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Objective: We sought to systematically review and meta-analyze the literature comparing motivational interviewing (MI) with a control condition for adolescent health behavior change. In the current article, we reviewed only studies targeting health behaviors other than substance use (e.g., sexual risk behavior, physical activity, diet). Method: Systematic literature searches of PsycINFO, PubMed/Medline, and ERIC were conducted through June 2013. Databases were combined, and studies were screened for inclusion or exclusion. To be included in the current review, studies were required to (a) compare the efficacy of at least 1 session of MI intervention with a control condition using a between-groups design and (b) examine a non-substance-use health behavior in adolescents. Fifteen studies met criteria for inclusion and were described qualitatively and quantitatively. Results: Using a fixed-effects model, we found that MI interventions produced a small, but significant, aggregate effect size for short-term postintervention effects-g = .16; 95% confidence interval (CI) [.05, .27]-compared with control conditions. Moreover, this effect was sustained at follow-up assessments averaging 33.6 weeks postintervention, n = 8, g = .18, 95% CI [.05, .32]. Conclusions: MI interventions for adolescent health behavior appear to be effective. In addition, the magnitude of the aggregate effect size does not appear to differ meaningfully from reports of interventions targeting only substance use in adolescents. However, significant lack of clarity exists regarding interventionist training requirements necessary to ensure intervention effectiveness.
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Meta-Analysis of Motivational Interviewing for Adolescent Health
Behavior: Efficacy Beyond Substance Use
Christopher C. Cushing
Oklahoma State University Chad D. Jensen
Brigham Young University
Mary B. Miller and Thad R. Leffingwell
Oklahoma State University
Objective: We sought to systematically review and meta-analyze the literature comparing motivational
interviewing (MI) with a control condition for adolescent health behavior change. In the current article, we
reviewed only studies targeting health behaviors other than substance use (e.g., sexual risk behavior, physical
activity, diet). Method: Systematic literature searches of PsycINFO, PubMed/Medline, and ERIC were
conducted through June 2013. Databases were combined, and studies were screened for inclusion or exclusion.
To be included in the current review, studies were required to (a) compare the efficacy of at least 1 session
of MI intervention with a control condition using a between-groups design and (b) examine a non-substance-
use health behavior in adolescents. Fifteen studies met criteria for inclusion and were described qualitatively
and quantitatively. Results: Using a fixed-effects model, we found that MI interventions produced a small, but
significant, aggregate effect size for short-term postintervention effects—g.16; 95% confidence interval
(CI) [.05, .27]—compared with control conditions. Moreover, this effect was sustained at follow-up assess-
ments averaging 33.6 weeks postintervention, n8, g.18, 95% CI [.05, .32]. Conclusions: MI
interventions for adolescent health behavior appear to be effective. In addition, the magnitude of the aggregate
effect size does not appear to differ meaningfully from reports of interventions targeting only substance use
in adolescents. However, significant lack of clarity exists regarding interventionist training requirements
necessary to ensure intervention effectiveness.
Keywords: motivational interviewing, health behavior, adolescents, meta-analysis
Motivational interviewing (MI) has been consistently effec-
tive in promoting health behavior change among adults. In the
past 10 years, several meta-analytic reviews have demonstrated
that MI is superior to no treatment, waitlist, and information-
only treatment conditions and equivalent to active treatments in
changing health behaviors such as substance use, HIV-related
behaviors, safe sexual practices, exercise, diet, and weight loss
(Armstrong et al., 2011;Burke, Arkowitz, & Menchola, 2003;
Hettema, Steele, & Miller, 2005;Lundahl, Kunz, Brownell,
Tollefson, & Burke, 2010;Vasilaki, Hosier, & Cox, 2006).
Although effect sizes are consistently small, MI is generally
briefer than alternative treatments (sometimes as brief as a
single conversation), demonstrates effects that are robust across
delivery format and interventionist training up to 1 year postin-
tervention, and appears equally effective when delivered in
conjunction with routine medical care (Lundahl & Burke, 2009;
Lundahl et al., 2010;Lundahl et al., 2013;VanBuskirk &
Wetherell, 2013). In a recent review, Lundahl et al. (2013)
found that use of MI increases the chance of positive treatment
outcomes by 55% compared with treatment as usual.
While the evidence for the efficacy of MI in adults is robust,
less is known about the effectiveness of this technique for
adolescents. A previous meta-analytic review suggested that MI
may have a significant and sustained effect for adolescent
substance use behavior (Jensen et al., 2011), but little is known
about the efficacy of the technique for modifying non-
substance-use health behavior. It is important to understand the
utility of MI as a brief approach to changing adolescent health
behavior because recent literature has suggested that medical
professionals can be trained to use an MI style of communica-
tion with their patients (Barwick, Bennett, Johnson, McGowan,
& Moore, 2012;Söderlund, Madson, Rubak, & Nilsen, 2011). If
training and program development is to move forward, it is
important to characterize both the populations and the problem
behaviors for which MI is most effective.
This article was published Online First May 19, 2014.
Christopher C. Cushing, Department of Psychology, Oklahoma State
University; Chad D. Jensen, Department of Psychology, Brigham Young
University; Mary B. Miller and Thad R. Leffingwell, Department of
Psychology, Oklahoma State University.
Correspondence concerning this article should be addressed to Christo-
pher C. Cushing, Department of Psychology, Oklahoma State University,
116 North Murray, Stillwater, OK 74078. E-mail: christopher.cushing@
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Journal of Consulting and Clinical Psychology © 2014 American Psychological Association
2014, Vol. 82, No. 6, 1212–1218 0022-006X/14/$12.00
The current study examines the aggregate effect size of
studies that employ MI for adolescent health behaviors other
than substance use. A secondary aim is to describe the main-
tenance of treatment gains in studies reporting follow-up data.
