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TRANSCRIPT
SUBJECTIVE CONSEQUENCE EVALUATIONS AND PERCEIVED
NORMS: USING MOBILE TECHNOLOGY TO ASSESS AND INTERVENE UPON MECHANISMS OF BEHAVIOR CHANGE AMONG COLLEGE
STUDENT DRINKERS
JENNIFER E. MERRILL, PH.D.CENTER FOR ALCOHOL AND ADDICTION STUDIES, BROWN UNIVERSITY
Three Mechanisms of Behavior Change, Two Methods
Study
1
Mechanism
Subjective Evaluations of Consequences
Mobile
Method
Ecological Momentary Assessment
Outcome
Naturalistic Change in Drinking
Study
2
Mechanisms
Descriptive Norms
Injunctive
Norms
Mobile
Method
Text-message intervention
Outcome
Post-Intervention Change in Drinking
Alcohol Misuse in College
Over 1/3 college students report heavy drinking (4+/5+ drinks for females/males) in the past 2 weeks (Johnston, O’Malley, Miech, Bachman, & Schulenberg, 2016)
Experience a diverse and expansive range of drinking-related consequences (Hingson et al., 2009)
646,000 physically assaults, 97,000 sexual assaults 599,000 unintentional injuries 1,825 alcohol-related deaths
MOBC for College Student Drinking
Supported
• Descriptive Norms
Mixed but Promising Support
• Protective Behavioral Strategies
• Outcome expectancies• Self-efficacy• Emotion, mental health
Limited Support
• Coping motives• Intention• Parent-child
communication• Self-regulation• Recall intervention
content • Injunctive Norms
Unsupported
• Motivation/readiness to change
• Cognitive dissonance• Drinking approval,
attitude• Goal commitment• Pros and cons• Self-monitoring• Study abroad
adjustment• Defensiveness• Expectancy awareness• Perceived risk• Substance free
reinforcement
Unexamined: Subjective Evaluations
Reid & Carey (2015)
Perceptions of peer drinking behavior
Perceptions of peer drinking approval
Perceptions of personally experienced consequences
Subjective Evaluations as Predictors of Naturalistic Change in Drinking Behavior
Study 1
K01AA022938
Three Mechanisms of Behavior Change, Two Methods
Study
1
Mechanism
Subjective Evaluations of Consequences
Mobile
Method
Ecological Momentary Assessment
Outcome
Naturalistic Change in Drinking
Study
2
Mechanisms
Descriptive Norms
Injunctive Norms
Mobile
Method
Text-message intervention
Outcome
Post-Intervention Change in Drinking
Ecological Momentary Assessment (EMA)
Ecological: Data collected in subjects’ real-world environments, as they go about their livesHelps substance use researchers get ecologically valid
data about behavior, thoughts, and feelings over time
Momentary: Focus on subjects’ current state/situation
Shiffman (2014)
Why use EMA to study MOBC?
Less biased recall of outcomes and potential mechanisms
Drinking behavior varies over time; mechanisms can tooWithin- and between-person associations can differ Individuals with more negative affect drink more
Less evidence that real-time negative affect increases drinking
May help us to study when contextual factors influence (or interfere with the impact of) a mechanism E.g., increased self-efficacy due to intervention may help
reduce drinking only during positive, not negative moods
Three Mechanisms of Behavior Change, Two Methods
Study
1
Mechanism
Subjective Evaluations of Consequences
Mobile
Method
Ecological Momentary Assessment
Outcome
Naturalistic Change in Drinking
Study
2
Mechanisms
Descriptive Norms
Injunctive Norms
Mobile
Method
Text-message intervention
Outcome
Post-Intervention Change in Drinking
Subjective Evaluations of Consequences
Some “negative” alcohol-related consequences are perceived as neutral or desirable
25% rated hangovers as positive (Mallett et al., 2008)
12% not bothered at all by blackouts (White & Ray, 2013)
Getting in trouble with police or authorities rated neutral or positive by 11% (Patrick & Maggs, 2011)
Weekly variability: 42% between-person
58% within-person (Merrill et al., 2013)
Subjective Evaluations as Predictors of Change
More negative evaluations of recent consequences associated with downward change in drinking at one-week intervals in upperclassmen (Merrill, Read & Barnett, 2013)
two-week intervals in underclassmen (Barnett, Merrill, Colby & Kahler, 2015)
1 week
2 weeks
NegativeEvaluations
Decreased Alcohol Use
E.g., Post-treatment
?
