Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2017 Mar 1.
Published in final edited form as: J Consult Clin Psychol. 2016 Nov 3;85(3):218–227. doi: 10.1037/ccp0000153

Excess Weight Gain Prevention in Adolescents: Three-year Outcome following a Randomized-Controlled Trial

Marian Tanofsky-Kraff 1,2, Lauren B Shomaker 2,3, Denise E Wilfley 4, Jami F Young 5, Tracy Sbrocco 1, Mark Stephens 6, Sheila M Brady 2, Ovidiu Galescu 2, Andrew Demidowich 2, Cara H Olsen 7, Merel Kozlosky 8, James C Reynolds 9, Jack A Yanovski 2
PMCID: PMC5319904  NIHMSID: NIHMS810831  PMID: 27808536

Abstract

Objective

Interpersonal psychotherapy (IPT) prevents weight gain in adults with obesity and binge-eating-disorder, and is especially effective among those with increased psychosocial problems. However, IPT was not superior to health-education (HE) to prevent excess weight gain at 1-year follow-up in 113 adolescent girls at high-risk for excess weight gain because of loss-of-control (LOC)-eating and high BMI (kg/m2) (Tanofsky-Kraff et al., 2014).

Method

Participants from the original trial were re-contacted 3-years later for assessment. At baseline, adolescent- and parent-reported social-adjustment problems and trait-anxiety were evaluated. At baseline and follow-ups, BMIz and adiposity by dual-energy X-ray absorptiometry were obtained.

Results

Nearly 60% were re-assessed at 3-years, with no group differences in participation (ps≥.70). Consistent with 1-year, there was no main effect of group on change in BMIz/adiposity (ps≥.18). In exploratory analyses, baseline social-adjustment problems and trait-anxiety moderated outcome (ps<.01). Among girls with high self-reported baseline social-adjustment problems or anxiety, IPT, compared to HE, was associated with the steepest declines in BMIz (p<.001). For adiposity, girls with high- or low-anxiety in HE, and girls with low-anxiety in IPT experienced gains (ps≤.03), while girls in IPT with high-anxiety stabilized. Parent-reports yielded complementary findings.

Conclusion

In obesity-prone adolescent girls, IPT was not superior to HE in preventing excess weight gain at 3-years. Consistent with theory, exploratory analyses suggested that IPT was associated with improvements in BMIz over 3-years among youth with high social-adjustment problems or trait-anxiety. Future studies should test the efficacy of IPT for obesity prevention among at-risk girls with social-adjustment problems and/or anxiety.

Keywords: Preventive adolescent IPT, social-adjustment problems, anxiety, BMIz, adiposity

Given the high rates of overweight and obesity among U.S. adolescent girls (Ogden et al., 2016), and the generally insufficient effects of standard weight management programs (Wilfley, Tibbs, et al., 2007), there have been calls for targeted intervention approaches for susceptible subgroups (Field, Camargo, & Ogino, 2013). One potentially modifiable target that is strongly correlated with obesity in youth is self-reported loss of control (LOC) eating episodes (Tanofsky-Kraff, Yanovski, & Yanovski, 2011). Presence of LOC in youth has been shown to prospectively predict excess weight and fat gain over 3–5 years (Field et al., 2003; Sonneville et al., 2013b; Stice, Cameron, Killen, Hayward, & Taylor, 1999; Tanofsky-Kraff et al., 2006; Tanofsky-Kraff et al., 2009). Thus, reducing LOC eating would be hypothesized to result in improved weight gain trajectories (less weight gain) for youth at high-risk for adult obesity (Tanofsky-Kraff et al., 2007). However, there has been limited research on reducing adolescent LOC eating for preventing excess weight gain (Berkman et al., 2015).

One model to explain LOC eating is interpersonal theory, which proposes that difficult social relationships lead to negative mood states that then result in perceived emotionally-induced, out of control eating (Tanofsky-Kraff et al., 2007). Interpersonal psychotherapy (IPT), based on interpersonal theory, focuses on improving relationships, decreasing negative affect (Weissman, Markowitz, & Klerman, 2000), which in turn is expected to reduce LOC eating (Wilfley, MacKenzie, Welch, Ayres, & Weissman, 2000) to lead to improvements in weight gain trajectories (Tanofsky-Kraff et al., 2007). Indeed, IPT has been shown to be effective in adults with overweight and obesity and binge eating disorder (BED); those who reduced binge episodes experienced weight maintenance or modest weight loss (Wilfley et al., 2002; Wilson, 2011). IPT appears to be as effective as other therapeutic modalities in reducing binge episodes (Wilson & Shafran, 2005). We, therefore, carried out a randomized, controlled prevention trial aimed at reducing undue weight gain in adolescent girls with LOC eating who were above average weight, but otherwise healthy. However, we found no differences at 1 year between a specially-adapted IPT group prevention program and a time- and attention-matched health education (HE) group in reported LOC eating, BMI indices or adiposity (Tanofsky-Kraff et al., 2014). Some data suggest that IPT for bulimia nervosa may take longer (8–12 months) than cognitive behavioral therapy to produce effects (Wilson & Shafran, 2005). Moreover, one study showed that for BED, IPT may be superior to cognitive behavioral therapy in the long-term, up to 4 years following therapy (Hilbert et al., 2012). Therefore, we hypothesized that a longer follow-up interval may be required for differential effects between IPT and a non-specific HE intervention to unfold.

In the current study, we aimed to determine whether differences would emerge during a longer follow-up interval in participants who were randomized to IPT compared to HE. We re-contacted girls 3 years following the initiation of group sessions of the original trial (Tanofsky-Kraff et al., 2014). We hypothesized that over a 3-year follow-up, adolescent girls randomized to IPT would experience greater age-adjusted BMI (BMIz) loss and less adiposity gain (unadjusted gain is expected in growing youth who are not obese) than girls who received HE. Further, data from adolescent depression trials have demonstrated that baseline social-adjustment problems and anxiety moderate outcome, such that those with more problems experience greater reductions in depression following IPT compared to standard of care (Gunlicks-Stoessel, Mufson, Jekal, & Turner, 2010; Young, Gallop, & Mufson, 2009; Young, Mufson, & Davies, 2006b). Such findings are consistent with interpersonal theory (Weissman et al., 2000). Therefore, we conducted exploratory, post-hoc analyses to determine whether these baseline constructs would positively impact BMIz among those randomized to IPT. Given the typical lack of concordance between child and parent reports (Hunsley & Mash, 2007), we anticipated that adolescent self-report would serve as a more robust predictor of outcome.