This study is novel in its focus on adolescent health behavior
and extends the adolescent MI literature initially characterized
by Jensen et al. (2011).
Literature Search
Comprehensive literature searches using psychological, medi-
cal, and educational databases, including PsycINFO, PubMed/
Medline, and ERIC were conducted to identify peer-reviewed
publications that reported results of motivational interventions for
pediatric health behavior. Searches were conducted using a Bool-
ean strategy for abbreviated and full keywords (motivational AND
OR enhancement] AND [child
OR adolescen
Searches were undertaken in June of 2013.
Inclusion/Exclusion Criteria
To be included in the current review, studies were required to
(a) compare the efficacy of at least one session of MI interven-
tion to a control condition using a between-groups design and
(b) examine a non-substance-use health behavior in adoles-
cents. Studies were included if they were published in peer-
reviewed English-language journals and used quantitative
methods to evaluate the study hypotheses. Studies were in-
cluded if MI was an adjunct to a larger treatment package or
administered as a stand-alone intervention. To meet the inclu-
sion criteria, studies were required to intervene in some capac-
ity with the adolescent directly. That is, studies targeting par-
ents only were excluded.
The dependent variable of interest in the current study was
change in adolescent health behavior. Health behavior was defined
as an action performed by an adolescent that is known to mean-
ingfully increase or decrease health risk (e.g., medication adher-
ence, diet, physical activity) and did not involve tobacco or other
substance use. As indicated in Figure 1, studies were excluded for
the following reasons: (a) the study was not available in English
(n15); (b) the abstract retrieved was for an unpublished disser-
tation (n26); (c) the article was a review, book chapter, or other
nonempirical work (n205); (d) the study design was not
experimental (n118); (e) the intervention did not use MI (n
9); (f) the study included a sample whose upper age limit was
greater than 21 or less than 12 (n167); (g) the outcome was not
a health behavior (n29); (h) the outcome was a substance-use
behavior (n81); (i) the study sample was composed entirely of
psychiatric inpatients (n3); (j) the study was a single group
Records idenfied through
database searching and reference
(n = 1,741)
Included Eligibility Idenficaon
Records aer duplicates removed
(n = 697)
Arcles assessed for
n= 697
Full text arcles excluded
(n = 682)
(a) Not English = 15
(b) Dissertaon = 26
(c) Nonempirical = 205
(d) Not experimental = 118
(e) No MI = 9
(f) Age = 167
(g) Not health behavior = 29
(h) Substance use = 81
(i) Psychiatric = 3
(j) Single group = 12
(k) Group differences at
baseline = 4
(l) Insufficient stascs = 13
Studies included in
qualitave synthesis
n= 15
Studies included in
quantave synthesis
(n = 15)
Figure 1. PRISMA (Preferred Reporting Items of Systematic Reviews and Meta-Analyses) flowchart.
MI motivational interviewing.
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design (n12); (k) the study examined groups that were signif-
icantly different at baseline and did not report adjusted means (n
4); and (l) the study reported insufficient statistics (n13).
Analytic Plan
To ensure consistency across effect size estimates, we aggre-
gated multiple outcome measures derived from the same sample
such that each study (or group of studies using the same sample)
contributed only one effect size to the analysis. This approach
mitigates the distortion of standard error estimates resulting from
treating nonindependent studies as independent (Gleser & Olkin,
1994). Moreover, this approach provides a conservative test of the
efficacy of MI. By aggregating all outcomes reported by a single
study, our effect size estimates are agnostic to study hypotheses
regarding which outcomes would be most influenced by MI. This
approach penalizes studies that include a large number of out-
comes in the initial design but ultimately only focus on significant
results from a small number of outcomes.
Two independent observers extracted data, and disagreements
were resolved through jointly examining research reports until
agreement was reached. Studies were weighted by their sample
size using a weighted least squares approach. This method gives
greater weight to studies employing larger sample sizes (Hedges &
Olsen, 1985).
Statistical Approach
In order to arrive at an aggregate effect size for the reviewed
studies, Hedges gwas calculated for each individual study and
then aggregated using an inverse variance weight. Between-group
studies providing F,t, or means and standard deviation were
converted to Hedges g. These values were used to demonstrate the
strength of the relationship between the treatment type and the
occurrence of the specified outcome of interest (e.g., medication
adherence, sexual risk behavior, weight loss). Effect sizes with
confidence bands that did not include zero were considered statis-
tically significant, while those with confidence bands including
zero were considered nonsignificant.
Description of Studies
Following application of the inclusion/exclusion criteria, 15
studies were available for data abstraction, representing a total of
1,610 participants. Half of the abstracted studies used an interven-
tionist with master’s-level or greater training in a mental health
profession while the other half of the sample included community
paraprofessionals, nurses, physicians, and dieticians (see Table 1).
Eight studies provided data after the posttreatment assessment.
These follow-up assessments ranged from 4 weeks to 2 years
(average 33.6 weeks). Other descriptive statistics are reported in
Table 1.
Overall effect size. The aggregate effect size for MI interven-
tions targeting adolescent health behaviors was small but signifi-
cant—g.16; 95% confidence interval (CI) [.05, 27]; Table 2.
The Qstatistic indicated that there was not significant heteroge-
neity in the effect sizes (Q17.29, p.24). For this reason,
potential moderators such as intervention length, interventionist
training, and other study characteristics could not be examined as
moderators of study effect size.
