nchcmm presentation 10 variables_the research_p_keller_8-2011

Punam Anand Keller, MBA, PhD

Charles Henry Jones Third Century Professor of Management

Tuck School of Business at Dartmouth

National Conference on Health Communication, Marketing, and Media

August 9-11, 2011

Building a Better Message: The 10 Variables That Really Matter

The Research

Division of Cancer Prevention and Control

National Center for Chronic Disease Prevention and Health Promotion

BACKGROUND METHODS AND RESULTS CONCLUSIONS IMPLICATIONS FOR PRACTICE


The Problem

Four barriers prevent the application of research to improve the effectiveness of public health communication campaigns.

5.The focus on one or two message tactics makes it difficult to generalize the results to situations where the audience is faced with a wide variety of message tactics in the same or different health campaigns

7.Most health communication studies do not provide guidelines for tailoring since they do not examine how message formats interact with measurable individual differences such as psychographics.

9.Small sample sizes in most studies raise concerns about whether findings can be replicated in the field.

11.There is no evidence that message formats determine health intentions when other factors such as peer influence are taken into account.

METHODS AND RESULTSBACKGROUND CONCLUSIONS IMPLICATIONS FOR PRACTICE


To address these barriers, Drs. Keller and Lehmann systematically examined the role of message tactics and individual differences on intentions to comply with health recommendations. A model, Advisor for Risk Communication (ARC), was the outcome.

A meta-analysis of 60 experimental studies, involving 584 health message conditions and 22,500 participants (Keller and Lehmann, 2008).

•main and interaction effects on intentions to comply with health recommendations

•22 message tactics (e.g. gain/loss framing, vividness, self/other referencing, emotion)

•six individual characteristics (e.g. gender, age, race, involvement)

•two approaches to identify matches between message tactics and audience characteristics: a full and a reduced regression model.



Table 1: Main Effects from the Keller and Lehmann Advisor for Risk Communication Model

Main Effects - Individual Characteristics

1.1. AgeAge2.2. GenderGender3.3. RaceRace

Older adults, women, whites have higher health intentions.

1.1. Regulatory FocusRegulatory Focus Those with either a promotion or a prevention focus have lower health intentions.

Main Effects – Message Tactics

1.1. Health Goal: Discouraging Behavior and Health Goal: Discouraging Behavior and Detection BehaviorDetection Behavior

Messages on detection behaviors enhance health intentions. Discouraging unhealthful behaviors enhanced health.

1.1. Gain/Loss FramingGain/Loss Framing Loss framing undermined health intentions and should not be used.

1.1. Physical vs. Social ConsequencesPhysical vs. Social Consequences Emphasizing social consequences may be more effective than emphasizing physical consequences because they arouse less fear

1.1. EmotionsEmotions Emotional messages may not be more persuasive then unemotional messages and are not advisable.

1.1. Individual vs. Other-ReferencingIndividual vs. Other-Referencing Health communications in which consequences of nonadherence are directed at others are more effective than when the consequences are directed at the individual.

1.1. Vividness and Base/Case EffectsVividness and Base/Case Effects Vivid presentations (e.g., pictures, examples of specific cases/stories) are more persuasive than non-vivid formats (e.g., text only, base-rate estimates.).



Table 2: Effective Matches between Message Tactics and

Audience Characteristics from the Keller and Lehmann

Advisor for Risk Communication ModelAll ages respond to messages advocating detection behaviors

Nonwhites seem to care more about vivid messages that emphasize the effect of health consequences on loved ones

Women respond to emotional messages with social consequences for themselves or health consequences to near and dear ones

Men are more influenced by unemotional messages that emphasize personal physical health consequences

Contrary to popular use, framed health messages (loss or gain frames) are not advisable without knowledge of target audience goals (promotion vs. prevention)

Behavioral Intentions Behavioral Intentions

White Males = .13 White Females = .30

Non-White Males = .52 Non-White Females = .30

Behavioral Intentions Behavioral Intentions

White Males = .28 White Females = .14

Non-White Males = .62 Non-White Females = .39

http://www.cdc.gov/index.htm

2004 2005

2006

Lifeguard

Dribbling

Bike Race

Venus Williams

Donovan McNabb

Landon Donovan

Runaway Cell

Sun

Emma Roberts

http://www.cdc.gov/index.htm



Results were further validated through application to the CDC Verb campaign (2004-2006), a process which involved: 1). coding CDC Verb campaign advertisements;

2). using the model to calculate intention and behavior estimates; and

3). comparing the model estimates to extensive evaluation data collected on outcomes of the Verb campaign.

