Characterising illness stages and recovery trajectories of eating disorders in young people via remote measurement technology (STORY): a multi-centre prospective cohort study protocol.
Clinical staging
Eating disorders
Longitudinal monitoring
Observational cohort
Progression
Prospective study
Recovery
Remote measurement technology
Journal
BMC psychiatry
ISSN: 1471-244X
Titre abrégé: BMC Psychiatry
Pays: England
ID NLM: 100968559
Informations de publication
Date de publication:
30 May 2024
30 May 2024
Historique:
received:
24
04
2024
accepted:
13
05
2024
medline:
31
5
2024
pubmed:
31
5
2024
entrez:
30
5
2024
Statut:
epublish
Résumé
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. 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. 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.
Sections du résumé
BACKGROUND
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
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
CONCLUSIONS
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.
Identifiants
pubmed: 38816707
doi: 10.1186/s12888-024-05841-w
pii: 10.1186/s12888-024-05841-w
doi:
Types de publication
Journal Article
Multicenter Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
409Subventions
Organisme : Medical Research Council
ID : MR/W002418/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/W002418/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/W002418/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/W002418/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/W002418/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/W002418/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/W002418/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/W002418/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/W002418/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/W002418/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/W002418/1
Pays : United Kingdom
Informations de copyright
© 2024. The Author(s).
Références
Schmidt U, Adan R, Böhm I, Campbell IC, Dingemans A, Ehrlich S, et al. Eating disorders: The big issue. The Lancet Psychiatry. 2016;3(4):313–5.
pubmed: 27063378
doi: 10.1016/S2215-0366(16)00081-X
Treasure J, Duarte TA, Schmidt U. Eating Disorders. The Lancet. 2020;396(10227):800–911.
Qian J, Wu Y, Liu F, Zhu Y, Jin H, Zhang H, et al. An update on the prevalence of eating disorders in the general population: a systematic review and meta-analysis. Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity. 2022;27(2):415–28.
doi: 10.1007/s40519-021-01162-z
van Hoeken D, Hoek HW. Review of the burden of eating disorders: mortality, disability, costs, quality of life, and family burden. Curr Opin Psychiatry. 2020;33(6):521–7.
pubmed: 32796186
pmcid: 7575017
doi: 10.1097/YCO.0000000000000641
Solmi M, Radua J, Olivola M, Croce E, Soardo L, Salazar de Pablo G, et al. Age at onset of mental disorders worldwide: large-scale meta-analysis of 192 epidemiological studies. Mol Psychiatry. 2022;27(1):281–95.
pubmed: 34079068
doi: 10.1038/s41380-021-01161-7
Ambwani S, Cardi V, Albano G, Cao L, Crosby RD, Macdonald P, et al. A multicenter audit of outpatient care for adult anorexia nervosa: Symptom trajectory, service use, and evidence in support of “early stage” versus “severe and enduring” classification. Int J Eat Disord. 2020;53(8):1337–48.
pubmed: 32064663
doi: 10.1002/eat.23246
Keski-Rahkonen A, Mustelin L. Epidemiology of eating disorders in Europe: prevalence, incidence, comorbidity, course, consequences, and risk factors. Curr Opin Psychiatry. 2016;29(6):340–5.
pubmed: 27662598
doi: 10.1097/YCO.0000000000000278
Christian C, Williams BM, Hunt RA, Wong VZ, Ernst SE, Spoor SP, et al. A network investigation of core symptoms and pathways across duration of illness using a comprehensive cognitive–behavioral model of eating-disorder symptoms. Psychol Med. 2021;51(5):815–24.
pubmed: 31907093
doi: 10.1017/S0033291719003817
Slof-Op ’t Landt MCT, Dingemans AE, Giltay EJ. Eating disorder psychopathology dimensions based on individual co-occurrence patterns of symptoms over time: a dynamic time warp analysis in a large naturalistic patient cohor. Eat Weight Disord. 2022;27(8):3649–63.
pubmed: 36469226
doi: 10.1007/s40519-022-01504-5
Steinglass JE, Walsh BT. Neurobiological model of the persistence of anorexia nervosa. J Eat Disord. 2016;4(1):19.
pubmed: 27195123
pmcid: 4870737
doi: 10.1186/s40337-016-0106-2
National Institute for Health and Care Excellence. Eating disorders: recognition and treatment NICE guideline [NG69]. [Internet]. 2017. [cited 2024 April 19]. Available from: https://www.nice.org.uk/guidance/ng69 .
