Brandon S. Aylward

Effectiveness of Motivational Interviewing Interventions for Adolescent Substance Use Behavior Change: A Meta-Analytic Review

OBJECTIVE This study was designed to quantitatively evaluate the effectiveness of motivational interviewing (MI) interventions for adolescent substance use behavior change. METHOD Literature searches of electronic databases were undertaken in addition to manual reference searches of identified review articles. Databases searched include PsycINFO, PUBMED/MEDLINE, and Educational Resources Information Center. Twenty-one independent studies, representing 5,471 participants, were located and analyzed. RESULTS An omnibus weighted mean effect size for all identified MI interventions revealed a small, but significant, posttreatment effect size (mean d = .173, 95% CI [.094, .252], n = 21). Small, but significant, effect sizes were observed at follow-up suggesting that MI interventions for adolescent substance use retain their effect over time. MI interventions were effective across a variety of substance use behaviors, varying session lengths, and different settings, and for interventions that used clinicians with different levels of education. CONCLUSIONS The effectiveness of MI interventions for adolescent substance use behavior change is supported by this meta-analytic review. In consideration of these results, as well as the larger literature, MI should be considered as a treatment for adolescent substance use.

Comparison of a Family-Based Group Intervention for Youths with Obesity to a Brief Individual Family Intervention: A Practical Clinical Trial of Positively Fit

OBJECTIVE To examine the effectiveness of a family-based behavioral group intervention (Positively Fit; PF) for pediatric obesity relative to a brief family intervention (BFI) in a sample of treatment-seeking children and adolescents. METHODS Families (n = 93) were randomized to treatment condition. Assessments were conducted at pre- and posttreatment and at 12-month follow-up. Outcome indices included standardized body mass index (BMI) and quality of life (QOL). RESULTS Results indicated a significant reduction in zBMI at posttreatment and follow-up across both conditions. At follow-up, BFI and PF participants evidenced average reductions of .12 and .19 zBMI units, respectively. Children demonstrated better outcomes than adolescents across both conditions. Results indicated clinically significant improvements in parent-reported QOL at postintervention and in self-reported QOL at follow-up for PF participants. CONCLUSIONS Results suggest the effectiveness of family-based interventions for pediatric obesity in clinical settings among younger children. Neither intervention was effective in terms of reducing zBMI among adolescents.

Quality of life and emotional functioning in youth with chronic migraine and juvenile fibromyalgia.

Summary:Chronic pain in children is associated with significant negative impact on social, emotional, and school functioning. Previous studies on the impact of pain on children’s functioning have primarily used mixed samples of pain conditions or single pain conditions (eg, headache and abdominal pain) with relatively small sample sizes. As a result, the similarities and differences in the impact of pain in subgroups of children with chronic pain have not been closely examined. Objective:To compare pain characteristics, quality of life, and emotional functioning among youth with pediatric chronic migraine (CM) and juvenile fibromyalgia (JFM). Methods:We combined data obtained during screening of patients for 2 relatively large intervention studies of youth (age range, 10 to 18 y) with CM (N=153) and JFM (N=151). Measures of pain intensity, quality of life (Pediatric Quality of Life; PedsQL, child and parent-proxy), depressive symptoms (Children’s Depression Inventory), and anxiety symptoms (Adolescent Symptom Inventory-4—Anxiety subscale) were completed by youth and their parent. A multivariate analysis of covariance controlling for effects of age and sex was performed to examine differences in quality of life and emotional functioning between the CM and JFM groups. Results:Youth with JFM had significantly higher anxiety and depressive symptoms, and lower quality of life in all domains. Among children with CM, overall functioning was higher but school functioning was a specific area of concern. Discussion:Results indicate important differences in subgroups of pediatric pain patients and point to the need for more intensive multidisciplinary intervention for JFM patients.

Treatment Adherence in Patients With Headache: A Systematic Review

To review and critically evaluate the extant research literature pertaining to adherence in youth and adults with headache and to provide recommendations for future research.

Predictors of attendance in a practical clinical trial of two pediatric weight management interventions.

