Using Personalized Avatars as an Adjunct to an Adult Weight Loss Management Program: Randomized Controlled Feasibility Study.

avatar feasibility obesity weight loss weight management

Journal

JMIR formative research
ISSN: 2561-326X
Titre abrégé: JMIR Form Res
Pays: Canada
ID NLM: 101726394

Informations de publication

Date de publication:
05 Oct 2022
Historique:
received: 11 01 2022
accepted: 23 07 2022
revised: 18 07 2022
entrez: 5 10 2022
pubmed: 6 10 2022
medline: 6 10 2022
Statut: epublish

Résumé

Obesity is a global public health concern. Interventions rely predominantly on managing dietary intake and increasing physical activity; however, sustained adherence to behavioral regimens is often poor. The lack of sustained motivation, self-efficacy, and poor adherence to behavioral regimens are recognized barriers to successful weight loss. Avatar-based interventions achieve better patient outcomes in the management of chronic conditions by promoting more active engagement. Virtual representations of self can affect real-world behavior, acting as a catalyst for sustained weight loss behavior. We evaluated whether a personalized avatar, offered as an adjunct to an established weight loss program, can increase participant motivation, sustain engagement, optimize service delivery, and improve participant health outcomes. A feasibility randomized design was used to determine the case for future development and evaluation of avatar-based technology in a randomized controlled trial. Participants were recruited from general practitioner referrals to a 12-week National Health Service weight improvement program. The main outcome measure was weight loss. Secondary outcome measures were quality-of-life and self-efficacy. Quantitative data were subjected to descriptive statistical tests and exploratory comparison between intervention and control arms. Feasibility and acceptability were assessed through interviews and analyzed using framework approach. Health Research Authority ethics approval was granted. Overall, 10 men (n=7, 70% for routine care and avatar and n=3, 30% for routine care) and 33 women (n=23, 70% for intervention and n=10, 30% for routine care) were recruited. Participants' initial mean weight was greater in the intervention arm than in the routine care arm (126.3 kg vs 122.9 kg); pattern of weight loss was similar across both arms of the study in T0 to T1 period but accelerated in T1 to T2 period for intervention participants, suggesting that access to the self-resembling avatar may promote greater engagement with weight loss initiatives in the short-to-medium term. Mean change in participants' weight from T0 to T2 was 4.5 kg (95% CI 2.7-6.3) in the routine care arm and 5.3 kg (95% CI 3.9-6.8) in the intervention arm. Quality-of-life and self-efficacy measures demonstrated greater improvement in the intervention arm at both T1 (105.5 for routine care arm and 99.7 for intervention arm) and T2 (100.1 for routine care arm and 81.2 for intervention arm). Overall, 13 participants (n=11, 85% women and n=2, 15% men) and two health care professionals were interviewed about their experience of using the avatar program. Participants found using the personalized avatar acceptable, and feedback reiterated that seeing a future self helped to reinforce motivation to change behavior. This feasibility study demonstrated that avatar-based technology may successfully promote engagement and motivation in weight loss programs, enabling participants to achieve greater weight loss gains and build self-confidence. ISRCTN Registry 17953876; https://doi.org/10.1186/ISRCTN17953876.

Sections du résumé

BACKGROUND BACKGROUND
Obesity is a global public health concern. Interventions rely predominantly on managing dietary intake and increasing physical activity; however, sustained adherence to behavioral regimens is often poor. The lack of sustained motivation, self-efficacy, and poor adherence to behavioral regimens are recognized barriers to successful weight loss. Avatar-based interventions achieve better patient outcomes in the management of chronic conditions by promoting more active engagement. Virtual representations of self can affect real-world behavior, acting as a catalyst for sustained weight loss behavior.
OBJECTIVE OBJECTIVE
We evaluated whether a personalized avatar, offered as an adjunct to an established weight loss program, can increase participant motivation, sustain engagement, optimize service delivery, and improve participant health outcomes.
METHODS METHODS
A feasibility randomized design was used to determine the case for future development and evaluation of avatar-based technology in a randomized controlled trial. Participants were recruited from general practitioner referrals to a 12-week National Health Service weight improvement program. The main outcome measure was weight loss. Secondary outcome measures were quality-of-life and self-efficacy. Quantitative data were subjected to descriptive statistical tests and exploratory comparison between intervention and control arms. Feasibility and acceptability were assessed through interviews and analyzed using framework approach. Health Research Authority ethics approval was granted.
RESULTS RESULTS
Overall, 10 men (n=7, 70% for routine care and avatar and n=3, 30% for routine care) and 33 women (n=23, 70% for intervention and n=10, 30% for routine care) were recruited. Participants' initial mean weight was greater in the intervention arm than in the routine care arm (126.3 kg vs 122.9 kg); pattern of weight loss was similar across both arms of the study in T0 to T1 period but accelerated in T1 to T2 period for intervention participants, suggesting that access to the self-resembling avatar may promote greater engagement with weight loss initiatives in the short-to-medium term. Mean change in participants' weight from T0 to T2 was 4.5 kg (95% CI 2.7-6.3) in the routine care arm and 5.3 kg (95% CI 3.9-6.8) in the intervention arm. Quality-of-life and self-efficacy measures demonstrated greater improvement in the intervention arm at both T1 (105.5 for routine care arm and 99.7 for intervention arm) and T2 (100.1 for routine care arm and 81.2 for intervention arm). Overall, 13 participants (n=11, 85% women and n=2, 15% men) and two health care professionals were interviewed about their experience of using the avatar program.
CONCLUSIONS CONCLUSIONS
Participants found using the personalized avatar acceptable, and feedback reiterated that seeing a future self helped to reinforce motivation to change behavior. This feasibility study demonstrated that avatar-based technology may successfully promote engagement and motivation in weight loss programs, enabling participants to achieve greater weight loss gains and build self-confidence.
TRIAL REGISTRATION BACKGROUND
ISRCTN Registry 17953876; https://doi.org/10.1186/ISRCTN17953876.

