Researchers ran what I'd call a design battle. Three versions of personalized drinking feedback - same data, same email delivery - and only the format changed. After 90 days the format mattered, at least for how often people drank.

What they did

222 young adults who drank regularly (mean age 21) got one of three feedback conditions, split by block allocation stratified on alcohol intake level and impulsivity:

  • Text. Researcher-written feedback on alcohol intake and brain health, in paragraphs.
  • Researcher image. Same content, turned into a visual by the research team.
  • Co-designed image. A visual built around what users themselves said they wanted, which took a whole separate phase to find out.

That phase: 40 participants in focus groups described what feedback would actually reach them. Six themes came up - visual representation, clarity, accessibility, brevity, peer comparison, harm. The third condition was built on those.

Feedback went out by email. The team measured total alcohol consumption, drinking frequency and alcohol-related harm over about 90 days. A few weeks after the first email landed, they also tracked capacity, opportunity and motivation to change - the three factors the study treated as predictors of behavior change.

What they found

Every group drank less. Even the plain-text email moved something. Total consumption dropped in all three conditions (η²=0.11), and alcohol-related harm dropped too (η²=0.05). There was no no-treatment control group, so regression to the mean stays on the table. The reductions were consistent anyway.

The format gap showed up in drinking frequency:

  • Image-based (researcher and co-designed alike): d=0.56 for cutting drinking days
  • Text-based: d=0.39

Modest numbers by conventional standards. The distance between 0.56 and 0.39 is real, not dramatic. But it held in both image conditions.

Preference was a different story. Participants liked the co-designed visual best: d=0.55 over the researcher-built image, d=0.83 over the text. It bought them nothing. On actual consumption the two image formats performed identically.

Format also did nothing for capacity, opportunity and motivation to change (η=0.01). It shifted behavior without shifting stated intentions first.

What it means

The sample skews young - mean age 21 - so I wouldn't stretch this to older drinkers. Self-reported consumption adds noise. And without a no-feedback arm, it's hard to separate "the format worked" from "any feedback works."

The visual-versus-text gap still rings true to me.

A chart of your drinking and a paragraph about your drinking are different kinds of information, even when the facts underneath are identical. A chart lands as a fact about you right now. A paragraph is a report. My guess is those two trigger different responses. Guess being the operative word: the study shows the gap, not the mechanism.

The co-design result is the part I keep coming back to. People helped build the feedback they wanted, and they did prefer it. It changed nothing in the outcomes. Better user experience, same behavior change.

On a night when you're keeping pace with the table, a text summary of your drinks doesn't land the way a curve does. Watching your BAC climb toward its peak and then fade puts you in a different relationship with the next drink than reading "3 standard drinks." AlcoBalance shows you that curve in real time - not a report of what happened, but where you are now and where you're heading.

Source: Journal of Medical Internet Research, 10.2196/87393