Royal College of Psychiatrists Position statement on early intervention for eating disorders 2019 [Available from: https://www.rcpsych.ac.uk/docs/default-source/improving-care/better-mh-policy/position-statements/ps03_19.pdf?sfvrsn=b1283556_2 .
McGorry PD, Purcell R, Hickie IB, Yung AR, Pantelis C, Jackson HJ. Clinical staging: a heuristic model for psychiatry and youth mental health. Med J Aust. 2007;187(S7):S40–2.
pubmed: 17908024
doi: 10.5694/j.1326-5377.2007.tb01335.x
Cosci F, Fava GA. Staging of Mental Disorders: Systematic Review. Psychother Psychosom. 2013;82(1):20–34.
pubmed: 23147126
doi: 10.1159/000342243
Shah JL, Jones N, van Os J, McGorry PD, Gülöksüz S. Early intervention service systems for youth mental health: integrating pluripotentiality, clinical staging, and transdiagnostic lessons from early psychosis. The Lancet Psychiatry. 2022;9(5):413–22.
pubmed: 35430004
doi: 10.1016/S2215-0366(21)00467-3
Hyam LE, Phillips M, Gracie L, Allen K, Schmidt U. Clinical staging across eating disorders: a scoping review protocol. BMJ Open. 2023;13(11):e077377.
pubmed: 37993158
pmcid: 10668169
doi: 10.1136/bmjopen-2023-077377
Treasure J, Willmott D, Ambwani S, Cardi V, Clark Bryan D, Rowlands K, Schmidt U. Cognitive Interpersonal Model for Anorexia Nervosa Revisited: The Perpetuating Factors that Contribute to the Development of the Severe and Enduring Illness. J Clin Med. 2020;9(3):630.
pubmed: 32120847
pmcid: 7141127
doi: 10.3390/jcm9030630
Solmi M, Monaco F, Højlund M, Monteleone AM, Trott M, Firth J, et al. Outcomes in people with eating disorders: a transdiagnostic and disorder-specific systematic review, meta-analysis and multivariable meta-regression analysis. World Psychiatry. 2024;23(1):124–38.
pubmed: 38214616
pmcid: 10785991
doi: 10.1002/wps.21182
Bardone-Cone AM, Hunt RA, Watson HJ. An Overview of Conceptualizations of Eating Disorder Recovery, Recent Findings, and Future Directions. Curr Psychiatry Rep. 2018;20(9):79.
pubmed: 30094740
doi: 10.1007/s11920-018-0932-9
Hower H, LaMarre A, Bachner-Melman R, Harrop EN, McGilley B, Kenny TE. Conceptualizing eating disorder recovery research: Current perspectives and future research directions. J Eat Disord. 2022;10(1):165.
pubmed: 36380392
pmcid: 9664434
doi: 10.1186/s40337-022-00678-8
de Vos JA, LaMarre A, Radstaak M, Bijkerk CA, Bohlmeijer ET, Westerhof GJ. Identifying fundamental criteria for eating disorder recovery: a systematic review and qualitative meta-analysis. J Eat Disord. 2017;5(1):34.
pubmed: 29118983
pmcid: 5664841
doi: 10.1186/s40337-017-0164-0
Miles S, Nedeljkovic M, Phillipou A. Investigating differences in cognitive flexibility, clinical perfectionism, and eating disorder-specific rumination across anorexia nervosa illness states. Eat Disord. 2023;31(6):610–31.
pubmed: 37128671
doi: 10.1080/10640266.2023.2206751
Wetzler S, Hackmann C, Peryer G, Clayman K, Friedman D, Saffran K, et al. A framework to conceptualize personal recovery from eating disorders: A systematic review and qualitative meta-synthesis of perspectives from individuals with lived experience. Int J Eat Disord. 2020;53(8):1188–203.
