“significant” p-value ≠ “significant” finding: The significance of statistical evidence for the true X (i.e., statistical significance of the p-value for the estimate of the true X) says absolutely nothing about the practical/scientific significance of the true X. That is, significance of evidence is not evidence of significance. Increasing your sample size in no way increases the practical/scientific significance of your practical/scientific hypothesis. “significant” p-value = “discernible” finding: The significance of statistical evidence for the true X does tell us how well the estimate can discern the true X. That is, significance of evidence is evidence of discernibility. Increasing your sample size does increase how well your finding can discern your practical/scientific hypothesis.

research on health comm messaging effects

The results suggest that there was no significant difference in compliance rates between treatment and control schools six months post-treatment. To our knowledge, it is the first randomized controlled trial evaluating the use of descriptive social norms in increasing immunization compliance rates in a school-based setting. In addition, it serves as an example of embedding a behaviorally-informed experiment in a government program utilizing high-quality administrative data.

Three of the best-known health messages are eating five portions a day of fruit and vegetables, getting 150 minutes of exercise a week and quitting smoking. But what evidence is there that these have worked?

Increases in condom use were larger for longer campaigns and in nations that scored lower on the human development index. Increases in transmission knowledge were larger to the extent that respondents reported greater campaign exposure, for more recent campaigns, and for nations that scored lower on the human development index.

Post on average effect size of health comm campaigns from On Social Marketing and Social Change