Eating DisordersNCT06544226
The Use of Smart Devices in Capturing Digital Biomarkers in Eating Disorders
An observational study of Eating Disorders, run by Univa Health at 1 site in United Kingdom.
Trial summary
This study aims to explore how smart devices can be used to monitor the health of individuals with eating disorders. Eating disorders are serious mental health conditions that impact both mental and physical health. Read more about this study
- Who is it for?
- Ages 10 years and older
- Conditions the study is for
- Eating Disorders
- What is being tested?
- UH100
- Type of treatment
- Medical device
- How many people
- 130 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 1 Nov 2024to 1 Sep 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 10 years and older
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: Participants will be identified and recruited from child and adult eating disorder hospital wards and specialist secondary care child and adult eating disorder outpatient treatment teams.
Who may be able to join
- All participants must be aged 10 years or older.
- Diagnosed with an eating disorder by a clinician as per the World Health Organization\'s ICD-10 (F50.0 through F50.9) or ICD-11 (6B80 - 6B85; 6B8Y, 6B8Z) classification
- Must have a minimum once weekly in-person clinic physical assessment as part of their current treatment plan at the start of the study participation
- Fluent in English
- Capable of reading and understanding the information sheets and consent forms to provide written informed consent.
- For participants aged between 10 and 16 years, parental consent is required first before offering the opportunity to the child. A parent or legal guardian must also be able to read and understand the information sheets and consent forms to provide written informed consent on behalf of the child under 16 years of age.
Who cannot join
- Active substance use such as drug or alcohol misuse
- For alcohol consumption of more than 21 units of alcohol per week (1 unit is equivalent to half a pint of beer (285ml), 25ml of spirits, or one glass of wine)
- Diagnostic coding for current mental and behavioural disorders due to substances (ICD10: F10 through F19; ICD11: QE10 through QE1Z and 6C40 through 6C4H)
- A diagnosis of a neurological disorder, including but not limited to cerebrovascular diseases, either currently or in the past or where the eating disorder for which the participant is being treated is considered aetiologically-secondary to a neurological disorder (e.g. pica secondary to a brain injury).
- A diagnosis of schizophrenia or related psychotic disorder.
- Pregnancy.
- A diagnosis of developmental learning disorder (ICD10 F80.0 through F81.9: ICD11: 6A03) or intellectual disorders (ICD10: F70.0 through F79.9; ICD11 6A00).
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Peter Sheng Yao Hsu, PhD contact
United Kingdom1 site, 1 recruiting
- Recruiting
University of Liverpool
Liverpool, L69 3GF
Daniel Joyce, MRCPsych, +441517950139, D.Joyce@liverpool.ac.uk
About this study
Official title: A Novel Pilot Study Examining the Potential of Smartphones to Capture New Types of Data That Can Accurately Assess the Physiological and Psychological Health Status of an Individual With an Eating Disorder
This study aims to explore how smart devices can be used to monitor the health of individuals with eating disorders. Eating disorders are serious mental health conditions that impact both mental and physical health. Effective monitoring is crucial for developing treatment plans and ensuring the safety of individuals both in hospitals and at home. Currently, healthcare professionals use manual methods to measure important health indicators like heart rate, blood pressure, and BMI. These methods can be time-consuming and may not always accurately reflect a patient's health due to the possibility of patients concealing the severity of their condition. Furthermore, monitoring at home is challenging due to the lack of professional equipment and training for caregivers. With advancements in digital technology, smartphones and smartwatches now have the potential to collect and analyse health data in real-time. These devices can capture data on heart rate, blood pressure, respiratory rate, and other vital signs through non-invasive methods like analysing facial and fingertip blood volume, namely the photoplethysmography technology. Additionally, video recordings from smartphone cameras can be used to assess physical and mental health by analysing facial expressions, voice patterns, and physical movements. By utilising these digital tools, combined with validated questionnaires and tasks to assess participants' psychological status and the severity of disorders, this study expects to create a more efficient and accessible way for individuals with eating disorders to monitor their health at home. The study will collect data from participants both in hospital settings and during outpatient care to ensure the reliability and effectiveness of these digital methods across participants with different levels of severity. This comprehensive approach aims to improve early detection of health issues, optimise treatment plans, and ultimately enhance the quality of life for individuals with eating disorders.
Read the detailed description
Eating disorders are complex mental health conditions characterised by abnormal eating habits and distressing thoughts about body weight and shape, significantly impacting both mental and physical health. According to the International Classification of Diseases, 11th Revision, feeding and eating disorders include several subtypes such as anorexia nervosa (AN), bulimia nervosa (BN), and binge eating disorder (BED). These subtypes often involve patterns of restrictive or excessive food intake, leading to severe health issues and impairments in daily functioning.
Given the rising incidence and profound impacts of eating disorders in recent years, including high mortality rates and significant economic burdens, there is an urgent need for innovative management strategies and more efficient triage and monitoring systems for early intervention and home-based care.
For the care of individuals with eating disorders, comprehensive and continuous assessment of physical and psychiatric conditions is essential. As recommended by the UK's National Institute for Health and Care Excellence (NICE) and the Royal College of Psychiatrists, key clinical markers monitored, include weight loss, BMI, heart rate, blood pressure, temperature, hydration status, and muscular function. Monitoring these markers is crucial for early detection of medical complications, such as electrolyte imbalances, cardiac arrhythmias, and orthostatic hypotension, which pose serious health risks. Additionally, these markers help evaluate the disorder's severity, guide treatment adjustments, and ensure patient safety during recovery.
However, traditional methods used to assess these biomarkers are burdensome and time-consuming. With the advancement of technology, novel smart devices can efficiently detect traditional biomarkers such as heart rate and blood pressure, while also exploring potential novel measures of the disease. Therefore, this study aims to validate and explore the potential of these technologies to provide monitoring comparable to traditional methods and to integrate collected data to generate sophisticated insights into the health status of individuals with eating disorders.
