To Leave or Stay? Influences on Early Exit and Completion in a New Zealand Residential Drug Rehabilitation Service

Research indicates a positive correlation between residential treatment duration and residents' positive outcomes. Between 2015 and 2019, a New Zealand residential drug rehabilitation service noted a rise in premature program exits, leading to an in-depth investigation into the individual and therapeutic community factors that impact residents' completion of the 18-week program. The aim of the study was to understand how to enhance support mechanisms that promote longer treatment stays with the view to improving well-being outcomes. The authors conducted a two-phase, mixed-methods study. They applied quantitative secondary data analysis to data collected between 2015 and 2019 from 796 participants and did follow-up qualitative data collection in 2023, where 15 former residents participated in focus groups. Six were then randomly selected to participate in an in-depth interview. This article reports findings from the interviews of that study. The aims of this article are threefold. The authors introduce data from a New Zealand drug rehabilitation service as a case for using ChatGPT to support AI-assisted thematic narrative analysis. Steps in the analysis are detailed through a reproducible prompting process. Second, the authors present findings highlighting factors influencing residents to leave treatment and those that influenced them to stay. The authors position AI as a complementary tool for qualitative data analysis that enhances methodological rigor and practical applications in addiction research.