Eating Behaviors 15 (2014) 241–243
Contents lists available at ScienceDirect
Eating Behaviors
Binge eating frequency and regular eating adherence: The role of eating pattern in cognitive behavioral guided self-help Elaina A. Zendegui ⁎, Julia A. West, Laurie J. Zandberg Rutgers, The State University of New Jersey, Graduate School of Applied and Professional Psychology, 41 Gordon Road, Suite C, Piscataway, NJ 08854, USA
a r t i c l e
i n f o
Article history: Received 31 August 2013 Received in revised form 24 December 2013 Accepted 4 March 2014 Available online 14 March 2014 Keywords: CBT Binge eating Guided self-help Regular eating Eating disorders
a b s t r a c t Cognitive behavioral guided self-help (CBTgsh) is an evidence-based, brief, and cost-effective treatment for eating disorders characterized by recurrent binge eating. However, more research is needed to improve patient outcomes and clarify treatment components most associated with symptom change. A main component of CBTgsh is establishing a regular pattern of eating to disrupt dietary restriction, which prior research has implicated in the maintenance of binge eating. The present study used session-by-session assessments of regular eating adherence and weekly binge totals to examine the association between binge frequency and regular eating in a sample of participants (n = 38) receiving 10 sessions of CBTgsh for recurrent binge eating. Analyses were conducted using Hierarchical Linear Modeling (HLM) to allow for data nesting, and a likelihood ratio test determined which out of three regression models best fit the data. Results demonstrated that higher regular eating adherence (3 meals and 2–3 planned snacks daily) was associated with lower weekly binge frequency in this sample, and both the magnitude and direction of the association were maintained after accounting for individual participant differences in binge and adherent day totals. Findings provide additional empirical support for the cognitive behavioral model informing CBTgsh. Possible clinical implications for treatment emphasis and sequencing in CBTgsh are discussed. © 2014 Elsevier Ltd. All rights reserved.
1. Introduction Cognitive behavioral guided self-help (CBTgsh) is a brief and costeffective evidence-based treatment for eating disorders characterized by recurrent binge eating (Lynch et al., 2010). Controlled outcome research has found CBTgsh consistently superior to waitlist control conditions (Sysko & Walsh, 2008; Wilson & Zandberg, 2012) and frequently comparable to longer-term therapies for eating disorders, including interpersonal psychotherapy for binge eating disorder (BED; Wilson, Wilfley, Agras, & Bryson, 2010) and family therapy for adolescents with bulimia nervosa (BN; Schmidt et al., 2007). Abstinence rates from binge eating following CBTgsh range from 28 to 58% in the treatment of BED and 11 to 44% in the treatment of BN. Although these outcomes are promising, a considerable subset of patients remains symptomatic following treatment. In addition, the self-help guides employed across CBTgsh studies vary both in the content and sequencing of interventions presented. To improve patient outcomes, research investigating putative mechanisms of change is necessary to clarify treatment components associated with symptom change. The proposed mechanisms of change in CBTgsh are grounded in the original cognitive behavioral conceptualization of bulimia nervosa ⁎ Corresponding author. Tel.: +1 646 370 0456. E-mail addresses: [email protected] (E.A. Zendegui), [email protected] (J.A. West), [email protected] (L.J. Zandberg).
http://dx.doi.org/10.1016/j.eatbeh.2014.03.002 1471-0153/© 2014 Elsevier Ltd. All rights reserved.
