Digital Behavior Change Interventions for Younger Children With Chronic Health Conditions: Systematic Review.
behavior
chronic illness
digital health
eHealth
electronic health
mHealth
mobile health
mobile phone
pediatrics
systematic review
Journal
Journal of medical Internet research
ISSN: 1438-8871
Titre abrégé: J Med Internet Res
Pays: Canada
ID NLM: 100959882
Informations de publication
Date de publication:
31 07 2020
31 07 2020
Historique:
received:
19
11
2019
accepted:
20
05
2020
revised:
30
04
2020
entrez:
1
8
2020
pubmed:
1
8
2020
medline:
8
1
2021
Statut:
epublish
Résumé
The prevalence of chronic health conditions in childhood is increasing, and behavioral interventions can support the management of these conditions. Compared with face-to-face treatment, the use of digital interventions may be more cost-effective, appealing, and accessible, but there has been inadequate attention to their use with younger populations (children aged 5-12 years). This systematic review aims to (1) identify effective digital interventions, (2) report the characteristics of promising interventions, and (3) describe the user's experience of the digital intervention. A total of 4 databases were searched (Excerpta Medica Database [EMBASE], PsycINFO, Medical Literature Analysis and Retrieval System Online [MEDLINE], and the Cochrane Library) between January 2014 and January 2019. The inclusion criteria for studies were as follows: (1) children aged between 5 and 12 years, (2) interventions for behavior change, (3) randomized controlled trials, (4) digital interventions, and (5) chronic health conditions. Two researchers independently double reviewed papers to assess eligibility, extract data, and assess quality. Searches run in the databases identified 2643 papers. We identified 17 eligible interventions. The most promising interventions (having a beneficial effect and low risk of bias) were 3 targeting overweight or obesity, using exergaming or social media, and 2 for anxiety, using web-based cognitive behavioral therapy (CBT). Characteristics of promising interventions included gaming features, therapist support, and parental involvement. Most were purely behavioral interventions (rather than CBT or third wave), typically using the behavior change techniques (BCTs) feedback and monitoring, shaping knowledge, repetition and substitution, and reward. Three papers included qualitative data on the user's experience. We developed the following themes: parental involvement, connection with a health professional is important for engagement, technological affordances and barriers, and child-centered design. Of the 17 eligible interventions, digital interventions for anxiety and overweight or obesity had the greatest promise. Using qualitative methods during digital intervention development and evaluation may lead to more meaningful, usable, feasible, and engaging interventions, especially for this underresearched younger population. The following characteristics could be considered when developing digital interventions for younger children: involvement of parents, gaming features, additional therapist support, behavioral (rather than cognitive) approaches, and particular BCTs (feedback and monitoring, shaping knowledge, repetition and substitution, and reward). This review suggests a model for improving the conceptualization and reporting of behavioral interventions involving children and parents.
Sections du résumé
BACKGROUND
The prevalence of chronic health conditions in childhood is increasing, and behavioral interventions can support the management of these conditions. Compared with face-to-face treatment, the use of digital interventions may be more cost-effective, appealing, and accessible, but there has been inadequate attention to their use with younger populations (children aged 5-12 years).
OBJECTIVE
This systematic review aims to (1) identify effective digital interventions, (2) report the characteristics of promising interventions, and (3) describe the user's experience of the digital intervention.
METHODS
A total of 4 databases were searched (Excerpta Medica Database [EMBASE], PsycINFO, Medical Literature Analysis and Retrieval System Online [MEDLINE], and the Cochrane Library) between January 2014 and January 2019. The inclusion criteria for studies were as follows: (1) children aged between 5 and 12 years, (2) interventions for behavior change, (3) randomized controlled trials, (4) digital interventions, and (5) chronic health conditions. Two researchers independently double reviewed papers to assess eligibility, extract data, and assess quality.
RESULTS
Searches run in the databases identified 2643 papers. We identified 17 eligible interventions. The most promising interventions (having a beneficial effect and low risk of bias) were 3 targeting overweight or obesity, using exergaming or social media, and 2 for anxiety, using web-based cognitive behavioral therapy (CBT). Characteristics of promising interventions included gaming features, therapist support, and parental involvement. Most were purely behavioral interventions (rather than CBT or third wave), typically using the behavior change techniques (BCTs) feedback and monitoring, shaping knowledge, repetition and substitution, and reward. Three papers included qualitative data on the user's experience. We developed the following themes: parental involvement, connection with a health professional is important for engagement, technological affordances and barriers, and child-centered design.
CONCLUSIONS
Of the 17 eligible interventions, digital interventions for anxiety and overweight or obesity had the greatest promise. Using qualitative methods during digital intervention development and evaluation may lead to more meaningful, usable, feasible, and engaging interventions, especially for this underresearched younger population. The following characteristics could be considered when developing digital interventions for younger children: involvement of parents, gaming features, additional therapist support, behavioral (rather than cognitive) approaches, and particular BCTs (feedback and monitoring, shaping knowledge, repetition and substitution, and reward). This review suggests a model for improving the conceptualization and reporting of behavioral interventions involving children and parents.
Identifiants
pubmed: 32735227
pii: v22i7e16924
doi: 10.2196/16924
pmc: PMC7428934
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Systematic Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
e16924Informations de copyright
©Amberly Brigden, Emma Anderson, Catherine Linney, Richard Morris, Roxanne Parslow, Teona Serafimova, Lucie Smith, Emily Briggs, Maria Loades, Esther Crawley. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 31.07.2020.