According to previous research, the analysis of facial information, including static features and dynamic movements, combined with advanced algorithms and machine learning, can estimate body weight, BMI, parotid gland size, and skin condition. When voice pattern analysis is integrated with facial dynamics during the video diary entry phase and the image response task, where participants share their thoughts on specific images, it is expected to further assess physical and psychological states, particularly when discussing sensitive topics or images, such as high-calorie foods. These estimations can be used to interpret the health status of individuals with eating disorders. Additionally, photoplethysmography (PPG) using smart devices can detect subtle changes in the colour spectrum induced by blood volume dynamics in facial and fingertip areas, allowing for the estimation of heart rate (HR), blood pressure (BP), respiratory rate (RR), blood oxygen level, blood glucose, and body temperature. This technology, which has been validated in healthy subjects, shows significant potential for application in patients with eating disorders, who are prone to cardiovascular and respiratory issues due to physiological stress and nutritional imbalances. This approach provides essential insights into their physical health status, particularly given the significant impairments in muscle strength often observed in individuals with eating disorders.
In addition to physical health, this study will also examine psychological traits that may improve the accuracy of identifying eating disorder status. This will include questionnaire-based assessments and a computerised task to measure psychological processes. Specifically, the 7-item Generalised Anxiety Disorder Questionnaire (GAD-7) and the 9-item Patient Health Questionnaire (PHQ-9) will assess anxiety and depression severity, respectively, while the Eating Disorder Examination Questionnaire (EDE-Q) will evaluate eating disorder traits, including eating restraint, eating concern, shape concern, and weight concern. Adolescent versions of these questionnaires will be used for younger participants. Moreover, since impulsivity and cognitive control are often altered in individuals with eating disorders, this study will assess these cognitive functions using an adapted Stop Signal Task (SST) that incorporates sensitive cues, such as high-calorie food cues (food-specific SST, FSST). This task will aid in monitoring cognitive control related to the progression of eating disorders and potentially improve the accuracy of health status assessments in these individuals.
This study aims to validate the aforementioned biomarkers and models captured by the smart device and to explore changes in these biomarkers and psychological status across different stages and severities of eating disorders. Data will be collected over 16 weeks from both hospitalised patients and outpatients. Most data, including vital and physical biomarkers, facial information, and self-reported anxiety and depression measures, will be collected weekly, either once or twice a week, with adjustments for those with less frequent visits. Whereas the EDE-Q, the FSST task, and the patient acceptance questionnaire, which assesses patients' acceptance of the data collection procedures, will be conducted three times during the study, in weeks 1, 8, and 16. By conducting this study, the investigators expect to enhance the usability and acceptance of non-invasive monitoring tools, providing valuable insights into the health status of individuals with eating disorders.
- Conditions
- Eating Disorders
- Being tested
- UH100
- Keywords
- Eating Disorders, Photoplethysmography, Biomarkers, Vital Signs, Physical Signs
- Medical subject headings
- Feeding and Eating Disorders
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
UH100Device
This is a non-interventional pilot study. Given the within-subject and longitudinal design used in this study, traditional intervention settings are not applicable. All participants will receive weekly and tri-point assessments,
- Weekly (twice per week) Assessments: Physical vitals such as BMI, Blood Pressure, Heart Rate
- Weekly (once per week) Assessments: Sit-Up-Squat-Stand Test, Video diary entries, GAD-7, and PHQ-9.
- Tri-point (week 1, 8, 6) assessments: EDE-Q, Patient Acceptance Questionnaire and the Food-specific Stop Signal Task.
| Study group | Role | What they receive |
|---|---|---|
| Group of eating disorder patients aged above 10 | This is a cohort study in which all participants are diagnosed with eating disorders and undertake the same set of assessments and tasks, although the frequency of these assessments and tasks is subject to their current care plan. Receives: Device: UH100 |
What is being measured
The primary outcome is the main question the study is designed to answer.
Height and Weight - traditional measurement
Height (cm) and weight (kg) will be measured using standard clinical techniques. These two measurements will be used independently or to calculate the body mass index (BMI).
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Height and Weight - PPG estimation and facial analysis
Height (cm) and weight (kg) will be estimated using independent or combined facial and fingertip photoplethysmogram (PPG) technology and facial feature analysis. These facial features will be identified and quantified using machine learning algorithms. These two measurements will be used independently or to calculate the body mass index (BMI).
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Heart Rate - traditional measurement
Heart rate (bpm) will be measured by a sphygmomanometer in both sitting and standing postures.
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Heart Rate - PPG estimation
Heart rate (bpm) will be estimated using facial and fingertip photoplethysmogram (PPG) technology in both sitting and standing postures.
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Pressure - traditional measurement
Temperature (°C) will be separately measured using a thermometer and estimated using independent or combined facial and fingertip photoplethysmogram (PPG) technology and facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Pressure - PPG estimation
Systolic and diastolic blood pressure (mmHg) will be measured using facial and fingertip photoplethysmogram (PPG) technology in both sitting and standing postures.
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Respiratory Rate - traditional measurement
Respiratory rate (breaths per minute) will be measured by counting the number per minute manually.
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Respiratory Rate - PPG estimation and facial analysis
Respiratory rate (breaths per minute) will be estimated using independent or combined facial and fingertip photoplethysmogram (PPG) technology and facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Temperature - traditional measurement
Temperature (°C) will be measured using a thermometer.