(Fairburn, Marcus, & Wilson, 1993) and have since been extended transdiagnostically to other eating disorder classifications (Fairburn, 2008). In this model, dietary restriction (i.e., limiting caloric intake) is hypothesized to drive physical and psychological vulnerability to binge eating episodes (Wilson, 1993; Wilson, Fairburn, Agras, Walsh, & Kraemer, 2002). Several studies have supported the link between alternating periods of caloric restriction and binge eating among women with BN, including a laboratory study demonstrating increased caloric intake after a six-hour vs. a one-hour food deprivation period (Telch & Agras, 1996) and a retrospective analysis of self-monitored food intake (Rosen, Leitenberg, Fisher, & Khazam, 1986). Implementation of a regular pattern of eating, defined as 3 meals and 2–3 planned snacks per day, explicitly disrupts dietary restriction in order to increase control over binge episodes. As such, it is considered a central and early component of cognitive behavioral treatment. For instance, in the CBTgsh companion book Overcoming Binge Eating (Fairburn, 1995), regular eating represents the second task introduced to participants and is referred to as “probably the single most potent element in this program” (p. 157). Despite the hypothesized contribution of regular eating to binge abstinence, there is limited research examining the association between regular eating adherence and binge eating in the treatment of eating disorders, and none pertaining to non-BN samples. Shah, Passi, Bryson, and Agras (2005) used signal detection analysis to determine whether an optimal number of meals and snacks consumed over a preceding 28 days was related to greater binge eating abstinence rates in 158
242
E.A. Zendegui et al. / Eating Behaviors 15 (2014) 241–243
individuals receiving full-protocol CBT or IPT for BN. Shah and colleagues found that participants who consumed 80 meals combined with at least 21 afternoon snacks within the preceding month (i.e., the pattern most closely approximating 3 meals and 1 afternoon snack per day) demonstrated the highest rates of binge abstinence (70%). However, the reliability of this finding was limited by retrospective patient report of meal timing and frequency over the past month at a single assessment time point. Additional research is required to replicate Shah and colleague's results with repeated measures throughout the course of treatment and to assess the impact of regular eating adherence in transdiagnostic (i.e., BED, EDNOS, and BN) samples. The present investigation aims to evaluate the relationship between regular eating adherence and binge frequency using session-by-session data across CBTgsh. Participants comprised heterogeneous eating disorders characterized by recurrent binge eating. Consistent with the underlying theoretical model, we hypothesized that participants reporting a greater number of regular eating adherent days would demonstrate fewer binge eating episodes in a given treatment week, and that this relationship would be maintained when accounting for individual effects. 2. Methods 2.1. Study overview Details regarding this clinical trial have been reported previously (Zandberg & Wilson, 2012). Briefly, the study evaluated CBTgsh in an open clinical trial utilizing the train-the-trainer implementation strategy. Participants (n = 38) were treatment-seeking students presenting at a university counseling center with recurrent binge eating (i.e., a minimum average of one binge episode per week over the preceding month). Exclusion criteria were minimized to promote external validity and included BMI less than 19 or greater than 40, severe current substance abuse, and significant suicide risk. CBTgsh was provided using the Fairburn (1995) text and graduate student therapists. Treatment retention was high (76.3%) and clinical outcomes were found to be comparable to randomized controlled trials of CBTgsh. Participants showed statistically significant reductions in specific eating disorder psychopathology, negative affect, and functional impairment that were maintained at one-month follow-up. At post-treatment and follow-up, 42.1 and 47.4%, respectively, obtained abstinence from binge eating over the preceding 28 days. 2.2. Participants Data was collected from 38 participants (92.1% female; 63.2% Caucasian; mean age = 21, SD = 3.00) preceding each therapy session. At pre-treatment, participants reported a mean binge frequency of 21.26 (SD = 15.81) over the preceding 28 days. Participant eating disorder diagnoses were made according to the DSM-IV-TR and were 52.6% BN, 31.6% BED, and 15.8% ED-NOS (i.e., fewer than two binge episodes per week).
2.3. Treatment Eligible participants received 10 sessions of CBTgsh using the text Overcoming Binge Eating (Fairburn, 1995). CBTgsh is a step-wise treatment in which the therapist determines treatment pace and helps the client troubleshoot problems as s/he adheres to the self-help program. The six treatment steps include: self-monitoring, regular eating, alternatives to binge eating, problem solving, addressing dieting and food avoidance, and relapse prevention. The present study also employed a supplemental module addressing body checking and avoidance behaviors.