pubmed: 32181532
doi: 10.1002/eat.23260
Melbye S, Kessing LV, Bardram JE, Faurholt-Jepsen M. Smartphone-Based Self-Monitoring, Treatment, and Automatically Generated Data in Children, Adolescents, and Young Adults With Psychiatric Disorders: Systematic Review. JMIR Ment Health. 2020;7(10):e17453.
pubmed: 33118950
pmcid: 7661256
doi: 10.2196/17453
Hickey BA, Chalmers T, Newton P, Lin C-T, Sibbritt D, McLachlan CS, et al. Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review. Sensors. 2021;21(10):3461.
pubmed: 34065620
pmcid: 8156923
doi: 10.3390/s21103461
Cummins N, Dineley J, Conde P, Matcham F, Siddi S, Lamers F, et al. Multilingual markers of depression in remotely collected speech samples: A preliminary analysis. J Affect Disord. 2023;341:128–36.
pubmed: 37598722
doi: 10.1016/j.jad.2023.08.097
Presseller EK, Patarinski AGG, Fan SC, Lampe EW, Juarascio AS. Sensor technology in eating disorders research: A systematic review. Int J Eat Disord. 2022;55(5):573–624.
pubmed: 35489036
doi: 10.1002/eat.23715
Hemmings A, Sharpe H, Allen K, Bartel H, Campbell IC, Desrivières S, et al. EDIFY (Eating Disorders: Delineating Illness and Recovery Trajectories to Inform Personalised Prevention and Early Intervention in Young People): project outline. BJPsych Bulletin. 2023;47(6):328–36. https://doi.org/10.1192/bjb.2022.83 .
Brown A, McClelland J, Boysen E, Mountford V, Glennon D, Schmidt U. The FREED Project (first episode and rapid early intervention in eating disorders): service model, feasibility and acceptability. Early Interv Psychiatry. 2018;12(2):250–7.
pubmed: 27619198
doi: 10.1111/eip.12382
Crow SJ, Agras WS, Halmi K, Mitchell JE, Kraemer HC. Full syndromal versus subthreshold anorexia nervosa, bulimia nervosa, and binge eating disorder: A multicenter study. Int J Eat Disord. 2002;32(3):309–18.
pubmed: 12210645
doi: 10.1002/eat.10088
Matcham F, Barattieri di San Pietro C, Bulgari V, de Girolamo G, Dobson R, Eriksson H, et al. Remote assessment of disease and relapse in major depressive disorder (RADAR-MDD): a multi-centre prospective cohort study protocol. BMC Psychiatry. 2019;19(1):72.
pubmed: 30777041
pmcid: 6379954
doi: 10.1186/s12888-019-2049-z
King's College London ESTRA: Earlier detection and stratification of eating disorders and comorbid mental illnesses 2022 [Available from: https://www.kcl.ac.uk/research/estra .
Bulik CM, Thornton LM, Parker R, Kennedy H, Baker JH, MacDermod C, et al. The Eating Disorders Genetics Initiative (EDGI): study protocol. BMC Psychiatry. 2021;21(1):234.
pubmed: 33947359
pmcid: 8097919
doi: 10.1186/s12888-021-03212-3
Bright SJ, Hübel C, Young KS, Bristow S, Peel AJ, Rayner C, et al. Sociodemographic, mental health, and physical health factors associated with participation within re-contactable mental health cohorts: an investigation of the GLAD Study. BMC Psychiatry. 2023;23(1):542.
pubmed: 37495971
pmcid: 10373233
doi: 10.1186/s12888-023-04890-x
Halbeisen G, Brandt G, Paslakis G. A Plea for Diversity in Eating Disorders Research. Front Psychiatry. 2022;13:820043
pubmed: 35250670
pmcid: 8894317
doi: 10.3389/fpsyt.2022.820043
Stice E, Telch CF, Rizvi SL. Development and validation of the Eating Disorder Diagnostic Scale: A brief self-report measure of anorexia, bulimia, and binge-eating disorder. Psychol Assess. 2000;12(2):123–31.
pubmed: 10887758
doi: 10.1037/1040-3590.12.2.123
Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81.
pubmed: 18929686
doi: 10.1016/j.jbi.2008.08.010
Fairburn CG, Beglin S. Eating Disorder Examination Questionnaire (EDE-Q). In: Fairburn CG, editor. Cognitive Behaviour Therapy and Eating Disorders. New York, NY: Guilford Press; 2008. p. 317–60.