The CDC Verb campaign validation research found that the ARC predictions and stated intentions are closely correlated when socioeconomic status, social influence, beliefs and attitudes, number of ads, and exposure frequency are accounted for.

Measures Constants Bike RacingBR CalcConstant 2.1 1 2.1Age -0.01 0.15 0.15Gender (male - female) 0.15 0 0Race (white - non-white) -1.97 1 -1.97Promotion Focus -0.09 0.5 -0.045Prevention Focus -0.13 0.5 -0.065Discourage Behavior 0.05 0 0Gain Frame -0.04 0 0Loss Frame -0.06 0 0Social Consequences 0.22 1 0.22Physical Consequences 0.06 0.5 0.03Emotion 1.13 0.3 0.339Referencing 0.7 0.4 0.28Vividness -3.26 0.8 -2.608Detection Behavior -0.22 0 0Prevention X Gain Frame 0.51 0 0Promotion Focus X Loss Frame 0.42 0 0Age X Detection Behavior 0.01 0 0Gender x Referencing 0.62 0 0Gender X Emotion -1.67 0 0Race X Vivid 4.31 0.8 3.448Race X Referencing -1.61 0.4 -0.644

Intentions 1.235

Predicted Average Intentions 0.774692

Ad ExposuresCommercial

Pattern 1 Pattern 2 Pattern 3 Pattern 4

Bike Race 1 1 1 1

Dribbling 0 1 1 1

Life Guard 0 0 1 1

Venus Williams 0 0 0 1

Exponent of Sum Rule .77 .81 .86 .93

Intention Max Rule .77 .77 .77 .78

Sample Size 184 309 572 104

CONCLUSIONSMETHODS AND RESULTSBACKGROUND IMPLICATIONS FOR PRACTICE


Keller and Lehmann's research suggests an empirical model to tailor health communications for different target audiences.

Keller and Lehmann's empirical model provides 10 variables that are significant predictors for stated intentions and behavior when socio-economic, social influence, beliefs and attitudes, number of ads, and exposure frequency are accounted for.

Intention and behavior predictions are approximately equally sensitive to family and social influence, parent education, and recall of message exposures, and in general have less impact than the child variables or model predictions.

IMPLICATIONS FOR PRACTICEMETHODS AND RESULTS CONCLUSIONSBACKGROUND


Results show there is a significant opportunity to tailor health communications and even market public health more efficiently to different market segments.

Keller and Lehmann's (2008) model formed the basis for CDC DCPC's Message Development Tool (MDT).

http://mba.tuck.dartmouth.edu/pages/faculty/punam.keller/docs/Designing%20Effective.pdf

http://mba.tuck.dartmouth.edu/pages/faculty/punam.keller/docs/Designing Effective.pdf

Four main features of the model:

•If you have a message, the model can predict how to improve it.

•If you have a message, the model can predict which audiences will respond better

•If you have multiple messages, the model can help you choose one or predict which message should be sent to different audiences

•If you don’t have a message, the model can provide guidelines for a health message

For more information please contact Centers for Disease Control and Prevention

1600 Clifton Road NE, Atlanta, GA 30333Telephone, 1-800-CDC-INFO (232-4636)/TTY: 1-888-232-6348E-mail: [email protected] Web: www.cdc.gov


National Center for Chronic Disease Prevention and Health Promotion

nchcmm presentation 10 variables_the research_p_keller_8-2011

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