2.4. Measures Participants completed a weekly Treatment Process Questionnaire (TPQ) recording the number of consumed meals and snacks, as well as the number of binge episodes, over each day in the preceding week. The TPQ was completed prior to sessions two through 10 of treatment and patients were encouraged to utilize their daily self-monitoring records to enhance recall. A dichotomous variable was created to indicate days on which a participant was “adherent to regular eating” (i.e., consuming three meals and two or three snacks). Each participant had a weekly total of binge episodes and a weekly total of regular eating adherent days for nine treatment sessions. 2.5. Statistical analyses Hierarchical Linear Modeling was used to examine the relationship between patient adherence to a regular pattern of eating and binge frequency during the same treatment week while accounting for the effects of participants. Hierarchical Linear Modeling is a variation of linear regression that allows within participant and between subjects data to be analyzed simultaneously, and it allows data to be nested at multiple levels. Analyses were conducted using SPSS Statistics 21.0 (IBM Corp., 2012) and restricted maximum likelihood computations. Three linear models were used to determine the model that best fit the data using a likelihood ratio test. The first model1 examined the relationship between regular eating adherence and weekly binge frequency, without accounting for the hierarchical structure of the data. The second2 and third3 models accounted for the hierarchical nature of the data by accounting for participants, where regular eating adherence (Level 1) was nested within participants (Level 2). The second model allowed intercepts but not slopes to vary, and the third model allowed both slopes and intercepts to vary. 3. Results The first model used linear modeling to examine the relationship between regular eating adherence and weekly binge frequency, without accounting for the effects of participants, F(1, 291) = 11.64, p b .01, b = − .32. This model indicated that a higher number of regular eating adherent days per week was significantly associated with lower weekly binge frequency (See Table 1). The second model accounted for the hierarchical nature of the data, such that regular eating adherence was nested within individuals, intercepts were allowed to vary, and slopes were fixed. Analyses indicated that the relationship between regular eating adherence and binge eating frequency showed significant variance in intercepts across participants, var(μ0j) = 8.75, χ2(1) = 93.87, p b .01. Therefore, allowing intercepts to vary significantly improved the model, and intercepts for the relationship between regular eating adherence and binge eating frequency vary significantly across individuals. Using this model, regular eating adherence was significantly associated with weekly binge frequency, F(1, 284.59) = 51.20, p b .001, such that those with higher adherence to regular eating had lower binge frequency, b = −.62. In the third model, regular eating adherence was nested within individuals, and both slopes and intercepts were allowed to vary. The model fit did not significantly improve when both slopes and intercepts 1 2
Bingesi = b0 + b1RegularEatingi + εi. Bingesij = b0j + b1RegularEatingij + b2Bingesij + εij
b0 j ¼ b0 þ u0 j : 3
Bingesij = b0j + b1RegularEatingij + εij
b0 j ¼ b0 þ u 0 j b1 j ¼ b1 þ u 1 j :
E.A. Zendegui et al. / Eating Behaviors 15 (2014) 241–243 Table 1 Hierarchical linear models estimating the relationship between regular eating and weekly binge frequency. Model
−2LL
b
SE b
F
df
p
Nonhierarchical data (Model 1) Fixed slopes, random intercepts (Model 2) Random slopes, random intercepts (Model 3)
1599.21 1505.34
−.32 −.62
.09 .09
11.64 51.20
1,291 284.59
b.01 b.001
1503.53
−.61
.10
35.12
24.11
b.001
were allowed to vary, as shown by the non-significant Chi square, var(μ1j) = .09, χ2(1) = 1.80, p N .05. Therefore, results did not suggest significant variability in regression slopes of individual participants. This model indicated that a higher number of regular eating adherent days per week were significantly associated with lower weekly binge frequency, F(1, 24.11) = 35.12, p b .001, b = −.62.
