ArticleJournal of studies on alcohol and drugs. Supplement2019
Measuring Unmet Demand for Alcohol and Other Drug Treatment: The Application of an Australian Population-Based Planning Model.
Article in Journal of studies on alcohol and drugs. Supplement, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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.
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Who cites it
19 citing papers in PubMed.
- A Personalized Approach Bias Modification Smartphone App ("SWiPE") to Reduce Alcohol Use: Open-Label Feasibility, Acceptability, and Preliminary Effectiveness Study.JMIR mHealth and uHealth · 2021Trial
- Mobile alcohol-specific inhibition training in adolescents and young adults with alcohol use disorder: study protocol for a randomized controlled feasibility trial.Frontiers in psychology · 2026Article
- Unmet treatment need: The size of the gap for alcohol and other drugs in Australia.Drug and alcohol review · 2025Article
- People who use drugs and the right to health.Harm reduction journal · 2024Review
- Diagnosing and managing prescription opioid use disorder in patients prescribed opioids for chronic pain in Australian general practice settings: a qualitative study using the theory of Planned Behaviour.BMC primary care · 2024Article
- Using the National Mental Health Service Planning Framework to inform integrated regional planning: a case study in Tasmania, Australia.International journal of mental health systems · 2023Article
- Polysubstance use in young people accessing residential and day-treatment services for substance use: substance use profiles, psychiatric comorbidity and treatment completion.Addiction (Abingdon, England) · 2022Article
- 'A circuit breaker' - Interrupting the alcohol autopilot: A qualitative exploration of participants' experiences of a personalised mHealth approach bias modification intervention for alcohol use.Addictive behaviors reports · 2022Article
- Comparing Cannabis Use Disorder in the General Population with Cannabis Treatment Seekers Using Multi-Source National Datasets: Who Receives Treatment?European addiction research · 2022Article
- SMART Recovery International and COVID-19: Expanding the reach of mutual support through online groups.Journal of substance abuse treatment · 2021Article
- Adapting harm reduction services during COVID-19: lessons from the supervised injecting facilities in Australia.Harm reduction journal · 2021Article
- Personalized Approach Bias Modification Smartphone App ("SWIPE") to Reduce Alcohol Use Among People Drinking at Hazardous or Harmful Levels: Protocol for an Open-Label Feasibility Study.JMIR research protocols · 2020Article
- Development of a Needs-Based Planning Model to Estimate Required Capacity of a Substance Use Treatment System.Journal of studies on alcohol and drugs. Supplement · 2019Article
- Key Considerations in Planning for Substance Use Treatment: Estimating Treatment Need and Demand.Journal of studies on alcohol and drugs. Supplement · 2019Review
- Seven Core Principles of Substance Use Treatment System Design to Aid in Identifying Strengths, Gaps, and Required Enhancements.Journal of studies on alcohol and drugs. Supplement · 2019Review
- Needs-Based Planning for Substance Use Treatment Systems: The New Generation of Principles, Methods, and Models.Journal of studies on alcohol and drugs. Supplement · 2019Article
- Needs-Based Planning for Substance Use Treatment Systems: Progress, Prospects, and the Search for a New Perspective.Journal of studies on alcohol and drugs. Supplement · 2019Review
- Addiction Treatment: Who Needs It?Journal of studies on alcohol and drugs. Supplement · 2019Review
- Characteristics of clients entering women-only substance use treatment services in New South Wales.Women's health (London, England)Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe estimation of demand for treatment is one of the important elements in planning for alcohol and other drug treatment services. This article reports on a demand-projection model used in Australia to estimate the extent of unmet treatment demand by drug type.
methodThe model incorporated the prevalence of substance use disorders (by drug type and age), with the application of a severity distribution, which distributed the substance abuse disorders into three disability categories: mild, moderate, and severe. The application of treatment rates derived from expert judgments reflecting the proportion of people within disability categories who would be suitable for, likely to seek, and benefit from treatment. Sensitivity analyses incorporating variations to the severity distributions and treatment rates were applied, along with adjustment for polydrug use.
resultsThe estimate for treatment demand for Australia varied between a low of 411,740 people and a high of 755,557 people. The most sensitive parameter is the expected treatment-seeking rate. Given that approximately 200,000 to 230,000 people are currently in treatment, this represents a met demand of between 26.8% and 56.4%.
conclusionsThere is insufficient alcohol and drug treatment available to meet the demand in Australia, despite Australia's relatively high met demand, when compared with other countries.
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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.