Evidence map›Paper›PMID 41069063›Full record

ArticleQualitative health research2026

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

Laura Ann Chubb, Suzette Jackson, Badhoora Naseer, Maree Matthews

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Laura Ann ChubbFaculty of Arts & Education, The Centre for Community Research and Evaluation, The University of Auckland, Auckland, New Zealand.ORCID 0000-0002-4073-1436
Suzette JacksonFaculty of Arts & Education, The Centre for Community Research and Evaluation, The University of Auckland, Auckland, New Zealand.
Badhoora NaseerFaculty of Arts & Education, The Centre for Community Research and Evaluation, The University of Auckland, Auckland, New Zealand.
Maree MatthewsHigher Ground Drug Rehabilitation Trust, Auckland, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Patient DropoutsResidential TreatmentSubstance Abuse Treatment CentersSubstance-Related DisordersAdultFemaleFocus GroupsHumansInterviews as TopicMaleMiddle AgedNew ZealandQualitative Researchaddictionartificial intelligencequalitative analysissubstance usetherapeutic communitiestreatment

Identifiers

PMID41069063
PMCPMC12949039

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.