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King's College London, Strand, London, UK

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"PhD Studentship: Investigate the effectiveness of Individual Placement and Support (IPS) for people with alcohol and drug dependence"

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PhD Studentship: Investigate the effectiveness of Individual Placement and Support (IPS) for people with alcohol and drug dependence

PhD Studentship: Investigate the effectiveness of Individual Placement and Support (IPS) for people with alcohol and drug dependence

The Addictions Department (School of Academic Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King’s College London) invites applications for a fully funded PhD studentship beginning in February 2026. Please note the funding is only available for Home Fees Status students.

Background

This doctoral research will investigate the effectiveness of Individual Placement and Support (IPS) for people with alcohol and drug dependence. IPS is a psychosocial intervention designed to help individuals obtain and sustain employment in the competitive job market. It is well established in mental and physical health conditions. A successful randomised controlled trial evaluated IPS for people with alcohol and drug dependence, and IPS services are now commissioned in 95% of local authority areas across England. In the past 12 months, approximately 8,000 people with alcohol and drug dependence commenced an episode of IPS.

Project Summary

This doctoral research will evaluate the effectiveness of IPS as delivered in routine practice for people with alcohol and drug dependence. This will be a large-scale longitudinal cohort study using national registry data on employment and health. A target trial emulation framework will be used with advanced causal inference methods – including inverse probability weighting to construct a valid comparison group. The analysis will use the potential outcomes approach to address time-dependent confounding, selection bias, and variation in how individuals receive and engage with IPS, alcohol and drug dependence treatment, and other health services. Traditional regression and marginal structural models will be extended with machine learning techniques for counterfactual prediction and to support sensitivity analyses.

Candidate

The studentship is suited to a candidate with a strong background in biostatistics or data science, and a clear interest in applying these skills to questions of causal inference in longitudinal observational designs. Please note the funding is only available for Home Fees Status students.

Contact

The project will be supervised by Professor John Marsden, in collaboration with the Department of Health and Social Care. To express interest, please send a short biographical summary (maximum 300 words) and an outline of how you would approach the research (maximum 300 words) to Margarita Bela (EA-Marsden@kcl.ac.uk). If you have any academic queries about the project, please contact Professor John Marsden (john.marsden@kcl.ac.uk). The deadline is Friday 17th October 2025.

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