Reducing Methamphetamine Use in Aboriginal and Torres Strait Islander Communities With the “We Can Do This” Web App: Qualitative Evaluation of Acceptability and Feasibility
Bibliographic record
Abstract
Background: Preventing and treating methamphetamine-related harm in Aboriginal and Torres Strait Islander populations is a significant challenge for health care services. Digital health care may offer opportunities to support individuals and families in ways that complement existing methamphetamine treatment options. This study responds to a community-identified priority as Aboriginal Community Controlled Health Services identified methamphetamine use as a key concern and sought support to respond to the needs of people who use methamphetamine and their families. Objective: This paper reports on a process evaluation of the web application's acceptability and feasibility when used by clients and clinicians in residential rehabilitation services and primary care. This study is part of a larger project entitled "Novel Interventions to address Methamphetamine use in Aboriginal and Torres Strait Islander Communities" (NIMAC), which seeks to develop culturally appropriate and strengths-based prevention and treatment interventions to reduce methamphetamine related harm. "We Can Do This" was a web application developed for Aboriginal and Torres Strait Islander people who are seeking to reduce or stop methamphetamine use. Methods: Clinicians and clients who had used the web application were recruited through Aboriginal Community Controlled Health Services and Aboriginal residential rehabilitation services in urban and regional Victoria and South Australia. Unidentified usage data was collected from all participants. After using the web application, those who indicated a willingness to be interviewed were contacted and interviewed by phone or in person and asked about the feasibility and acceptability of the web application. The framework method of analysis was used to structure and summarise the resulting qualitative data. Results: Interviews with 24 clients and 11 clinicians explored the acceptability and feasibility of the web application. Acceptability incorporated the following domains: affective attitude, burden, ethicality, cultural appropriateness, coherence, opportunity cost, perceived effectiveness, and self-efficacy. The evaluation of feasibility assessed barriers and facilitators to the implementation of the program, with a focus on demand, practicality, fidelity, and integration. Results indicated that both clients and clinicians found the web application content coherent, relatable, empowering, and culturally safe. Barriers to using the web application for clients included a lack of internet connectivity and personal issues such as scheduling. Conclusions: Process evaluation is often under-valued. However, as "We Can Do This" was new, innovative and targeted a hard-to-reach population, understanding its feasibility and acceptability as a clinical tool was essential to understanding its potential. "We Can Do This" is unique as the only evidence-based, culturally appropriate internet-based therapeutic program specifically designed for Aboriginal and Torres Strait Islander people who use methamphetamine. Findings suggest it was both acceptable and feasible as a low-cost adjunct to usual care in residential rehabilitation and primary care settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".