4. Discussion This study examined the relationship between weekly regular eating adherence and binge frequency using session-by-session data. Results demonstrated that higher adherence to regular eating was associated with lower weekly binge frequency for individuals with recurrent binge eating undergoing CBTgsh. Both the direction and the slope of the relationship between regular eating adherence and binge frequency were maintained across participants. These results support the hypothesis that a higher number of regular eating adherent days during CBTgsh treatment is associated with lower weekly binge frequency. While cognitive behavioral therapies for eating disorders emphasize the importance of disrupting dietary restriction by establishing a pattern of regular eating, this is the first study to demonstrate an association between the prescribed pattern of regular eating (three meals and two-to-three planned snacks) and lower binge frequency within successive, defined time periods. Taken together with previous studies (Rosen et al., 1986; Shah et al., 2005; Telch & Agras, 1996), the current findings provide additional empirical support for the cognitive behavioral model of eating disorders that informs CBTgsh, which emphasizes the role of dietary restriction in the maintenance of recurrent binge eating across diagnostic groups. Based on the present results, it is possible that the emphasis on regular eating at the beginning of CBT treatment may contribute to documented instances of early response. Wilson et al. (2002) found that in a study of full-protocol CBT, reductions in self-reported attempts to restrict dietary intake by the fourth treatment week mediated decreases in binge and purge frequency. The findings in this study in conjunction with the 2002 work of Wilson et al. support the use of the regular eating intervention early in eating disorder treatment and can help guide therapists implementing the treatment. Therapists providing CBTgsh could use the current findings in several ways. Clinicians may incorporate the present results into the psycho-education used to introduce regular eating; such information may help motivate clients and generate hope that eating regularly will be associated with reduced binge frequency. Therapists may also benefit by making regular eating a priority throughout treatment, continuously troubleshooting non-compliance and addressing lapses in adherence. Moreover, for those clients who present with low adherence to regular eating early in treatment, therapists may incorporate an increased emphasis on regular eating and utilize motivational enhancement strategies to promote greater compliance. Several study limitations are noteworthy. The present analyses did not account for time, which in future research could elucidate whether improvements in regular eating adherence predict subsequent reductions in binge eating, and thereby rule out the possibility of reverse
243
causation. In addition, the current study did not account for adherence to other steps in the treatment that may also contribute to a reduction in binge frequency. Given this, future research may seek to establish the relative contribution of various treatment steps to binge eating. Answering these questions would help validate other components of the theoretical model underlying CBT treatment for eating disorders and could inform decisions about whether the treatment can be made more efficient, and thus more amenable to dissemination (Wilson & Zandberg, 2012). Finally, the present study was an open clinical trial and therefore it cannot be ruled out that factors outside of the treatment were responsible for the relationship between regular eating and binge frequency. Replications from randomized control trials are recommended to augment the current findings. Role of funding sources No funding was provided for this study. Contributors Julia West and Elaina Zendegui designed the study, conducted the statistical analyses, and drafted the manuscript. Laurie Zandberg collected and managed the data and provided feedback and revisions for several drafts of the manuscript. All authors contributed to and approved the final manuscript. Conflict of interest All authors declare that they have no conflicts of interest. Acknowledgments The authors wish to thank Eun-Young Mun, Ph.D. and Laura Skriner, M.S., for their helpful comments and invaluable assistance regarding the statistical plan and analyses for the present manuscript. Additionally, the authors thank G. Terence Wilson, Ph. D., for his mentorship and support throughout both the implementation of the trial and the preparation of the current manuscript.
References Fairburn, C. G. (1995). Overcoming binge eating. New York: The Guilford Press. Fairburn, C. G. (2008). Cognitive behavior therapy and eating disorders. New York: The Guilford Press. Fairburn, C. G., Marcus, M. D., & Wilson, G. T. (1993). Cognitive–behavioral therapy for binge eating and bulimia nervosa: A comprehensive treatment manual. In C. Fairburn, & G. T. Wilson (Eds.), Binge eating: Nature, assessment, and treatment (pp. 361–404). New York: The Guilford Press. I.B.M. Corp (2012). IBM SPSS Statistics for Windows (Version 21.0) [Computer software]. Armonk, NY: IBM Corp. Lynch, F. L., Dickerson, J., Perrin, N., DeBar, L., Wilson, G. T., Kraemer, H., et al. (2010). Cost-effectiveness of treatment for recurrent binge eating. Journal of Consulting and Clinical Psychology, 78, 322–333. Rosen, J. C., Leitenberg, H., Fisher, C., & Khazam, C. (1986). Binge