Evaluating the Acceptability of a Brief Web-Based Alcohol Misuse Prevention Program Among US Military Cadets: Mixed Methods Formative Evaluation
Bibliographic record
Abstract
BACKGROUND: As alcohol misuse remains pervasive within the military, evidence-based prevention programs that are feasible to implement and appropriately tailored to meet the needs and norms of military personnel are critically needed. Further, programs that target future military leaders, such as trainees, recruits, and cadets, may be especially impactful. eCHECKUP TO GO is an online, evidence-based brief alcohol intervention designed to reduce alcohol misuse through education and personalized feedback that may be suitable for military trainees. However, because it was developed for civilian students, efforts to adapt the content for military settings are needed. OBJECTIVE: The objective of this study was to evaluate the acceptability of a military version of eCHECKUP TO GO, tailored to include military-specific terminology and alcohol use statistics. METHODS: US Air Force Academy cadets were recruited to participate in a single-arm, mixed methods study. Following completion of eCHECKUP TO GO, participants completed a survey that assessed satisfaction with specific aspects of the user experience, including ease of use, design, and relevance of the information and personalized feedback (range: 1 [strongly disagree] to 7 [strongly agree]). A subset of cadets also participated in a focus group to expound on the survey responses. RESULTS: Survey participants included 22 cadets (54.5% male; mean [M] age 19.6 years, SD 1.8). Six cadets (27.2%) also participated in the focus group. Participants were satisfied with the program overall (M 5.8, SD 0.9) and gave the highest ratings to ease of use (M 6.6, SD 0.7), site design (M 6.5, SD 0.6), and site interactivity (M 6.4, SD 1.0). Items pertaining to tailoring, relevance, and amount of content specific to cadets scored lowest (M 5.8, SD 1.4; M 5.6, SD 1.4; M 5.5, SD 1.5, respectively). Most (68.2%) said they would act upon the information they were provided. Focus group participants made suggestions for improved tailoring, such as increasing content on social aspects of drinking and military-specific risks of alcohol misuse (eg, Uniform Code of Military Justice violations). CONCLUSIONS: Although acceptability of eCHECKUP TO GO was high, continued efforts are needed to ensure the content accurately reflects the experiences of cadets. Researchers who design military health promotion interventions need to consider the varied contexts within the force and rigorously evaluate the acceptability of all content before implementation.
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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 | 0.058 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".