Method

Participants

Psychologically and physically healthy adolescent girls (12 to 17 years) who had participated in a 1-year randomized-controlled clinical trial (ClinicalTrials.gov ID#: NCT00680979) at the Uniformed Services University (USU) and the National Institutes of Health (NIH) Hatfield Clinical Research Center in Bethesda, MD were studied. Recruitment and inclusion and exclusion criteria are described in detail in a previous report (Tanofsky-Kraff et al., 2014). In brief, participants were considered at risk for excess weight gain because of an above-average but not severely obese BMI, between the 75th and 97th percentiles (Field, Cook, & Gillman, 2005), and the report of LOC eating in the past month (Tanofsky-Kraff et al., 2009). Girls were excluded if they had any major medical or psychiatric condition (other than BED), were simultaneously participating in a structured weight loss program or psychotherapy, or were taking medications known to affect body weight or appetite. Approximating the follow-up of the one long-term adult study of IPT for BED (Hilbert et al., 2012), participants were re-contacted 3 years after the initiation of the group programs to request participation in an additional assessment that was not pre-specified in the original trial design. The study was approved by the USU and Eunice Kennedy Shriver National Institute of Child Health and Human Development institutional review boards. A parent/guardian provided written consent for participation in both the original trial and the additional 3-year assessment for daughters who had not reached the age of consent. Their adolescent daughters provided written assent or consent, as appropriate, for the original study and the add-on 3-year follow-up.

Measures

At the baseline assessment, the Eating Disorder Examination, v14 OD/C.2 (Fairburn & Cooper, 1993) was administered to identify girls reporting at least one episode of LOC eating in the past month, to assess baseline frequency of LOC episodes in the past month, and to identify youth with current or past anorexia nervosa or bulimia nervosa, which resulted in study exclusion and referrals (Tanofsky-Kraff et al., 2014). The Eating Disorder Examination has demonstrated excellent internal consistency in adolescents for the presence and frequency of LOC episodes (Glasofer et al., 2007). For the present sample, the EDE demonstrated good reliability (Cronbach’s α=.88). Also at baseline, the Social Adjustment Scale – Self-Report (SAS) total score (Weissman & Bothwell, 1976) and the State-Trait Anxiety Inventory for Children–A Trait Scale (STAIC) (Spielberger, 1983), both valid and reliable measures for adolescents, were completed by all girls to assess social-adjustment problems and trait anxiety, respectively. Both questionnaires serve as screeners without clinical cutoffs, and were intended to capture continuous dimensions of these constructs; higher scores reflect more social-adjustment problems and higher anxiety. The SAS (Cronbach’s α=.83) and STAIC (α=.83) both demonstrated good reliability in the present sample. Parents also completed the widely-used Child Behavior Checklist (CBCL) for ages 4–18 (Achenbach & Elderbrock, 1991), an empirically derived measure with excellent psychometric properties. The total raw scores from the social-adjustment problems and anxiety profile subscales were examined as a continuous measure of parents’ report of their daughters’ social-adjustment problems and anxiety, respectively; higher scores reflected greater social problems and higher anxiety. In the present sample, the CBCL scales demonstrated adequate reliability (social-adjustment problems: α=.64 and anxiety: α=.62). Continuous versions of all scales were utilized in all primary analyses. To illustrate interaction effects, graphs display categorical versions of the SAS, STAIC, and CBCL scores, which were determined as values below or at versus above the sample median (SAS total ≤2.2 vs. ≥2.3; STAIC anxiety ≤34 vs. ≥35; CBCL social problems ≤2 vs. ≥3; and CBCL anxiety ≤1 vs. ≥2).

At baseline and 12-week, 6-month, and 1-year post-intervention follow-up visits, girls’ height was measured three times to the nearest millimeter with a calibrated electronic stadiometer, and weight was measured to the nearest 0.1 kg with a calibrated digital scale following an overnight fast. Shoes and outerwear were removed. If a girl wore her hair styled such that it added height, she was asked to take her hair down prior to measurement. Fasting weight and the average of the three heights were used to calculate BMI (kg/m2). The U.S. Centers for Disease Control and Prevention growth standards were used to derive the primary outcome of BMIz, standardized BMI score for age and sex (Kuczmarski et al., 2002). Adiposity was determined as body fat mass (kg) by dual-energy X-ray absorptiometry (DXA) using a Hologic QDR-4500A or Discovery instrument (Bedford, MA) at baseline, 6-month, and 1-year follow-up visits.

3-year Follow-up Assessment

Approximately 3 years following the initiation of their participation in the group programs, girls were re-contacted to request participation in an additional assessment. Participants who agreed to take part had height and weight measured as described above and underwent DXA. Participants were also queried regarding any type of therapy received during the follow-up interval.

Prevention Programs

As previously described (Tanofsky-Kraff et al., 2014), in this parallel-group, controlled trial, participants were randomized to either an adapted version of IPT or a HE comparison group using computer-generated random numbers. Both programs involved an individual 1.5-hour meeting with each girl followed by 12 consecutive weekly 90-minute group sessions. Leader training and program delivery and fidelity have been described (Tanofsky-Kraff et al., 2014). In brief, both the IPT and the HE groups were co-facilitated by a trained PhD-level clinical psychologist and a trained graduate student in clinical psychology. Clinicians delivered both interventions. Independent psychologists listened to randomly selected sessions and rated items as present or absent in reflecting IPT. Results indicated excellent adherence to IPT; with 82–100% of each session rated as adherent and 96.5% of all sessions rated as adherent. HE groups also were rated as to presence of IPT techniques and were rated as low on inclusion of IPT techniques, suggesting minimal contamination between conditions.

Adapted Interpersonal Psychotherapy (IPT)

The IPT program was adapted from two previously established IPT manuals: i) IPT-Adolescent Skills Training for the prevention of depression (Young & Mufson, 2003) and ii) group IPT for BED (Wilfley et al., 2000). In this adapted program (Tanofsky-Kraff et al., 2014), girls were taught to identify the connections among their relationships, mood, and eating. By guiding them to improve their interpersonal interactions both within and outside of the group milieu, the goal of IPT was to reduce negative affect-induced LOC eating episodes that promote excess weight gain. See Tanofsky-Kraff et al., 2014 for details on the adapted IPT program.

