collection | DOAJ |
| description | Background
Various effective psychotherapies exist for the treatment of depression; however, only approximately half of patients recover after treatment. In efforts to improve clinical outcomes, research has focused on personalised psychotherapy – an attempt to match patients to treatments they are most likely to respond to.
Aim
The present research aimed to evaluate the benefit of a data-driven model to support clinical decision-making in differential treatment allocation to cognitive–behavioural therapy versus counselling for depression.
Method
The present analysis used electronic healthcare records from primary care psychological therapy services for patients receiving cognitive–behavioural therapy (n = 14 544) and counselling for depression (n = 4725). A linear regression with baseline sociodemographic and clinical characteristics was used to differentially predict post-treatment Patient Health Questionnaire (PHQ-9) scores between the two treatments. The benefit of differential prescription was evaluated in a held-out validation sample.
Results
On average, patients who received their model-indicated optimal treatment saw a greater improvement (by 1.78 PHQ-9 points). This translated into 4–10% more patients achieving clinically meaningful changes. However, for individual patients, the estimated differences in benefits of treatments were small and rarely met the threshold for minimal clinically important differences.
Conclusion
Precision prescription of psychotherapy based on sociodemographic and clinical characteristics is unlikely to produce large benefits for individual patients. However, the benefits may be meaningful from an aggregate public health perspective when applied at scale.
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| first_indexed | 2024-04-10T04:58:12Z |
| format | Article |
| id | doaj.art-8d42e94490b14e80a01ec7ff626e46c5 |
| institution | Directory Open Access Journal |
| issn | 2056-4724 |
| language | English |
| last_indexed | 2024-04-10T04:58:12Z |
| publishDate | 2023-03-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | BJPsych Open |
| spelling | doaj.art-8d42e94490b14e80a01ec7ff626e46c52023-03-09T12:29:28ZengCambridge University PressBJPsych Open2056-47242023-03-01910.1192/bjo.2022.628Personalised psychotherapy in primary care: evaluation of data-driven treatment allocation to cognitive–behavioural therapy versus counselling for depressionClarissa Bauer-Staeb0Emma Griffith1Julian J. Faraway2Katherine S. Button3https://orcid.org/0000-0003-4332-8789Department of Psychology, University of Bath, UKDepartment of Psychology, University of Bath, UK Avon and Wiltshire Mental Health Partnership NHS Trust, UKDepartment of Mathematical Sciences, University of Bath, UKDepartment of Psychology, University of Bath, UKBackground Various effective psychotherapies exist for the treatment of depression; however, only approximately half of patients recover after treatment. In efforts to improve clinical outcomes, research has focused on personalised psychotherapy – an attempt to match patients to treatments they are most likely to respond to. Aim The present research aimed to evaluate the benefit of a data-driven model to support clinical decision-making in differential treatment allocation to cognitive–behavioural therapy versus counselling for depression. Method The present analysis used electronic healthcare records from primary care psychological therapy services for patients receiving cognitive–behavioural therapy (n = 14 544) and counselling for depression (n = 4725). A linear regression with baseline sociodemographic and clinical characteristics was used to differentially predict post-treatment Patient Health Questionnaire (PHQ-9) scores between the two treatments. The benefit of differential prescription was evaluated in a held-out validation sample. Results On average, patients who received their model-indicated optimal treatment saw a greater improvement (by 1.78 PHQ-9 points). This translated into 4–10% more patients achieving clinically meaningful changes. However, for individual patients, the estimated differences in benefits of treatments were small and rarely met the threshold for minimal clinically important differences. Conclusion Precision prescription of psychotherapy based on sociodemographic and clinical characteristics is unlikely to produce large benefits for individual patients. However, the benefits may be meaningful from an aggregate public health perspective when applied at scale. https://www.cambridge.org/core/product/identifier/S2056472422006287/type/journal_articleDepressive disordersindividual psychotherapycognitive–behavioural therapiesprimary careoutcome studies |
| spellingShingle | Clarissa Bauer-Staeb Emma Griffith Julian J. Faraway Katherine S. Button Personalised psychotherapy in primary care: evaluation of data-driven treatment allocation to cognitive–behavioural therapy versus counselling for depression BJPsych Open Depressive disorders individual psychotherapy cognitive–behavioural therapies primary care outcome studies |
| title | Personalised psychotherapy in primary care: evaluation of data-driven treatment allocation to cognitive–behavioural therapy versus counselling for depression |
| title_full | Personalised psychotherapy in primary care: evaluation of data-driven treatment allocation to cognitive–behavioural therapy versus counselling for depression |
| title_fullStr | Personalised psychotherapy in primary care: evaluation of data-driven treatment allocation to cognitive–behavioural therapy versus counselling for depression |
| title_full_unstemmed | Personalised psychotherapy in primary care: evaluation of data-driven treatment allocation to cognitive–behavioural therapy versus counselling for depression |
| title_short | Personalised psychotherapy in primary care: evaluation of data-driven treatment allocation to cognitive–behavioural therapy versus counselling for depression |
| title_sort | personalised psychotherapy in primary care evaluation of data driven treatment allocation to cognitive behavioural therapy versus counselling for depression |
| topic | Depressive disorders individual psychotherapy cognitive–behavioural therapies primary care outcome studies |
| url | https://www.cambridge.org/core/product/identifier/S2056472422006287/type/journal_article |
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