Participants and procedures
The current study was a post-hoc analysis of data collected during a pilot randomized controlled trial (PI: [blinded for review]) evaluating the feasibility, acceptability, and efficacy of a novel acceptance-based behavioral treatment (ABBT) compared to CBT for BN [16]. The sample included 42 adults with a DSM-5 Diagnosis of BN spectrum disorders, i.e., full threshold BN or subthreshold BN [17].
Participants were recruited from the community and completed a phone screen with a trained screener to determine initial eligibility. Eligible participants were randomized to receive 20 sessions of manualized ABBT (N =24) or CBT (N = 18) for BN. In both treatment conditions, sessions occurred over a five-month period in three phases: eight twice-weekly sessions, seven weekly sessions, and five biweekly sessions. Treatment was delivered by Master’s- or Doctoral-level clinicians receiving weekly supervision from a licensed clinical psychologist. All participants provided informed consent and the study was approved by the [blinded for review] Institutional Review Board.
Because the current study utilized weekly session questionnaire data, we removed participants (N =7) who dropped out before Session 10. Therefore, the final sample included 35 participants (MeanAge = 30.34, MeanBMI = 25.7, 94.30% female, 71.4% White). Initial analyses were run to include treatment condition as a predictor and produced similar results for the study aims across treatment conditions. Accordingly, we collapsed the data across treatment conditions to increase the sample size and to generate more reliable estimates for the study aims.
Measures
Weekly BN symptoms. In weekly pre-session surveys, participants reported the frequency of binge eating (i.e., any eating episode where loss of control was experienced, regardless of the amount of food consumed), purging episodes (i.e., total number of vomiting, laxative, and diuretics misuse episodes), days of restrictive eating (i.e., restricting or dieting to control weight), and days of compulsive exercise in the past week (i.e., exercising hard to control weight). Participants were prompted to provide the frequencies with the statement: “Over the past week, how many times have you …” (e.g., binged (felt out of control of your eating, and eaten far more than a person normally would at one go)).
Satisfaction with Life. Before each session, participants rated the statement, “In terms of my overall satisfaction with my life, I am...” on a Likert scale from 0 (not at all satisfied) to 7 (perfectly satisfied).
Subjective Wellbeing. Before each session, participants rated the statement, “Overall, I would rate my general sense of well-being over the past week as...” on a Likert scale from 1 (very poor) to 7 (very good).
Statistical Analyses
For aims 1 and 2, we employed linear mixed effects modeling to analyze change in SWB, SWL, and BN symptoms over time [18]. The SWB, SWL, and BN symptoms ratings were lagged. For aim 1, separate models were conducted that simultaneously included time-lagged main effects modeled as fixed effects for each of the predictors, including each BN symptom (i.e., frequency of binge eating and purging and days of restrictive eating and compulsive exercise) and the outcomes (i.e., SWB and SWL). SWB and SWL ratings in the previous week, BN symptoms in the following week, and treatment conditions were entered as covariates. For aim 2, separate models were conducted that simultaneously included time-lagged main effects modeled as fixed effects for each predictor (i.e., SWB and SWL) and outcome including each BN symptom (i.e., frequency of binge eating and purging and days of restrictive eating and compulsive exercise). BN symptoms in the previous week, SWB and SWL the following week, and treatment conditions were entered as covariates. For both aims, we included fixed and random effects of time in the model to control for general effects of time (i.e., detrending [19]). To account for the dependence within the session-by-session data, a first order autoregressive (AR[1]) structure was used. An unstructured covariance structure was chosen, which allowed intercept and slopes to correlate. All statistical analyses were conducted using SPSS v.26 [20].