Health Education (HE)

As previously detailed (Tanofsky-Kraff et al., 2014), the HE intervention was based upon the “Hey-Durham” manual for high school students (Bravender, 2005). The HE program was adapted and delivered as a manualized, attention comparison to match session duration and frequency of IPT (Tanofsky-Kraff et al., 2014; Tanofsky-Kraff et al., 2010). The curriculum topics include domestic violence, alcohol, drug and tobacco, basic information on nutrition, body image, symptoms and prevalence of depression and suicide, gang violence, non-violent conflict resolution, and sun safety.

Statistical Analyses

All analyses were performed using SPSS v.23 (IBM). Baseline LOC episodes was log transformed; all other variables approximated a normal distribution. Descriptive information was generated for study variables at baseline and at 3-year follow-up. Pearson correlations were used to describe the associations among key baseline variables. The 3-year follow-up missing data patterns were characterized by group, and logistic regression was used to predict 3-year attrition from baseline variables. Power analyses for this randomized controlled trial were estimated for the original, pre-specified 1-year age adjusted BMI endpoint (Tanofsky-Kraff et al., 2014). Post-hoc power analyses for 3-year BMIz and adiposity change indicated 80% power to detect a medium effect (d = .50) of group and 80% power to detect a medium effect (d = .50) for the interaction of group with baseline social-adjustment problems or anxiety. To evaluate the primary hypotheses, we conducted linear mixed models using restricted maximum likelihood (ML) estimation to handle missing data (West & Galecki, 2012), a flexible set of tools that permits modeling of all available data points across time-varying intervals and which incorporates a recommended approach (ML estimation) for treating missing data (Schafer & Graham, 2002). Completer analyses, using listwise deletion, yielded nearly identical results, and are therefore, not presented in the results. The model fixed effects were group (IPT, HE), time (baseline, 12-week follow-up, 6-month follow-up, 1-year follow-up, 3-year follow-up), and group by time. Since adiposity was not measured at the 12-week follow-up, this interval was omitted from the modeling of that outcome. The primary outcome (dependent variables) were BMIz and adiposity. Participant was the random effect. The intraclass correlation coefficients (ICC) for participants nested within cohorts of groups was 0, indicating that none of the variability in BMIz or adiposity was accounted for by inter-dependence within group cohorts, and suggesting that a 3-level model was not necessary. Time, centered at baseline (0), was calculated as the number of weeks from baseline for each girl in order to allow for variability in the spacing of each participant’s follow-up assessments. To ensure that any observed effects were after accounting for differences in baseline age and height, we evaluated these factors as covariates. For BMIz, we retained baseline age, but not height, as the latter was not significant, likely because this metric already adjusts for height. Both covariates were retained for DXA adiposity. To evaluate if baseline social-functioning or anxiety served as moderators of intervention outcomes, in post-hoc analyses, we included baseline social-adjustment problems (by adolescent-reported SAS or parent-reported CBCL social-adjustment problems) or baseline anxiety (by adolescent-reported STAIC trait anxiety or parent-reported CBCL anxiety) and the two- and three-way interactions with group and time as model fixed effects. In order to facilitate the interpretation of any observed, significant interactions, we plotted group effects across time by participants who were below or at versus above the sample median for baseline social-adjustment problems or anxiety.

Results

Two-hundred-forty-six families responded to recruitment materials. Among those, 80 were excluded following a telephone screen, six due to lack of reported LOC eating. As previously reported (Tanofsky-Kraff et al., 2014), 166 were assessed for study participation, seven of whom were excluded due to not reporting LOC eating. See Tanofsky-Kraff and colleagues (2014) for the trial’s complete CONSORT diagram.

Table 1 displays descriptive information for participant demographic and anthropometric characteristics and psychological symptoms at baseline and 3-year follow-up. As previously reported (Tanofsky-Kraff et al., 2014), at baseline, participants randomized to HE were slightly older (p < .05) and reported more frequent episodes of LOC eating in the past month (p = .02), with no other significant baseline differences. Correlations among all key baseline variables are displayed in Table 2. Adolescent reports of social-adjustment problems and anxiety symptoms were significantly correlated (r = .35, p < .001), as were parent-reports of their daughters’ social-adjustment problems and anxiety (r = .47, p < .001). Adolescent and parent reports of adolescents’ social-adjustment did not correspond (r = .05, p = .57), and adolescent and parent reports of adolescents’ anxiety symptoms had a low, positive correlation (r = .26, p < .01).

TABLE 1.

Characteristics of Participants Randomized to Interpersonal Psychotherapy (IPT) or Health Education (HE) Groups

IPT Group HE Control Group
Baselinea
M, SD		 3-Year Follow-upb
M, SD		 Baselinec
M, SD		 3-Year
Follow-upd M, SD
Age, y† 14.18, 1.52 17.22, 1.59 14.80, 1.73 17.93, 1.80
Puberty, Tanner breast stage (median) 5 -- 5 --
Race/ethnicity, n (%)
 Non-Hispanic White 29 (53) 35 (60)
 Non-Hispanic Black 14 (26) 13 (22)
 Hispanic 5 (9) 5 (9)
BMI, kg/m2† 26.86, 2.61 27.78, 3.90 27.08, 2.43 28.89, 4.24
BMIz† 1.55, 0.34 1.32, 0.53 1.52, 0.32 1.40, 0.50
BMI percentile† 92.35, 4.59 87.28, 10.42 92.10, 4.84 88.94, 9.76
Body fat, kg 26.38, 5.81 27.74, 8.02 26.40, 6.00 28.68, 8.13
Adolescent-reported social-adjustment problems 2.35, 0.81 2.38, 0.80 2.55, 0.84 2.40, 0.89
Parent-reported social-adjustment problems 2.95, 2.19 1.50, 1.58 2.65, 2.49 1.85, 2.33
Adolescent-reported anxiety† 33.25, 7.13 32.18, 7.63 34.88, 6.34 34.03, 7.58
Parent-reported anxiety† 1.38, 1.64 0.93, 1.36 1.40±1.47 1.37, 1.86
LOC-eating episodes, past month‡ 2.55, 0.91–5.61 0.58, −0.13, 1.88 3.79, 1.34–8.77 0.41, −0.24, 1.63
Open in a new tab

Note.

a

n = 55.

b

n = 28–33.

c

n = 57–58.

d

n = 27–37.

†

Mean±Standard Deviation.

‡

Geometrics mean and 95% confidence interval.

TABLE 2.