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Temperature - PPG estimation and facial analysis
Temperature (°C) will be estimated using independent or combined facial and fingertip photoplethysmogram (PPG) technology and facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Oxygen Level - traditional measurement
Blood oxygen level (SpO2) will be measured using a saturation meter
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Oxygen Level - PPG estimation and facial analysis
Blood oxygen level (SpO2) will be estimated using independent or combined facial and fingertip photoplethysmogram (PPG) technology and facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Glucose Level - traditional measurement
Blood glucose level (mmol/L or mg/dL) will be measured through blood tests.
Measured: A maximum of two sessions per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Glucose Level - PPG estimation and facial analysis
Blood glucose level (mmol/L or mg/dL) will be estimated using independent or combined facial and fingertip photoplethysmogram (PPG) technology and facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Hydration Level - traditional measurement
Hydration level will be assessed through the number and type of dehydration symptoms.
Measured: A maximum of two sessions per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Hydration Level - PPG estimation and facial analysis
Hydration level will be estimated using independent or combined facial and fingertip photoplethysmogram (PPG) technology and facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Rating of Skin Conditions - traditional measurement
Skin conditions will be assessed through the number and type of skin conditions.
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Rating of Skin Conditions - PPG estimation and facial analysis
Skin conditions will be estimated using facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Sit-Up-Squat-Stand Test - traditional measurement
Participants' core strength, flexibility, and balance will be assessed using the Sit-Up-Squat-Stand Test with a 4-point scale to separately rate Sit-Up and the Squat-Stand performance.
Measured: A maximum of two sessions per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Sit-Up-Squat-Stand Test - PPG estimation and facial and body movement analysis
Participants' core strength, flexibility, and balance will be estimated by using independent or combined facial photoplethysmogram (PPG) technology and the analysis of changes in body movements and facial features. These movements and features will be identified and quantified using machine learning algorithms.
Measured: A maximum of two sessions per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Single Anxiety and Depression Questions
Participants' anxiety and depression (mood) status on the day of the assessment session will be evaluated using two single-item questions, each with a 100-point visual analogue scale.
Measured: A maximum of two sessions per week, with two tests conducted after each set of readings, will be carried out from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The Size of The Parotid Glands - traditional measurement
The size of the parotid glands will be assessed by clinicians or professionals to determine if it is normal.
Measured: A maximum of two sessions per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The Size of The Parotid Glands - PPG estimation and facial and body movement analysis
The size of the parotid glands will be estimated using facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Measured: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (full blood count)
The blood test is used to assess electrolyte balance, including the result of full blood count.
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (Haemoglobin)
The blood test is used to assess electrolyte balance, including the result of Haemoglobin (g/dL or g/L).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (Platelets)
The blood test is used to assess electrolyte balance, including the result of Platelets (10^3/μL or 10^9/L).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (white cell counts)
The blood test is used to assess electrolyte balance, including the result of white cell counts (10^3/μL or 10^9/L).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (potassium (K+))
The blood test is used to assess electrolyte balance, including the result of potassium (K+) (mEq/L or mmol/L).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (sodium (Na+))
The blood test is used to assess electrolyte balance, including the result of sodium (Na+) (mEq/L or mmol/L).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (magnesium (Mg++))
The blood test is used to assess electrolyte balance, including the result of magnesium (Mg++) (mEq/L, mg/dL, or mmol/L).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (phosphorous (PO4))
The blood test is used to assess electrolyte balance, including the result of phosphorous (PO4) (mEq/L, mg/dL, or mmol/L).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (urea)
The blood test is used to assess electrolyte balance, including the result of urea (mEq/L, mg/dL, or mmol/L).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (creatine kinase)
The blood test is used to assess electrolyte balance, including the result of creatine kinase (U/L or µkat/L).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (albumin)
The blood test is used to assess electrolyte balance, including the result of albumin (g/dL).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (alkaline phosphatase (ALP))
The blood test is used to assess electrolyte balance, including the result of alkaline phosphatase (ALP) (U/L or µkat/L).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (aspartate transaminase (AST))
The blood test is used to assess electrolyte balance, including the result of aspartate transaminase (AST) (U/L or µkat/L).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (alanine transaminase (ALT))
The blood test is used to assess electrolyte balance, including the result of alanine transaminase (ALT) (U/L or µkat/L).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (gamma-glutamyl transferase (GGT))
The blood test is used to assess electrolyte balance, including the result of gamma-glutamyl transferase (GGT) (U/L or µkat/L).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (bilirubin)
The blood test is used to assess electrolyte balance, including the result of bilirubin (mg/dL or μmol/L).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood Tests (glucose)
The blood test is used to assess electrolyte balance, including the result of glucose (mg/dL or mmol/L).
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Video Diary Entry
When participants are asked to record their thoughts on diary questions, changes in their aforementioned facial PPG-related biomarkers, facial features, and voice patterns, along with their qualitative responses, will be recorded and analysed. The facial features and voice patterns will be identified and quantified using machine learning algorithms.
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Image Response Task
When participants are asked to record their thoughts on high-calorie food, low-calorie food, neutral, and positive images, changes in their aforementioned facial PPG-related biomarkers, facial features, and voice patterns, along with their qualitative responses, will be recorded and analysed. The facial features and voice patterns will be identified and quantified using machine learning algorithms.
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Generalised Anxiety Disorder (GAD-7) and Patient Health (PHQ-9) Questionnaires
Participants' overall anxiety and depression levels will be assessed using the 7-item GAD-7 and the 9-item PHQ-9, respectively. Both scales are rated on a 4-point scale from 0 to 3. Adolescents will use the adolescent version of the PHQ-9 (PHQ-A), which employs the same scaling and scoring system, allowing for direct comparison with adults.
Measured: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The Eating Disorder Examination Questionnaire (EDE-Q)
Participants' eating disorder traits, including eating restraint, eating concern, weight concern, and shape concern, along with qualitative responses regarding the frequency of eating disorder behaviours, will be assessed using the 28-item EDE-Q. This questionnaire is rated on a 7-point scale from 0 to 6. Adolescents will use the adolescent version of the EDE-Q (EDE-A). While this adolescent version contains 36 items, 28 of them capture the same domains as the adult version.