Follow-up effect size. To determine the stability of treatment
effects over time, we aggregated reports of follow-up data. The
results of the analysis revealed that MI produces relatively stable
effects over time (n8, g.18; 95% CI [.05, .32]). The
follow-up analysis yielded a significant Qstatistic (Q18.28,
p.01). However, this appeared to be due to variability intro-
duced by one study (Wang et al., 2010) that reported a strong
negative effect size rather than from systematic variability among
the sample of studies. The Qstatistic was nonsignificant with
Wang et al. (2010) removed from the analysis. This suggests that
this study was the primary contributor to the variability in
follow-up effect sizes. However, Wang et al. (2010) was retained
in all analyses to avoid arbitrarily biasing the effect size estimates
due to post hoc deletion.
Fail-Safe N Calculation
To protect against the possibility that studies with a null or even
unfavorable effect size might be unpublished, we used Orwin’s
(1983) Fail-Safe N formula to determine the number of studies
required to overturn the current finding. Given that the current
mean effect size is g.16, it was assumed that unpublished
studies might have a mean effect size of g–.16, and the mean
standard error of .055 from the current sample was used as the
criterion for a trivial difference. Under these parameters, 34 studies
with null or negative findings would be required to overturn the
current results.
Results of the current study indicate that MI interventions for
adolescent and child health behaviors produced small but signifi-
cant effect sizes across numerous health behavior outcomes. These
findings are consistent with previous meta-analyses demonstrating
the overall effectiveness of MI interventions targeting health be-
haviors among adults (e.g., Burke et al., 2003;Rubak, Sandbaek,
Lauritzen, & Christensen, 2005). Moreover, within the present
analysis, a subset of intervention studies employed additional
follow-up analyses, ranging from 1 month to 24 months posttreat-
ment. The effect size for this subset of studies was small, but
significant. This is particularly noteworthy, given that the average
number of intervention sessions for all studies assessed in the
present meta-analysis was 5.6, with three interventions producing
a positive effect requiring only two sessions. This is important
because it suggests that a relatively small number of meetings can
produce meaningful change. Moreover, brief interventions such as
MI allow for multiple intervention opportunities across repeated
encounters with the health care system, which could multiply the
effects of a small but reliable change and may result in larger
population improvements over time.
Reviews of the adult literature have reported superior effect
sizes for interventions targeting non-substance-use behaviors, a
finding that has been attributed to the addictive component of
substance use (Burke et al., 2003). However, when compared with
findings from previous meta-analyses of substance use behavior
(Jensen et al., 2011), the current results do not support the notion
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Table 1
Description of Studies Included in the Meta-Analysis
Author Outcome Follow-up length Age
(years) Total sample
used % male/
% female Ethnicity No. of
sessions Interventionist Weighted mean
effect size (g)
Ball 2011 Anthropometry NA 13–17 46 39.1/60.9 84.8% White 16 Registered dietician/nurse .05
Metabolic functioning 15.2% other
Physical activity
Barnet 2009 Repeat birth NA 12–19 235 0/100 97.0% African American 7–9 Community paraprofessionals .23
Cain 2011 Sleep 6 weeks 15.8–16.6 104 40.4/59.6 Not given (South Australia) 4 Psychologist and teacher .04
Channon 2003 HbA
13.6 weeks 14–18 17 Not given Not given 9 Youth worker .14
Channon 2007 HbA
24 months 14–18 60 48/52 100% White 4 Interventionist .54
Gourlan 2013 Anthropometry 6 months 11–18 54 59/41 Not given (France) 8 Physician and doctoral
student .06
Objective energy
Objective physical
Self-reported energy
Kiene 2006 Risky sexual behavior NA College
age 149 29.7/71.3 81% White 2 Computer-based intervention .62
6.4% Hispanic
4.5% African American
8.1% other
Kong 2013 Anthropometry NA 13.9–16 51 41.2/58.8 68.6% Hispanic 8 Nurse practitioner .07
Diet 15.7% biracial
Metabolic functioning 9.8% Asian
Physical activity 5.9% American Indian
Sedentary activity
Neumark-Sztainer 2010 Anthropometry 9 months 14–17 356 0/100 28.4% African American 5–7 Interventionist .07
Diet 24.4% White
Physical activity 23.0% Asian
Restrictive eating 14.3% Hispanic
Sedentary activity 7.3% Other
2.5% American Indian
Olson 2008 Diet NA 11–20 284 51/49 96% White 2 Clinician .21
3.5% Hispanic
Resnicow 2005 Diet NA 12–16 123 0/100 100% African American 6 Master’s-level clinician .25
Seid 2012 Symptom days
(asthma) 3 months 12–18 26 69.2/30.8 76.9% African American 2 Master’s-level graduate
students .08
14.3% White
7.1% other
Viner 2003 HbA
NA 10–17 21 56/44 Not given (United Kingdom) 6 Clinician .69
Walpole 2013 Anthropometry NA 12–15 40 42.5/57.5 73.3% White 6 Clinical psychology doctoral
8.3% African Canadian
3.3% Native Canadian
3.3% Asian
3.3% South Asian
8.3% other
Wang 2010 HbA
9 months 13–17 44 50/50 68.2% White 2 Diabetes educators .64
31.8% Other
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that substance use is more difficult to modify than other health
behaviors in adolescents. Indeed, a great deal of overlap was
observed between the confidence band in our previous work ag-
gregating substance use studies (95% CI [.08, .25]) and the current
examination of non-substance-use studies (95% CI [.05, .27]). It is
possible that future meta-analyses of adolescent studies will find
significantly larger effect sizes for non-substance-use interven-
tions, but at present there appears to be more similarity than
difference. One reason for this finding may be that substance use
interventions in adolescents tend to target subclinical problems
(Jensen et al., 2011). In cases where adolescents have developed
clinically significant substance use disorders, it would be reason-
able to suspect that effect sizes may be smaller.
Although some studies specifically indicated the amount of MI
training received by clinicians (e.g., 1-day workshop, self-directed
learning, supervised training), the majority of included studies did
not. Questions concerning level of MI training are salient, given
evidence that MI practice may not change with brief MI work-
shops (Miller & Mount, 2001). Future studies should include
information regarding the MI training obtained by clinicians,
which may be used to ascertain effects of MI-specific training (see
Miller & Rose, 2009, for a discussion).