Schmidt U, Ryan EG, Bartholdy S, Renwick B, Keyes A, O’Hara C, et al. Two-year follow-up of the MOSAIC trial: A multicenter randomized controlled trial comparing two psychological treatments in adult outpatients with broadly defined anorexia nervosa. Int J Eat Disord. 2016;49(8):793–800.
pubmed: 27061709
doi: 10.1002/eat.22523
Tatham M, Turner H, Mountford VA, Tritt A, Dyas R, Waller G. Development, psychometric properties and preliminary clinical validation of a brief, session-by-session measure of eating disorder cognitions and behaviors: The ED-15. Int J Eat Disord. 2015;48(7):1005–15.
pubmed: 26011054
doi: 10.1002/eat.22430
Chua YW, Lewis G, Easter A, Lewis G, Solmi F. Eighteen-year trajectories of depressive symptoms in mothers with a lifetime eating disorder: findings from the ALSPAC cohort. Br J Psychiatry. 2020;216(2):90–6.
pubmed: 31084625
doi: 10.1192/bjp.2019.89
McCreary DR. The Drive for Muscularity Scale: Description, psychometrics, and research findings. In: Thompson JK, Cafri G, editors. The muscular ideal: Psychological, social, and medical perspectives. Washington, DC: American Psychological Association; 2007. p. 87–106.
doi: 10.1037/11581-004
McNair DM, Lorr M, Droppelman LF. Manual for the Profile of Mood States. San Diego, CA: Educational and Industrial Testing Service; 1971.
Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS scales. J Pers Soc Psychol. 1988;54(6):1063.
pubmed: 3397865
doi: 10.1037/0022-3514.54.6.1063
Kroenke K, Strine TW, Spitzer RL, Williams JBW, Berry JT, Mokdad AH. The PHQ-8 as a measure of current depression in the general population. J Affect Disord. 2009;114(1):163–73.
pubmed: 18752852
doi: 10.1016/j.jad.2008.06.026
Spitzer RL, Kroenke K, Williams JB, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166(10):1092–7.
pubmed: 16717171
doi: 10.1001/archinte.166.10.1092
Foa EB, Coles M, Huppert JD, Pasupuleti RV, Franklin ME, March J. Development and Validation of a Child Version of the Obsessive Compulsive Inventory. Behav Ther. 2010;41(1):121–32.
pubmed: 20171333
doi: 10.1016/j.beth.2009.02.001
Allison C, Auyeung B, Baron-Cohen S. Toward Brief “Red Flags” for Autism Screening: The Short Autism Spectrum Quotient and the Short Quantitative Checklist in 1,000 Cases and 3,000 Controls. J Am Acad Child Adolesc Psychiatry. 2012;51(2):202-12.e7.
pubmed: 22265366
doi: 10.1016/j.jaac.2011.11.003
Ashworth M, Shepherd M, Christey J, Matthews V, Wright K, Parmentier H, et al. A client-generated psychometric instrument: The development of ‘PSYCHLOPS.’ Couns Psychother Res. 2004;4(2):27–31.
doi: 10.1080/14733140412331383913
Jassi A, Lenhard F, Krebs G, Gumpert M, Jolstedt M, Andrén P, et al. The Work and Social Adjustment Scale, Youth and Parent Versions: Psychometric Evaluation of a Brief Measure of Functional Impairment in Young People. Child Psychiatry Hum Dev. 2020;51(3):453–60.