Measured: Three times throughout the study: in Weeks 1, 8, and 16-or-at early discharge, or when care plans change and no further visits to clinical sites are scheduled before Week 16.
The Food-specific Stop Signal Task
Three variables are generated by this task to assess participants' inhibitory control related to food. These variables include stop signal reaction time (SSRT), go reaction time (GORT), and the proportion of successful stops or error rates. SSRT, measured in milliseconds, assesses the latency of inhibition and reflects an individual's ability to suppress an automatic response. GORT, also measured in milliseconds, evaluates the speed of responses to go signals, providing insight into baseline response times and overall task performance. The proportion of successful stops or error rates indicates the percentage of trials where participants successfully inhibit their responses.
Measured: Three times throughout the study: in Weeks 1, 8, and 16-or-at early discharge, or when care plans change and no further visits to clinical sites are scheduled before Week 16.
Patient Acceptance Questionnaire
Participants' comfort with conducting the procedures of this study, such as recording their faces, will be assessed using an 8-item self-developed questionnaire with a 6-point rating scale, such as from 'Very comfortable' to 'Very uncomfortable'.
Measured: Three times throughout the study: in Weeks 1, 8, and 16-or-at early discharge, or when care plans change and no further visits to clinical sites are scheduled before Week 16.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Aug 2024
- Study start1 Nov 2024
- Primary completion1 Apr 2025 (estimated)
- Study completion1 Sep 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (41)Papers the sponsor has linked to this study.
- Other trials for Eating DisordersStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 130 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Univa Health
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
- Investigators
- Daniel Joyce, MRCPsych, Principal investigator, University of Liverpool
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06544226
- Sponsor's protocol ID
- ST001
- Status last verified
- Dec 2024
- First submitted
- 16 Jul 2024
- Last updated
- 6 Dec 2024
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Johnson JG, Cohen P, Kasen S, Brook JS. Eating disorders during adolescence and the risk for physical and mental disorders during early adulthood. Arch Gen Psychiatry. 2002 Jun;59(6):545-52. doi: 10.1001/archpsyc.59.6.545.
PubMed 12044197Engel SG, Adair CE, Las Hayas C, Abraham S. Health-related quality of life and eating disorders: a review and update. Int J Eat Disord. 2009 Mar;42(2):179-87. doi: 10.1002/eat.20602.
PubMed 18949768The Hearts Minds and Genes Coalition (2021). The Cost of Eating Disorders in the UK 2019 and 2020. The Hearts Minds and Genes Coalition. https://www.yumpu.com/en/document/view/65877873/the-cost-of-eating-disorders-in-the-uk-2019-and-2020-with-annex
Jenkins PE. Cost-of-illness for non-underweight binge-eating disorders. Eat Weight Disord. 2022 May;27(4):1377-1384. doi: 10.1007/s40519-021-01277-3. Epub 2021 Jul 30.
PubMed 34327651The Royal College of Psychiatrists (2023). Medical Emergencies in Eating Disorders: Guidance on Recognition and Management. The Royal College of Psychiatrists. https://www.rcpsych.ac.uk/docs/default-source/improving-care/better-mh-policy/college-reports/college-report-cr233-medical-emergencies-in-eating-disorders-(meed)-guidance.pdf?sfvrsn=2d327483_63
Eating disorders: recognition and treatment. London: National Institute for Health and Care Excellence (NICE); 2020 Dec 16. Available from http://www.ncbi.nlm.nih.gov/books/NBK568394/
PubMed 33689256NHS England (2021). Hospital admissions for eating disorders. NHS England. https://digital.nhs.uk/supplementary-information/2021/hospital-admissions-for-eating-disorders-2015-2021
Arcelus J, Mitchell AJ, Wales J, Nielsen S. Mortality rates in patients with anorexia nervosa and other eating disorders. A meta-analysis of 36 studies. Arch Gen Psychiatry. 2011 Jul;68(7):724-31. doi: 10.1001/archgenpsychiatry.2011.74.
PubMed 21727255Dantcheva, A., Bremond, F., & Bilinski, P. (2018). Show me your face and I will tell you your height, weight and body mass index. In 2018 24th International Conference on Pattern Recognition (ICPR) (pp. 3555-3560). IEEE.
Pascali MA, Giorgi D, Bastiani L, Buzzigoli E, Henriquez P, Matuszewski BJ, Morales MA, Colantonio S. Face morphology: Can it tell us something about body weight and fat? Comput Biol Med. 2016 Sep 1;76:238-49. doi: 10.1016/j.compbiomed.2016.06.006. Epub 2016 Jun 14.
PubMed 27504744Hasan S, Ahmed S, Panigrahi R, Chaudhary P, Vyas V, Saeed S. Oral cavity and eating disorders: An insight to holistic health. J Family Med Prim Care. 2020 Aug 25;9(8):3890-3897. doi: 10.4103/jfmpc.jfmpc_608_20. eCollection 2020 Aug.
PubMed 33110784Bozzato A, Burger P, Zenk J, Uter W, Iro H. Salivary gland biometry in female patients with eating disorders. Eur Arch Otorhinolaryngol. 2008 Sep;265(9):1095-102. doi: 10.1007/s00405-008-0598-8. Epub 2008 Feb 6.
PubMed 18253742Colella G, Lo Giudice G, De Luca R, Troiano A, Lo Faro C, Santillo V, Tartaro G. Interventional sialendoscopy in parotidomegaly related to eating disorders. J Eat Disord. 2021 Feb 17;9(1):25. doi: 10.1186/s40337-021-00378-9.