Correlations among Baseline Characteristics for All Participants

1. 2. 3. 4. 5. 6. 7. 8.
1. Age, y --
2. BMIz −.25** --
3. Body fat, kg .27** .65*** --
4. Adolescent-reported social-adjustment problems .00 .13 .10 --
5. Parent-reported social-adjustment problems −.11 .25** .13 .05 --
6. Adolescent-reported anxiety† .09 −.06 −.01 .35*** .10 --
7. Parent-reported anxiety† .09 .02 −.05 .16 .47*** .26** --
8. LOC-eating episodes, past month‡ .03 −.18 −.06 .02 −.04 .27** .00 --
Open in a new tab

Sixty-two percent of adolescents in IPT (n = 36) and 58% (n = 32) in HE completed a 3-year follow-up (p = .70). Of the original sample of 113, 21 girls were not interested in participating, 15 were unable to be reached, and nine moved out of the area. Attrition was not significantly predicted by race, baseline age, BMIz, adiposity, adolescent- or parent-reported social-adjustment problems or anxiety, or number of LOC eating episodes (ps > .11).

At the 3-year follow-up visit, 6.1% who had been randomized to IPT reported that they had received therapy since their last assessment, as compared to 16.7% in HE (p = .26). Adjusting for reported receipt of therapy did not alter the results. In addition, if the participants who reported receipt of therapy were excluded, the results also remained unchanged.

Primary Outcome: Effects of IPT vs. HE on 3-year BMIz

Accounting for baseline age, there was no significant group effect on changes in BMIz over time, F(1, 379) = 1.82, p = .18. BMIz had a significant, negative slope (−.001 ± .0002, p < .001), indicating that, on average, all adolescent girls decreased BMIz score over time, F(1, 380) = 41.99, p < .001.1 Accounting for baseline age and height, there was no group effect on changes in adiposity over the study period, F(1, 272) = .11, p = .75. Adiposity had a positive slope, indicating that, on average, adolescent girls’ adiposity increased (Unstandardized estimate ± SE .01 ± .003, p < .001) over the 3-years of follow-up, F(1, 273) = 14.63, p < .001.

Post-hoc Exploratory Outcomes

Interactions between Group Assignment and Baseline Psychosocial Functioning for 3-year BMIz

Baseline social-adjustment problems

Baseline adolescent-reported social-adjustment was a significant moderator of the effect of group on BMIz change, F(1, 376) = 6.24, p = .013. Based on a median split of social-adjustment problems, among adolescent girls who reported higher social-problems, there was a significant effect of group assignment on 3-year BMIz change (p = .009). In girls with higher social-adjustment problems, those in IPT had a steeper decline in BMIz (p < .001) than those in HE (p = .01; Figure 1a). Conversely, among girls with lower social-adjustment problems, there was no group difference in BMIz change over time (p = .49); girls in both HE (p = .01) and IPT (p = .03) displayed decreases in BMIz over 3-years. Accounting for baseline age and height, baseline adolescent-reported social-adjustment problems did not moderate the group effect on adiposity change over time, F(1, 269) = 1.67, p = .20.

FIGURE 1.

FIGURE 1

Open in a new tab

Change in body mass index standard score (BMIz) over a 3-year follow-up in adolescent girls randomized to interpersonal psychotherapy (IPT) or health education (HE) by low (≤ median) versus high (>median) A: adolescent-reported baseline social-adjustment problems on the Social Adjustment Scale (SAS) and B: parent-reported baseline social-adjustment problems on the Child Behavior Checklist (CBCL). All estimates are adjusted for baseline age. P values depicted indicate whether significant change occurred over the 3-year period in each subset.

Baseline parent-reported social-adjustment problems also was a significant moderator of the group effect on changes in adolescent BMIz over time, F(1, 377) = 6.38, p = .01. Among adolescents with higher parent-reported social-problems, there was a significant effect of group on 3-year change in adolescent BMIz (p = .004). Only in adolescents with higher parent-reported social-problems, girls who participated in IPT had significant declines in BMIz (p < .001), whereas girls who participated in HE showed no decrease in BMIz (p = .64; Figure 1b). Conversely, there was no effect of group on changes in 3-year BMIz scores among girls with lower baseline parent-reported social-adjustment problems (p = .84). In girls who were lower in baseline parent-reported social-adjustment problems, those who participated in IPT and HE both showed declines over 3-years in BMIz (ps < .001).2 Baseline parent-reported social-adjustment problems were not a significant moderator of the group by time effect on adolescent adiposity, F(1, 270) = 2.35, p = .13.

Baseline anxiety

Baseline adolescent-reported anxiety was a significant moderator of 3-year change in BMIz, F(1, 376) = 13.34, p < .001. Among girls with higher baseline self-reported anxiety, those who participated in IPT showed a steeper decline in 3-year BMIz (p < .001) than those who participated in HE (p = .02; Figure 2a). Among girls with lower baseline self-reported anxiety, those in IPT and HE had similar decreases in BMIz over time (ps < .01). Adjusting for baseline age and height, baseline adolescent-reported anxiety was a significant moderator of the group effect on adiposity over time F(1, 269) = 12.0, p = .001; Figure 2b); girls with lower anxiety in both groups and girls with higher anxiety in HE, all experienced significant adiposity gains (ps < .05). By contrast, girls with higher anxiety in IPT experienced no significant gains (p = .81).

FIGURE 2.

FIGURE 2

Open in a new tab

Change in dual body mass index standard score (BMIz) and energy x-ray absorptiometry (DXA) adiposity (kg) over a 3-year follow-up in adolescent girls randomized to interpersonal psychotherapy (IPT) or health education (HE) by low (≤median) versus high (>median) A/B: adolescent-reported baseline trait anxiety on the State Trait Anxiety Inventory for Children (STAIC) and C/D: parent-reported baseline trait anxiety on the Child Behavior Checklist (CBCL). BMIz estimates are adjusted for baseline age. DXA estimates are adjusted for baseline age and change in height. P values depicted indicate whether significant change occurred over the 3-year period in each subset.

Baseline parent-reported adolescent anxiety also was a significant moderator of the group by time effect on adolescent BMIz, F(1, 376) = 19.35, p < .001. There was a significant group effect on BMIz only in girls with higher baseline parent-reported adolescent anxiety (p = .007). Girls with higher anxiety in HE had no decline in BMIz score (p = .16), whereas those in IPT significantly decreased BMIz score over 3-years (p < .001; Figure 2c). In adolescent girls with lower baseline parent-reported anxiety, those in both HE and IPT had similar declines in BMIz (ps≤.001).3 Baseline parent-reported anxiety was a significant moderator of the group by time effect on adolescent adiposity, F(1, 268) = 13.18, p < .001. Among adolescents with higher parent-reported anxiety, those who received HE increased adiposity over 3-years (p = .007), whereas those who received IPT stabilized adiposity (p = .85; Figure 2c).