Results from this meta-analytic review must be interpreted in
the context of several limitations. First, our analysis of treat-
ment follow-up assessments is limited by our aggregation of
effect sizes across measurement periods. We did not account for
nonequivalent follow-up duration in the model. Thus, we were
unable to assess whether effects remain similar across varying
follow-up periods. Similarly, racially diverse samples were not
always used in the studies included in the current sample.
Therefore, the aggregate treatment effect size should be taken to
represent Caucasian American participants to a greater degree
than other racial or ethnic groups.
Future Directions
The limitations present in existing studies of the effectiveness of
MI for adolescent health behavior change suggest that several
areas of further investigation are warranted. First, few randomized
controlled trials examining the efficacy of MI for pediatric health
behavior changes have been conducted. Often considered the “gold
standard” in demonstrating treatment efficacy (American Psycho-
logical Association Presidential Task Force on Evidence-Based
Practice, 2006), more randomized clinical trials of MI used to
effect pediatric health behavior change would increase confidence
in the efficacy of MI when used with children and adolescents. Of
particular importance will be studies that examine the efficacy and
effectiveness of MI in underrepresented populations (e.g., based on
ethnicity, socioeconomic status), using designs that allow compar-
isons of MI against treatment as usual, rather than attention con-
Second, many existing MI studies have suffered from poor
treatment fidelity (Martins & McNeil, 2009). That is, the imple-
mentation of treatment protocols has been inconsistent in most
trials, preventing conclusions about whether MI is truly more
effective than standard of care interventions. No widely adopted
criteria exist for what does and does not qualify as an MI inter-
vention, making interpretation of mixed results from different
studies difficult (Resnicow, Davis, & Rollnick, 2006). Specific
behavioral coding systems (e.g., Motivational Interviewing Skill
Code (MISC; Moyers, Martin, Catley, Harris, & Ahluwalia, 2003)
2.1 and Motivational Interviewing Treatment Integrity (MITI;
Moyers, Martin, Manuel, Hendrickson, & Miller, 2005) Version
3.0) have been developed to assess treatment integrity for MI
interventions (see Madson & Campbell, 2006 for further review).
However, only five of the studies included in the current review
conducted assessments of fidelity using one of these measures,
and only three reported whether the interventionist met the
criteria for proficiency. Moreover, many interventionists who
deliver MI in health care settings received limited MI training.
Future research examining the efficacy of MI interventions
delivered by practitioners with less psychosocial training (e.g.,
physicians, nurses, and so on) will be valuable. Clearly, there is
a great need to improve assessment and reporting of clinician
training and intervention fidelity in studies of MI for adolescent
health behavior change.
Finally, the degree to which treatment effects of MI are attrib-
utable to specific treatment components (i.e., MI specific vs.
common factors) remains unclear. While this problem exists with
many empirically supported treatments, the supportive nature of
MI suggests that nonspecific factors may play an important role
(Miller & Rose, 2009). Direct comparisons of MI to other sup-
portive therapies for health behavior change will assist in answer-
ing this question.
Results of this meta-analysis suggest that MI is an effective
intervention to promote adolescent health behavior change. The
application of this method to adolescent populations is increasing,
and results of studies applying MI for a number of adolescent
health conditions are promising. MI can be implemented by a
variety of health care professionals (e.g., physicians, nurses, dieti-
cians; Martins & McNeil, 2009), a characteristic that is likely to
increase the reach of this technique in health-related domains. MI
interventions for adolescents are efficacious for a variety of health
behaviors, including substance use, diet, sexual health, weight
management, diabetes, and physical activity. Clinicians should
consider using MI as one component of their treatment when
attempting to help adolescents make health behavior changes.
Continued application of this technique to adolescent health be-
haviors is encouraged, and examination of the technique with new
adolescent populations is warranted.
Table 2
Summary of Mean Effect Sizes
Variable No. of effect
sizes Weighted mean
effect size (g)95% confidence
interval Q
Omnibus test 60 .16 [.05, .27] 17.29
Follow-up data 23 .18 [.05, .32] 18.28
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Received November 22, 2013
Revision received March 5, 2014
Accepted March 19, 2014
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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
... An additional study showed that as few as 20% of adolescents aged 13-15 met the PA guidelines, with boys being more active than girls [4]. Adolescents, which WHO defines as individuals in the [10][11][12][13][14][15][16][17][18][19] year age group, is a critical time for behavior development, as behavior established during adolescence carries over into adulthood [5]. Studies suggest that PA levels increase in early childhood and then decline through adolescence and adulthood [6,7]. ...
... In adults, MI has been found to impact improvements in several health behaviors, including eating habits, PA, and disease management [17]. Emerging studies among children and adolescents have found a similar improvement in health behaviors such as substance use, diet, sexual health, diabetes, and asthma [18,19]. It is further evident that MI can have positive outcomes in young children's anthropometric measures [20], and may be an effective method for promoting PA in adolescents. ...
... It is further evident that MI can have positive outcomes in young children's anthropometric measures [20], and may be an effective method for promoting PA in adolescents. [18] As this age range is critical for lifelong PA habits, and evidence indicates almost 80% of adolescents do not meet the recommendations for Americans, [4] it is vital to examine the effects of MI on adolescent PA levels [21,22]. At the time of writing this paper, the authors could not locate a systematic review examining MI's impact on PA levels in adolescence. ...