PubMed 33597023Fagherazzi G, Fischer A, Ismael M, Despotovic V. Voice for Health: The Use of Vocal Biomarkers from Research to Clinical Practice. Digit Biomark. 2021 Apr 16;5(1):78-88. doi: 10.1159/000515346. eCollection 2021 Jan-Apr.
PubMed 34056518Opladen V, Tanck JA, Baur J, Hartmann AS, Svaldi J, Vocks S. Body exposure and vocal analysis: validation of fundamental frequency as a correlate of emotional arousal and valence. Front Psychiatry. 2023 May 24;14:1087548. doi: 10.3389/fpsyt.2023.1087548. eCollection 2023.
PubMed 37293400
Study at a glance
From the registry record, last updated by the sponsor on 6 Dec 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Novel Pilot Study Examining the Potential of Smartphones to Capture New Types of Data That Can Accurately Assess the Physiological and Psychological Health Status of an Individual With an Eating Disorder
- ClinicalTrials.gov ID
- NCT06544226
- Acronym / sponsor ID
- ST001
- Conditions
- Eating Disorders
- Keywords
- Eating Disorders, Photoplethysmography, Biomarkers, Vital Signs, Physical Signs
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 130 participants (estimated)
- Lead sponsor
- Univa HealthIndustry (pharma, biotech, devices)
- Study start
- 1 Nov 2024 (actual)
- Primary completion
- 1 Apr 2025 (estimated)
- Study completion
- 1 Sep 2025 (estimated)
- First posted
- 9 Aug 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study aims to explore how smart devices can be used to monitor the health of individuals with eating disorders. Eating disorders are serious mental health conditions that impact both mental and physical health. Effective monitoring is crucial for developing treatment plans and ensuring the safety of individuals both in hospitals and at home. Currently, healthcare professionals use manual methods to measure important health indicators like heart rate, blood pressure, and BMI. These methods can be time-consuming and may not always accurately reflect a patient's health due to the possibility of patients concealing the severity of their condition. Furthermore, monitoring at home is challenging due to the lack of professional equipment and training for caregivers. With advancements in digital technology, smartphones and smartwatches now have the potential to collect and analyse health data in real-time. These devices can capture data on heart rate, blood pressure, respiratory rate, and other vital signs through non-invasive methods like analysing facial and fingertip blood volume, namely the photoplethysmography technology. Additionally, video recordings from smartphone cameras can be used to assess physical and mental health by analysing facial expressions, voice patterns, and physical movements. By utilising these digital tools, combined with validated questionnaires and tasks to assess participants' psychological status and the severity of disorders, this study expects to create a more efficient and accessible way for individuals with eating disorders to monitor their health at home. The study will collect data from participants both in hospital settings and during outpatient care to ensure the reliability and effectiveness of these digital methods across participants with different levels of severity. This comprehensive approach aims to improve early detection of health issues, optimise treatment plans, and ultimately enhance the quality of life for individuals with eating disorders.
Detailed description
Eating disorders are complex mental health conditions characterised by abnormal eating habits and distressing thoughts about body weight and shape, significantly impacting both mental and physical health. According to the International Classification of Diseases, 11th Revision, feeding and eating disorders include several subtypes such as anorexia nervosa (AN), bulimia nervosa (BN), and binge eating disorder (BED). These subtypes often involve patterns of restrictive or excessive food intake, leading to severe health issues and impairments in daily functioning.
Given the rising incidence and profound impacts of eating disorders in recent years, including high mortality rates and significant economic burdens, there is an urgent need for innovative management strategies and more efficient triage and monitoring systems for early intervention and home-based care.
For the care of individuals with eating disorders, comprehensive and continuous assessment of physical and psychiatric conditions is essential. As recommended by the UK's National Institute for Health and Care Excellence (NICE) and the Royal College of Psychiatrists, key clinical markers monitored, include weight loss, BMI, heart rate, blood pressure, temperature, hydration status, and muscular function. Monitoring these markers is crucial for early detection of medical complications, such as electrolyte imbalances, cardiac arrhythmias, and orthostatic hypotension, which pose serious health risks. Additionally, these markers help evaluate the disorder's severity, guide treatment adjustments, and ensure patient safety during recovery.
However, traditional methods used to assess these biomarkers are burdensome and time-consuming. With the advancement of technology, novel smart devices can efficiently detect traditional biomarkers such as heart rate and blood pressure, while also exploring potential novel measures of the disease. Therefore, this study aims to validate and explore the potential of these technologies to provide monitoring comparable to traditional methods and to integrate collected data to generate sophisticated insights into the health status of individuals with eating disorders.
According to previous research, the analysis of facial information, including static features and dynamic movements, combined with advanced algorithms and machine learning, can estimate body weight, BMI, parotid gland size, and skin condition. When voice pattern analysis is integrated with facial dynamics during the video diary entry phase and the image response task, where participants share their thoughts on specific images, it is expected to further assess physical and psychological states, particularly when discussing sensitive topics or images, such as high-calorie foods. These estimations can be used to interpret the health status of individuals with eating disorders. Additionally, photoplethysmography (PPG) using smart devices can detect subtle changes in the colour spectrum induced by blood volume dynamics in facial and fingertip areas, allowing for the estimation of heart rate (HR), blood pressure (BP), respiratory rate (RR), blood oxygen level, blood glucose, and body temperature. This technology, which has been validated in healthy subjects, shows significant potential for application in patients with eating disorders, who are prone to cardiovascular and respiratory issues due to physiological stress and nutritional imbalances. This approach provides essential insights into their physical health status, particularly given the significant impairments in muscle strength often observed in individuals with eating disorders.