The objective of this study was to evaluate demographic and psychosocial predictors of attendance in a family‐based behavioral weight management clinical trial. Ninety‐three children and adolescents aged 7–17 (Mean age = 11.59, s.d. = 2.6) who were either overweight or obese (Mean BMI percentile = 98.2) and their parents received either a 10‐session behavioral treatment or a three‐session brief family intervention in the context of a randomized clinical trial (10). Psychosocial and anthropometric measures were obtained before enrollment and at the end of 10 weeks for both treatment groups. Univariate linear regression and hierarchical multiple regression analyses were used to identify predictors of attendance to treatment from an a priori set of hypothesized predictors. Three variables demonstrated significant associations with the dependent variable, percent of treatment sessions attended. Specifically, distance from participants home to treatment site, lower gross family income, and youth self‐report of depressive symptoms were each associated with lower percent attendance (all Ps < 0.05). These results corroborate (i.e., income, depressive symptoms) and expand (i.e., distance from treatment site) previous reports in the literature of potential barriers to effective treatment for pediatric obesity, and suggest the need for research on treatment delivery methods that could increase participation among low‐income families (e.g., eHealth, mHealth options). Depressive symptoms could represent an additional barrier to treatment attendance, suggesting that assessment and treatment for these symptoms may be appropriate before commencing weight management treatment.

Strategies for Recruitment and Retention of Families From Low-Income, Ethnic Minority Backgrounds in a Longitudinal Study of Caregiver Feeding and Child Weight

Children from low socioeconomic status (SES) and ethnic minority backgrounds are at heightened risk for overweight, yet are underrepresented in the pediatric obesity literature. This article describes strategies employed to minimize barriers to recruitment and retention of African American families receiving Women, Infants, and Children services in a longitudinal study examining caregiver feeding and child weight. Seventy-six families enrolled in the study over 3½ years, and 50% of the families completed the study. Despite effortful planning, unanticipated barriers likely contributed to lengthy recruitment and a modest retention rate. Future research should incorporate lessons learned to modify and develop effective strategies for increasing engagement of low-SES and ethnic minority families in research.

The Use of Cluster Analytic Techniques in Developmental and Behavioral Pediatric Research

Ric G. Steele, PhD, ABPP, Brandon S. Aylward, MA Cluster analysis refers to several person-centered exploratory data analytic approaches that identify and describe groups of individuals who are defined by similarities along one or more dimensions of interest.1 At a very basic level, the techniques can be seen as similar to factor analysis, except that in cluster analysis, similarities across cases (rather than covariance between items) are used to empirically define cluster group membership. Cluster analysis techniques have a relatively long history of use in the fields of business and economics and have also been used extensively in biology and sociology. However, the use of cluster analytic techniques has emerged relatively recently in the medical and psychological literature. Cluster analytic techniques are often used as a means of describing change across time but may also be used to identify patterns of differences across multiple measures at a single point in time.2,3 For example, a marketing specialist might use cluster analysis to determine that individuals who (a) own a home, (b) have incomes between

The changing yardstick in measurement of cognitive abilities in infancy.

75,000 and

Searching the scientific literature: Implications for quantitative and qualitative reviews

99,000, (c) read the Journal of Developmental and Behavioral Pediatrics, and (d) work in a hospital setting constitute a unique “cluster” and that members of this cluster are more likely than members of other cluster groups to purchase a particular product. Conversely, a developmental pediatrician might use cluster analysis to determine that the weight gain trajectories of premature infants fall into four distinct groups and that these distinct groups (clusters) differentially predict longterm outcomes. Thus, regardless of whether longitudinal (i.e., developmental) or cross-sectional data contribute to the development of clusters, group membership can then be used for descriptive or predictive purposes. Because cluster analytic techniques are typically exploratory in nature, authors often recommend a fairly rigorous two-step process to identify the most robust and ecologically valid (i.e., clinically relevant) cluster patterns.1,4 Specifically, these steps include (a) the use of hierarchical cluster analysis to identify the nature and number of clusters and (b) the use of nonhierarchical (k-means) cluster analysis to confirm these clusters. This process is roughly analogous to how one might follow an exploratory factor analysis with a confirmatory factor analysis to ensure robust and nonsample-dependent factors. As Henry and colleagues1 note, using a combination of hierarchical and nonhierarchical clustering methods “capitalizes on the strengths of both methods and compensates for their weaknesses.”

Psychosocial functioning of pediatric renal and liver transplant recipients

There are concerns regarding accurate measurement of cognitive function in infants, particularly those at biologic risk. Herein we discuss these issues and make recommendations. Concerns include: 1) secular changes in test norms, referred to as the Flynn effect; 2) changes in the content of revised test versions; 3) recent findings of higher mean scores in newer test versions when compared to previous scores; and 4) correction for prematurity. Caution is necessary when comparing the same test scores over extended periods of time, and using different versions of the same test when mean scores of the tests vary or evaluate different areas of functioning. Ideal solutions are not readily apparent and thus we provide several suggestions: control groups are essential for longitudinal studies; clinicians should not rely totally on cognitive scores; and further investigation of the Flynn effect in different subgroups of children at different ages is necessary.