Cannabis Healthcare Education Impact Assessment

What I noticed

Cannabis-healthcare education is usually judged by attendance and by how the room felt at the end. Both are easy to collect and both answer a question nobody actually had. The questions that matter arrive later: whether a person understands disclosure and interaction risk, whether they feel able to raise cannabis use with a clinician, and whether they behave differently the next time they are in a care setting. A single survey handed out as people leave collapses all of that into one number. It also mixes together what someone already knew with what the session added, and treats a stated intention as though it were an action. Separating those requires asking the same person twice, which in turn requires linking two responses without holding a name.

What I researched

The instrument uses a matched pre and post design with Knowledge, Attitude, and Behaviour subscales, followed by Outcome, Confidence, Motivation, Barriers, stage-of-change items, and a one-to-three-month follow-up. It collects optional demographic and care context, groups responses through event codes, normalises item scores, and sets out matched-pair, regional, legal-status, and intention-to-action analysis. Jacques et al. (2025) is identified in the public methodology as a continuing-education precedent for the format, and the page states the thresholds a data set would have to reach before publication. Every one of those choices is visible on the page rather than held in a protocol document, which is what makes the design reviewable by the people it would be run on.

What exists

An anonymous pre/post assessment experience for education sessions, held entirely in the visitor's browser. A participant completes an intake, answers the pre items, and returns after the session for the post items; an event code groups the two responses to each other without ever holding a name. The pseudonymous linkage is the part worth looking at, because it is the part most demonstrations describe rather than show: the mechanism is visible in the running page, so a researcher can decide whether it would survive their own ethics review before anyone builds a study around it.

Who it serves

Healthcare educators running sessions for clinicians and patients, institutions that fund those sessions and want to know what they bought, participants who deserve to know what happens to their answers, and program evaluators designing the study that would come next.

What it demonstrates

Evaluation design, behaviour-change measurement, health education, and assessment infrastructure a session facilitator could actually run in a room. The design decisions are the substance here: subscale structure, matched-pair logic, event-code grouping, and a follow-up window chosen to sit past the point where enthusiasm alone carries an answer.

Current evidence

The live artifact demonstrates the participant intake, optional-context fields, pre and post selection, public study explanation, scoring model, follow-up concept, session-code architecture, publication thresholds, and the stated anonymity boundary. What it demonstrates is the design, not a result: the instrument is unvalidated, no sample has been collected, and the named comparison study is a precedent for the format rather than a validation of this adaptation. Any real deployment would need psychometric validation, an ethics review, and a consent process before a single response was gathered. The experience is informational and not medical advice.