pubmed: 32006302
pmcid: 7235060
doi: 10.1007/s10578-020-00956-z
Bjureberg J, Ljótsson B, Tull MT, Hedman E, Sahlin H, Lundh L-G, et al. Development and Validation of a Brief Version of the Difficulties in Emotion Regulation Scale: The DERS-16. J Psychopathol Behav Assess. 2016;38(2):284–96.
pubmed: 27239096
doi: 10.1007/s10862-015-9514-x
Russell D, Peplau LA, Cutrona CE. The revised UCLA Loneliness Scale: Concurrent and discriminant validity evidence. J Pers Soc Psychol. 1980;39(3):472–80.
pubmed: 7431205
doi: 10.1037/0022-3514.39.3.472
Woicik PA, Stewart SH, Pihl RO, Conrod PJ. The substance use risk profile scale: A scale measuring traits linked to reinforcement-specific substance use profiles. Addict Behav. 2009;34(12):1042–55.
pubmed: 19683400
doi: 10.1016/j.addbeh.2009.07.001
Toledano MB, Mutz J, Röösli M, Thomas MSC, Dumontheil I, Elliott P. Cohort Profile: The Study of Cognition, Adolescents and Mobile Phones (SCAMP). Int J Epidemiol. 2019;48(1):25–6.
pubmed: 30325429
doi: 10.1093/ije/dyy192
Rodgers RF, McLean SA, Gordon CS, Slater A, Marques MD, Jarman HK, Paxton SJ. Development and Validation of the Motivations for Social Media Use Scale (MSMU) Among Adolescents. Adolescent Res Rev. 2021;6(4):425–35.
doi: 10.1007/s40894-020-00139-w
Saunders JB, Aasland OG, Babor TF, De La Fuente JR, Grant M. Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO Collaborative Project on Early Detection of Persons with Harmful Alcohol Consumption-II. Addiction. 1993;88(6):791–804.
pubmed: 8329970
doi: 10.1111/j.1360-0443.1993.tb02093.x
Perman-Howe PR, Horton M, Robson D, McDermott MS, McNeill A, Brose LS. Harm perceptions of nicotine-containing products and associated sources of information in UK adults with and without mental ill health: A cross-sectional survey. Addiction. 2022;117(3):715–29.
pubmed: 34338387
doi: 10.1111/add.15657
Matcham F, Leightley D, Siddi S, Lamers F, White KM, Annas P, et al. Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD): recruitment, retention, and data availability in a longitudinal remote measurement study. BMC Psychiatry. 2022;22(1):136.
pubmed: 35189842
pmcid: 8860359
doi: 10.1186/s12888-022-03753-1
Bruno E, Biondi A, Böttcher S, Vértes G, Dobson R, Folarin A, et al. Remote Assessment of Disease and Relapse in Epilepsy: Protocol for a Multicenter Prospective Cohort Study. JMIR Res Protoc. 2020;9(12):e21840.
pubmed: 33325373
pmcid: 7773514
doi: 10.2196/21840
Ranjan Y, Rashid Z, Stewart C, Conde P, Begale M, Verbeeck D, et al. RADAR-Base: Open Source Mobile Health Platform for Collecting, Monitoring, and Analyzing Data Using Sensors, Wearables, and Mobile Devices. JMIR Mhealth Uhealth. 2019;7(8):e11734.
pubmed: 31373275
pmcid: 6694732
doi: 10.2196/11734
International Phonetic Association. Handbook of the International Phonetic Association: A guide to the use of the International Phonetic Alphabet. Cambridge: Cambridge University Press; 1999.
Lammert Adam C, Melot J, Sturim Douglas E, Hannon Daniel J, DeLaura R, Williamson James R, et al. Analysis of Phonetic Balance in Standard English Passages. J Speech Lang Hear Res. 2020;63(4):917–30.
pubmed: 32302242
doi: 10.1044/2020_JSLHR-19-00001
Zhang Y, Folarin AA, Dineley J, Conde P, de Angel V, Sun S, et al. Identifying depression-related topics in smartphone-collected free-response speech recordings using an automatic speech recognition system and a deep learning topic model. J Affect Disord. 2024;355:40–9.
