key: cord-1023484-hn46u739
authors: Zhou, Yuan; Wade, Tracey D.
title: The impact of COVID‐19 on body‐dissatisfied female university students
date: 2021-04-13
journal: Int J Eat Disord
DOI: 10.1002/eat.23521
sha: ca3825d17720073600abcee6a29b65d6a76b46ad
doc_id: 1023484
cord_uid: hn46u739

OBJECTIVE: This study investigated the impact of COVID‐19 on young women's disordered eating and their responses to online interventions to reduce disordered eating. METHOD: University students at risk of developing an eating disorder (N = 100) were randomly assigned to either receiving an online intervention to reduce disordered eating or not. Forty‐one participants entered the study from September 2019 to March 2020 (pre‐COVID) and 59 after physical distancing was introduced due to COVID pandemic (during COVID). Online assessments were conducted at baseline and 1‐week follow up. RESULTS: There was a significant increase in weight concerns, disordered eating, and negative affect among participants entering the trial during COVID compared to pre‐COVID. The increases in the first two variables remained when adjusting for baseline negative affect. No significant interactions between time, condition and COVID status were observed. DISCUSSION: Young women experienced increased levels of disordered eating after the onset of COVID. While no interactions with COVID were detected, changes to within‐group effect sizes for disordered eating more than doubled for both online interventions and assessment from pre‐COVID to during COVID, suggesting any attention to issues related to disordered eating in the context of reduced social contact may be beneficial.

Researchers have raised concerns that people with EDs are at significant risk for increased symptomology during COVID-19 (e.g., Cooper et al., 2020; Rodgers et al., 2020) . Using retrospective reporting, Phillipou et al. (2020) found that a general population in Australia increased their restricting and binge eating behaviors during COVID-19, whereas those who had an ED history increased not only their restricting, binge eating but also purging and exercise behaviors.

Qualitative retrospective research has found that those who experienced disordered eating tend to report similar themes; an increase in ED symptoms, need for help and support, limited access to services during COVID-19 (Brown et al., 2021; Nutley et al., 2021; Richardson, Patton, Phillips, & Paslakis, 2020) . To date only one study has used a prospective design to report on the impact of COVID on disordered eating, where college students in the US recorded no significant change in weight, BMI, or BMI category, between January and April 2020, but over this time the subjective descriptions of weight changed to significantly be more likely to fall into a higher category (Keel et al., 2020) . Keel Killen et al., 1994, p.232) . Only those who met a score above 47 on this scale, which is considered to have good predictive validity for development of an eating disorder (Jacobi, Abascal, & Taylor, 2004, p.290) , were invited to participate in the study.

This study, advertised as "an investigation of new methods to improve body image among young women", was approved by Social and Behavioural Research Ethics Committee (#8041). Data collection commenced in September 2021 where participants completed interventions in the laboratory with the presence of a research assistant. The online format of the study was introduced in April 2021 due to the physical distancing requirement amidst COVID where participants can complete the same study at home. Other than the presence of a research assistant, all study procedure and questionnaires were the same as they were all delivered online.

Specifically, participants first completed baseline measures after which they received a body-specific negative mood induction (details can be found in Zhou, Pennesi, & Wade, 2020) . Then participants either get randomly allocated to an active intervention (e.g., imagery rescripting, psychoeducation, or the combination of the two) or control. Participants were asked to complete a one-week follow-up survey online. All participants were provided with a feedback sheet with contact information of support services included. For the purpose of this investigation, the original design was modified, as we found a main effect of COVID status on our results. In effect, this was an extra moderator for which our study was not powered. We thus combined all active interventions and compared to these to the control (assessment only) condition.

These validated measures were selected to assess the following constructs: disordered eating measured by the global Eating Disorder Examination Questionnaire (EDE-Q; Fairburn & Beglin, 1994) 

2.4.1 | Baseline differences pre-versus during COVID Differences between the group of participants who entered the study pre-and during COVID were compared using analysis of variance (ANOVA). Between-groups effect sizes and 95% confidence intervals that did not cross zero were interpreted as indicating a significant difference.

Linear Mixed Modeling (LMM) was used to compare the effectiveness of active versus control condition with respect to outcome measures at oneweek, adjusting for baseline negative affect that is, 2 (condition) × 2 (time:

baseline, one-week) × 2 COVID timeframe (pre-and during COVID).

