Kendra R. Becker’s research while affiliated with Harvard Medical School and other places

Objective Avoidant/restrictive food intake disorder (ARFID) is a relatively new formal diagnosis for which empirical classification research (defined here as studies using latent class/latent profile analysis‐type methods) is still emerging. Such research focused on ARFID is an important gap to fill given questions about (1) the boundaries between ARFID and phenotypically similar presentations (e.g., eating disorders [EDs] such as anorexia nervosa [AN], and pediatric feeding disorder [PFD]), and (2) within‐ARFID heterogeneity. These questions have practical implications, including diagnostic reliability and treatment selection. Method This forum synthesizes the limited empirical classification literature seeking to quantitatively distinguish ARFID from non‐ARFID EDs or from PFD, and/or characterize within‐ARFID heterogeneity. Results To our knowledge, only five studies in clinical samples have used empirical classification methods to delineate ARFID from non‐ARFID EDs and/or characterize within‐ARFID heterogeneity; no studies have used such methods to delineate ARFID from PFD. Existing studies are mixed in determining how well ARFID can be distinguished from other EDs (particularly AN), but converge in identifying several potential ARFID subclasses (i.e., sensory sensitivity, low appetite, feared eating‐related consequences, and subclass representing a combination of these) with some overlapping features. Discussion The existing ARFID empirical classification literature should guide future ARFID classification research priorities (e.g., incorporating mechanistic variables as classification indicators, incorporating longitudinal variables as classification validators) to inform differences between ARFID and other disorders and between ARFID presentations. Dimensional approaches to conceptualizing, studying, and modeling psychopathology (namely, the Hierarchical Taxonomy of Psychopathology [HiTOP] and the Research Domain Criteria [RDoC]) may offer useful insights.

Objective Despite substantial research indicating difficulties with emotion regulation across eating disorder presentations, emotion regulation has yet to be studied in adults with avoidant/restrictive food intake disorder (ARFID). We hypothesized that (1) those with ARFID would report greater overall emotion regulation difficulties than nonclinical participants, and (2) those with ARFID would not differ from those with other eating disorders on the level of emotion regulation difficulty. Methods One hundred and thirty‐seven adults (age 18–30) from an outpatient clinic with ARFID ( n = 27), with other primarily restrictive eating disorders (e.g., anorexia nervosa; n = 34), and with binge/purge eating disorders (e.g., bulimia nervosa; n = 51), as well as nonclinical participants ( n = 25) recruited via Amazon Mechanical Turk (MTurk) completed the Difficulties in Emotion Regulation Scale (DERS). We compared DERS scores across groups. Results In line with expectations, patients with ARFID scored significantly higher than nonclinical participants on the DERS Total ( p = 0.01) with a large effect size ( d = 0.87). Also as hypothesized, those with ARFID did not differ from those with other primarily restrictive ( p = 0.99) or binge/purge disorders ( p = 0.29) on DERS Total. Discussion Adults with ARFID appear to exhibit emotion regulation difficulties which are greater than nonclinical participants, and commensurate with other eating disorders. These findings highlight the possibility of emotion regulation difficulties as a maintenance mechanism for ARFID.

Objective Avoidant/restrictive food intake disorder (ARFID) is common among populations with nutrition‐related medical conditions. Less is known about the medical comorbidity/complication frequencies in youth with ARFID. We evaluated the medical comorbidities and metabolic/nutritional markers among female and male youth with full/subthreshold ARFID across the weight spectrum compared with healthy controls (HC). Method In youth with full/subthreshold ARFID ( n = 100; 49% female) and HC ( n = 58; 78% female), we assessed self‐reported medical comorbidities via clinician interview and explored abnormalities in metabolic (lipid panel and high‐sensitive C‐reactive protein [hs‐CRP]) and nutritional (25[OH] vitamin D, vitamin B12, and folate) markers. Results Youth with ARFID, compared with HC, were over 10 times as likely to have self‐reported gastrointestinal conditions (37% vs. 3%; OR = 21.2; 95% CI = 6.2–112.1) and over two times as likely to have self‐reported immune‐mediated conditions (42% vs. 24%; OR = 2.3; 95% CI = 1.1–4.9). ARFID, compared with HC, had a four to five times higher frequency of elevated triglycerides (28% vs. 12%; OR = 4.0; 95% CI = 1.7–10.5) and hs‐CRP (17% vs. 4%; OR = 5.0; 95% CI = 1.4–27.0) levels. Discussion Self‐reported gastrointestinal and certain immune comorbidities were common in ARFID, suggestive of possible bidirectional risk/maintenance factors. Elevated cardiovascular risk markers in ARFID may be a consequence of limited dietary variety marked by high carbohydrate and sugar intake.

