ArticlePatient preference and adherence2022
Feasibility of Testing Client Preferences for Accessing Injectable Opioid Agonist Treatment (iOAT): A Pilot Study.
Article in Patient preference and adherence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- "I'm just searching to get better": Constructions of treatment citizenship on injectable opioid agonist treatment.Social science & medicine (1982) · 2024Article
- Clients' experiences on North America's first take-home injectable opioid agonist treatment (iOAT) program: a qualitative study.BMC health services research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Injectable opioid agonist treatment (iOAT) is an effective treatment for opioid use disorder (OUD). To our knowledge, no research has systematically studied client preferences for accessing iOAT. Incorporating preferences could help meet the heterogenous needs of clients and make addiction care more person-centred. This paper presents a pilot study of a best-worst scaling (BWS) preference elicitation survey that aimed to assess if the survey was feasible and accessible for our population and to test that the survey could gather sound data that would suit our planned analyses. Patients and Methods: Current and former iOAT clients (n = 18) completed a BWS survey supported by an interviewer using a think-aloud approach. The survey was administered on PowerPoint, and responses and contextual field notes were recorded manually. Think-aloud audio was recorded on Audacity. Results: Clients' feedback fell into five categories: framing of the task, accessibility, conceptualization of attributes and levels, formatting, and behaviour predicting questions. Survey repetitiveness was the most consistent feedback. The data simulation showed that 100 responses should provide an adequate sample size. Conclusion: This pilot demonstrates the type of analysis that can be done with BWS in our population, suggests that such analysis is feasible, and highlights the importance of the interviewer and participant working side-by-side throughout the task.
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Registered trials
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.