In addition to physical health, this study will also examine psychological traits that may improve the accuracy of identifying eating disorder status. This will include questionnaire-based assessments and a computerised task to measure psychological processes. Specifically, the 7-item Generalised Anxiety Disorder Questionnaire (GAD-7) and the 9-item Patient Health Questionnaire (PHQ-9) will assess anxiety and depression severity, respectively, while the Eating Disorder Examination Questionnaire (EDE-Q) will evaluate eating disorder traits, including eating restraint, eating concern, shape concern, and weight concern. Adolescent versions of these questionnaires will be used for younger participants. Moreover, since impulsivity and cognitive control are often altered in individuals with eating disorders, this study will assess these cognitive functions using an adapted Stop Signal Task (SST) that incorporates sensitive cues, such as high-calorie food cues (food-specific SST, FSST). This task will aid in monitoring cognitive control related to the progression of eating disorders and potentially improve the accuracy of health status assessments in these individuals.
This study aims to validate the aforementioned biomarkers and models captured by the smart device and to explore changes in these biomarkers and psychological status across different stages and severities of eating disorders. Data will be collected over 16 weeks from both hospitalised patients and outpatients. Most data, including vital and physical biomarkers, facial information, and self-reported anxiety and depression measures, will be collected weekly, either once or twice a week, with adjustments for those with less frequent visits. Whereas the EDE-Q, the FSST task, and the patient acceptance questionnaire, which assesses patients' acceptance of the data collection procedures, will be conducted three times during the study, in weeks 1, 8, and 16. By conducting this study, the investigators expect to enhance the usability and acceptance of non-invasive monitoring tools, providing valuable insights into the health status of individuals with eating disorders.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Group of eating disorder patients aged above 10 | – | Device: UH100This is a cohort study in which all participants are diagnosed with eating disorders and undertake the same set of assessments and tasks, although the frequency of these assessments and tasks is subject to their current care plan. |
Who may qualify
- Ages
- 10 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Participants will be identified and recruited from child and adult eating disorder hospital wards and specialist secondary care child and adult eating disorder outpatient treatment teams.
Key inclusion criteria (6 listed)
- All participants must be aged 10 years or older.
- Diagnosed with an eating disorder by a clinician as per the World Health Organization\'s ICD-10 (F50.0 through F50.9) or ICD-11 (6B80 - 6B85; 6B8Y, 6B8Z) classification
- Must have a minimum once weekly in-person clinic physical assessment as part of their current treatment plan at the start of the study participation
- Fluent in English
- Capable of reading and understanding the information sheets and consent forms to provide written informed consent.
Key exclusion criteria (7 listed)
- Active substance use such as drug or alcohol misuse
- A diagnosis of a neurological disorder, including but not limited to cerebrovascular diseases, either currently or in the past or where the eating disorder for which the participant is being treated is considered aetiologically-secondary to a neurological disorder (e.g. pica secondary to a brain injury).
- A diagnosis of schizophrenia or related psychotic disorder.
- Pregnancy.
- A diagnosis of developmental learning disorder (ICD10 F80.0 through F81.9: ICD11: 6A03) or intellectual disorders (ICD10: F70.0 through F79.9; ICD11 6A00).
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| UH100This is a non-interventional pilot study. Given the within-subject and longitudinal design used in this study, traditional intervention settings are not applicable. All participants will receive weekly and tri-point assessments, * Weekly (twice per week) Assessments: Physical vitals such as BMI, Blood Pressure, Heart Rate * Weekly (once per week) Assessments: Sit-Up-Squat-Stand Test, Video diary entries, GAD-7, and PHQ-9. * Tri-point (week 1, 8, 6) assessments: EDE-Q, Patient Acceptance Questionnaire and the Food-specific Stop Signal Task. | Device | Group of eating disorder patients aged above 10 |
Primary outcome
Height and Weight - traditional measurement
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Height (cm) and weight (kg) will be measured using standard clinical techniques. These two measurements will be used independently or to calculate the body mass index (BMI).
Height and Weight - PPG estimation and facial analysis
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Height (cm) and weight (kg) will be estimated using independent or combined facial and fingertip photoplethysmogram (PPG) technology and facial feature analysis. These facial features will be identified and quantified using machine learning algorithms. These two measurements will be used independently or to calculate the body mass index (BMI).
Heart Rate - traditional measurement
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Heart rate (bpm) will be measured by a sphygmomanometer in both sitting and standing postures.
Heart Rate - PPG estimation
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Heart rate (bpm) will be estimated using facial and fingertip photoplethysmogram (PPG) technology in both sitting and standing postures.
Blood Pressure - traditional measurement
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Temperature (°C) will be separately measured using a thermometer and estimated using independent or combined facial and fingertip photoplethysmogram (PPG) technology and facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Blood Pressure - PPG estimation
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Systolic and diastolic blood pressure (mmHg) will be measured using facial and fingertip photoplethysmogram (PPG) technology in both sitting and standing postures.
Respiratory Rate - traditional measurement
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Respiratory rate (breaths per minute) will be measured by counting the number per minute manually.
Respiratory Rate - PPG estimation and facial analysis
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Respiratory rate (breaths per minute) will be estimated using independent or combined facial and fingertip photoplethysmogram (PPG) technology and facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Temperature - traditional measurement
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Temperature (°C) will be measured using a thermometer.
Temperature - PPG estimation and facial analysis
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Temperature (°C) will be estimated using independent or combined facial and fingertip photoplethysmogram (PPG) technology and facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Blood Oxygen Level - traditional measurement
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood oxygen level (SpO2) will be measured using a saturation meter
Blood Oxygen Level - PPG estimation and facial analysis
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood oxygen level (SpO2) will be estimated using independent or combined facial and fingertip photoplethysmogram (PPG) technology and facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Blood Glucose Level - traditional measurement
Time frame: A maximum of two sessions per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood glucose level (mmol/L or mg/dL) will be measured through blood tests.
