ArticleQualitative health research2026
To Leave or Stay? Influences on Early Exit and Completion in a New Zealand Residential Drug Rehabilitation Service.
Article in Qualitative health research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Generative Artificial Intelligence for Qualitative Methods in Health Research: Rapid Review.Journal of medical Internet research · 2026Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
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