Within group effect sizes and 95% confidence intervals were calculated to demonstrate the magnitude of change, accounting for the correlation between the two measures (Lenhard & Lenhard, 2016) , using the online effect size calculator for repeated measures: https://www.psychometrica. de/effect_size.html#repeated).

A hundred females ranging in age from 17 to 26 (Mean = 19.85, SD = 2.01) entered the study. Most participants self-reported as Caucasian (88%) with the next largest groups being Asian (6%), and other (6%). Overall, most participants (53%) were within the normal BMI range (i.e., 18.5 < BMI < 25); 27% were classified as overweight (i.e., 25 < BMI < 30); 17% were obese (i.e., BMI > 30), and 3% were classified as underweight (i.e., BMI < 18.5). Most participants (92%) reported engaging in some form of disordered eating behaviors over the previous 28 days: fasting (71%), driven exercise (71%), binge eating (65%), self-induced vomiting (13%), and laxative misuse (7%). The clinical cut-off on the EDE-Q Global score (i.e., ≥2.77, norm for young adult women +1 SD; Mond, Hay, Rodgers, & Owen, 2006) was attained by 76% of participants. Mean WCS was 68.48 (SD = 12.85; scores beyond 47 were identified as at-risk). See Table 1 for means and standard deviations of outcome measures at baseline.

T A B L E 1 Descriptive statistics (mean and standard deviation) at baseline by condition and by COVID status. Estimated marginal means and standard errors were presented after adjusting for negative affect, except for negative affect itself. Effect sizes and 95% confidence intervals were provided for pre-and during COVID mean comparisons 

Overall, no significant differences among baseline variables were found when comparing active intervention versus control without considering COVID status. However, significant differences were found among those who completed the study pre-and during-COVID. During-COVID, participants reported significantly higher symptomology compared to pre-COVID, all associated with moderate effect sizes (Cohen's d = 0.40-0.55, see Table 1 ). Specifically, the two groups differed in weight concerns, disordered eating, and negative affect. After adjusting for baseline negative affect, the difference in global eating psychopathology remained. The percentage of participants who reported disordered eating behaviors increased during COVID: fasting (from 61% to 78% of participants), binge-eating (61% to 68%), vomiting (7% to 17%), and driven exercise (66% to 75%).

Of the 100 participants in the analytic sample, 7 (7%) did not complete the one-week follow-up questionnaire. Table 2 

This study investigated the impact of COVID-19 on young women's risk of developing an eating disorder and the effectiveness of active interventions during COVID-19. Findings suggest that during COVID, disordered eating behaviors and negative affect were significantly higher than pre-COVID levels, which echoed findings from qualitative research (Brown et al., 2021; Nutley et al., 2021; Richardson et al., 2020) . Significant difference in disordered eating preversus during COVID remained when adjusting for negative affect.

While no interactions with COVID were detected, within-group effect sizes for disordered eating related to either condition increased considerably after onset of COVID. While it makes sense that greater distress over COVID means that effect size decreases will be bigger, the reason for the differential impact on the control condition on disordered eating during COVID is unclear. During T A B L E 2 Linear Mixed Models estimated marginal means and standard error for one-week variables by Time (2), Condition (2) and COVID (2) controlling for baseline negative affect Note: Higher EDEQ scores suggest higher level of disordered eating; higher BIAAQ score suggest higher level of body image flexibility; higher SCS score suggest higher level of self-compassion and higher fear of self-compassion score suggest higher level of fear of self-compassion. Bold font indicates a significant difference between baseline and one-week follow-up.

COVID, assessments only may have produced some level of awareness or self-efficacy to reduce disordered eating (i.e., a placebo effect; Weimer, Colloca, & Enck, 2015) . It may be that any attention to issues related to disordered eating in the context of reduced social contact may be beneficial.

The main limitation of this current study is that we used a design of convenience to address our questions, rather than the original design, due to the unexpected advent of COVID. This meant the study was not powered to account for the onset of the COVID-19 midway through the study. Therefore, the sample size of active versus control group was unbalanced; however, this does not present an issue when using linear mixed modeling. Second, as we could not randomly assign participants to COVID status, these analyses should be interpreted as an exploratory attempt to detect naturally occurring changes. We acknowledge that COVID status could be impacted by many factors not measured in this study, such as willingness to participate in the study mid-COVID, or deterioration in people's mood. We do note, however the key result 

The authors declare no conflict of interest.

The data that support the findings of this study are available from the corresponding author upon reasonable request.

https://orcid.org/0000-0002-1123-7973

Tracey D. Wade https://orcid.org/0000-0003-4402-770X

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