eating episodes in bulimia nervosa: The amount and type of food consumed. International Journal of Eating Disorders, 5, 255–267. Schmidt, U., Lee, S., Beecham, J., Perkins, S., Treasure, J., Yi, I., et al. (2007). A randomized controlled trial of family therapy and cognitive–behavioral guided self-care for adolescents with bulimia nervosa or related disorders. The American Journal of Psychiatry, 164, 591–598. Shah, N., Passi, V., Bryson, S., & Agras, W. S. (2005). Patterns of eating and abstinence in women treated for bulimia nervosa. International Journal of Eating Disorders, 38, 330–334. Sysko, R., & Walsh, B. T. (2008). A critical evaluation of the efficacy of self-help interventions for the treatment of bulimia nervosa and binge-eating disorder. International Journal of Eating Disorders, 41, 97–112. Telch, C. F., & Agras, W. S. (1996). The effects of short-term food deprivation on caloric intake in eating-disordered subjects. Appetite, 26, 221–233. Wilson, G. T. (1993). Relation of dieting and voluntary weight loss to psychological functioning and binge eating. Annals of Internal Medicine, 119, 727–730. Wilson, G. T., Fairburn, C. G., Agras, W. S., Walsh, B. T., & Kraemer, H. (2002). Cognitive– behavioral therapy for bulimia nervosa: Time course and mechanisms of change. Journal of Consulting and Clinical Psychology, 70, 267–274. Wilson, G. T., Wilfley, D. E., Agras, W. S., & Bryson, S. W. (2010). Psychological treatments for binge eating disorder. Archives of General Psychiatry, 67, 94–101. Wilson, G. T., & Zandberg, L. J. (2012). Cognitive–behavioral guided self-help for eating disorders: Effectiveness and scalability. Clinical Psychology Review, 32, 343–357. Zandberg, L. J., & Wilson, G. T. (2012). Train-the-trainer: Implementation of cognitive behavioural guided self-help for recurrent binge eating in a naturalistic setting. European Eating Disorders Review, 21, 230–237.
Contents lists available at ScienceDirect
Eating Behaviors
Binge eating frequency and regular eating adherence: The role of eating pattern in cognitive behavioral guided self-help Elaina A. Zendegui ⁎, Julia A. West, Laurie J. Zandberg Rutgers, The State University of New Jersey, Graduate School of Applied and Professional Psychology, 41 Gordon Road, Suite C, Piscataway, NJ 08854, USA
a r t i c l e
i n f o
Article history: Received 31 August 2013 Received in revised form 24 December 2013 Accepted 4 March 2014 Available online 14 March 2014 Keywords: CBT Binge eating Guided self-help Regular eating Eating disorders
a b s t r a c t Cognitive behavioral guided self-help (CBTgsh) is an evidence-based, brief, and cost-effective treatment for eating disorders characterized by recurrent binge eating. However, more research is needed to improve patient outcomes and clarify treatment components most associated with symptom change. A main component of CBTgsh is establishing a regular pattern of eating to disrupt dietary restriction, which prior research has implicated in the maintenance of binge eating. The present study used session-by-session assessments of regular eating adherence and weekly binge totals to examine the association between binge frequency and regular eating in a sample of participants (n = 38) receiving 10 sessions of CBTgsh for recurrent binge eating. Analyses were conducted using Hierarchical Linear Modeling (HLM) to allow for data nesting, and a likelihood ratio test determined which out of three regression models best fit the data. Results demonstrated that higher regular eating adherence (3 meals and 2–3 planned snacks daily) was associated with lower weekly binge frequency in this sample, and both the magnitude and direction of the association were maintained after accounting for individual participant differences in binge and adherent day totals. Findings provide additional empirical support for the cognitive behavioral model informing CBTgsh. Possible clinical implications for treatment emphasis and sequencing in CBTgsh are discussed. © 2014 Elsevier Ltd. All rights reserved.
1. Introduction Cognitive behavioral guided self-help (CBTgsh) is a brief and costeffective evidence-based treatment for eating disorders characterized by recurrent binge eating (Lynch et al., 2010). Controlled outcome research has found CBTgsh consistently superior to waitlist control conditions (Sysko & Walsh, 2008; Wilson & Zandberg, 2012) and frequently comparable to longer-term therapies for eating disorders, including interpersonal psychotherapy for binge eating disorder (BED; Wilson, Wilfley, Agras, & Bryson, 2010) and family therapy for adolescents with bulimia nervosa (BN; Schmidt et al., 2007). Abstinence rates from binge eating following CBTgsh range from 28 to 58% in the treatment of BED and 11 to 44% in the treatment of BN. Although these outcomes are promising, a considerable subset of patients remains symptomatic following treatment. In addition, the self-help guides employed across CBTgsh studies vary both in the content and sequencing of interventions presented. To improve patient outcomes, research investigating putative mechanisms of change is necessary to clarify treatment components associated with symptom change. The proposed mechanisms of change in CBTgsh are grounded in the original cognitive behavioral conceptualization of bulimia nervosa ⁎ Corresponding author. Tel.: +1 646 370 0456. E-mail addresses: [email protected] (E.A. Zendegui), [email protected] (J.A. West), [email protected] (L.J. Zandberg).