Vachon H, Viechtbauer W, Rintala A, Myin-Germeys I. Compliance and Retention With the Experience Sampling Method Over the Continuum of Severe Mental Disorders: Meta-Analysis and Recommendations. J Med Internet Res. 2019;21(12): e14475.
pubmed: 31808748
pmcid: 6925392
doi: 10.2196/14475
Kristiansson E, Fridolfsson J, Arvidsson D, Holmäng A, Börjesson M, Andersson-Hall U. Validation of Oura ring energy expenditure and steps in laboratory and free-living. BMC Med Res Methodol. 2023;23(1):50.
pubmed: 36829120
pmcid: 9950693
doi: 10.1186/s12874-023-01868-x
Miller DJ, Sargent C, Roach GD. A Validation of Six Wearable Devices for Estimating Sleep, Heart Rate and Heart Rate Variability in Healthy Adults. Sensors. 2022;22(16):6317.
pubmed: 36016077
pmcid: 9412437
doi: 10.3390/s22166317
Chami R, Cardi V, Lawrence N, MacDonald P, Rowlands K, Hodsoll J, Treasure J. Targeting binge eating in bulimia nervosa and binge eating disorder using inhibitory control training and implementation intentions: a feasibility trial. Psychol Med. 2022;52(5):874–83.
pubmed: 32713405
doi: 10.1017/S0033291720002494
Vogel V, Dittrich M, Horndasch S, Kratz O, Moll GH, Erim Y, et al. Pavlovian-to-instrumental transfer in Anorexia Nervosa: A pilot study on conditioned learning and instrumental responding to low- and high-calorie food stimuli. Eur J Neurosci. 2020;51(8):1794–805.
pubmed: 31606905
doi: 10.1111/ejn.14592
Steinglass J, Foerde K, Kostro K, Shohamy D, Walsh BT. Restrictive food intake as a choice—A paradigm for study. Int J Eat Disord. 2015;48(1):59–66.
pubmed: 25130380
doi: 10.1002/eat.22345
Werthmann J, Simic M, Konstantellou A, Mansfield P, Mercado D, van Ens W, Schmidt U. Same, same but different: Attention bias for food cues in adults and adolescents with anorexia nervosa. Int J Eat Disord. 2019;52(6):681–90.
pubmed: 30912189
doi: 10.1002/eat.23064
Kerr-Gaffney J, Jones E, Mason L, Hayward H, Murphy D, Loth E, Tchanturia K. Social attention in anorexia nervosa and autism spectrum disorder: Role of social motivation. Autism. 2022;26(7):1641–55.
pubmed: 34845940
doi: 10.1177/13623613211060593
Elsabbagh M, Volein A, Holmboe K, Tucker L, Csibra G, Baron-Cohen S, et al. Visual orienting in the early broader autism phenotype: disengagement and facilitation. J Child Psychol Psychiatry. 2009;50(5):637–42.
pubmed: 19298466
pmcid: 3272379
doi: 10.1111/j.1469-7610.2008.02051.x
Garrido L, Furl N, Draganski B, Weiskopf N, Stevens J, Tan GC-Y, et al. Voxel-based morphometry reveals reduced grey matter volume in the temporal cortex of developmental prosopagnosics. Brain. 2009;132(12):3443–55.
pubmed: 19887506
pmcid: 2792372
doi: 10.1093/brain/awp271
Glennon JM, D’Souza H, Mason L, Karmiloff-Smith A, Thomas MSC. Visuo-attentional correlates of Autism Spectrum Disorder (ASD) in children with Down syndrome: A comparative study with children with idiopathic ASD. Res Dev Disabil. 2020;104:103678.
pubmed: 32505966
pmcid: 7429984
doi: 10.1016/j.ridd.2020.103678
Diaz BA, Van Der Sluis S, Moens S, Benjamins J, Migliorati F, Stoffers D, et al. The Amsterdam Resting-State Questionnaire reveals multiple phenotypes of resting-state cognition. Front Human Neuroscience. 2013;7:446.