... 10,11 However, the effects of MI in promoting healthy behaviours, such as healthy eating and physical activity, are inconsistent and inconclusive in both child and adult populations. 11,12 Given that MI is an emerging approach applied in childhood obesity by targeting either children and/or parents, limited research, especially systematic reviews, exists to fully evaluate the effects of MI on children's healthy behaviours and anthropometric factors. One meta-analysis with 15 studies found that MI had a small, but significant and stable effect ( g = 0.16) on promoting non-substance-use healthy behaviours (e.g., eating, physical activity, sleep, medication adherence) among adolescents. ...
... One meta-analysis with 15 studies found that MI had a small, but significant and stable effect ( g = 0.16) on promoting non-substance-use healthy behaviours (e.g., eating, physical activity, sleep, medication adherence) among adolescents. 12 Another meta-analysis evaluated the effects of MI interventions targeting children and/or parents on the psychosocial factors and physical health of children <18 years old. 13 The meta-analysis identified a significant effect (g = 0.28) on promoting overall child health in 35 studies and a smaller effect (g = 0.15) on reducing childhood obesity in 12 studies, but moderation analyses were not performed for the childhood obesity outcome. ...
Background: Limited systematic reviews exist to evaluate the effects of motivational interviewing (MI) on children's anthropometric factors. Objective: This review examined the effects of MI interventions for children and/or parents on children's anthropometric factors and included moderation analyses and Grading of Recommendations Assessment, Development and Evaluation (GRADE) assessment. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement, we searched Cochrane Library, PubMed, CINAHL, EMBASE, PsycINFO, Sociological Abstracts, SPORTDiscus, Education Resources Information Center, and Web of Science in December 2020. A two-step double screening approach was applied: (1) screening titles and abstracts, and (2) screening full-text articles obtained in step 1. At each step, discussion occurred until reaching consensus. The Cochrane risk-of-bias tool was used to evaluate risk of bias, and GRADE system was applied to assess overall quality of evidence. We performed meta-analyses using the Comprehensive Meta-Analysis software. Results: A total of 2209 records were found, and 45 eligible articles were retained. MI interventions had a pooled effect of -0.15 on body mass index (BMI; 95% confidence interval [CI]: -0.24 to -0.06), -0.36 on waist circumference (WC; 95% CI: -0.71 to -0.01) and -0.22 on percent body fat (95% CI: -0.41 to -0.03). Child baseline weight status and percent low-income families were identified as significant intervention moderators. According to the GRADE assessment, the quality of evidence on BMI percentile, BMI z-score and percent body fat was moderate, while quality on BMI and WC was low. Conclusions: In conclusion, culturally appropriate clinic- or home-based MI interventions with adequate duration, dose and active parental involvement are promising in reducing anthropometrics among children.
... Motivational interviewing (MI)-a client-centered counseling approach used to elicit behavior change by helping patients to explore and resolve ambivalence to change 7,8 -has been applied in interventions to manage adolescent obesity. [9][10][11] During MI, the focus is on creating an empathetic approach with clients by using techniques and strategies, such as affirmations, reflective listening, agenda setting as well as shared decision making, to support clients' self-efficacy. [12][13][14][15] A recent meta-analysis reported that MI-based interventions for managing adolescent obesity had no significant effects on reducing body mass index (BMI) and BMI percentile 16 ; however, the qualitative synthesis that accompanied the review suggested that MI-based interventions can result in positive behavior changes. ...
Motivational interviewing (MI) is an evidence‐based counseling approach that can help individuals make positive behavioral and cognitive changes for managing obesity. We conducted a scoping review to summarize evidence on fidelity and key elements of MI‐based interventions for managing adolescent obesity and examine the reporting of these interventions. Ten electronic databases and gray literature were searched systematically and included literature from January 1983 to February 2022, and 26 studies were included. Data on MI features, delivery context, training, and fidelity to treatment were summarized. Fidelity was assessed using an assessment grid with five domains—theory, training, implementation, treatment receipt, and treatment enactment. The last step of the review involved stakeholder consultation with clinician‐scientists and researchers with experience in MI and managing adolescent obesity. Thirteen stakeholders were interviewed about our review findings on MI and treatment fidelity. Our analyses revealed that MI‐based interventions for managing adolescent obesity had “low treatment fidelity”; no studies had “high treatment fidelity” across all five domains. Fidelity strategies adhered to the most was theory, and treatment enactment was the lowest. Stakeholders mentioned that “low treatment fidelity” may be due to increased time to complete fidelity assessments and increased cost associated with treatment fidelity. These findings have implications for planning, implementing, and evaluating MI‐based interventions for managing adolescent obesity.
... It is designed to elicit patients' goals and foster motivation for change using a reflective and non-confrontational style [10]. MI is effective for treating adolescent substance use and for facilitating changes in eating and physical activity behaviors [11,12]. There is mixed evidence regarding benefits of MI as a stand-alone treatment for adolescent obesity [13,14]. ...
Full-text available
Objective Describe perspectives of teens and caregivers regarding motivations, successes, and challenges related to participation in ACTION PAC ( NCT02502383), a two-year weight management trial. Methods Intervention group participants received 16 short motivational interviewing (MI) sessions with school-based health center (SBHC) primary care clinicians over two years. Post-study, we conducted semi-structured interviews with purposefully sampled intervention group teens and their caregivers. Interviews were audio recorded, transcribed, and managed in NVivo 11. Three independent coders analyzed the data, developed a coding tree, examined how codes intersected and clarified relationships through memo writing. Results The clinician’s role and use of motivational interviewing and family involvement in behavior changes were cited as critical to success. Some adolescents noted difficulty in sustaining behavior changes post-intervention and social and systemic barriers to behavior change. Conclusion Future studies should identify strategies to sustain teen motivation, better involve families, and address systemic barriers. Innovation In this study, which simulated real-world SBHC conditions, adolescents appreciated the use of an MI approach and felt that was key to their success, indicating the potential to continue use of this approach to motivating behavior changes in SBHC settings.