Baseline depressive symptoms and number of LOC eating episodes

We repeated analyses to determine whether other variables proposed in the interpersonal model of LOC eating (Tanofsky-Kraff et al., 2007) moderated the effect of group on change over time in BMIz over the 3-year follow-up period. Neither baseline depressive symptoms measured by the Beck Depression Inventory-II (Beck, Steer, & Brown, 1996) (p = .95) nor number of LOC eating episodes (p = .68) moderated the effect of group on BMIz or adiposity change over time.

Discussion

In a targeted program for excess weight gain prevention, we found no group differences in 3-year outcome in adolescent girls randomized to IPT or HE. Yet, in post-hoc, exploratory analyses, baseline social-adjustment problems and anxiety moderated outcome, such that girls with more problems given IPT typically had the greatest improvements in BMIz and adiposity. Despite some data showing that IPT takes longer than other programs to exert its effects (Hilbert et al., 2012; Wilson & Shafran, 2005), IPT was not superior to HE for BMIz or adiposity at 3-years. This result is consistent with our findings at 1-year follow-up (Tanofsky-Kraff et al., 2014). It is possible that above-average weight adolescent girls with LOC eating do not require a specialized program for excess weight gain prevention. Alternatively, our sample may have not been sufficiently targeted for IPT to impact BMIz and adiposity trajectories. Indeed, our sample was primarily psychologically healthy. Interestingly, despite a sample deemed at high-risk for excessive weight gain due to both their current body weight and LOC eating (Field et al., 2003; Sonneville et al., 2013a; Stice et al., 1999; Tanofsky-Kraff et al., 2009), regardless of group assignment, girls reduced BMIz. Although recent data show that obesity rates have continued to increase in adolescents (Ogden et al., 2016), the impact of our programs is unclear, due to lack of an untreated contemporaneous control group. Yet, it is possible that given the social support provided, both groups were effective in decreasing the rate of BMIz gain. Indeed, data suggests that social support improves weight outcomes for adults (Wing & Jeffery, 1999), adolescents (Tanofsky-Kraff et al., 2014), and children (Wilfley, Stein, et al., 2007).

Exploratory, post-hoc analyses evaluating baseline social-adjustment problems and anxiety as moderators of the group effect on gain revealed that adolescents with more psychosocial difficulties initially had the most benefit from IPT as compared to HE. These results are consistent with previous IPT randomized controlled trials showing that both social functioning and anxiety moderate intervention outcomes for depressed adolescents (Gunlicks-Stoessel et al., 2010; Young et al., 2009; Young et al., 2006b), such that youth with worse baseline psychosocial functioning experience the greatest improvements in depressive symptoms if they received IPT as opposed to treatment as usual. Social-adjustment problems and anxiety are important components of the interpersonal model (Weissman et al., 2000), and IPT directly focuses on improving interpersonal functioning and negative mood states. The compensation model (Rude & Rehm, 1991), which proposes that individuals are especially responsive to interventions that target their vulnerabilities, may explain why girls in our sample with social-adjustment problems and high anxiety benefitted most from IPT. These data speak to the possibility of considering presenting psychological characteristics when choosing appropriate weight management interventions. However, due to their post-hoc, exploratory nature, moderation findings should be interpreted with caution.

Given the typical lack of concordance between child and parent reports of psychological functioning (Briggs-Gowan, Carter, & Schwab-Stone, 1996; Grills & Ollendick, 2003; Hunsley & Mash, 2007), it was not surprising that baseline correspondence of social-adjustment and anxiety problems between daughters and parents was modest to poor. Despite the poor baseline correspondence, it is notable that the moderating impact of social-adjustment and anxiety on group effects on 3-year BMIz was generally consistent based on self and parent informant. Yet, findings were not entirely parallel, but rather complementary. Girls with higher self-reported social-adjustment problems and anxiety experienced greater improvements if randomized to IPT. If parents reported higher child problems, their daughters experienced the least improvements in BMIz if assigned to HE. If replicated in future studies, these data support the notion that youth who self-perceived social problems and anxiety may benefit from an intervention targeting such difficulties. Whereas when relying on parents’ perspectives, social problems and/or outward manifestations of anxiety could be identifying a phenotype of youth who are particularly prone to excess weight gain and thus may fail to respond to non-specific intervention. Given the exploratory nature of moderation findings, these theories require testing.

Depressive symptoms did not moderate outcome. Given that IPT is an effective treatment (Mufson et al., 2004) and prevention (Young, Mufson, & Davies, 2006a) strategy for adolescent depression, this finding was somewhat surprising. High depressive scores (Beck Depression Inventory-II (Beck et al., 1996) score ≥25) were a study exclusion; thus, the range of scores may have been too narrow to observe any impact on outcome. Alternatively, anxiety specifically, may be the driving obesity-promoting mood state in these youth. Data in adolescents have shown heavier body weight to be associated with increased anxiety symptoms and maintenance of increased weight (Kubzansky, Gilthorpe, & Goodman, 2012). Further, youth with overweight and obesity who have high anxiety present with greater psychosocial distress compared to their counterparts with low anxiety (Lim, Espil, Viana, & Janicke, 2015), potentially requiring a specialized intervention. Due to the exploratory nature of findings, IPT should be explicitly evaluated for its impact on weight among obesity-prone youth who present with an anxiety phenotype.

There was no indication that baseline LOC eating frequency was an intervention moderator. As all girls reported LOC at baseline and very few reported enough episodes to meet criteria for BED, the severity of LOC as a moderator of intervention effects was limited. Alternatively, research using functional neuroimaging and the feeding laboratory (Jarcho et al., 2015; Vannucci et al., 2014) demonstrates that for a subset of adolescents with overweight, overeating may promote obesity when anxiety induces non-homeostatic eating, perceived as out of control. As proposed in the context of adult BED (Stunkard & Allison, 2003), self-reports of LOC eating may be potentially a manifestation of important underlying constructs. Thus, while LOC eating may be a marker that predicts adverse weight outcomes (Field et al., 2003; Sonneville et al., 2013b; Stice et al., 1999; Tanofsky-Kraff et al., 2006; Tanofsky-Kraff et al., 2009), it may not be the central construct for shaping obesity prevention interventions for some youth. It is possible that for IPT to exert a positive impact on BMIz and adiposity, baseline reports of LOC eating may be neither necessary nor sufficient. Among girls screened either over the telephone or in person, only 13 were deemed ineligible due to lack of LOC eating. This raises the possibility that IPT may be promising for youth with overweight and social problems and/or anxiety even in the absence of out of control eating. Given the exploratory nature of the moderation analyses, this possibility should be considered with caution and warrants thorough evaluation. Regardless, our data speak to the considerable overlap of psychopathological behaviors and the need for novel conceptualizations of psychiatric problems (Insel et al., 2010; National Institute of Mental Health (NIMH), 2008). Future data are required to confirm whether youth with reported social problems and/or anxiety who are prone to excess weight gain are especially responsive to IPT.