Background DSM-5 differentiates avoidant/restrictive food intake disorder (ARFID) from other eating disorders (EDs) by a lack of overvaluation of body weight/shape driving restrictive eating. However, clinical observations and research demonstrate ARFID and shape/weight motivations sometimes co-occur. To inform classification, we: (1) derived profiles underlying restriction motivation and examined their validity and (2) described diagnostic characterizations of individuals in each profile to explore whether findings support current diagnostic schemes. We expected, consistent with DSM-5 , that profiles would comprise individuals endorsing solely ARFID or restraint (i.e. trying to eat less to control shape/weight) motivations. Methods We applied latent profile analysis to 202 treatment-seeking individuals (ages 10–79 years [ M = 26, s.d. = 14], 76% female) with ARFID or a non-ARFID ED, using the Nine-Item ARFID Screen (Picky, Appetite, and Fear subscales) and the Eating Disorder Examination-Questionnaire Restraint subscale as indicators. Results A 5-profile solution emerged: Restraint/ARFID-Mixed ( n = 24; 8% [ n = 2] with ARFID diagnosis); ARFID-2 (with Picky/Appetite; n = 56; 82% ARFID); ARFID-3 (with Picky/Appetite/Fear; n = 40; 68% ARFID); Restraint ( n = 45; 11% ARFID); and Non-Endorsers ( n = 37; 2% ARFID). Two profiles comprised individuals endorsing solely ARFID motivations (ARFID-2, ARFID-3) and one comprising solely restraint motivations (Restraint), consistent with DSM-5 . However, Restraint/ARFID-Mixed (92% non-ARFID ED diagnoses, comprising 18% of those with non-ARFID ED diagnoses in the full sample) endorsed ARFID and restraint motivations. Conclusions The heterogeneous profiles identified suggest ARFID and restraint motivations for dietary restriction may overlap somewhat and that individuals with non-ARFID EDs can also endorse high ARFID symptoms. Future research should clarify diagnostic boundaries between ARFID and non-ARFID EDs.

Background Avoidant/restrictive food intake disorder (ARFID) is a feeding/eating disorder characterized by avoidance/restriction of food intake by volume and/or variety. The emergence of shape/weight-related eating disorder symptoms in the longitudinal course of ARFID is an important clinical phenomenon that is neither robustly documented nor well understood. We aimed to characterize the emergence of eating disorder symptoms among adults with an initial diagnosis of ARFID who ultimately developed other eating disorders. Method Thirty-five participants (94% female; Mage = 23.17 ± 5.84 years) with a history of ARFID and a later, separate eating disorder completed clinical interviews (i.e., Structured Clinical Interview for DSM-5 – Research Version and Longitudinal Interval Follow-Up Evaluation) assessing the period between ARFID and the later eating disorder. Participants used calendars to aid in recall of symptoms over time. Descriptive statistics characterized the presence, order of, and time to each symptom. Paired samples t-tests compared weeks to emergence between symptoms. Results Most participants (71%) developed restricting eating disorders; the remainder (29%) developed binge-spectrum eating disorders. Cognitive symptoms (e.g., shape/weight concerns) tended to onset initially and were followed by behavioral symptoms. Shape/weight-related food avoidance presented first, objective binge eating, fasting, and excessive exercise occurred next, followed by subjective binge eating and purging. Conclusions Diagnostic crossover from ARFID to another (typically restricting) eating disorder following the development of shape/weight concerns may represent the natural progression of a singular clinical phenomenon. Findings identify potential pathways from ARFID to the development of another eating disorder, highlighting possible clinical targets for preventing this outcome.

Objective Few studies have focused on brain structure in atypical anorexia nervosa (atypical AN). This study investigates differences in gray matter volume (GMV) between females with anorexia nervosa (AN) and atypical AN, and healthy controls (HC). Method Structural magnetic resonance imaging data were acquired for 37 AN, 23 atypical AN, and 41 HC female participants. Freesurfer was used to extract GMV, cortical thickness, and surface area for six brain lobes and associated cortical regions of interest (ROI). Primary analyses employed linear mixed‐effects models to compare group differences in lobar GMV, followed by secondary analyses on ROIs within significant lobes. We also explored relationships between cortical gray matter and both body mass index (BMI) and symptom severity. Results Our primary analyses revealed significant lower GMV in frontal, temporal and parietal areas (FDR < .05) in AN and atypical AN when compared to HC. Lobar GMV comparisons were non‐significant between atypical AN and AN. The parietal lobe exhibited the greatest proportion of affected cortical ROIs in both AN versus HC and atypical AN versus HC. BMI, but not symptom severity, was found to be associated with cortical GMV in the parietal, frontal, temporal, and cingulate lobes. No significant differences were observed in cortical thickness or surface area. Discussion We observed lower GMV in frontal, temporal, and parietal areas, when compared to HC, but no differences between AN and atypical AN. This indicates potentially overlapping structural phenotypes between these disorders and evidence of brain changes among those who are not below the clinical underweight threshold. Public significance Despite individuals with atypical anorexia nervosa presenting above the clinical weight threshold, lower cortical gray matter volume was observed in partial, temporal, and frontal cortices, compared to healthy individuals. No significant differences were found in cortical gray matter volume between anorexia nervosa and atypical anorexia nervosa. This underscores the importance of continuing to assess and target weight gain in clinical care, even for those who are presenting above the low‐weight clinical criteria.

