psychological architectures of health behaviour change websites
TRANSCRIPT
THE PSYCHOLOGICAL ARCHITECTURES OF HEALTH BEHAVIOUR CHANGE WEBSITESDesigning interventions with the CBICMBrian Cugelman, PhD
29 November 2010
Health changing websites: the cutting edge of online behaviour changeToronto, Canada
Presentation partners:
1. ONLINE SOCIAL MARKETING
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SOCIAL MARKETING
“Social marketing is the systematic application of marketing alongside other concepts and techniques to achieve specific behavioural goals, for social or public good.”
(National Social Marketing Centre, 2006)
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EXAMPLES OF CAMPAIGNSQuit smokingExercise more
Drive saferDrink less
Eat healthierEat moreEat less
ONLINE SOCIAL MARKETING
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NEW BREED OF ONLINE HEALTH INTERVENTIONS
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2. THE RESEARCH PROJECT
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RESEARCH QUESTIONS
1. How can online interventions scale to the population level?
2. With such high attrition, what can be done to improve intervention efficacy?
3. How do you design an online health intervention?
4. Which psychological architectures work best?
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CHALLENGES
• Few studies of voluntary behaviours, as most dealt with chronic disease management
• No magic list of psychological design
• Traditional one-way communication models only partially describe online communications, which is increasingly two-way
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SOLUTIONS
• Communication-base Influence Components Model (CBICM)• Psychological architectures• One or two-way communications
• Meta-analysis (what’s meta-analysis?)• Psychology• Adherence
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3. COMMUNICATION-BASED INFLUENCE COMPONENTS MODEL (CBICM)
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THERE IS NO “ONE SIZE FITS ALL” TAXONOMY TO DESCRIBE ONLINE INTERVENTIONS
Stages of change Cialdini
CAPTOLOGY Community-based social marketing
Evidence-based behavioural medicineLearning Theories/Behaviourism
Social Cognitive TheoryTheory of Reasoned Action/Planned Behaviour
And many more....
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ONE-WAY: ONE-TO-ONE, ONE-TO-MANY
(One
-Way
) One
-toOne
Impersonal
Many
Mass Media
(Tw
o-W
ay) O
ne-w
ith Interpersonal Mass Interpersonal
one-with-one
one-to-one
CUGELMAN, B., THELWALL, M., & DAWES, P. (2009) Communication-based influence components model. Paper presented at the Persuasive 2009, Claremont.
(One
-Way
) One
-toOne
Impersonal
Many
Mass Media
(Tw
o-W
ay) O
ne-w
ith Interpersonal Mass Interpersonal
one-with-one
one-to-one
TWO-WAY: ONE-WITH-ONE
CUGELMAN, B., THELWALL, M., & DAWES, P. (2009) Communication-based influence components model. Paper presented at the Persuasive 2009, Claremont.
(One
-Way
) One
-toOne
Impersonal
Many
Mass Media
(Tw
o-W
ay) O
ne-w
ith Interpersonal Mass Interpersonal
one-with-one
one-to-one
MASS/INTERPERSONAL DIVIDE
CUGELMAN, B., THELWALL, M., & DAWES, P. (2009) Communication-based influence components model. Paper presented at the Persuasive 2009, Claremont.
(One
-Way
) One
-toOne
Impersonal
Many
Mass Media
(Tw
o-W
ay) O
ne-w
ith Interpersonal Mass Interpersonal
one-with-one
one-to-one
MASS-INTERPERSONAL COMMUNICATION
CUGELMAN, B., THELWALL, M., & DAWES, P. (2009) Communication-based influence components model. Paper presented at the Persuasive 2009, Claremont.
COMMUNICATION-BASED INFLUENCE COMPONENTS MODEL (CBICM)
SourceInterpreter
InterventionMessage
AudienceInterpreter
FeedbackMessage
Media ChannelContext
Decode
EncodeDecode
Encode
CUGELMAN, B., THELWALL, M., & DAWES, P. (2009) Communication-based influence components model. Paper presented at the Persuasive 2009, Claremont.