?
That was bad
Hypotheses
More negative evaluations of alcohol consequences will predict: longer latency to next drinking event
fewer drinks at the next drinking event
Evaluations will differ by context
Number of Drinks at Next
Event
Real-time evaluations
Next morning evaluations
Latency to Next Drink
Contextual Variables
Planned Study Design
~100 heavy drinking students
Baseline survey and in-person orientation of procedures
28 days of EMA
Compliance-based payment schedule
Four Types of Reports
Participants will make up to 4 types of reports per day: (x1) Morning report daily
(x1) Self-initiated drinking report
(x?) Hourly drinking follow-up reports
(x1) 8pm check-in daily
EMA to Assess Evaluations as Predictors of Subsequent Drinking
Evaluations at last drinking event
Drinking at next drinking event
Qualitative Evidence for the Role of Context
Subjective Evaluations
of Cons
Perceived Social Norms
Location
Discussions with Friends
Level of Intoxication
Passage of Time
Concurrent Positive Cons
Mood
Contextual Influences On Evaluations
Subjective Evaluations
MoodIntoxication
LevelLocation
Discussion with Friends
A small first step…
In order to establish subjective evaluations as an MOBC, much more would need to happen Develop intervention targeting evaluations
Using an experimental design, demonstrate mediation of intervention evaluations drinking
Intervention
More negative
evaluations
Decreased drinking
Clinical and MOBC Implications: Interventions for College Drinking
Pre-intervention assessments of consequences could include evaluation scales Provide feedback only on consequences viewed as
particularly bothersome
Focus prevention and intervention on interpretation of negative alcohol consequences Education and/or normative feedback
on consequences
Ecological momentary intervention/just-in-time interventions Target evaluations close in time to consequence occurrence
Three Mechanisms of Behavior Change, Two Methods
Study
1
Mechanism
Subjective Evaluations of Consequences
Mobile
Method
Ecological Momentary Assessment
Outcome
Naturalistic Change in Drinking
Study
2
Mechanisms
Descriptive Norms
Injunctive Norms
Mobile
Method
Text-message intervention
Outcome
Post-Intervention Change in Drinking
Perceived Social Norms
Descriptive norms: perceived drinking behavior of peers
Injunctive norms: perceived approval of drinking behavior of peers
Strong predictors of high-risk drinking among college students (Perkins, 2002)
Students overestimate both types of norms, and conform to their perceptions over time
Normative Feedback as an MOBC
Correcting normative misperceptions is useful
Strong support for descriptive norms as a mediator of normative feedback interventions (Reid & Carey, 2015)
Existing Interventions Targeting Norms
Most focus on descriptive norms only Yet, injunctive norms may also be viable
targets (Prince & Carey, 2010; Prince et al., 2015)
Norms feedback is most persuasive when descriptive and injunctive norms align to present a consistent message (Reid et al., 2010)
Most rely on traditional in-person or computer-delivered formats, producing significant but small effects (Scott-Sheldon et al., 2014).
Three Mechanisms of Behavior Change, Two Methods
Study
2
Mechanisms
Descriptive Norms
Injunctive Norms
Mobile
Method
Text-message intervention
Outcome
Post-Intervention Change in Drinking
Study
1
Mechanism
Subjective Evaluations of Consequences
Mobile
Method
Ecological Momentary Assessment
Outcome
Naturalistic Change in Drinking
Technology to Deliver Care
Most students who drink heavily won’t seek care
Technology based interventions allow remote access
Why Use Text Messaging for Intervention Delivery?