http://dx.doi.org/10.1016/j.eatbeh.2014.03.002 1471-0153/© 2014 Elsevier Ltd. All rights reserved.
(Fairburn, Marcus, & Wilson, 1993) and have since been extended transdiagnostically to other eating disorder classifications (Fairburn, 2008). In this model, dietary restriction (i.e., limiting caloric intake) is hypothesized to drive physical and psychological vulnerability to binge eating episodes (Wilson, 1993; Wilson, Fairburn, Agras, Walsh, & Kraemer, 2002). Several studies have supported the link between alternating periods of caloric restriction and binge eating among women with BN, including a laboratory study demonstrating increased caloric intake after a six-hour vs. a one-hour food deprivation period (Telch & Agras, 1996) and a retrospective analysis of self-monitored food intake (Rosen, Leitenberg, Fisher, & Khazam, 1986). Implementation of a regular pattern of eating, defined as 3 meals and 2–3 planned snacks per day, explicitly disrupts dietary restriction in order to increase control over binge episodes. As such, it is considered a central and early component of cognitive behavioral treatment. For instance, in the CBTgsh companion book Overcoming Binge Eating (Fairburn, 1995), regular eating represents the second task introduced to participants and is referred to as “probably the single most potent element in this program” (p. 157). Despite the hypothesized contribution of regular eating to binge abstinence, there is limited research examining the association between regular eating adherence and binge eating in the treatment of eating disorders, and none pertaining to non-BN samples. Shah, Passi, Bryson, and Agras (2005) used signal detection analysis to determine whether an optimal number of meals and snacks consumed over a preceding 28 days was related to greater binge eating abstinence rates in 158
242
E.A. Zendegui et al. / Eating Behaviors 15 (2014) 241–243
individuals receiving full-protocol CBT or IPT for BN. Shah and colleagues found that participants who consumed 80 meals combined with at least 21 afternoon snacks within the preceding month (i.e., the pattern most closely approximating 3 meals and 1 afternoon snack per day) demonstrated the highest rates of binge abstinence (70%). However, the reliability of this finding was limited by retrospective patient report of meal timing and frequency over the past month at a single assessment time point. Additional research is required to replicate Shah and colleague's results with repeated measures throughout the course of treatment and to assess the impact of regular eating adherence in transdiagnostic (i.e., BED, EDNOS, and BN) samples. The present investigation aims to evaluate the relationship between regular eating adherence and binge frequency using session-by-session data across CBTgsh. Participants comprised heterogeneous eating disorders characterized by recurrent binge eating. Consistent with the underlying theoretical model, we hypothesized that participants reporting a greater number of regular eating adherent days would demonstrate fewer binge eating episodes in a given treatment week, and that this relationship would be maintained when accounting for individual effects. 2. Methods 2.1. Study overview Details regarding this clinical trial have been reported previously (Zandberg & Wilson, 2012). Briefly, the study evaluated CBTgsh in an open clinical trial utilizing the train-the-trainer implementation strategy. Participants (n = 38) were treatment-seeking students presenting at a university counseling center with recurrent binge eating (i.e., a minimum average of one binge episode per week over the preceding month). Exclusion criteria were minimized to promote external validity and included BMI less than 19 or greater than 40, severe current substance abuse, and significant suicide risk. CBTgsh was provided using the Fairburn (1995) text and graduate student therapists. Treatment retention was high (76.3%) and clinical outcomes were found to be comparable to randomized controlled trials of CBTgsh. Participants showed statistically significant reductions in specific eating disorder psychopathology, negative affect, and functional impairment that were maintained at one-month follow-up. At post-treatment and follow-up, 42.1 and 47.4%, respectively, obtained abstinence from binge eating over the preceding 28 days. 2.2. Participants Data was collected from 38 participants (92.1% female; 63.2% Caucasian; mean age = 21, SD = 3.00) preceding each therapy session. At pre-treatment, participants reported a mean binge frequency of 21.26 (SD = 15.81) over the preceding 28 days. Participant eating disorder diagnoses were made according to the DSM-IV-TR and were 52.6% BN, 31.6% BED, and 15.8% ED-NOS (i.e., fewer than two binge episodes per week).