Study strengths include the use of objectively measured height and weight. Additionally, we were able to obtain data 3-years after program initiation. Long-term follow-up for the outcomes of programs are particularly important for body weight, since the effects of interventions that appear impressive in the short-term frequently show few benefits when evaluated 2–3 years later (MacLean et al., 2015; Wilfley, Tibbs, et al., 2007). Yet, as with most studies that involve additional follow-ups after completion of a protocol, particularly with an age cohort that is often geographically mobile (following high school), we were able to capture data only from 60% of the sample. Yet, retention was comparable or better than at least one study that included an additional long-term assessment after the trial concluded (Hilbert et al., 2012). We observed no difference in baseline characteristics among those who did and did not participate, and our analytic approach is considered robust when accounting for missing data. Our findings may be only generalizable to adolescent girls who are above-average weight, but not severely obese, with reported LOC eating, and without clinically significant psychological disorders. In addition, our post-hoc analyses, although based on theory (Weissman et al., 2000) and prior data (Gunlicks-Stoessel, Mufson, Jekal, & Turner, 2010; Young, Gallop, & Mufson, 2009; Young, Mufson, & Davies, 2006b), were added after the initiation of the study and thus should be considered a limitation. Future studies are needed to determine whether reported social-adjustment problems, anxiety and/or LOC eating are required for IPT to exert beneficial weight outcomes. Finally, despite the use of multiple informants for some measures, all baseline psychological measures were based on report as opposed to physiological indices. Brain functional data, for example, may provide a clearer understanding of the mechanistic impact of social functioning/anxiety on weight outcomes following IPT.

In conclusion, at 3-years following intervention, IPT adapted to prevent excess weight gain was not superior to a standard-of-care HE program among high-risk adolescent girls. In exploratory analyses, IPT was associated with the best weight outcomes at 3-year follow-up as compared to HE only among girls with greater psychosocial problems, lending support to the relevance of social-anxiety models of LOC overeating. Specialized IPT programs should be tested to determine their effectiveness for obesity prevention among youth struggling with social-adjustment problems and/or anxiety who are also at high-risk for inappropriate weight gain.

Public health significance.

This study suggests that an adapted preventive group interpersonal psychotherapy prevents excess weight gain among adolescents with social-adjustment problems or high anxiety. Youth with lower social-adjustment problems and anxiety may benefit from other forms of obesity prevention approaches.

Acknowledgments

Research Support: NIDDK 1R01DK080906 (MTK), USUHS grant R072IC (MTK), NICHD Intramural Research Program ZIA-HD-00641 (JAY), and NIMH 1K24MH070446 (DEW).

Footnotes

1

When unadjusted BMI served as the outcome variable, findings remained consistent. Regardless of assignment, girls gained, on average, about 0.5 BMI units per year, which is consistent with the expected gain of adolescent females with a BMI at the 50th percentile (Kuczmarski et al., 2002).

2

Findings were consistent when unadjusted BMI was considered as the outcome variable.

3

All interactions for adolescent- and parent-reported anxiety remained significant when unadjusted BMI was considered as the independent variable.

Disclaimers: JAY and MK are Commissioned Officers in the U.S. Public Health Service. The opinions and assertions expressed herein are those of the authors and are not to be construed as reflecting the views of the PHS, the Department of the Navy, USU, or the U.S. Department of Defense.

