Integrated treatment program for alcohol related problems in community hospitals, Songkhla province of Thailand: A social return on investment analysis
Bibliographic record
Abstract
OBJECTIVES: To estimate the impacts and social value relative to the cost of the Integrated Management of Alcohol Intervention Program in the Health Care System (i-MAP) on direct beneficiaries, using a Social Return on Investment (SROI) analysis. METHOD: A mixed-method approach was conducted among stakeholders and 113 drinkers (29 low-risk, 43 high-risk, and 41 dependent drinkers) who consecutively received i-MAP at four community hospitals in Songkhla province of Thailand. Resources for program implementation as well as drinking and a list of psychosocial outcomes, selected through stakeholder interviews, were measured among participants during and at the sixth month after participation, respectively. SROI (societal benefit-to-cost) ratio of i-MAP was estimated over a 5-year time horizon and shown in 2017 Thai baht, where US$1.00 = 33.1 baht. One-way and probabilistic sensitivity analyses of key parameters were performed among treatment subgroups. RESULTS: Baseline estimates of the annual cost and 5-year social value of i-MAP were 25.5 and 51.0 million baht, respectively, yielding an estimated SROI ratio of 2.0, with a possible range of 1.3 to 2.4. Value created by the program was mostly attributed to broader gains to society (productivity gains and averted crime costs) and drinkers. Subgroup analyses suggested that the SROI ratio for high-risk drinkers was twice that for dependent drinkers (2.8 vs. 1.5). The probabilistic sensitivity analysis showed that more than 99% of the simulated treatments for both high-risk and dependent groups yielded benefits beyond the corresponding costs. CONCLUSIONS: By considering societal perspective, the i-MAP program has demonstrated its social value is twice its investment cost and potential for the program to be implemented nationwide.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".