Personalized Feedback Interventions: A Meta-Analysis

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Brief Alcohol Interventions for
College Students and At-Risk
Populations
Jennifer Cadigan, M.A.
Department of Educational, School,
and Counseling Psychology
University of Missouri
Outline
• Review research on prevalence of harmful alcohol use/risk factors,
focus on college students
• Discuss concept of “brief interventions”
• Brief motivational interventions (BMI)
• Personalized drinking feedback interventions
• Provide an example of content from an intervention
• Personalized feedback interventions for other at-risk groups
Prevalence of Alcohol Use
• 80% of college students consume alcohol
(O’Malley & Johnson, 2002)
• 20% of college students met criteria for alcohol abuse or
dependence (Dawson et al., 2004)
• Binge drinking (heavy episodic drinking)
• Has historically been defined as 5+ drinks for men or 4+ drinks for
women in one “sitting”
• “Binge” drinkers more likely to experience problems as a result of
alcohol use
• 41% of men and 34% of women reported heavy drinking (binge
drinking) within the past 2 weeks (White et al., 2006)
Harmful Alcohol Use
• Heavy alcohol use has been considered the primary public
health concern among college students (Wechsler, Lee, Kuo & Lee,
2000)
• Approximately:
• 1,800 deaths
• 599,000 injuries
• 646,000 assaults
• 97,000 sexual assaults
related to alcohol use each year among college students (Hingson,
Zha, & Weitzman, 2009)
Alcohol-Related Problems
• Heavy drinking - > more alcohol-related problems
(Wechsler et al., 2000, 2002)
•
•
•
•
•
Among students who used alcohol…
35% did something later regretted
27% blacked out
7% trouble with police/authorities
21% unplanned sexual activity
• physical injury
• poor academic performance
• felt sick
• argument or fight
• operating a car under the
influence
Alcohol-Related Problems
• As a result of other students’ drinking…
• 29% of college students were insulted/humiliated
• 15% had property damaged
• 20% experienced an unwanted sexual advance
• 9% were assaulted
Greenbaum et al., 2005
Biphasic Effect
• Myth that more alcohol is better
• Physiological phases
• Euphoria; reduce inhibitions (occurs at low BACs and as BAC
is initially rising)
• Depressant-at high BACs (over .05) and when the BAC curve
is descending (after you have finished drinking)
• feel tired; slows thinking and reflexes
• Alcohol is ultimately a depressant-slows heart-rate and
breathing, and these effects are more prominent
Slide courtesy http://www.luc.edu
BAC
• Measure of the amount of alcohol in bloodstream
• As BAC
, level of intoxication
• Influenced by….
• alcohol quantity
•
•
•
•
•
speed of drinking
gender- slower for females to process it than males
weight
food
individual variations
At-risk groups
• College Students
• Intercollegiate Athletes
• Greek Students
College Athletes
• Consume more alcohol than those not
participating in athletics (Leichliter et al., 1998)
• More alcohol-related problems than nonathletes (Leichliter et al., 1998; Nelson & Wechsler, 2001)
• arguments or fights, driving while intoxicated,
police, hurt or injured while drinking
%Binge Drinking
70
60
50
40
Athlete
30
Non-Athlete
20
10
0
Male
Female
Nelson &Wechsler, 2001; Wechsler et al., 1997
Alcohol Outcomes
Non-athletes
Athletes
7
Alcohol-Related Problems
2.0
Heavy Drinking
1.8
1.6
1.4
1.2
1.0
Non-athletes
Athletes
6
5
4
3
Freshman Year Senior Year
Freshman Year
Senior Year
Cadigan, Littlefield, Martens, & Sher, 2013
Alcohol Outcomes
2.0
Nonathlete
Nonathlete
1.4
athlete
1.2
Stop
athlete
Alcohol-Related Problems
Heavy Drinking
1.8
1.6
7
athlete
6
athlete
5
Nonathlete
4
Stop
Start
1.0
Nonathlete
Start
3
Freshman Year
Senior Year
Freshman Year Senior Year
Cadigan, Littlefield, Martens, & Sher, 2013
Intercollegiate Athletes
• Apparent risk factor for problem drinking- athletes show
sharper increases in problem drinking
• Need for prevention/ intervention efforts for athletes based
on their current status (i.e., becoming an athlete vs. stopping)
• Psychological and behavioral differences
• Increased time constraints, isolated environment on campus,
have a higher social status (Harvey, 1999; Parham, 1993)
• Anxiety, pressure from teammates, athletic culture (Martens, 2012)
Brief Motivational Interventions
(BMI)
The Need for Interventions…
• Historically, alcohol treatment involved 12-step programs or
some type of inpatient program
• Intensive treatment may not be appropriate for all those
experiencing alcohol-related risks
• Unmotivated/non-treatment seeking individuals
• Individuals experiencing relatively mild/moderate risks
Harm Reduction Approach
• Differ from zero-tolerance/abstinence
based programs
“emphasize the positive aspects of using
alcohol” AND “lessen negative
consequences of alcohol” (Marlatt, 1998)
Moderation or abstinence goals
Intervention Response Spectrum
None
Mild
Moderate
Thresholds
for Action
Severe
Specialized
Treatment
Brief
Intervention
Primary
Prevention
Slide courtesy of the Addictive Behaviors Research Center, University of Washington, adapted from the Institute of Medicine
Motivational Interviewing and
Brief Interventions
• Many brief interventions are delivered in a Motivational
Interviewing (MI) based format
• 1-2 sessions; 15-50 mins
• MI defined as: “A client-centered, directive method for
enhancing intrinsic motivation to change by exploring and
resolving ambivalence” (Miller & Rollnick, 2002, p. 25)
• MI promotes a nonconfrontational and collaborative
discussion
• Goal-directed
• Key aspects of MI:
• Recognizes ambivalence regarding changing behaviors
• Working collaboratively with a client
• Helping clients verbalize their own reasons for change
• Respecting client autonomy (e.g., a decision not to engage in change)
• MI interventions involve:
• Expressing empathy of the client’s behaviors, attitudes, etc.