2.3. Treatment Eligible participants received 10 sessions of CBTgsh using the text Overcoming Binge Eating (Fairburn, 1995). CBTgsh is a step-wise treatment in which the therapist determines treatment pace and helps the client troubleshoot problems as s/he adheres to the self-help program. The six treatment steps include: self-monitoring, regular eating, alternatives to binge eating, problem solving, addressing dieting and food avoidance, and relapse prevention. The present study also employed a supplemental module addressing body checking and avoidance behaviors.
2.4. Measures Participants completed a weekly Treatment Process Questionnaire (TPQ) recording the number of consumed meals and snacks, as well as the number of binge episodes, over each day in the preceding week. The TPQ was completed prior to sessions two through 10 of treatment and patients were encouraged to utilize their daily self-monitoring records to enhance recall. A dichotomous variable was created to indicate days on which a participant was “adherent to regular eating” (i.e., consuming three meals and two or three snacks). Each participant had a weekly total of binge episodes and a weekly total of regular eating adherent days for nine treatment sessions. 2.5. Statistical analyses Hierarchical Linear Modeling was used to examine the relationship between patient adherence to a regular pattern of eating and binge frequency during the same treatment week while accounting for the effects of participants. Hierarchical Linear Modeling is a variation of linear regression that allows within participant and between subjects data to be analyzed simultaneously, and it allows data to be nested at multiple levels. Analyses were conducted using SPSS Statistics 21.0 (IBM Corp., 2012) and restricted maximum likelihood computations. Three linear models were used to determine the model that best fit the data using a likelihood ratio test. The first model1 examined the relationship between regular eating adherence and weekly binge frequency, without accounting for the hierarchical structure of the data. The second2 and third3 models accounted for the hierarchical nature of the data by accounting for participants, where regular eating adherence (Level 1) was nested within participants (Level 2). The second model allowed intercepts but not slopes to vary, and the third model allowed both slopes and intercepts to vary. 3. Results The first model used linear modeling to examine the relationship between regular eating adherence and weekly binge frequency, without accounting for the effects of participants, F(1, 291) = 11.64, p b .01, b = − .32. This model indicated that a higher number of regular eating adherent days per week was significantly associated with lower weekly binge frequency (See Table 1). The second model accounted for the hierarchical nature of the data, such that regular eating adherence was nested within individuals, intercepts were allowed to vary, and slopes were fixed. Analyses indicated that the relationship between regular eating adherence and binge eating frequency showed significant variance in intercepts across participants, var(μ0j) = 8.75, χ2(1) = 93.87, p b .01. Therefore, allowing intercepts to vary significantly improved the model, and intercepts for the relationship between regular eating adherence and binge eating frequency vary significantly across individuals. Using this model, regular eating adherence was significantly associated with weekly binge frequency, F(1, 284.59) = 51.20, p b .001, such that those with higher adherence to regular eating had lower binge frequency, b = −.62. In the third model, regular eating adherence was nested within individuals, and both slopes and intercepts were allowed to vary. The model fit did not significantly improve when both slopes and intercepts 1 2
Bingesi = b0 + b1RegularEatingi + εi. Bingesij = b0j + b1RegularEatingij + b2Bingesij + εij
b0 j ¼ b0 þ u0 j : 3
Bingesij = b0j + b1RegularEatingij + εij
b0 j ¼ b0 þ u 0 j b1 j ¼ b1 þ u 1 j :
E.A. Zendegui et al. / Eating Behaviors 15 (2014) 241–243 Table 1 Hierarchical linear models estimating the relationship between regular eating and weekly binge frequency. Model
−2LL
b
SE b
F
df
p
Nonhierarchical data (Model 1) Fixed slopes, random intercepts (Model 2) Random slopes, random intercepts (Model 3)
1599.21 1505.34
−.32 −.62
.09 .09
11.64 51.20
1,291 284.59
b.01 b.001
1503.53
−.61
.10
35.12
24.11
b.001
were allowed to vary, as shown by the non-significant Chi square, var(μ1j) = .09, χ2(1) = 1.80, p N .05. Therefore, results did not suggest significant variability in regression slopes of individual participants. This model indicated that a higher number of regular eating adherent days per week were significantly associated with lower weekly binge frequency, F(1, 24.11) = 35.12, p b .001, b = −.62.