... Meta-analytic reviews have documented that motivational interviewing outperforms traditional advice giving across treatment studies of adults [20][21][22] and adolescents. [23][24][25] In the field of speechlanguage pathology, motivational interviewing has been applied to voice therapy, 26,27 hearing aid use, 28 and cognitive rehabilitation. [29][30][31][32] The spirit of motivational interviewing is threefold. ...
Adolescents who stutter often pose a unique clinical challenge for clinicians. They are a population simultaneously striving for independence from adults and social connection with their peers at a time when social fears surge and lifelong habits take root. It is a time when they may seem “unmotivated” to learn and utilize new communication or coping skills related to stuttering. How can clinicians maximize adolescents' engagement in stuttering therapy to improve meaningful outcomes? The purpose of this article is to describe a transtheoretical approach to assessing adolescents' readiness to make positive changes to living with stuttering, and to provide motivational interviewing strategies that clinicians can employ to help propel adolescents toward personally significant change. These principles will be applied to the case study of a 14-year-old who stutters to demonstrate how clinicians can put this approach to work as they meet their adolescent clients “where they're at.”
... The social workers underwent a two-day intensive training in motivational interviewing with a Motivational Interviewing Network of Trainers™ certified trainer. Motivational interviewing (MI) has previously been used for behavior change for a variety of health conditions and outcomes (Cushing, Jensen, Miller, & Leffingwell, 2014;Lee, Choi, Yum, Yu, & Chair, 2016;Mifsud, Galea, Garside, Stephenson, & Astin, 2020). We chose to utilize motivational interviewing in order to increase participant self-efficacy with exercising and achieving their fitness goals. ...
Objectives Bipolar disorder (BD) is associated with decreased cardiorespiratory fitness (CRF) and exercise. Despite the potential benefits for physical and mental health, there is a gap in knowledge regarding treatments targeting improved CRF for BD. This treatment development and feasibility study sought to bridge the knowledge-to-action gap in this area. Methods Twenty youth with BD, 18.0 ± 2.3 years old, enrolled in an exercise behavior change counselling (BCC) intervention targeting improved CRF. The 12-week active intervention included four in-person sessions, augmented by phone/texting sessions on intervening weeks. Optional modules included exercise coaching, family involvement, and peer support. Booster phone/texting sessions occurred at weeks 16 and 20. Participants completed CRF testing at weeks 0, 2, 8, 12, and 24. Results Seventy percent of participants (14/20) completed all study visits and measures. In the overall enrolled sample, 82% of CRF tests were completed (range 0–5 of 5). There were no significant changes in subjective (via self-report) and objective (via Fitbit) measures of physical activity or in CRF, though CRF testing was consistently associated with active post-exercise improvement in mood. Most participants reported being very satisfied with the intervention following the 12-week active intervention (13/14) and at week 24 (12/14). Therapist fidelity to the BCC manual was high. Conclusion Good attendance and study adherence provides preliminary evidence of the feasibility and acceptability of a behavioral intervention targeting CRF in youth with BD. Future studies refining the current intervention are warranted toward a goal of demonstrating improved CRF in a randomized controlled trial.
Background: To determine whether the 2gether intervention increases use of a dual protection (DP; concurrent prevention of pregnancy and sexually transmitted infections [STIs]) strategy and decreases pregnancy and STIs among young African American females, who disproportionately experience these outcomes. Materials and Methods: We conducted a randomized clinical trial comparing the 2gether intervention to standard of care (SOC). Participants were self-identified African American females aged 14-19 years who were sexually active with a male partner in the past 6 months. Participants were followed for 12 months; 685 were included in the analytic sample. The primary biologic outcome was time to any incident biologic event (chlamydia, gonorrhea, trichomonas infections, or pregnancy). The primary behavioral outcomes were use of and adherence to a DP strategy. Results: 2gether intervention participants had a decreased hazard of chlamydia, gonorrhea, trichomonas infections, or pregnancy during follow-up, hazard ratio = 0.73 (95% confidence interval [CI] 0.58-0.92), and were more likely to report use of condoms plus contraception, generally, adjusted risk ratio (aRR) = 1.61 (95% CI 1.15-2.26) and condoms plus an implant or intrauterine device (IUD), specifically, aRR = 2.11 (95% CI 1.35-3.29) in the prior 3 months compared with those receiving SOC. 2gether participants were also more likely to report use of condoms plus an implant or IUD at last sex and consistently over the prior 3 months. Conclusions: 2gether was efficacious in increasing use of condoms with contraception and decreasing pregnancy or selected STIs in our participants. Implementation of this intervention in clinical settings serving young people with high rates of pregnancy and STIs may be beneficial., No. NCT02291224 (
Aim: A large body of evidence demonstrates the importance of the family environment in the developmental trajectory of mental illness in young people. Caregiver communication skills training represents a potential model for influencing the outcomes of adolescents and young adults struggling with emerging mental health and behavioural difficulties. The aim of the current study is to describe the development of a telehealth group training intervention for caregivers of adolescents and young adults, and to report the results of a pilot feasibility‐effectiveness study that took place in 2020–2021. Methods: The “School of Hard Talks” intervention consisted of 8 h of training in communication skills consistent with motivational interviewing techniques. All pilot study participants were assigned to receive the intervention. Outcomes of interest were family conflict, caregiver stress, caregiver self‐efficacy and expressed emotion (EE). Participants were assessed three times: prior to the intervention, after the intervention and 12 weeks later. Results: A total of 62 participants enrolled in the study, of whom 49 completed the intervention. Large, significant improvements were observed over time in all four domains of interest. Qualitative feedback from parents was very positive and added context to quantitative observations. Conclusions: The School of Hard Talks was a feasible and effective intervention targeting both caregiver wellbeing as well as important mechanisms of risk for youth psychopathology, namely family conflict and EE. Further research involving a larger sample and a control condition are needed to confirm these findings.