References

  1. Achenbach TM, Elderbrock C. Manual for the Child Behavior Checklist and Revised Child Behavior Profile. University of Vermont, Department of Psychiatry; Burlington: 1991. [Google Scholar]
  2. Beck AT, Steer RA, Brown GK. Manual for the Beck Depression Inventory-II. San Antonio, TX: Psychological Corporation; 1996. [Google Scholar]
  3. Berkman ND, Brownley KA, Peat CM, Lohr KN, Cullen KE, Morgan LC, … Bulik CM. Management and Outcomes of Binge-Eating Disorder. Rockville (MD): 2015. [PubMed] [Google Scholar]
  4. Bravender T. Health, Education, and Youth in Durham: HEY-Durham Curricular Guide. 2. Durham, NC: Duke University; 2005. [Google Scholar]
  5. Briggs-Gowan MJ, Carter AS, Schwab-Stone M. Discrepancies among mother, child, and teacher reports: examining the contributions of maternal depression and anxiety. Journal of Abnormal Child Psychology. 1996;24(6):749–765. doi: 10.1007/BF01664738. [DOI] [PubMed] [Google Scholar]
  6. Fairburn CG, Cooper Z, editors. The Eating Disorder Examination. 12. New York: Guilford Press; 1993. [Google Scholar]
  7. Field AE, Austin SB, Taylor CB, Malspeis S, Rosner B, Rockett HR, … Colditz GA. Relation between dieting and weight change among preadolescents and adolescents. Pediatrics. 2003;112(4):900–906. doi: 10.1542/peds.112.4.900. [DOI] [PubMed] [Google Scholar]
  8. Field AE, Camargo CA, Jr, Ogino S. The merits of subtyping obesity: one size does not fit all. JAMA. 2013;310(20):2147–2148. doi: 10.1001/jama.2013.281501. 1765798 [pii] [DOI] [PubMed] [Google Scholar]
  9. Field AE, Cook NR, Gillman MW. Weight status in childhood as a predictor of becoming overweight or hypertensive in early adulthood. Obes Res. 2005;13(1):163–169. doi: 10.1038/oby.2005.21. 13/1/163 [pii] [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Gameroff MJ, Wickramaratne P, Weissman MM. Testing the Short and Screener versions of the Social Adjustment Scale-Self-report (SAS-SR) International Journal of Methods in Psychiatry Research. 2012;21(1):52–65. doi: 10.1002/mpr.358. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Glasofer DR, Tanofsky-Kraff M, Eddy KT, Yanovski SZ, Theim KR, Mirch MC, … Yanovski JA. Binge eating in overweight treatment-seeking adolescents. Journal of Pediatric Psychology. 2007;32(1):95–105. doi: 10.1093/jpepsy/jsl012. jsl012 [pii] [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Grills AE, Ollendick TH. Multiple informant agreement and the anxiety disorders interview schedule for parents and children. Journal of the American Academy of Child and Adolescent Psychiatry. 2003;42(1):30–40. doi: 10.1097/00004583-200301000-00008. [DOI] [PubMed] [Google Scholar]
  13. Gunlicks-Stoessel M, Mufson L, Jekal A, Turner JB. The impact of perceived interpersonal functioning on treatment for adolescent depression: IPT-A versus treatment as usual in school-based health clinics. Journal of Consulting and Clinical Psychology. 2010;78(2):260–267. doi: 10.1037/a0018935. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Hilbert A, Bishop ME, Stein RI, Tanofsky-Kraff M, Swenson AK, Welch RR, Wilfley DE. Long-term efficacy of psychological treatments for binge eating disorder. Br J Psychiatry. 2012;200(3):232–237. doi: 10.1192/bjp.bp.110.089664. bjp.bp.110.089664 [pii] [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Hunsley J, Mash EJ. Evidence-based assessment. Annu Rev Clin Psychol. 2007;3:29–51. doi: 10.1146/annurev.clinpsy.3.022806.091419. [DOI] [PubMed] [Google Scholar]
  16. Insel T, Cuthbert BN, Garvey MA, Heinssen RK, Pine DS, Quinn KJ, … Wang PS. Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. American Journal of Psychiatry. 2010;167(7):748–751. doi: 10.1176/appi.ajp.2010.09091379. [DOI] [PubMed] [Google Scholar]
  17. Jarcho JM, Tanofsky-Kraff M, Nelson EE, Engel SG, Vannucci A, Field SE, … Yanovski JA. Neural activation during anticipated peer evaluation and laboratory meal intake in overweight girls with and without loss of control eating. Neuroimage. 2015;108:343–353. doi: 10.1016/j.neuroimage.2014.12.054. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Kubzansky LD, Gilthorpe MS, Goodman E. A prospective study of psychological distress and weight status in adolescents/young adults. Annals of Behavior Medicine. 2012;43(2):219–228. doi: 10.1007/s12160-011-9323-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Kuczmarski RJ, Ogden CL, Guo SS, Grummer-Strawn LM, Flegal KM, Mei Z, … Johnson CL. 2000 CDC Growth Charts for the United States: methods and development. Vital Health Statistics. 2002;(246):1–190. [PubMed] [Google Scholar]
  20. Lim CS, Espil FM, Viana AG, Janicke DM. Associations Between Anxiety Symptoms and Child and Family Factors in Pediatric Obesity. Journal of Developmental Behavior in Pediatrics. 2015 doi: 10.1097/DBP.0000000000000225. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. MacLean PS, Wing RR, Davidson T, Epstein L, Goodpaster B, Hall KD, … Ryan D. NIH working group report: Innovative research to improve maintenance of weight loss. Obesity. 2015;23(1):7–15. doi: 10.1002/oby.20967. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Mufson L, Dorta KP, Wickramaratne P, Nomura Y, Olfson M, Weissman MM. A randomized effectiveness trial of interpersonal psychotherapy for depressed adolescents. Arch Gen Psychiatry. 2004;61(6):577–584. doi: 10.1001/archpsyc.61.6.577. [DOI] [PubMed] [Google Scholar]
  23. National Institute of Mental Health (NIMH) NIMH Strategic Plan. Bethesda, MD: 2008. [Google Scholar]
  24. Ogden CL, Carroll MD, Lawman HG, Fryar CD, Kruszon-Moran D, Kit BK, Flegal KM. Trends in Obesity Prevalence Among Children and Adolescents in the United States, 1988–1994 Through 2013–2014. JAMA. 2016;315(21):2292–2299. doi: 10.1001/jama.2016.6361. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Rude SS, Rehm LP. Response to treatments for depression: The role of intial status on targeted cognitive and behavioral skills. Clinical Psychology Review. 1991;11:493. [Google Scholar]
  26. Schafer JL, Graham JW. Missing data: our view of the state of the art. Psychol Methods. 2002;7(2):147–177. [PubMed] [Google Scholar]
  27. Sonneville KR, Horton NJ, Micali N, Crosby RD, Swanson SA, Solmi F, Field AE. Longitudinal associations between binge eating and overeating and adverse outcomes among adolescents and young adults: does loss of control matter? JAMA Pediatr. 2013a;167(2):149–155. doi: 10.1001/2013.jamapediatrics.12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Sonneville KR, Horton NJ, Micali N, Crosby RD, Swanson SA, Solmi F, Field AE. Longitudinal associations between binge eating and overeating and adverse outcomes among adolescents and young adults: does loss of control matter? JAMA Pediatrics. 2013b;167(2):149–155. doi: 10.1001/2013.jamapediatrics.12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Spielberger G, Lushene Vagg, Jacobs . Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologist Press; 1983. [Google Scholar]