4. Discussion This study examined the relationship between weekly regular eating adherence and binge frequency using session-by-session data. Results demonstrated that higher adherence to regular eating was associated with lower weekly binge frequency for individuals with recurrent binge eating undergoing CBTgsh. Both the direction and the slope of the relationship between regular eating adherence and binge frequency were maintained across participants. These results support the hypothesis that a higher number of regular eating adherent days during CBTgsh treatment is associated with lower weekly binge frequency. While cognitive behavioral therapies for eating disorders emphasize the importance of disrupting dietary restriction by establishing a pattern of regular eating, this is the first study to demonstrate an association between the prescribed pattern of regular eating (three meals and two-to-three planned snacks) and lower binge frequency within successive, defined time periods. Taken together with previous studies (Rosen et al., 1986; Shah et al., 2005; Telch & Agras, 1996), the current findings provide additional empirical support for the cognitive behavioral model of eating disorders that informs CBTgsh, which emphasizes the role of dietary restriction in the maintenance of recurrent binge eating across diagnostic groups. Based on the present results, it is possible that the emphasis on regular eating at the beginning of CBT treatment may contribute to documented instances of early response. Wilson et al. (2002) found that in a study of full-protocol CBT, reductions in self-reported attempts to restrict dietary intake by the fourth treatment week mediated decreases in binge and purge frequency. The findings in this study in conjunction with the 2002 work of Wilson et al. support the use of the regular eating intervention early in eating disorder treatment and can help guide therapists implementing the treatment. Therapists providing CBTgsh could use the current findings in several ways. Clinicians may incorporate the present results into the psycho-education used to introduce regular eating; such information may help motivate clients and generate hope that eating regularly will be associated with reduced binge frequency. Therapists may also benefit by making regular eating a priority throughout treatment, continuously troubleshooting non-compliance and addressing lapses in adherence. Moreover, for those clients who present with low adherence to regular eating early in treatment, therapists may incorporate an increased emphasis on regular eating and utilize motivational enhancement strategies to promote greater compliance. Several study limitations are noteworthy. The present analyses did not account for time, which in future research could elucidate whether improvements in regular eating adherence predict subsequent reductions in binge eating, and thereby rule out the possibility of reverse
243
causation. In addition, the current study did not account for adherence to other steps in the treatment that may also contribute to a reduction in binge frequency. Given this, future research may seek to establish the relative contribution of various treatment steps to binge eating. Answering these questions would help validate other components of the theoretical model underlying CBT treatment for eating disorders and could inform decisions about whether the treatment can be made more efficient, and thus more amenable to dissemination (Wilson & Zandberg, 2012). Finally, the present study was an open clinical trial and therefore it cannot be ruled out that factors outside of the treatment were responsible for the relationship between regular eating and binge frequency. Replications from randomized control trials are recommended to augment the current findings. Role of funding sources No funding was provided for this study. Contributors Julia West and Elaina Zendegui designed the study, conducted the statistical analyses, and drafted the manuscript. Laurie Zandberg collected and managed the data and provided feedback and revisions for several drafts of the manuscript. All authors contributed to and approved the final manuscript. Conflict of interest All authors declare that they have no conflicts of interest. Acknowledgments The authors wish to thank Eun-Young Mun, Ph.D. and Laura Skriner, M.S., for their helpful comments and invaluable assistance regarding the statistical plan and analyses for the present manuscript. Additionally, the authors thank G. Terence Wilson, Ph. D., for his mentorship and support throughout both the implementation of the trial and the preparation of the current manuscript.
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