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

Piloting a Text Message Intervention Targeting Perceived Social Norms

Study 2

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

Text Message Examples

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)

Study 2 Results

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

Questions and Suggestions?

Thank you!