Blood Glucose Level - PPG estimation and facial analysis
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Blood glucose level (mmol/L or mg/dL) will be estimated using independent or combined facial and fingertip photoplethysmogram (PPG) technology and facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Hydration Level - traditional measurement
Time frame: A maximum of two sessions per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Hydration level will be assessed through the number and type of dehydration symptoms.
Hydration Level - PPG estimation and facial analysis
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Hydration level will be estimated using independent or combined facial and fingertip photoplethysmogram (PPG) technology and facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Rating of Skin Conditions - traditional measurement
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Skin conditions will be assessed through the number and type of skin conditions.
Rating of Skin Conditions - PPG estimation and facial analysis
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Skin conditions will be estimated using facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Sit-Up-Squat-Stand Test - traditional measurement
Time frame: A maximum of two sessions per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Participants' core strength, flexibility, and balance will be assessed using the Sit-Up-Squat-Stand Test with a 4-point scale to separately rate Sit-Up and the Squat-Stand performance.
Sit-Up-Squat-Stand Test - PPG estimation and facial and body movement analysis
Time frame: A maximum of two sessions per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Participants' core strength, flexibility, and balance will be estimated by using independent or combined facial photoplethysmogram (PPG) technology and the analysis of changes in body movements and facial features. These movements and features will be identified and quantified using machine learning algorithms.
Single Anxiety and Depression Questions
Time frame: A maximum of two sessions per week, with two tests conducted after each set of readings, will be carried out from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Participants' anxiety and depression (mood) status on the day of the assessment session will be evaluated using two single-item questions, each with a 100-point visual analogue scale.
The Size of The Parotid Glands - traditional measurement
Time frame: A maximum of two sessions per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The size of the parotid glands will be assessed by clinicians or professionals to determine if it is normal.
The Size of The Parotid Glands - PPG estimation and facial and body movement analysis
Time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The size of the parotid glands will be estimated using facial feature analysis. These facial features will be identified and quantified using machine learning algorithms.
Blood Tests (full blood count)
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of full blood count.
Blood Tests (Haemoglobin)
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of Haemoglobin (g/dL or g/L).
Blood Tests (Platelets)
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of Platelets (10^3/μL or 10^9/L).
Blood Tests (white cell counts)
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of white cell counts (10^3/μL or 10^9/L).
Blood Tests (potassium (K+))
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of potassium (K+) (mEq/L or mmol/L).
Blood Tests (sodium (Na+))
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of sodium (Na+) (mEq/L or mmol/L).
Blood Tests (magnesium (Mg++))
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of magnesium (Mg++) (mEq/L, mg/dL, or mmol/L).
Blood Tests (phosphorous (PO4))
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of phosphorous (PO4) (mEq/L, mg/dL, or mmol/L).
Blood Tests (urea)
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of urea (mEq/L, mg/dL, or mmol/L).
Blood Tests (creatine kinase)
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of creatine kinase (U/L or µkat/L).
Blood Tests (albumin)
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of albumin (g/dL).
Blood Tests (alkaline phosphatase (ALP))
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of alkaline phosphatase (ALP) (U/L or µkat/L).
Blood Tests (aspartate transaminase (AST))
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of aspartate transaminase (AST) (U/L or µkat/L).
Blood Tests (alanine transaminase (ALT))
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of alanine transaminase (ALT) (U/L or µkat/L).
Blood Tests (gamma-glutamyl transferase (GGT))
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of gamma-glutamyl transferase (GGT) (U/L or µkat/L).
Blood Tests (bilirubin)
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of bilirubin (mg/dL or μmol/L).
Blood Tests (glucose)
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
The blood test is used to assess electrolyte balance, including the result of glucose (mg/dL or mmol/L).
Video Diary Entry
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
When participants are asked to record their thoughts on diary questions, changes in their aforementioned facial PPG-related biomarkers, facial features, and voice patterns, along with their qualitative responses, will be recorded and analysed. The facial features and voice patterns will be identified and quantified using machine learning algorithms.
Image Response Task
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
When participants are asked to record their thoughts on high-calorie food, low-calorie food, neutral, and positive images, changes in their aforementioned facial PPG-related biomarkers, facial features, and voice patterns, along with their qualitative responses, will be recorded and analysed. The facial features and voice patterns will be identified and quantified using machine learning algorithms.
Generalised Anxiety Disorder (GAD-7) and Patient Health (PHQ-9) Questionnaires
Time frame: A maximum of one session per week will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.
Participants' overall anxiety and depression levels will be assessed using the 7-item GAD-7 and the 9-item PHQ-9, respectively. Both scales are rated on a 4-point scale from 0 to 3. Adolescents will use the adolescent version of the PHQ-9 (PHQ-A), which employs the same scaling and scoring system, allowing for direct comparison with adults.
The Eating Disorder Examination Questionnaire (EDE-Q)
Time frame: Three times throughout the study: in Weeks 1, 8, and 16-or-at early discharge, or when care plans change and no further visits to clinical sites are scheduled before Week 16.
Participants' eating disorder traits, including eating restraint, eating concern, weight concern, and shape concern, along with qualitative responses regarding the frequency of eating disorder behaviours, will be assessed using the 28-item EDE-Q. This questionnaire is rated on a 7-point scale from 0 to 6. Adolescents will use the adolescent version of the EDE-Q (EDE-A). While this adolescent version contains 36 items, 28 of them capture the same domains as the adult version.
The Food-specific Stop Signal Task
Time frame: Three times throughout the study: in Weeks 1, 8, and 16-or-at early discharge, or when care plans change and no further visits to clinical sites are scheduled before Week 16.