doi: 10.3389/fnhum.2013.00446
Knutson B, Westdorp A, Kaiser E, Hommer D. FMRI Visualization of Brain Activity during a Monetary Incentive Delay Task. Neuroimage. 2000;12(1):20–7.
pubmed: 10875899
doi: 10.1006/nimg.2000.0593
Bartholdy S, Dalton B, O’Daly OG, Campbell IC, Schmidt U. A systematic review of the relationship between eating, weight and inhibitory control using the stop signal task. Neurosci Biobehav Rev. 2016;64:35–62.
pubmed: 26900651
doi: 10.1016/j.neubiorev.2016.02.010
Eickhoff SB, Milham M, Vanderwal T. Towards clinical applications of movie fMRI. Neuroimage. 2020;217: 116860.
pubmed: 32376301
doi: 10.1016/j.neuroimage.2020.116860
Braun V, Clarke V. Conceptual and design thinking for thematic analysis. Qualitative Psychology. 2022;9(1):3–26.
doi: 10.1037/qup0000196
Flatt RE, Thornton LM, Smith T, Mitchell H, Argue S, Baucom BRW, et al. Retention, engagement, and binge-eating outcomes: Evaluating feasibility of the Binge-Eating Genetics Initiative study. Int J Eat Disord. 2022;55(8):1031–41.
pubmed: 35502471
pmcid: 9357123
doi: 10.1002/eat.23726
Bulik CM, Butner JE, Tregarthen J, Thornton LM, Flatt RE, Smith T, et al. The Binge Eating Genetics Initiative (BEGIN): study protocol. BMC Psychiatry. 2020;20(1):307.
pubmed: 32546136
pmcid: 7298834
doi: 10.1186/s12888-020-02698-7
Presseller EK, Lampe EW, Zhang F, Gable PA, Guetterman TC, Forman EM, Juarascio AS. Using Wearable Passive Sensing to Predict Binge Eating in Response to Negative Affect Among Individuals With Transdiagnostic Binge Eating: Protocol for an Observational Study. JMIR Res Protoc. 2023;12: e47098.
pubmed: 37410522
pmcid: 10360009
doi: 10.2196/47098
Cooper AR, Loeb KL, McGlinchey EL. Sleep and eating disorders: current research and future directions. Curr Opin Psychol. 2020;34:89–94.
pubmed: 31841832
doi: 10.1016/j.copsyc.2019.11.005
Peyser D, Scolnick B, Hildebrandt T, Taylor JA. Heart rate variability as a biomarker for anorexia nervosa: A review. Eur Eat Disord Rev. 2021;29(1):20–31.
pubmed: 32975349
doi: 10.1002/erv.2791
Tam HE, Ronan K. The application of a feedback-informed approach in psychological service with youth: Systematic review and meta-analysis. Clin Psychol Rev. 2017;55:41–55.
pubmed: 28501021
doi: 10.1016/j.cpr.2017.04.005
Parikh A, Fristad MA, Axelson D, Krishna R. Evidence Base for Measurement-Based Care in Child and Adolescent Psychiatry. Child Adolesc Psychiatr Clin N Am. 2020;29(4):587–99.
pubmed: 32891364
doi: 10.1016/j.chc.2020.06.001
Simpson CC, Mazzeo SE. Calorie counting and fitness tracking technology: Associations with eating disorder symptomatology. Eat Behav. 2017;26:89–92.
pubmed: 28214452
doi: 10.1016/j.eatbeh.2017.02.002
Boldi A, Silacci A, Boldi M-O, Cherubini M, Caon M, Zufferey N, et al. Exploring the impact of commercial wearable activity trackers on body awareness and body representations: A mixed-methods study on self-tracking. Comput Hum Behav. 2024;151:108036.
doi: 10.1016/j.chb.2023.108036
Oetzmann C, White KM, Ivan A, Julie J, Leightley D, Lavelle G, et al. Lessons learned from recruiting into a longitudinal remote measurement study in major depressive disorder. npj Digital Med. 2022;5(1):133.
doi: 10.1038/s41746-022-00680-z