Background Avoidant/restrictive food intake disorder (ARFID) and anorexia nervosa (AN) are the two primary restrictive eating disorders; however, they are driven by differing motives for inadequate dietary intake. Despite overlap in restrictive eating behaviors and subsequent malnutrition, it remains unknown if ARFID and AN also share commonalities in their cognitive profiles, with cognitive alterations being a key identifier of AN. Discounting the present value of future outcomes with increasing delay to their expected receipt represents a core cognitive process guiding human decision-making. A hallmark cognitive characteristic of individuals with AN (vs. healthy controls [HC]) is reduced discounting of future outcomes, resulting in reduced impulsivity and higher likelihood of favoring delayed gratification. Whether individuals with ARFID display a similar reduction in delay discounting as those with AN (vs. an opposing bias towards increased delay discounting or no bias) is important in informing transdiagnostic versus disorder-specific cognitive characteristics and optimizing future intervention strategies. Method To address this research question, 104 participants (ARFID: n = 57, AN: n = 28, HC: n = 19) completed a computerized Delay Discounting Task. Groups were compared by their delay discounting parameter (ln)k. Results Individuals with ARFID displayed a larger delay discounting parameter than those with AN, indicating steeper delay discounting (M ± SD = −6.10 ± 2.00 vs. −7.26 ± 1.73, p = 0.026 [age-adjusted], Hedges’ g = 0.59), with no difference from HC (p = 0.514, Hedges’ g = −0.35). Conclusion Our findings provide a first indication of distinct cognitive profiles among the two primary restrictive eating disorders. The present results, together with future research spanning additional cognitive domains and including larger and more diverse samples of individuals with ARFID (vs. AN), will contribute to identifying maintenance mechanisms that are unique to each disorder as well as contribute to the optimization and tailoring of treatment strategies across the spectrum of restrictive eating disorders.

Background Cognitive‐behavioral therapy for avoidant/restrictive food intake disorder (ARFID; CBT‐AR) theoretically targets three prototypic motivations (sensory sensitivity, lack of interest/low appetite, fear of aversive consequences), aligned with three modularized interventions. As an exploratory investigation, we: (1) evaluated change in candidate mechanisms in relationship to change in ARFID severity, and (2) tested if assignment (vs. not) to a module resulted in larger improvements in the corresponding mechanism. Method Males and females ( N = 42; 10–55 years) participated in an open trial of CBT‐AR. Results Decreases in scaled scores for each candidate mechanism had medium to large correlations with decreases in ARFID severity—sensory sensitivity: −0.7 decrease ( r = .42, p = .01); lack of interest/low appetite: −0.3 decrease ( r = .60, p < .0001); and fear of aversive consequences: −1.1 decrease ( r = .33, p = .05). Linear mixed models revealed significant weekly improvements for each candidate mechanism across the full sample ( ps < .0001). There were significant interactions for the sensory and fear of aversive consequences modules–for each, participants who received the corresponding module had significantly larger decreases in the candidate mechanism than those who did not receive the module. Discussion Sensory sensitivity and fear of aversive consequences improved more if the CBT‐AR module was received, but lack of interest/low appetite may improve regardless of receipt of the corresponding module. Future research is needed to test target engagement in CBT‐AR with adaptive treatment designs, and to identify valid and sensitive measures of candidate mechanisms. Public Significance The mechanisms through which components of CBT‐AR work have yet to be elucidated. We conducted an exploratory investigation to test if assignment (vs. not) to a CBT‐AR module resulted in larger improvements in the corresponding prototypic ARFID motivation that the module intended to target. Measures of the sensory sensitivity and the fear of aversive consequences motivations improved more in those who received the corresponding treatment module, whereas the lack of interest/low appetite measure improved regardless of if the corresponding module was received.