• Developing discrepancy between current behavior and goals
• Supporting self-efficacy for change (e.g., helping interested clients set
goals)
• Open ended questions- “How does your alcohol use fit with your
career goals?”
• Affirmations- “You’ve tried very hard to cut down”
• Summary- “What I’ve heard Is.....Is that right?”
BMI Structure
• Intervention may begin with brief orientation and/or decisional
balance exercise
• Core of the session involves covering personalized drinking
feedback that is based on the client’s response to different
questionnaires
• Feedback example
• Session may conclude with goal setting or other discussions
regarding plans for behavior change
• Decisional Balance Exercises
• Ask the client to address both the positive and negative aspects of
his/her behavior in question
• Can directly get at some of the reasons for change in the early part of
the session
Facilitator: “I’m wondering if we can just start out with you explaining to
me what it is you enjoy about drinking, as well as the things that you
don’t enjoy about it.”
BMI Structure
• Intervention may begin with brief orientation and/or decisional
balance exercise
• Core of the session involves covering personalized drinking
feedback that is based on the client’s response to different
questionnaires
• Feedback example
• Session may conclude with goal setting or other discussions
regarding plans for behavior change
Personalized Feedback
• Commonly used as a strategy for reducing alcohol use and
related problems among college students (Carey et al., 2012)
• Exact components of feedback can vary among interventions
• Typically include:
• social norms comparisons (e.g., how a student’s typical
drinks per week compares to campus norms/age/gender
norms, often expressed as a percentile rank)
• feedback on alcohol use (e.g., self-reported BAC levels and
consequences typically associated with such levels)
• alcohol-related problems experienced over some time
interval
• calories consumed from alcohol
Personalized Feedback Example pg. 1
Personalized Feedback Example pg. 2
Personalized Feedback Example pg. 3
Personalized Feedback Example pg. 4
Personalized Feedback Example pg. 5
Personalized Feedback Example pg. 6
Brief Interventions
• Brief alcohol interventions that include personalized
feedback about one’s alcohol-use and related-problems
have been efficacious in reducing use and consequences
(Carey, Scott-Sheldon, Elliott, Garey, & Carey, 2012)
• Interventions aim to change alcohol use by developing a
discrepancy between one’s actual and desired behaviors
(Miller & Rollnick, 2002)
• Personalized Feedback Interventions are considered a
core component of alcohol interventions
Targeted interventions
• For whom?
