Bulimic-spectrum disorders such as bulimia nervosa (BN), binge eating disorder (BED), and other specified feeding or eating disorder (OSFED) are among the most common eating disorders (EDs) and can significantly impact an individual’s wellbeing and quality of life (Galmiche et al., 2019). Yet, there are significant barriers to accessing treatment due to a general oversubscription of treatment centres and increased prioritisation of patients with Anorexia Nervosa (AN). Spending significant time on a waiting list can cause reduced engagement in treatments when they become available, and negatively impact outcomes for EDs (Fursland et al., 2018), which calls for increased waitlist management and support.
Interest in digital interventions for EDs has grown significantly in the past few years. These are appealing due to their ability to provide care without increasing the burden on healthcare providers, but their effectiveness is still being established (Linardon et al., 2020).
The paper presented here by Vollert and colleagues (2024) is a randomised controlled trial (RCT) that explored the effectiveness of a web-based guided self-help programme named everyBody Plus for female patients with BN, BED, and OSFED.
Despite being the most prevalent eating disorders, patients with bulimic-spectrum conditions encounter substantial barriers to accessing treatment. Can digital interventions help?
Methods
Vollert et al. (2024) conducted a RCT comparing participants who had access to everyBody Plus (intervention group) against those with no access to an intervention (control group). Both groups were assessed before, during, and at the end of the intervention period, with two follow-up assessments 6- and 12-months post-intervention to establish long-term effects. They recruited individuals with a diagnosis of BN, BED, or OSFED with binge eating who were on a waiting list for psychological treatment in Germany or the UK. Participants were randomised in a 1:1 ratio to the two study arms, stratified by country.
EveryBody Plus is a guided self-help programme which contains eight modules covering a range of topics. It also includes some interactive elements such as group forums and homework tasks, as well as a weekly symptom monitoring diary addressing body weight and frequency of ED behaviours. To encourage continued participation, participants who did not access the intervention in a given week received motivational messages encouraging further engagement.
The primary outcome for this study was the number of weeks until a patient reached an absence of ED behaviors for at least four consecutive weeks, which was measured based on weekly symptom diary entries. Secondary outcomes were core eating disorder symptoms and attitudes, depression, anxiety, alcohol consumption, self-esteem, and quality of life, measured using a range of questionnaires. The authors used log-rank tests on the primary outcome to establish the effect of the intervention, applying the intention- to-treat (ITT) principle. Additionally, multilevel mixed effect models were used to analyse the primary and secondary outcomes, also following the ITT principle.
Results
Participants
This study included 337 female participants at baseline (mean age = 32.10), 113 of which were recruited in Germany and 224 in the UK. Of those, 170 were randomised to the intervention group and 167 to the control group. Half of the participants met the criteria for BED, a third for BN, and the rest for OSFED, with no significant differences in the distribution of symptoms or diagnoses between groups.
Main findings
- Participants in the intervention group showed more improvements overall, as well as significantly more rapid symptom reduction compared to those in the control group (p = .021; corresponding hazard ratio [HR] = 1.997, 95% CI [1.09 to 3.65], p = .025).
- There were significant interactions between group and time for ED symptoms, anxiety, and quality of life across all assessment points.
- There were also significant interactions for depression at all timepoints, except the 12-month follow-up (p = .060).
- These findings suggest that participating in the intervention led to differences in ED symptoms and other indicators of mental wellbeing. Indeed, all significant interactions demonstrated larger improvements in the intervention group compared to the control, with small to large effect sizes (d’s = 0.29 to 0.82).
- Additionally, although there was no significant difference in the number of participants who began face-to-face therapy between both groups, the intervention group had significantly higher probability of being free from core ED symptoms at 6- and 12-month follow-up, highlighting the importance of intervention engagement rather than receiving further treatment.
- Finally, participants indicated that they were satisfied with the intervention, rating it an average of 2.95 on a 0-4 scale. Their working alliance ratings with the online therapist were also high, and the authors claim that it was “comparable to scores found in psychotherapy patients”.
This study found that participants who were randomised to receive the everyBody Plus intervention showed faster and greater improvements in eating disorder symptomatology, anxiety, depression, and quality of life than those who did not.