This book is a practical manual for clinical practitioners seeking to take an interdisciplinary and multidisciplinary approach to the diagnosis and management of functional movement disorder (FMD). It discusses case vignettes, reviews the diagnostic approach, provides an update on available treatments, highlights clinical pearls and details references for further reading. Organized into three parts, the book begins with a framework for conceptualizing FMD - including its historical context, the biopsychosocial model and an integrated neurologic-psychiatric perspective towards overcoming mind-body dualism. Part II then provides a comprehensive overview of different FMD presentations including tremor, dystonia, gait disorders, and limb weakness, as well as common non-motor issues such as pain and cognitive symptoms. The book concludes with chapters on updated practices in delivering the diagnosis, working with patients and care partners to achieve shared understanding of a complex condition, as well as an overview of evidence-based and evolving treatments. Supplemented with high-quality patient videos, Functional Movement Disorder is written for practicing neurologists, psychiatrists, psychologists, allied mental health professionals, and rehabilitation experts with an interest in learning more about diagnosis and management of FMD.
Motivational interviewing (MI) is a patient-centered counseling style that focuses on eliciting a patient’s own reasons for behavioral change and using this “change talk” to support and promote healthy behaviors, such as engaging in psychotherapies, physical therapy, and other medical treatments. There is a large and growing body of evidence for MI’s efficacy in promoting healthy behaviors and treatment adherence in a range of medical settings. While patients with functional movement disorder (FMD) do not exercise conscious control over their disordered movements, MI has the potential to enhance engagement – over which there is conscious control – with therapeutic interventions, such as psychotherapies and physical therapy. Limited patient engagement with these interventions is a common obstacle to treatment of many functional neurological disorder (FND) subtypes, including FMD. Non-adherence is associated with worse outcomes for patients with FND. This chapter discusses the use of MI by clinicians as an intervention to enhance patient adherence to psychotherapy, physical therapy, and other aspects of the treatment plan for FMD.The chapter begins with an illustrative vignette, followed by a review of the theoretical reasons and the evidence for the use of MI generally and in the management of FND specifically. The chapter then gives an overview of MI and reviews the four overlapping core processes of MI (engaging, focusing, evoking, and planning) and strategies for eliciting change talk from patients, as well as for handling “sustain talk” (i.e., reasons for refraining from healthy behavior changes). The chapter concludes with resources for learning MI.KeywordsFunctional movement disorderFunctional neurological disorderMotivational interviewingEngagement
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In 2011, the Board of Directors of the Canadian Psychological Association (CPA) launched the Task Force on Evidence-Based Practice of Psychological Treatments to support and guide practice as well as to inform stakeholders. This article describes the work of this task force, outlining its raison d'etre, providing a comprehensive definition of evidence-based practice (EBP), and advancing a hierarchy of evidence that is respectful of diverse research methodologies, palatable to different groups, and yet comprehensive and compelling. The primary objective was to present an overarching methodology or approach to thinking about EBP so that psychologists can provide and implement the best possible psychological treatments. To this end, our intention for this document was to provide a set of guidelines and standards that will foster interest, encourage development, and promote effectiveness in EBP.
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Objective: The authors investigated the unique contribution motivational interviewing (MI) has on counseling outcomes and how MI compares with other interventions. Method: A total of 119 studies were subjected to a meta-analysis. Targeted outcomes included substance use (tobacco, alcohol, drugs, marijuana), health-related behaviors (diet, exercise, safe sex), gambling, and engagement in treatment variables. Results: Judged against weak comparison groups, MI produced statistically significant, durable results in the small effect range (average g = 0.28). Judged against specific treatments, MI produced nonsignificant results (average g = 0.09). MI was robust across many moderators, although feedback (Motivational Enhancement Therapy [MET]), delivery time, manualization, delivery mode (group vs. individual), and ethnicity moderated outcomes. Conclusions: MI contributes to counseling efforts, and results are influenced by participant and delivery factors.
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Objective This systematic review sought to determine the current state of the literature on the effectiveness of training health and mental health professionals in motivational interviewing (MI).Method Data sources: The following databases were searched: MEDLINE/PreMEDLINE, Embase, PsycINFO, Cochrane Database of Systematic Reviews, and CENTRAL Cochrane Central Trials Register. Inclusion criteria were empirical studies of any year that employed any research design to evaluate the effectiveness of training health or mental health professionals in MI. Studies with main outcomes other than behavioral or organizational were excluded. To minimize bias, dual review was employed. Full data abstraction was conducted independently by two reviewers. A qualitative synthesis of the findings and risk of bias data are reported.ResultsA total of 22 studies were included in this review. Seventeen of the 22 studies reported significant practitioner behavior change relative to motivational interviewing skills, notwithstanding variation in training approach, population, outcome measures, and study quality.Conclusion This review demonstrates practitioner behavior change on MI skills utilizing a variety of training and outcome methods. Future work of high methodological rigor, clear reporting, and that attends to training as one part of the implementation process will help to elucidate the factors that lead to the uptake of new practices.
