Evaluation of Positive Choices, a National Initiative to Disseminate Evidence-Based Alcohol and Other Drug Prevention Strategies: Web-Based Survey Study
Bibliographic record
Abstract
BACKGROUND: To prevent adolescents from initiating alcohol and other drug use and reduce the associated harms, effective strategies need to be implemented. Despite their availability, effective school-based programs and evidence-informed parental guidelines are not consistently implemented. The Positive Choices alcohol and other drug prevention initiative and website was launched to address this research and practice gap. The intended end users were school staff, parents, and school students. An 8-month postlaunch evaluation of the website showed that end users generally had positive feedback on the website's usability, and following its use, most of them would consider the evidence base and effectiveness of drug education resources. This study extends this initial evaluation by examining the effectiveness and impact of the Positive Choices initiative over a 3-year period. OBJECTIVE: Guided by the five dimensions of the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework, the study assessed the impact of the Positive Choices initiative in increasing awareness and implementation of evidence-based drug prevention. METHODS: Data were collected between 2017 and 2019, using web-based evaluation and community awareness surveys. Data from the surveys were merged to examine reach, effectiveness, adoption, implementation, and maintenance using descriptive statistics. Google Analytics was used to further understand the reach of the website. The System Usability Scale was used to measure website usability. In addition, inductive analysis was used to assess the participants' feedback about Positive Choices. RESULTS: A total of 5 years after launching, the Positive Choices website has reached 1.7 million users. A national Australian campaign increased awareness from 8% to 14% among school staff and from 15% to 22% among parents after the campaign. Following a brief interaction with the website, most participants, who were not already following the recommended strategies, reported an intention to shift toward evidence-based practices. The System Usability Scale score for the website was good for both user groups. The participants intended to maintain their use of the Positive Choices website in the future. Both user groups reported high level of confidence in communicating about topics related to alcohol and other drugs. Participants' suggestions for improvement informed a recent website update. CONCLUSIONS: The Positive Choices website has the capacity to be an effective strategy for disseminating evidence-based drug prevention information and resources widely. The findings highlight the importance of investing in ongoing maintenance and promotion to enhance awareness of health websites. With the increased use and acceptability of health education websites, teams should ensure that websites are easy to navigate, are engaging, use simple language, contain evidence-informed resources, and are supported by ongoing promotional activities.
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 | 0.047 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".