Text messaging is a delivery system that affords a cost-effective opportunity to promote health behavior change, with nearly universal reach98% of young adults own cell phones
97% of cell phone users use texts (Pew Research Internet Project, 2014)
Growing support for text interventions to reduce alcohol use in young people (Bock et al, 2016; Suffoletto et al., 2012, 2014)
A text-based intervention designed to correct misperceived norms has not been developed
Pilot Study Aims
• Pilot an experimental intervention to correct misperceptions in injunctive and descriptive norms, delivered via text messaging
• Examine feasibility
• Examine acceptability
• Gather preliminary evidence of the efficacy
Intervention
Decreased norms
Decreased drinking
a
c
b
Procedures
Eligibility screener 2nd year student
Risky drinking
Weekly use of text messaging
Baseline survey and orientation session
Random assignment to condition Accurate norms (experimental)
Fun facts (control)
28 daily text messages sent via Qualtrics
Follow-up survey within one week
Enrolled
n=68
Experimental
n=34
Control
n=34
Measures
Overall satisfaction (follow-up)Outcomes Drinks per drinking day (DDD) Frequency of heavy episodic drinking (HED) Peak blood alcohol concentration (BAC) Consequences (BYAACQ, Kahler et al., 2005)Mechanisms Descriptive norms weekly grid (perceived DDD) Injunctive norms (approval of drinking, drinking 5+,
getting drunk)
PARTICIPANT DESCRIPTIVESControl Experimental
Age 19.00 (0.43) 19.03 (0.52)Female Sex 22 (65%) 26 (77%)Race
White only 22 (65%) 20 (59%)Black/African-American only 1 (3%) 3 (9%)Asian only 1 (3%) 3 (9%)Native American/Alaskan only 0 (0%) 1 (3%)Multiracial 8 (24%) 5 (15%)
Hispanic/Latino Ethnicity 8 (24%) 2 (6%)Drinking Behavior
Drinks per drinking day 5.16 (2.16) 4.46 (2.14)Frequency of HED 3.65 (2.59) 3.88 (3.22)Peak BAC .16 (.08) .15 (.08)Alcohol consequences 3.38 (2.61) 4.56 (2.72)
Feasibility
• Targeted enrollment met, with a final N of 68
• No programming errors
• 98% of messages sent were rated
• 100% completed follow-up survey
Acceptability
• Moderate interest ratings for experimental texts (M=2.8, SD=1.2)
• Higher interest in students from same university (M=3.05, SD=0.83) than college students in general (M=2.77, SD=0.74), t(33)=3.18, p <.01
Acceptability
• No differences in interest of injunctive versus descriptive norms feedback (t=1.35, p=.19)
• Qualitative data indicated daily frequency of messages was appropriate/good
M SDHow acceptable was it to receive text messages as a part of this study?
4.53 0.86
How convenient was it to received text messages as a part of this study?
4.32 0.91
To what extent would you recommend this text message program to other students?
3.62 1.07
1= not at all, 5= extremely
Preliminary Efficacy Tests: Between-group
Between Groups Effect Sizes
Outcomes Mechanisms
Drinks/drinking day
HED frequency
Peak BAC Alcohol Cons
DescriptiveNorms
InjunctiveNorms
.11 -.11 -.12 -.59 .34 -.07
Preliminary Efficacy Tests: Within-Group
Experimental GroupOutcome Baseline
M (SD)FU
M (SD)Within-group d
Drinks/Drink day 4.46 (2.14) 4.31 (2.14) -.07
HED frequency 3.88 (3.22) 3.29 (2.75) -.18
Peak BAC .15 (.08) .13 (.08) -.24Alcohol Consequences 4.56 (2.72) 3.00 (2.40) -.56
MechanismDescriptive Norms 4.24 (1.81) 4.14 (1.81) -.05
Injunctive Norms 2.93 (0.56) 2.67 (0.52) -.45
Study 2 Conclusions
A text-message intervention focusing on corrective feedback for both descriptive and injunctive norms was feasible and acceptable
A larger trial to test the efficacy of this intervention is needed Stronger test of “a path” and “c path” Campus specific norms Student input on messages Higher dose First year students Longer follow-up Better measures
Intervention
Decreased norms
Decreased drinking/
consequencec
a b
Next Steps
Collection of campus-specific normative data
Generate and refine text messages conveying pro-moderation norms
Pilot RCT to test SMS-delivered intervention for first-year students, with post-test and 3 month follow-up
R21 AA024771 (PI: Kate Carey)
Conclusions
Advances in technology offer exciting opportunities for uncovering new mechanisms and testing old ones!
Subjective evaluations may predict naturalistic change, and could therefore be a potential intervention target
Tests of whether the same constructs (e.g., norms) represent MOBC when new intervention modalities are used (e.g., text messaging) are needed
Acknowledgments
NIAAA funding (K01AA022938, Study 1)
Research Excellence Award from the Center for Alcohol and Addiction Studies at Brown (Study 2)
Mentors/Collaborators: Kate Carey Nancy Barnett Rochelle Rosen Kristina Jackson Robert Miranda
Research Assistants: Tiffany Glynn, Holly Boyle, Cassandra Sutten-Coats
Organizing Committee of the MOBC Pre-conference Satellite