A framework to describe the psychology of interventions
4. THE STUDY
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THE META-ANALYSIS
• Searched five databases + grey literature
• Obtained 1,271 results• Retrieved 95 full text studies• Selected 31
• Primary analysis: 30 interventions from 29 studies (N=17,524)
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Study name Statistics for each study Std diff in means and 95% CI
Std diff Standard Lower Upper in means error limit limit Z-Value p-Value
Bersamin et al. (2007) 0.470 0.174 0.130 0.810 2.707 0.007Bewick et al. (2008) 0.123 0.113 -0.099 0.345 1.084 0.278Bruning Brown et al. (2004) a 0.294 0.172 -0.043 0.632 1.708 0.088Bruning Brown et al. (2004) b 0.637 0.264 0.120 1.154 2.413 0.016Celio et al. (2000) 0.494 0.298 -0.090 1.077 1.657 0.097Chiauzzi et al. (2005) 0.145 0.137 -0.122 0.413 1.064 0.288Dunton et al. (2008) 0.196 0.177 -0.152 0.543 1.103 0.270Gueguen et al. (2001) 0.303 0.325 -0.334 0.939 0.931 0.352Hunter et al. (2008) 0.178 0.095 -0.008 0.364 1.870 0.061Jacobi et al. (2007) 0.478 0.206 0.074 0.881 2.319 0.020Kim et al. (2006) -0.435 0.288 -1.000 0.130 -1.509 0.131Kosma et al. (2005) 0.361 0.239 -0.107 0.829 1.512 0.131Kypri et al. (2004) 0.400 0.222 -0.035 0.835 1.802 0.072Kypri et al. (2005) 0.206 0.549 -0.869 1.282 0.376 0.707Lenert et al. (2004) 0.201 0.567 -0.910 1.311 0.354 0.723Marshall et al. (2003) -0.068 0.125 -0.314 0.177 -0.547 0.585McConnon et al. (2007) -0.092 0.178 -0.440 0.256 -0.519 0.604McKay et al. (2001) 0.116 0.243 -0.360 0.592 0.477 0.634Moore et al. (2005) -0.008 0.200 -0.401 0.384 -0.042 0.966Napolitano et al. (2003) 0.527 0.287 -0.036 1.090 1.833 0.067Oenema et al. (2005) 0.169 0.102 -0.032 0.369 1.648 0.099Petersen et al. (2008) 0.014 0.031 -0.047 0.074 0.444 0.657Roberto et al. (2007) 0.162 0.434 -0.688 1.012 0.374 0.709Severson et al. (2008) 0.189 0.106 -0.019 0.397 1.778 0.075Strecher et al. (2005) 0.116 0.077 -0.035 0.266 1.505 0.132Strom et al. (2000) 0.476 0.304 -0.120 1.072 1.565 0.118Swartz et al. (2006) 0.327 0.419 -0.494 1.148 0.781 0.435Tate et al. (2001) 0.194 0.223 -0.244 0.632 0.869 0.385Verheijden et al. (2004) -0.002 0.176 -0.346 0.342 -0.012 0.991Winett et al. (2007) 0.507 0.082 0.346 0.667 6.201 0.000
0.194 0.042 0.111 0.278 4.582 0.000
-2.00 -1.00 0.00 1.00 2.00
Favours Control Favours Intervention
Meta Analysis
Meta Analysis
EFFECT SIZES
-0.4-0.3-0.2-0.10.00.10.20.30.4
Survey Only (Waitlistor Placebo)
Website Print (Major)
Overall: d=.194, p=.000, k=30
d
EFFECT SIZE BY INTERVENTION DURATION
-0.4-0.3-0.2-0.10.00.10.20.30.40.50.60.7
One-time From 2 days to 1month
Beyond 1 to 4months
Beyond 4 to 7months
Beyond 7 to 13months
d
DOSE: ADHERENCE OVER TIME
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DOSE: THREE VARIABLES
COR r=.37, p<.000, k=5
InterventionAdherence
OutcomeEffect Size
StudyAdherence MR r=.481, p=.006, k=28
MR r=.455, p=.109, k=13COR r=.240, p<.000, k=9
COR: Correlation effect sizeMR: Meta-regression estimate
RELATIVE INFLUENCE COMPONENTS AND OUTCOMES
876543210
Relative Behavioural Determinants (sum)
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3
-0.4
-0.5
Effe
ct S
ize
(d)
Print (Major)Website
Survey Only (Waitlist or Placebo)
ControlMediaSimple
CBICM SourceInterpreter
InterventionMessage
AudienceInterpreter
FeedbackMessage
Media ChannelContext
Decode
EncodeDecode
Encode
INTERVENTION MESSAGE
SourceInterpreter
InterventionMessage
AudienceInterpreter
FeedbackMessage
Media ChannelContext
Decode
EncodeDecode
Encode
AUDIENCE INTERPRETER
SourceInterpreter
InterventionMessage
AudienceInterpreter
FeedbackMessage
Media ChannelContext
Decode
EncodeDecode
Encode
LOOKING FORWARD
• CBICM to help build future systems (and social media engagement)
• Mass-interpersonal public health campaigns
• State eHealth
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STUDY CREDITSFirst comprehensive meta-analysis on the
psychological design of online interventions
• CBICM in 2009: CUGELMAN, B., THELWALL, M., & DAWES, P. (2009) Communication-based influence components model. Paper presented at the Persuasive 2009, Claremont.
• 1st published Jan 2010 : CUGELMAN, B. (2010) Online social marketing: Website factors in behavioural change. University of Wolverhampton, Wolverhampton.
• 2nd extended publication in 2011: CUGELMAN, B., THELWALL, M., & DAWES, P. (2011, forthcoming) Online interventions for social marketing health behaviour change campaigns: A meta-analysis of psychological architectures and adherence factors. Journal of Medical Internet Research. (Get a pre-publication copy at www.cugelman.com) 35
THANK YOUBrian Cugelman, PhD
Phone: +1 (416) [email protected]
Get in touch
www.AlterSpark.com
@AlterSpark alterspark alterspark alterspark
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