Three variables are generated by this task to assess participants' inhibitory control related to food. These variables include stop signal reaction time (SSRT), go reaction time (GORT), and the proportion of successful stops or error rates. SSRT, measured in milliseconds, assesses the latency of inhibition and reflects an individual's ability to suppress an automatic response. GORT, also measured in milliseconds, evaluates the speed of responses to go signals, providing insight into baseline response times and overall task performance. The proportion of successful stops or error rates indicates the percentage of trials where participants successfully inhibit their responses.
Patient Acceptance Questionnaire
Time frame: Three times throughout the study: in Weeks 1, 8, and 16-or-at early discharge, or when care plans change and no further visits to clinical sites are scheduled before Week 16.
Participants' comfort with conducting the procedures of this study, such as recording their faces, will be assessed using an 8-item self-developed questionnaire with a 6-point rating scale, such as from 'Very comfortable' to 'Very uncomfortable'.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Dec 2024.
- Background: PubMed 12044197Johnson JG, Cohen P, Kasen S, Brook JS. Eating disorders during adolescence and the risk for physical and mental disorders during early adulthood. Arch Gen Psychiatry. 2002 Jun;59(6):545-52. doi: 10.1001/archpsyc.59.6.545.
- Background: PubMed 18949768Engel SG, Adair CE, Las Hayas C, Abraham S. Health-related quality of life and eating disorders: a review and update. Int J Eat Disord. 2009 Mar;42(2):179-87. doi: 10.1002/eat.20602.
- BackgroundThe Hearts Minds and Genes Coalition (2021). The Cost of Eating Disorders in the UK 2019 and 2020. The Hearts Minds and Genes Coalition. https://www.yumpu.com/en/document/view/65877873/the-cost-of-eating-disorders-in-the-uk-2019-and-2020-with-annex
- Background: PubMed 34327651Jenkins PE. Cost-of-illness for non-underweight binge-eating disorders. Eat Weight Disord. 2022 May;27(4):1377-1384. doi: 10.1007/s40519-021-01277-3. Epub 2021 Jul 30.
- BackgroundThe Royal College of Psychiatrists (2023). Medical Emergencies in Eating Disorders: Guidance on Recognition and Management. The Royal College of Psychiatrists. https://www.rcpsych.ac.uk/docs/default-source/improving-care/better-mh-policy/college-reports/college-report-cr233-medical-emergencies-in-eating-disorders-(meed)-guidance.pdf?sfvrsn=2d327483_63
- Background: PubMed 33689256Eating disorders: recognition and treatment. London: National Institute for Health and Care Excellence (NICE); 2020 Dec 16. Available from http://www.ncbi.nlm.nih.gov/books/NBK568394/
- BackgroundNHS England (2021). Hospital admissions for eating disorders. NHS England. https://digital.nhs.uk/supplementary-information/2021/hospital-admissions-for-eating-disorders-2015-2021
- Background: PubMed 21727255Arcelus J, Mitchell AJ, Wales J, Nielsen S. Mortality rates in patients with anorexia nervosa and other eating disorders. A meta-analysis of 36 studies. Arch Gen Psychiatry. 2011 Jul;68(7):724-31. doi: 10.1001/archgenpsychiatry.2011.74.
- BackgroundDantcheva, A., Bremond, F., & Bilinski, P. (2018). Show me your face and I will tell you your height, weight and body mass index. In 2018 24th International Conference on Pattern Recognition (ICPR) (pp. 3555-3560). IEEE.
- Background: PubMed 27504744Pascali MA, Giorgi D, Bastiani L, Buzzigoli E, Henriquez P, Matuszewski BJ, Morales MA, Colantonio S. Face morphology: Can it tell us something about body weight and fat? Comput Biol Med. 2016 Sep 1;76:238-49. doi: 10.1016/j.compbiomed.2016.06.006. Epub 2016 Jun 14.
- Background: PubMed 33110784Hasan S, Ahmed S, Panigrahi R, Chaudhary P, Vyas V, Saeed S. Oral cavity and eating disorders: An insight to holistic health. J Family Med Prim Care. 2020 Aug 25;9(8):3890-3897. doi: 10.4103/jfmpc.jfmpc_608_20. eCollection 2020 Aug.
- Background: PubMed 18253742Bozzato A, Burger P, Zenk J, Uter W, Iro H. Salivary gland biometry in female patients with eating disorders. Eur Arch Otorhinolaryngol. 2008 Sep;265(9):1095-102. doi: 10.1007/s00405-008-0598-8. Epub 2008 Feb 6.
- Individual participant dataSharing planned: No
Related trials for Eating Disorders
Not yet recruiting
Be Body Brave: Digital Written Exposure Therapy for Eating Disorders
Eating Disorders
Enrolling by invitationPhase 3
A Study to Assess the Long-term Safety and Efficacy of Solriamfetol in Subjects With Binge Eating Disorder
Binge-Eating Disorder
Recruiting
An Online Intuitive Eating Program for Pregnant Women With Obesity to Support Well-Being
Excessive Gestational Weight Gain, Pregnancy
Not yet recruiting
Compulsive Eating and Brain's Reward System in Different Pathologies
PARKINSON DISEASE (Disorder), Bipolar 1 Disorder
Not yet recruitingObservational study
Assessing the Impact of Perceptions of Unpredictability on Objective Measures of Food Consumption and Metabolism
Healthy Volunteer, Obestity
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Peter Sheng Yao Hsu, PhD contact
Daniel Joyce, MRCPsych principal investigator
University of Liverpool
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Eating Disorders, run by Univa Health at 1 site in United Kingdom.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 6 Dec 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Richard Andrews, BSc (+441488892853, research@univa.health), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Height and Weight - traditional measurement (time frame: A maximum of two sessions per week, with two readings per session, will be conducted from week 1 to week 16. The frequency may be adjusted to align with participants' clinical visits, but the maximum duration will remain 16 weeks.). The study lists 46 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06544226, which also lists 41 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Dec 2024.