A METAANALYSIS OF THE EFFECT OF MEDICATED HEALTH

A META-ANALYSIS OF THE EFFECT OF MEDICATED HEALTH COMMUNICATION CAMPAIGNS TRENT C. JOSEPH PCH 586

WHAT IS META-ANALYSIS? -Statistical procedure for combining data from independent studies. -Used to determine the effectiveness of a study by using a common measure called effect size. -Successful meta-analysis can be used to identify the reason for the variation of effect.

BIOSTAT 101: EFFECT SIZE • Effect size is a simple way of quantifying the difference between two groups. *valuable for quantifying effectiveness of a particular intervention • “Does it work or not? ” vs. “How well does it work in a range of contexts? ” • Important tool for reporting and interpreting effectiveness than statistical significance (p-value).

THE CURRENT STUDY -Snyder et al. (2004) performed a meta-analysis of studies of mediated health campaigns in the United States. Purpose: To estimate the average effects of medicated health campaigns for different health topics and types of behavior. Research Questions: 1. What is the average effect size for different campaign topics? 2. Which function best describes the impact of baseline behavior rates on campaign effect size?

VARIABLES Independent Variable(s): Campaign Topic Type of Behavior Adoption Type Addictiveness of Behavior Baseline Behavior Rate Dependent Variable(s): Effect on behavior change

HYPOTHESES 1. Campaigns promoting the commencement of a new behavior will have a greater average effect size than campaigns promoting the prevention of an undesirable behavior, which in turn, will have a greater average effect size than campaigns promoting the cessation of an existing undesirable behavior. 2. Campaigns that promote the cessation of addictive behaviors will have a smaller effect size than those promoting the cessation of non-addictive behaviors.

CAMPAIGN TOPIC/BEHAVIOR The broad categories of campaign topics included: • Smoking • Drinking • Seat-belt use • Cardiovascular (diet and exercise) • Mammography • Dental care • Sexual behavior Unfortunately, it is not feasible to meta-analyze the effects of mediated campaigns on most specific behaviors because there are few studies conducted on those specific behaviors.

ADOPTION TYPE • The “goal of the campaign” • However, it may be difficult to categorize that “goal” to only prevent a behavior without necessarily promoting a new behavior. A promising distinction is to differentiate between: (a)The commencement or a new behavior (b)The prevention of an undesirable new behavior (c)The cessation/reduction of an old behavior

WHAT ADOPTION TYPE DO THESE CAMPAIGNS HAVE? UK Campaign: http: //youtu. be/ymi. F-okrd. Mg Embrace Life Campaign: http: //youtu. be/h-8 PBx 7 iso. M Strong 4 Life Campaign: http: //youtu. be/HKz. Y 0 v. Xlhn. Q

ADDICTIVE BEHAVIOR Is the behavior addictive or not? • Campaigns should seek to alter an individual’s intentions and attitudes towards the behavior • Addiction increases resistance to campaign messages • There are often physiological barriers to changing an addictive behavior

BASELINE BEHAVIOR RATE -The pretest percentage of the desired behavior in the invention community. Diffusion Theory: the percentage of the population that adopts to a new behavior and follows a predictable pattern over time. Bandwagon effect: positive impact on baseline behavior rate. The more people who engage in the behavior the more correct the behavior appears to be. “Resistance effect”

MEASURES • To compute the effect size for each campaign researchers converted the published statistic into a correlation (r) using standard deviation formulas. • The correlation was then converted from r to d with the DSTAT. To calculate the d-statistic researchers used the following formula: Cohen’s D

KEY FINDINGS • The average media campaign effect on behavior was r=. 09. Cohen's d 0. 2 0. 5 0. 8 Interpretation Small meduim Large

FINDINGS CONT’D • Half (48) of the campaigns promoted the adoption of a new behavior and were more successful than prevention and cessation campaigns (r=. 12). • Smoking was the only addictive behavior represented in the campaigns making the test of H 1 weak. • Behavior rate results were inconclusive.

RECOMMENDATIONS • Campaign planners should set modest goals for campaigns and be sure to use large sample sizes to detect effect size. • It would also help to consider the type of behavior being promoted (CCP) and whether or not the campaign behavior is addictive. • To effectively test campaign effect size researchers' should design a field experiment to directly test novel campaign designs.

• It is essential to understand the key characteristics of campaigns that moderate effect size and it is critical to remember that small percentages may affect very large numbers of people. • For new campaign topics, it is important to know whether or not there will be enforcement messages since they have greater success rates. • Lastly, media campaigns may be more costeffective when compared to clinical-based education

REFERENCES Comprehensive meta-analysis. (2006). Retrieved from http: //www. metaanalysis. com/pages/why_do. html Communicate and Collaborate. (2009). http: //www. peersnet. com/General/12857