Identifiants

pubmed: 36197703
pii: v6i10e36275
doi: 10.2196/36275
pmc: PMC9582922
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e36275

Informations de copyright

©Maria Horne, Maryann Hardy, Trevor Murrells, Hassan Ugail, Andrew John Hill. Originally published in JMIR Formative Research (https://formative.jmir.org), 05.10.2022.

Références

Curr Cardiovasc Risk Rep. 2012 Apr;6(2):120-134
pubmed: 23082235
J Diabetes Sci Technol. 2013 Jul 01;7(4):1057-65
pubmed: 23911189
Int J Environ Res Public Health. 2020 Jun 05;17(11):
pubmed: 32517117
Annu Rev Psychol. 2001;52:1-26
pubmed: 11148297
J Med Internet Res. 2012 Sep 20;14(5):e120
pubmed: 22995535
Obes Sci Pract. 2020 Aug 27;6(6):587-595
pubmed: 33354337
Public Health Nutr. 2022 Sep;25(9):2426-2435
pubmed: 35190011
Clin Obes. 2017 Oct;7(5):290-299
pubmed: 28544443
Nutrients. 2021 Dec 30;14(1):
pubmed: 35011045
J Technol Behav Sci. 2021 Jun;6(2):406-418
pubmed: 35356149
Obes Rev. 2011 Nov;12(11):912-34
pubmed: 21815990
Trials. 2014 Jul 03;15:264
pubmed: 24993581
Immun Ageing. 2021 Jan 4;18(1):1
pubmed: 33390183
Eat Behav. 2012 Dec;13(4):375-8
pubmed: 23121791
Telemed J E Health. 2010 Nov;16(9):931-8
pubmed: 21091286
JMIR Mhealth Uhealth. 2019 Dec 13;7(12):e13311
pubmed: 31833836
BJS Open. 2021 Mar 5;5(2):
pubmed: 33688953
BMJ. 2008 Sep 29;337:a1655
pubmed: 18824488
JAMA. 2018 Sep 18;320(11):1172-1191
pubmed: 30326501
BMJ. 2014 May 14;348:g2646
pubmed: 25134100
Internet Interv. 2019 Nov 28;19:100295
pubmed: 31871900
BMJ. 2022 May 30;377:e069719
pubmed: 35636762
Lancet. 2011 Aug 27;378(9793):815-25
pubmed: 21872750
Philos Trans R Soc Lond B Biol Sci. 2011 Jun 27;366(1572):1905-12
pubmed: 21576148
Qual Life Res. 2011 Dec;20(10):1727-36
pubmed: 21479777
Am J Public Health. 2010 Jun;100(6):1019-28
pubmed: 20075322
Nutrients. 2022 May 10;14(10):
pubmed: 35631145
J Hum Nutr Diet. 2021 Jun;34(3):485-493
pubmed: 33368624
J Am Diet Assoc. 2007 Oct;107(10):1755-67
pubmed: 17904936
J Public Health (Oxf). 2011 Dec;33(4):527-35
pubmed: 21562029
Diabetes Obes Metab. 2021 Feb;23 Suppl 1:50-62
pubmed: 32969147
J Mark Res. 2011 Nov;48:S23-S37
pubmed: 24634544
Obes Facts. 2021;14(3):320-333
pubmed: 33915534
J Diabetes Sci Technol. 2011 Mar 01;5(2):265-71
pubmed: 21527092

Auteurs

Maria Horne (M)

Faculty of Medicine and Health, School of Healthcare, University of Leeds, Leeds, United Kingdom.

Maryann Hardy (M)

Faculty of Health Studies, School of Allied Health Professions and Midwifery, University of Bradford, Bradford, United Kingdom.

Trevor Murrells (T)

Florence Nightingale Faculty of Nursing, Midwifery and Palliative Care, King's College London, London, United Kingdom.

Hassan Ugail (H)

University of Bradford, Centre for Visual Computing, Bradford, United Kingdom.

Andrew John Hill (AJ)

Institute of Health Sciences, School of Medicine, University of Leeds, Leeds, United Kingdom.

Classifications MeSH