• Drinking norms for specific reference group
• “Typical” College Student
•
•
•
•
•
Athletes
Greek
Demographic Group
Age
Gender
Delivery Modality
• Traditionally Personalized Feedback Interventions have
been delivered:
• in-person
• typically include MI component
• mail
• computer
• In-person and computer-based /mailed PFIs have
resulted in a significant reduction of alcohol use when
compared to control conditions (Larimer et al., 2007; Lewis et al.,
2007; Neighbors et al. 2004)
Research Findings
• Study of adolescents in an emergency room setting
• Subjects were 94 older adolescents (18-19) who were
“alcohol positive” when receiving ER treatment
• Control condition was standard care
• Handout on alcohol-related dangers
• List of treatment services
• Experimental condition was brief MI session + Personalized
Drinking Feedback (PDF)
Monti et al., 1999, Journal of Consulting and Clinical Psychology
• At 6-month follow-up, those in the control condition:
• Were 4x as likely to report drinking and driving and
experiencing an alcohol-related injury than those in the
MI + PDF group
• Reported more alcohol-related problems
• Reported greater drinking levels
MI + Personalized Drinking
Feedback Summary
• MI can be effective at changing behaviors across a variety of
domains
• MI interventions can be delivered by a wide array of health
professionals
• MI interventions can be effectively combined with other
behavioral approaches
• “Very brief” MI-inspired approaches may also be effective at
changing behavior
Personalized Drinking
Feedback (PDF) Interventions
Computer/mailed PDF
• Cost effective- don’t require a trained clinician
• Ease of dissemination
• Have been shown to be more effective than control
conditions and/or as effective as in-person interventions
in several clinical trials (e.g., Larimer et al., 2007; Neighbors et al. 2004)
Personalized Drinking Feedback
• Personalized drinking feedback-only (PDF) intervention
targeted specifically toward college athletes (Martens et al., 2010)
• No MI component (no clinician contact)
• N = 263
• Randomized to one of three conditions:
• PDF-targeted
• PDF-standard
• Education-only
PDF Targeted
PDF standard
• Review of weekly drinking pattern
• Comparison of personal drinking to
norm for typical college athlete
• Estimated BAC /risks associated for
peak drinking over past 30 days,
typical weekend drinking, and
drinking the last time partied
• Stated motivations for drinking
• General alcohol-related problems
• Calories per week from alcohol
• Financial costs of alcohol
• Use of protective behaviors
• Review of weekly drinking pattern
• Comparison of personal drinking to
norm for typical college student
• Estimated BAC and risks associated with
it for peak drinking over past 30 days,
typical weekend drinking, and drinking
the last time partied
• Stated motivations for drinking
• General alcohol-related problems
• Calories per week from alcohol
• Financial costs of alcohol
• Use of protective behaviors
• Sport-specific alcohol-related
problems
• Possible impact of alcohol use on
athletic performance
• Possible impact of alcohol use on
athletic injury
Martens et al. (2010)
Six-Month Peak BAC-Full
Sample
0.12
0.1
0.08
PDF-Targeted
0.06
PDF-Standard
EO
0.04
0.02
0
Baseline
Six-Month
Martens et al. (2010)
Six Month Peak BAC-Heavy
Drinkers
0.25
0.2
0.15
PDF-Targeted
PDF-Standard
0.1
EO
0.05
0
Baseline
Six-Month
Martens et al. (2010)
Personalized Drinking
Feedback Interventions For
Other At-Risk Populations
OEF/OIF Veterans
• Afghanistan: Operation Enduring Freedom (OEF)
• Iraq: Operation Iraqi Freedom (OIF)
• Veterans report higher levels of alcohol use than non-veterans
(Wagner et al., 2007)
• Rates of alcohol misuse among OEF/OIF veterans twice the
rates of the general VA outpatient population (Calhoun et al., 2008)
• At risk for PTSD/other mental
health concerns
• Harry S Truman VA Memorial Hospital, Columbia, MO
• N = 325
• Randomized to one of two conditions:
• computer delivered Personalized Drinking Feedback
intervention in preventing hazardous alcohol use and
alcohol-related problems among OEF/OIF veterans
• Education-only
Baseline
1 Month
6 Month
•
•
•
•
Average age: 32 yrs old (range 20-54 yrs old)
93% Male
82% White; 9% African-American
Occupation: 30% Students
Branch
6%
5%
14%
Army
Marines
75%
Air Force
Navy
• Content of PDF intervention included:
• How one’s drinking compares to typical drinking of the
same gender, same age adult in the United States
• BAC
• Alcohol-related problems
• OEF/OIF veterans drinking norms
• Mental health problems (i.e., depression and anxiety) and
possible association with alcohol use
• Cost
• Calories
Personalized Feedback Summary
• Data collection from Project Transition ongoing…
initial results promising
• Personalized feedback alone is effective in drinking
reduction in general population and student samples
(Riper et al., 2009; Walters & Neighbors, 2005)
• Both in-person and computer personalized feedback
better than control conditions
Future Directions
• Emerging technology
• Cell phones/apps
• Ecological Momentary Assessment (EMA)
• “real time”
• Targeted interventions
Concluding Thoughts
• Brief interventions (MI + PDF; PDF only) designed to decrease
or prevent excessive alcohol use have been shown to be
effective in multiple settings
• Effects from these interventions are relatively modest, but…
• They can provide “bang for your buck,” in terms of being
relatively inexpensive and efficient
• May have tremendous cost benefits in certain settings
Acknowledgments
• Matthew Martens, Ph.D.
Questions?
Additional Personalized
Feedback Information
• For students who endorse using both alcohol + other drugs
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