Sensor technology in eating disorders research: A systematic review

Measures of nutrition status and health for weight-inclusive patient care: A narrative review

In healthcare, weight is often equated to and used as a marker for health. In examining nutrition and health status, there are many more effective markers independent of weight. In this article, we review practical and emerging clinical applications of technologies and tools used to collect non-weight-related data in nutrition assessment, monitoring, and evaluation in the outpatient setting. The aim is to provide clinicians with new ideas about various types of data to evaluate and track in nutrition care.

Momentary physiological indices related to eating disorders: A systematic and methodological review

Eating disorders (ED) are serious psychiatric illnesses, with no everyday support to intervene on the high rates of relapse. Understanding physiological indices that can be measured by wearable sensor technologies may provide new momentary interventions for individuals with ED. This systematic review, searching large databases, synthesises studies investigating peripheral physiological (PP) indices commonly included in wearable wristbands (heart rate [HR], heart rate variability [HRV], electrodermal activity [EDA], peripheral skin temperature [PST], and acceleration) in ED. Inclusion criteria included: (a) full peer-reviewed empirical articles in English; (b) human participants with active ED; and (c) containing one of five wearable physiological measures. Kmet risk of bias was assessed. Ninety-four studies were included (Anorexia nervosa [AN; N = 4418], bulimia nervosa [BN; N = 916], binge eating disorder [BED; N = 1604], other specified feeding and eating disorders [OSFED; N = 424], and transdiagnostic [N = 47]). Participants with AN displayed lower HR and EDA and higher HRV compared to healthy individuals. Those with BN showed higher HRV, and lower EDA and PST compared to healthy individuals. Other ED and Transdiagnostic samples showed mixed results. PP differences are indicated through various assessments in ED, which may suggest diagnostic associations, although more studies are needed to validate observed patterns. Results suggest important therapeutic potential for PP in ED, and larger studies including diverse participants and diagnostic groups are needed to fully uncover their role in ED.

Characterising illness stages and recovery trajectories of eating disorders in young people via remote measurement technology (STORY): a multi-centre prospective cohort study protocol

BACKGROUND

Eating disorders (EDs) are serious, often chronic, conditions associated with pronounced morbidity, mortality, and dysfunction increasingly affecting young people worldwide. Illness progression, stages and recovery trajectories of EDs are still poorly characterised. The STORY study dynamically and longitudinally assesses young people with different EDs (restricting; bingeing/bulimic presentations) and illness durations (earlier; later stages) compared to healthy controls. Remote measurement technology (RMT) with active and passive sensing is used to advance understanding of the heterogeneity of earlier and more progressed clinical presentations and predictors of recovery or relapse.

METHODS

STORY follows 720 young people aged 16-25 with EDs and 120 healthy controls for 12 months. Online self-report questionnaires regularly assess ED symptoms, psychiatric comorbidities, quality of life, and socioeconomic environment. Additional ongoing monitoring using multi-parametric RMT via smartphones and wearable smart rings ('Ōura ring') unobtrusively measures individuals' daily behaviour and physiology (e.g., Bluetooth connections, sleep, autonomic arousal). A subgroup of participants completes additional in-person cognitive and neuroimaging assessments at study-baseline and after 12 months.

DISCUSSION

By leveraging these large-scale longitudinal data from participants across ED diagnoses and illness durations, the STORY study seeks to elucidate potential biopsychosocial predictors of outcome, their interplay with developmental and socioemotional changes, and barriers and facilitators of recovery. STORY holds the promise of providing actionable findings that can be translated into clinical practice by informing the development of both early intervention and personalised treatment that is tailored to illness stage and individual circumstances, ultimately disrupting the long-term burden of EDs on individuals and their families.

Using machine learning with passive wearable sensors to pilot the detection of eating disorder behaviors in everyday life

BACKGROUND

Eating disorders (ED) are serious psychiatric disorders, taking a life every 52 minutes, with high relapse. There are currently no support or effective intervention therapeutics for individuals with an ED in their everyday life. The aim of this study is to build idiographic machine learning (ML) models to evaluate the performance of physiological recordings to detect individual ED behaviors in naturalistic settings.

METHODS

From an ongoing study (Final N = 120), we piloted the ability for ML to detect an individual's ED behavioral episodes (e.g. purging) from physiological data in six individuals diagnosed with an ED, all of whom endorsed purging. Participants wore an ambulatory monitor for 30 days and tapped a button to denote ED behavioral episodes. We built idiographic (N = 1) logistic regression classifiers (LRC) ML trained models to identify onset of episodes (~600 windows) v. baseline (~571 windows) physiology (Heart Rate, Electrodermal Activity, and Temperature).

RESULTS

Using physiological data, ML LRC accurately classified on average 91% of cases, with 92% specificity and 90% sensitivity.

CONCLUSIONS

This evidence suggests the ability to build idiographic ML models that detect ED behaviors from physiological indices within everyday life with a high level of accuracy. The novel use of ML with wearable sensors to detect physiological patterns of ED behavior pre-onset can lead to just-in-time clinical interventions to disrupt problematic behaviors and promote ED recovery.

EDIFY (Eating Disorders: Delineating Illness and Recovery Trajectories to Inform Personalised Prevention and Early Intervention in Young People): project outline

EDIFY (Eating Disorders: Delineating Illness and Recovery Trajectories to Inform Personalised Prevention and Early Intervention in Young People) is an ambitious research project aiming to revolutionise how eating disorders are perceived, prevented and treated. Six integrated workstreams will address key questions, including: What are young people's experiences of eating disorders and recovery? What are the unique and shared risk factors in different groups? What helps or hinders recovery? How do the brain and behaviour change from early- to later-stage illness? How can we intervene earlier, quicker and in a more personalised way? This 4-year project, involving over 1000 participants, integrates arts, design and humanities with advanced neurobiological, psychosocial and bioinformatics approaches. Young people with lived experience of eating disorders are at the heart of EDIFY, serving as advisors and co-producers throughout. Ultimately, this work will expand public and professional perceptions of eating disorders, uplift under-represented voices and stimulate much-needed advances in policy and practice.

Exploring the Relationship between Disordered Sleep and Mood in Male Anorexia Nervosa: An Actigraphy Study

Eating disorders (EDs), including anorexia nervosa (AN), are severe psychological disorders that affect individuals' eating behaviours and body perception. Previous research has shown that people with EDs often report poorer sleep. Some literature has suggested that it is mood dysregulation that mediates the link between EDs and sleep. However, the majority of previous studies only focused on females, while male ED patients have been overlooked. Therefore, the present study aimed to investigate the relationships between EDs, mood, and sleep among male ED patients. Using a mixture of actigraphy recordings and self-reported questionnaires, the current study analysed a total 33 adult male participants diagnosed with AN. The participants first wore an actigraphy device for seven continuous days, following which their ED severity and mood were assessed by the Eating Disorder Examination Questionnaire (EDE-Q) and Depression Anxiety Stress Scale (DASS), respectively. The descriptive actigraphy results suggested that, similar to females, males with AN also showed disturbed sleep, including insomnia, sleep fragmentation, low sleep efficiency, and increased napping sessions. However, when ED severity was correlated against actigraphy data and mood, no significant relationships were found between them. Thus, it was suggested that future studies may investigate discrete ED symptoms instead of global ED severity interacting with sleep and mood. Overall, this study represents an initial step in the investigation of EDs and sleep and mood dysregulation among an under-represented sample.