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Using self-determination theory (SDT) as an explanatory framework, this randomised-controlled study evaluates the effect of a motivational interviewing (MI)-based intervention as an addition to a standard weight loss programme (SWLP) on physical activity (PA) practice in obese adolescents over a six-month period. Fifty-four obese adolescents (mean age = 13 years, mean BMI = 29.57 kg/m²) were randomly assigned to an SWLP group (n = 28) or SWLP + MI group (n = 26). Both groups received two SWLP sessions, supplemented for the SWLP + MI group, by six MI sessions. Perceived autonomy support, perceived competence, motivational regulations, PA and BMI were assessed at baseline, three and six months (i.e. the end of the programme). MLM analyses revealed that compared to SWLP, the SWLP + MI group had a greater BMI decrease and a greater PA practice increase over time. Moreover, the SWLP + MI group reported greater autonomy support from medical staff at the end of the programme, greater increase in integrated and identified regulations and a stronger decrease in amotivation. MI appears as an efficient counselling method as an addition to an SWLP to promote PA in the context of pediatric obesity. The full-text version of the paper is available at:
Much of the literature on meta-analysis deals with analyzing effect sizes obtained from k independent studies in each of which a single treatment is compared with a control (or with a standard treatment). Because the studies are statistically independent, so are the effect sizes. Studies, however, are not always so simple. For example, some may compare multiple variants of a type of treatment against a common control. Thus, in a study of the beneficial effects of exercise on blood pressure, independent groups of subjects may each be assigned one of several types of exercise: running for twenty minutes daily, running for forty minutes daily, running every other day, brisk walking, and so on. Each of these exercise groups is to be compared with a common sedentary control group. In consequence, such a study will yield more than one exercise versus control effect size. Because the effect sizes share a common control group, the estimates of these effect sizes will be correlated. Studies of this kind are called multiple-treatment studies. In other studies, the single-treatment, single-control paradigm may be followed, but multiple measures will be used as endpoints for each subject. Thus, in comparing exercise and lack of exercise on subjects' health, measurements of systolic blood pressure, diastolic blood pressure, pulse rate, cholesterol concentration, and so on, may be taken for each subject. Similarly, studies of the use of carbon dioxide for storage of apples can include measures of flavor, appearance, firmness, and resistance to disease. A treatment versus control effect-size estimate may be calculated for each endpoint measure. Because measures on a common subject are likely to be correlated, corresponding estimated effect sizes for these measures will be correlated within studies. Studies of this type are called multiple-endpoint studies (for further discussions of multiple-endpoint studies, see Gleser and Olkin 1994; Raudenbush, Becker, and Kalaian 1988; Timm 1999). A special, but common, kind of multiple-endpoint study is that in which the measures (endpoints) used are sub-scales of a psychological test. For study-to-study comparisons, or to have a single effect size for treatment versus control, we may want to combine the effect sizes obtained from the subscales into an overall effect size. Because subscales have differing accuracies, it is well known that weighted averages of such effect sizes are required. Weighting by inverses of the variances of the estimated subscale effect sizes is appropriate when these effect sizes are independent, but may not produce the most precise estimates when the effect sizes are correlated. In each of these above situations, possible dependency among the estimated effect sizes needs to be accounted for in the analysis. To do so, additional information has to be obtained from the various studies. For example, in the multiple-endpoint studies, dependence among the end-point measures leads to dependence between the corresponding estimated effect sizes, and values for between-measures correlations will thus be needed for any analysis. Fortunately, as will be seen, in most cases this is all the extra information that will be needed. When the studies themselves fail to provide this information, the correlations can often be imputed from test manuals (when the measures are subscales of a test, for example) or from published literature on the measures used. When dealing with dependent estimated effect sizes, we need formulas for the covariances or correlations. Note that the dependency between estimated effect sizes in multiple-endpoint studies is intrinsic to such studies, arising from the relationships between the measures used, whereas the dependency between estimated effect sizes in multiple-treatment studies is an artifact of the design (the use of a common control). Consequently, formulas for the covariances between estimated effect sizes differ between the two types of studies, necessitating separate treatment of each type. On the other hand, the variances of the estimated effect sizes have the same form in both types of study - namely, that obtained from considering each effect size in isolation (see chapters 15 and 16, this volume). Recall that such variances depend on the true effect size, the sample sizes for treatment and control, and (possibly) the treatment-to-control variance ratio (when the variance of a given measurement is assumed to be affected by the treatment). As is often the case in analyses in other chapters in this volume, the results obtained are large sample (within studies) normality approximations based on use of the central limit theorem.
This meta-analysis synthesized the findings from randomized controlled trials (RCTs) of motivational interviewing (MI) for health behavior outcomes within primary care populations. Published and unpublished RCTs were identified using databases and online listservs. Studies were synthesized by outcome subgroup and meta-regression analyses were conducted to determine potential moderators accounting for heterogeneity within samples. Mean effect sizes ranged from .07 to .47; significant effect sizes were found for the adherence subgroup of studies (p = .04) and all outcomes combined (p = .02). Professional credentials of intervention deliverer were found to significantly moderate the association between MI and effect size in substance use subgroup (p = .0005) and all outcomes combined (p = .004). Mean effect sizes were largest in outcomes related to weight loss, blood pressure, and substance use. MI appears to be useful in clinical settings and as few as 1 MI session may be effective in enhancing readiness to change and action directed towards reaching health behavior-change goals.
Rosenthan's (1979) concept of fail-safeN has thus far been applied to probability levels exclusively. This note introduces a fail-safeN for effect size.
Objective To evaluate the efficacy of Motivational Interviewing (MI) as an intervention for promoting self-efficacy and weight loss in a sample of overweight and obese youth. Methods/Design 40 participants (aged 10–18 years) were randomly assigned to control (social skills training) or treatment (MI) group. Both groups received individual therapy (∼30 min/month) in addition to usual care of diet/exercise counseling. Pre- and post- (at 6 months follow-up) variables included measures of self-efficacy and anthropometrics. Results Although significant between-group differences were not found, individuals in the MI group attended more sessions. Overall, participants in both groups showed significant increases in self-efficacy and a trend of decreased body mass index z-scores. Conclusions Health benefits from participation in individual therapy may have been accrued; however, specific benefits attributable to MI were limited. Findings suggest that more than one type of counseling intervention (i.e., MI and social skills training) may be beneficial when providing integrative treatment for obese youth.