Conclusions
Overall, the authors concluded that,
The everyBody Plus intervention not only benefits females with subclinical level of eating disorders, but it also leads to significant improvement among females with clinical threshold of eating disorders in routine clinical and pragmatic settings.
I believe that the results of this study are promising in showing that everyBody Plus may help bridge the treatment gap for those with bulimic-spectrum disorders, with successful symptom reduction. I believe it has the potential to be adopted into the clinical field, although more scientific investigations are needed before direct recommendations can be made to clinical practice.
everyBody Plus, a digital guided self-help tool shows promise for helping to improve eating disorder symptoms for individuals waiting to access treatment for bulimic-spectrum disorders.
Strengths and limitations
Overall, this is a strong paper underpinned by a controlled and systematic methodology, with measures that are well validated and widely used. The inclusion of both 6- and 12-month follow-ups enables conclusions to be drawn on whether the effects from the intervention can be maintained in the long-term, which is important given high relapse rates in EDs following successful treatment (i.e., 27% for BN; Olmsted et al., 2015). Additionally, in the context of this paper where it can be assumed that most participants will subsequently enter the treatment they were initially on the waiting list for, the inclusion of such follow-ups helps us to establish whether the effects from the intervention can lead to more successful treatment. However, the type of treatment accessed and at what timepoint add significant confounds to any such conclusions, and these were not explored by the authors.
Additionally, only 39.4% of participants in the intervention group completed the full course of the intervention, which decreases reliability by adding uncertainty to whether the effects found were due to the intervention or further treatments accessed. Furthermore, participants in the control group were significantly more likely to complete the 6- and 12-month follow ups than those in the intervention group, and those who dropped out demonstrated higher weight concern and anxiety symptoms, which decreases the generalizability of the findings to people with more severe symptomatology.
Including participants from the UK and Germany significantly improves the generalisability of these findings, as do the varied methods used for recruitment and the large sample size gathered. However, given that a majority of participants were from the UK and primarily recruited via the NHS, caution should be taken on making broad generalisations. Although the authors conclude that this tool can be used in both countries, and in a variety of contexts, I would argue that further work which focuses on the underrepresented populations in this study needs to be done to reach such conclusions. Additionally, the study could have benefitted from independent analyses of the two countries, which would enable clearer conclusions on the applicability of the tool in the two different healthcare systems.
A further limitation is the inclusion of only women in the sample, and fact that they did not collect data on participants’ ethnicities. There is a significant lack of ED research on males, leading to decreased efficacy of care (Foye, 2018). Additionally, people of minority ethnicities have been shown to have worse ED prognosis (Miskovic-Wheatley et al., 2023), illustrating the need for further research on tools that can support these groups. The lack of inclusion of these aspects in the present study means that it fails to address these significant gaps in the literature.
Additionally, previous research has criticised the use of waiting lists controls when evaluating digital mental health interventions, finding that effects tend to be stronger when tools are compared to waiting list controls than to information-only controls (Linardon et al., 2020). It is suggested that the positive effects of digital intervention tools may simply be due to using the technology itself rather than its therapeutic elements – a sort of “digital placebo” (Torous et al., 2016).
Finally, the authors did not report any potential harms that can result from the use of this intervention, which is important to investigate and disclose to enable an evaluation of the intervention’s risks compared to its benefits. Without this information it is not possible to fully evaluate this tool.
Despite its strengths in including participants from the UK and Germany and using varied recruitment methods, this study should be cautious about overgeneralizing its findings due to a majority of participants being White, female, from the UK, and recruited via the NHS.
Implications for practice
This study has implications for clinical practice. The use of digital interventions has potential for decreasing the burden on healthcare professionals and the NHS (Foley & Woollard, 2019). Additionally, the use of EveryBody Plus while on a waitlist may help with the previously established detrimental effects of this time (Fursland et al., 2018). The authors suggest that this tool can make treatment itself more effective once patients access it by sustaining motivation for recovery and providing psychoeducation, but this needs to be investigated further through systematic investigations of patients who accessed treatment after having used everybody Plus for waiting list management compared to those who did not.