  30. Stice E, Cameron RP, Killen JD, Hayward C, Taylor CB. Naturalistic weight-reduction efforts prospectively predict growth in relative weight and onset of obesity among female adolescents. Journal of Consulting and Clinical Psychology. 1999;67(6):967–974. doi: 10.1037//0022-006x.67.6.967. [DOI] [PubMed] [Google Scholar]
  31. Stunkard AJ, Allison KC. Binge eating disorder: disorder or marker? International Journal of Eating Disorders. 2003;34(Suppl):S107–116. doi: 10.1002/eat.10210. [DOI] [PubMed] [Google Scholar]
  32. Tanofsky-Kraff M, Cohen ML, Yanovski SZ, Cox C, Theim KR, Keil M, … Yanovski JA. A prospective study of psychological predictors of body fat gain among children at high risk for adult obesity. Pediatrics. 2006;117(4):1203–1209. doi: 10.1542/peds.2005-1329. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Tanofsky-Kraff M, Faden D, Yanovski SZ, Wilfley DE, Yanovski JA. The perceived onset of dieting and loss of control eating behaviors in overweight children. The International journal of eating disorders. 2005;38(2):112–122. doi: 10.1002/eat.20158. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Tanofsky-Kraff M, Shomaker LB, Olsen C, Roza CA, Wolkoff LE, Columbo KM, … Yanovski JA. A prospective study of pediatric loss of control eating and psychological outcomes. J Abnorm Psychol. 2011;120(1):108–118. doi: 10.1037/a0021406. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Tanofsky-Kraff M, Shomaker LB, Wilfley DE, Young JF, Sbrocco T, Stephens M, … Yanovski JA. Targeted prevention of excess weight gain and eating disorders in high-risk adolescent girls: a randomized controlled trial. American Journal of Clinical Nutrition. 2014;100(4):1010–1018. doi: 10.3945/ajcn.114.092536. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Tanofsky-Kraff M, Wilfley DE, Young JF, Mufson L, Yanovski SZ, Glasofer DR, Salaita CG. Preventing excessive weight gain in adolescents: interpersonal psychotherapy for binge eating. Obesity. 2007;15(6):1345–1355. doi: 10.1038/oby.2007.162. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Tanofsky-Kraff M, Wilfley DE, Young JF, Mufson L, Yanovski SZ, Glasofer DR, … Schvey NA. A pilot study of interpersonal psychotherapy for preventing excess weight gain in adolescent girls at-risk for obesity. Int J Eat Disord. 2010;43(8):701–706. doi: 10.1002/eat.20773. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Tanofsky-Kraff M, Yanovski SZ, Schvey NA, Olsen CH, Gustafson J, Yanovski JA. A prospective study of loss of control eating for body weight gain in children at high risk for adult obesity. Int J Eat Disord. 2009;42(1):26–30. doi: 10.1002/eat.20580. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Tanofsky-Kraff M, Yanovski SZ, Yanovski JA. Loss of control over eating in children and adolescents. In: Striegel-Moore R, Wonderlich SA, Walsh BT, Mitchell JE, editors. Developing an Evidence-Based Classification of Eating Disorders: Scientific Findings for DSM-5. American Psychiatric Association Press; 2011. pp. 221–236. [Google Scholar]
  40. Ulfvebrand S, Birgegard A, Norring C, Hogdahl L, von Hausswolff-Juhlin Y. Psychiatric comorbidity in women and men with eating disorders results from a large clinical database. Psychiatry Research. 2015 doi: 10.1016/j.psychres.2015.09.008. [DOI] [PubMed] [Google Scholar]
  41. Vannucci A, Field S, Crosby R, Theim K, Cohen L, Hannallah L, … Tanofsky-Kraff M. Examination of the Interpersonal Model of Loss of Control Eating in the Laboratory. Paper presented at the Annual International Conference on Eating Disorders.2014. [Google Scholar]
  42. Weissman MM, Bothwell S. Assessment of social adjustment by patient self-report. Archives of General Psychiatry. 1976;33(9):1111–1115. doi: 10.1001/archpsyc.1976.01770090101010. [DOI] [PubMed] [Google Scholar]
  43. Weissman MM, Markowitz J, Klerman GL. Comprehensive guide to Interpersonal psychotherapy. New York: Basic Behavioral Science Books; 2000. [Google Scholar]
  44. West BT, Galecki AT. An Overview of Current Software Procedures for Fitting Linear Mixed Models. Am Stat. 2012;65(4):274–282. doi: 10.1198/tas.2011.11077. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Wilfley DE, MacKenzie KR, Welch RR, Ayres VE, Weissman MM. Interpersonal Psychotherapy for Group. New York: Basic Books; 2000. [Google Scholar]
  46. Wilfley DE, Pike KM, Streigel-Moore RH. Toward an integrated model of risk for binge eating disorder. Journal of Gender, Culture, and Health. 1997;2:1–3. [Google Scholar]
  47. Wilfley DE, Stein RI, Saelens BE, Mockus DS, Matt GE, Hayden-Wade HA, … Epstein LH. Efficacy of maintenance treatment approaches for childhood overweight: a randomized controlled trial. JAMA. 2007;298(14):1661–1673. doi: 10.1001/jama.298.14.1661. [DOI] [PubMed] [Google Scholar]
  48. Wilfley DE, Tibbs TL, Van Buren DJ, Reach KP, Walker MS, Epstein LH. Lifestyle interventions in the treatment of childhood overweight: a meta-analytic review of randomized controlled trials. Health Psychol. 2007;26(5):521–532. doi: 10.1037/0278-6133.26.5.521. 2007-13009-002 [pii] [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Wilfley DE, Welch RR, Stein RI, Spurrell EB, Cohen LR, Saelens BE, … Matt GE. A randomized comparison of group cognitive-behavioral therapy and group interpersonal psychotherapy for the treatment of overweight individuals with binge-eating disorder. Arch Gen Psychiatry. 2002;59(8):713–721. doi: 10.1001/archpsyc.59.8.713. [DOI] [PubMed] [Google Scholar]
  50. Wilson GT. Treatment of binge eating disorder. Psychiatr Clin North Am. 2011;34(4):773–783. doi: 10.1016/j.psc.2011.08.011. S0193-953X(11)00088-8 [pii] [DOI] [PubMed] [Google Scholar]
  51. Wilson GT, Shafran R. Eating disorders guidelines from NICE. Lancet. 2005;365(9453):79–81. doi: 10.1016/S0140-6736(04)17669-1. [DOI] [PubMed] [Google Scholar]
  52. Wing RR, Jeffery RW. Benefits of recruiting participants with friends and increasing social support for weight loss and maintenance. J Consult Clin Psychol. 1999;67(1):132–138. doi: 10.1037//0022-006x.67.1.132. [DOI] [PubMed] [Google Scholar]
  53. Young JF, Gallop R, Mufson L. Mother-child conflict and its moderating effects on depression outcomes in a preventive intervention for adolescent depression. Journal of Clinical Child and Adolescent Psychology. 2009;38(5):696–704. doi: 10.1080/15374410903103577. [DOI] [PubMed] [Google Scholar]
  54. Young JF, Mufson L. Manual for Interpersonal Psychotherapy-Adolescent Skills Training (IPT-AST) 2003 [Google Scholar]
  55. Young JF, Mufson L, Davies M. Efficacy of Interpersonal Psychotherapy-Adolescent Skills Training: an indicated preventive intervention for depression. J Child Psychol Psychiatry. 2006a;47(12):1254–1262. doi: 10.1111/j.1469-7610.2006.01667.x. [DOI] [PubMed] [Google Scholar]
  56. Young JF, Mufson L, Davies M. Impact of comorbid anxiety in an effectiveness study of interpersonal psychotherapy for depressed adolescents. Journal of the American Academy of Child and Adolescent Psychiatry. 2006b;45(8):904–912. doi: 10.1097/01.chi.0000222791.23927.5f. [DOI] [PubMed] [Google Scholar]

RESOURCES