It’s estimated that approximately 1.25 million people in the UK have an eating disorder (Beat, n.d.). With 95% of first-time eating disorders (EDs) occurring before the age of 25 (Ward et al., 2019), it’s unsurprising that this figure is elevated amongst university and college students. However, this does not mean that colleges and universities are better equipped to identify and treat EDs among their students, in fact, fewer than 20% of students with EDs report receiving any treatment (Eisenberg et al., 2011; Fitzsimmons-Craft et al., 2019).
Being able to rapidly respond to and provide treatment for ED’s is critical to an individual’s long-term progress (Solmi, 2016) and so the need for effective screening and ED interventions is crucial for this high-risk group. However, previous research has found various barriers preventing these institutions from doing just that, including students’ lack of time and feelings of stigma (Solmi, 2017) which prevent students from seeking help (Eisenberg, Speer & Hunt, 2012).
Screening tools and interventions which can overcome these barriers, such as online and digital interventions, may have the potential to improve the mental health care provided by colleges and universities (Kumar et al., 2013). However, there is still yet to be any large-scale studies in this area assessing the effectiveness of such tools in a student population. Therefore, this study aimed to test whether a digital cognitive behavioural intervention would significantly reduce ED psychopathology in female university students, compared to usual care.
Whilst university and college students present an at-risk group for developing eating disorders, campuses are currently not well equipped to provide effective screening and interventions.
Methods
The authors of this study carried out a cluster randomised clinical trial to test whether a digital cognitive behavioural therapy guided self-help program (Student Bodies-Eating Disorders; SB-ED) would significantly reduce EDs in college women screening positive for an ED, compared to usual care.
Twenty-seven US universities (randomised as either in the intervention or control condition) were included, with participants having to meet the following inclusion criteria:
- A female student at one of the participating universities
- Aged 18+
- Screened positive for an ED (excluding anorexia nervosa) on the Stanford-Washington ED Screen (Graham et al., 2019).
Eligible participants who consented to take part were asked to complete online assessments at baseline, post-intervention, 1-year, and 2 years follow-up. All participants were provided with information about how to access their assigned condition treatment immediately upon completion of screening.
Intervention (SB-ED) condition
Those in the SB-ED condition received access to a digital, guided self-help CBT intervention online for 8 months. This included the core components of CBT for EDs (Fairburn, 2008), alongside meal planning, self-monitoring and tracking tools, and access to online communication with a personal coach. Coaches had various backgrounds but were all working at one of the participating universities, had to undergo extensive training and were all overseen by a clinical psychologist.
Control condition
Participants in the control group received written feedback following completion of the baseline assessment, which encouraged them to seek further evaluation and/or treatment at their university’s counselling centre with information about how to do this.
Measures
A reduction in overall ED psychopathology, measured by the Eating Disorder Examination-Questionnaire (EDE-Q; Fairburn & Beglin, 2008) was the primary outcome measure assessed.
Secondary outcome measures were:
- Abstinence from all ED behaviours
- ED behaviour frequencies
- Depression
- Anxiety
- ED associated clinical impairment
- Academic impairment
- Realised treatment access
Results
Overall, 385 participants were randomised to the intervention and 305 to the control, with 82.6% completing at least one follow-up assessment.
Most participants were undergraduate students, with a mean age of 22.12 years and 60% identifying as White. The sample was made up of participants who screened positive for bulimia nervosa (19.9%, including subthreshold; 24.8%), binge-eating disorder (10%, including subthreshold; 9.6%), purging disorder (4.5%), and other specified feeding or eating disorder (31.2%).
Primary outcome
There was a significantly greater reduction in ED psychopathology (as measured by the EDE-Q) in the intervention group vs the control group at post-intervention and at follow-up (d=0.40).
Secondary outcomes
- There were no significant differences between the conditions for abstinence from all ED behaviours and in whether participants withdrew or took leave from university at post-intervention or follow-up
- The frequency of binge eating was significantly lower in the intervention group at post-intervention, but not at follow-up
- The frequency of overall compensatory behaviours was significantly lower in the intervention group at post-intervention and follow-up
- There were no significant differences in anxiety scores at post-intervention between the two groups, but there was a significant reduction at follow-up in the intervention group
- There was a significantly greater reduction in depression scores and ED-associated clinical impairment in the intervention group at post-intervention and follow-up.
Engagement
Whilst 83% of participants in the intervention condition began the intervention, only 28% of the control condition reported to obtain an ED treatment at any point. However, an average of only 31% of the intervention content was completed, with percentage engagement significantly associated with greater reductions in EDE-Q scores post-intervention.
The intervention group were found to significantly improve in ED psychopathology, binge eating frequency, compensatory behaviours, depression, and clinical impairment versus those receiving usual care.
Conclusions
Given the findings of this study, the coached, digital CBT intervention (SB-ED) seems effective for college women with a range of EDs. The authors of this study concluded:
“A digital CBT-guided self-help intervention for EDs has great potential to address the wide treatment gap for this problem”.
The findings of this study support the use of a digital guided CBT intervention for a wide range of eating disorders, compared to referral to usual care.
Strengths and limitations
This research had various strengths:
- The intervention was delivered to samples of students on a national scale across the US
- Long term follow-ups showed improvements after 2 years
- The sample included individuals with multiple different ED diagnoses, including those with subthreshold diagnoses.