Furthermore, the results showed that compensatory behaviors were more resistant to change for those who accessed the intervention compared to bingeing and restricting. This information has implications for clinical practice as healthcare professionals can allocate more treatment time to those aspects which seem to be more difficult to change.
However, I think that before it can be implemented into wider practice, further research still needs to be done on this tool. Firstly, it has consistently been shown that social support is a large component in recovery from EDs (Kim et al., 2023), and the inclusion of the group forum in the intervention tested here is a strength. However, I was disappointed to see that the paper did not spend time explaining this component, nor did they report participants’ opinions on it. For this and other reasons, I believe it would be beneficial to conduct some qualitative analyses on this tool, examining participant perspectives and attitudes towards different components of the intervention. It is ineffective to research interventions without knowing whether they are acceptable to those who will use them, and rating-scale scores are often not enough to discern people’s real and nuanced opinions (Uher, 2023).
Additionally, as the authors also note, it is important to establish the characteristics of patients who may benefit most from this tool. Such tailoring is crucial to ensure effectiveness, as well as minimise harm. Furthermore, understanding the reasons behind why some patients do or do not benefit from this intervention may enable for multiple versions of it to be created and tailored to specific contexts. My own PhD is concerned with looking in-depth at recovery from AN, with the goal of adapting an intervention tool so that it can target different factors at the points in recovery during which they are most relevant. I believe this is one of the biggest untapped potentials for tools of this sort, as adapting them to people’s needs is likely to significantly improve their effectiveness. In this way, the study presented here also opens many doors for future research endeavours.
Although these results are promising, further work needs to be done to help tailor this intervention and understand the specific characteristics of people who would benefit most from it in order to improve its effectiveness and applicability to clinical practice.
Statement of interests
None.
Links
Primary paper
Vollert, B., Yim, S. H., Görlich, D., Beintner, I., Gordon, G., Musiat, P., … & Jacobi, C. (2024). Using web-based, guided self-help to bridge the waiting time for face-to-face out-patient treatment for bulimic-spectrum disorders: randomised controlled trial. BJPsych Open, 10(2), e53.
Other references
Foley, T., & Woollard, J. (2019). The digital future of mental healthcare and its workforce a report on a mental health stakeholder engagement to inform the Topol Review. Health Education England.
Foye, U. (2018). Treating men with eating disorders: do we need gender-specific care? The Mental Elf.
Fursland, A., Erceg‐Hurn, D. M., Byrne, S. M., & McEvoy, P. M. (2018). A single session assessment and psychoeducational intervention for eating disorders: Impact on treatment waitlists and eating disorder symptoms. International Journal of Eating Disorders, 51(12), 1373-1377.
Galmiche, M., Déchelotte, P., Lambert, G., & Tavolacci, M. P. (2019). Prevalence of eating disorders over the 2000-2018 period: a systematic literature review. American Journal of Clinical Nutrition, 109(5), 1402-1413.
Kim, S., Smith, K., Udo, T., & Mason, T. (2023). Social support across eating disorder diagnostic groups: results from the National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III). Eating Behaviors, 48, 101699.
Linardon, J., Shatte, A., Messer, M., Firth, J., & Fuller-Tyszkiewicz, M. (2020). E-Mental Health Interventions for the Treatment and Prevention of Eating Disorders: An Updated Systematic Review and Meta-Analysis. Journal of Consulting and Clinical Psychology, 88(11), 994-1007.
Miskovic-Wheatley, J., Bryant, E., Ong, S. H., Vatter, S., Le, A. V., Touyz, S., Maguire, S., & Consortium, N. E. D. R. (2023). Eating disorder outcomes: findings from a rapid review of over a decade of research. Journal of Eating Disorders, 11(1).
Olmsted, M. P., MacDonald, D. E., McFarlane, T., Trottier, K., & Colton, P. (2015). Predictors of rapid relapse in bulimia nervosa. International Journal of Eating Disorders, 48(3), 337-340.
Torous, J., & Firth, J. (2016). The digital placebo effect: mobile mental health meets clinical psychiatry. The Lancet Psychiatry, 3(2), 100-102.
Uher, J. (2023). What’s wrong with rating scales? Psychology’s replication and confidence crisis cannot be solved without transparency in data generation. Social and Personality Psychology Compass, 17(5), e12740.