However, limitations include:
- Engagement with the intervention was only at 31%
- Inclusion into the study was dependent on a self-report screen rather than a diagnostic interview, along with the results of each follow-up assessment which were reliant on self-report, leaving the results open to bias. However, this method is more realistic of use if rolled out to university campuses
- Whilst the sample was large, only US universities were included, with the majority of participants White undergraduates. Other large exclusions from the sample included those with anorexia nervosa and males. This makes it hard to generalise the results to other groups, particularly to students in the UK, where usual care is likely to be different.
This eating disorders research, like many other studies in this area, did not include males.
Implications for practice
Whilst the engagement with the intervention in this study was low, the authors acknowledged that this level of engagement was similar to other studies using digital interventions (Baumel et al., 2019). Therefore, whilst the results of this study are encouraging, future research looking into improving engagement with digital interventions may help to improve outcomes even further. More research looking at the effectiveness of SB-ED is also still needed, including comparing its effectiveness directly to face-to-face CBT.
This research is especially relevant now more than ever, as more digital interventions are needed whilst living in a Covid-world where face-to-face appointments are few and far between. However, a need to bridge the treatment gap in ED treatments in the UK is crucial regardless, with access to treatments described as a ‘postcode lottery’ (Beat, 2019). Therefore, being able to provide an easily accessible digital treatment, not reliant on face-to-face appointments, might help to improve our ability to treat EDs early or at least as an interim treatment for those on a waitlist.
Those with anorexia nervosa were excluded from this study, likely due to the low BMI status associated with this group. When trying to obtain treatment, it’s common that access for those with this disorder is dependent on having a low BMI, due to the lack of available services. Therefore, interventions such as the SB-ED could be offered to individuals who do not meet the BMI cut-off for anorexia treatment (and thus not needing as much medical monitoring) instead of being denied treatment altogether, which seems to spread the message that they are not yet ‘ill enough’ to receive treatment. Especially as the improvements found from this intervention occurred without any observed changes in BMI.
Finally, online interventions might also provide crucial support for those who feel unable to seek face-to-face treatments due to stigma (particularly males – see Foye, 2018). As males were excluded from this study, this could also be an avenue for future research.
Whilst there seems to be a ‘postcode lottery’ in the UK for those receiving help for eating disorders, digital interventions might help to bridge the gap for those currently struggling to access help.
Statement of interests
None.
Links
Primary paper
Fitzsimmons-Craft, E, E., Barr Taylor, C., Graham, A. K., Sadeh-Sharvit, S., Balantekin, K. N., Eichen, D. M., … & Wilfley, D. E. (2020). Effectiveness of a digital cognitive behaviour therapy-guided self-help intervention for eating disorders in college women. A cluster randomized clinical trial (PDF). JAMA Network Open, 3(8), e2015633.
Other references
Baumel, A., Muench, F., Edan, S., Kane, J. M. (2019). Objective user engagement with mental health apps: systematic search and panel-based usage analysis [HTML]. J Med Internet Res., 21(9), e14567.
Beat. (2019, November 26). Adult eating disorder services postcode lottery puts lives at risk.
Beat. (n.d., November 26). How many people have an eating disorder in the UK?
Eisenberg, D., Nicklett, E. J., Roeder, K., & Kirz, N. E. (2011). Eating disorder symptoms among college students: prevalence, persistence, correlates, and treatment-seeking (PDF). J Am Coll Health, 59(8), 700-707.
Eisenberg, D., Speer, N., & Hunt, J. B. (2011). Attitudes and beliefs about treatment among college students with untreated mental health problems (PDF). Psychiatr Serv, 63(7), 711-713.
Fairburn, C. G. (2008). Cognitive Behavior Therapy and Eating Disorders (PDF). Guilford Press.
Fairburn, C. G., & Beglin, S. J. (2008). Eating Disorder Examination Questionnaire (EDE-Q 6.0). In: Fairburn CG, ed. Cognitive Behavioral Therapy for Eating Disorders (PDF). Guilford Press; 309-313.
Fitzsimmons-Craft, E. E., Karam, A. M., Monterubio, G. E., Taylor, C. B., & Wilfley, D. E. (2019). Screening for eating disorders on college campuses: a review of the recent literature (PDF). Curr Psychiatry Rep, 21(10), 101.
Foye U. Treating men with eating disorders: do we need gender specific care? The Mental Elf, 11 Dec 2018.
Graham, A. K., Trockel, M., Weisman, H., Fitzsimmons-Craft, E. E., Balantekin, K. N., Wilfley, D. E., & Taylor, C. B. (2019). A screening tool for detecting eating disorder risk and diagnostic symptoms among college-age women (PDF). J Am Coll Health, 67(4), 357-366.
Kumar, S., Nilsen, W. J., Abernethy, A., Atienza, A, Patrick, K., Pavel, M., … & Swendeman, D. (2013). Mobile health technology evaluation: the mHealth evidence workshop (PDF). Am J Prev Med, 45(2), 228-236.
Solmi F. Rapid response to eating disorders predicts better outcomes. The Mental Elf, 8 Nov 2016.
Solmi F. The stigma of eating disorders: which interventions might help? The Mental Elf, 20 April 2017.
Ward, Z. J., Rodriguez, P., Wright, D. R., Austin, S. B., Long, M. W. (2019). Estimation of eating disorders prevalence by age and associations with mortality in a simulated nationally representative US cohort [HTML]. JAMA Netw Open, 2(10), e1912925.
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