Références
Am J Prev Med. 2016 Nov;51(5):816-824
pubmed: 27745681
Pediatr Phys Ther. 2019 Jan;31(1):129
pubmed: 30557292
J Med Internet Res. 2014 Feb 18;16(2):e51
pubmed: 24550161
Hosp Pediatr. 2018 Oct;8(10):643-650
pubmed: 30213798
Health Aff (Millwood). 2014 Dec;33(12):2099-105
pubmed: 25489027
J Pediatr Rehabil Med. 2017 May 17;10(2):145-154
pubmed: 28582885
Pediatrics. 2015 Apr;135(4):e927-38
pubmed: 25755242
J Health Serv Res Policy. 2002 Oct;7(4):209-15
pubmed: 12425780
Games Health J. 2016 Dec;5(6):413-421
pubmed: 27911621
J Child Psychol Psychiatry. 2017 Apr;58(4):474-503
pubmed: 27943285
Games Health J. 2017 Feb;6(1):19-27
pubmed: 28051877
Behav Res Ther. 2017 Mar;90:67-75
pubmed: 28012300
Behav Res Ther. 2016 Jan;76:47-56
pubmed: 26649465
Medicine (Baltimore). 2018 Sep;97(36):e12061
pubmed: 30200086
Clin Child Fam Psychol Rev. 2019 Jun;22(2):147-171
pubmed: 30229343
Worldviews Evid Based Nurs. 2014 Apr;11(2):81-8
pubmed: 24597522
Health Psychol. 2010 Jan;29(1):1-8
pubmed: 20063930
Lancet Child Adolesc Health. 2018 Nov;2(11):792-801
pubmed: 30241993
J Health Commun. 2015;20(7):843-50
pubmed: 25996181
Br J Psychiatry. 2010 Nov;197(5):378-85
pubmed: 21037215
J Adv Nurs. 2017 Apr;73(4):794-811
pubmed: 27688056
PLoS One. 2014 May 20;9(5):e98118
pubmed: 24844847
J Med Internet Res. 2016 Feb 16;18(2):e26
pubmed: 26883052
Trials. 2014 Jan 14;15:20
pubmed: 24422788
BMC Med Res Methodol. 2007 Jul 05;7:32
pubmed: 17615054
Ann Epidemiol. 2006 Feb;16(2):91-104
pubmed: 16257232
Cochrane Database Syst Rev. 2015 Apr 15;(4):CD009660
pubmed: 25874881
Nutr J. 2018 Aug 2;17(1):74
pubmed: 30071855
Clin Psychol Rev. 2004 Aug;24(4):399-420
pubmed: 15245828
Control Clin Trials. 1989 Dec;10(4):407-15
pubmed: 2691207
Soc Sci Med. 2010 May;70(10):1618-25
pubmed: 20207464
Pediatr Obes. 2018 Nov;13(11):724-733
pubmed: 30027607
Int J Nurs Stud. 2013 May;50(5):587-92
pubmed: 23159157
Pediatrics. 2015 Apr;135(4):e965-73
pubmed: 25755233
Psychol Res Behav Manag. 2012;5:25-36
pubmed: 22427736
Pain. 2016 Jan;157(1):174-85
pubmed: 26335910
Curr Opin Psychiatry. 2012 Nov;25(6):522-8
pubmed: 22992547
Ann Behav Med. 2013 Aug;46(1):81-95
pubmed: 23512568
BMJ. 2014 Mar 07;348:g1687
pubmed: 24609605
BMJ. 2000 Jul 29;321(7256):255-6
pubmed: 10915111
BMC Public Health. 2015 Feb 12;15:130
pubmed: 25886385
J R Soc Med. 2016 Oct;109(10):364-366
pubmed: 27729592
Eur J Pediatr. 2008 Dec;167(12):1441-7
pubmed: 18340463
Child Obes. 2018 Jan;14(1):4-10
pubmed: 29019418
Br J Health Psychol. 2016 Sep;21(3):493-8
pubmed: 27028293
J Clin Psychiatry. 2015 Oct;76(10):e1320-3
pubmed: 26528658
Transl Behav Med. 2018 Mar 1;8(2):212-224
pubmed: 29381786
J Med Internet Res. 2015 Feb 24;17(2):e52
pubmed: 25803266
Telemed J E Health. 2014 Jun;20(6):570-83
pubmed: 24787747
Behav Res Ther. 2015 Apr;67:1-18
pubmed: 25727678
Health Psychol Rev. 2016;10(1):89-112
pubmed: 26315814
Diabetes Technol Ther. 2019 Jan;21(1):51-55
pubmed: 30620642
J Med Internet Res. 2013 Dec 06;15(12):e272
pubmed: 24317406
JAMA. 2010 Feb 17;303(7):682
pubmed: 20159879
BMJ. 2019 Aug 28;366:l4898
pubmed: 31462531
J Health Psychol. 2015 Jun;20(6):806-15
pubmed: 26032797
J Clin Epidemiol. 2009 Oct;62(10):e1-34
pubmed: 19631507
BMJ. 2001 Dec 1;323(7324):1280-4
pubmed: 11731390
Cochrane Database Syst Rev. 2018 Aug 15;8:CD012489
pubmed: 30110718
J Med Internet Res. 2015 Jan 30;17(1):e30
pubmed: 25639757
Am Psychol. 2016 Oct;71(7):590-601
pubmed: 27690487
Res Synth Methods. 2013 Mar;4(1):12-25
pubmed: 26053536
Health Technol Assess. 2014 Jul;18(47):i-xxiii, 1-75
pubmed: 25043221
Patient Educ Couns. 2013 Jul;92(1):13-22
pubmed: 23566427
Arch Dis Child. 2015 Apr;100(4):308-16
pubmed: 25784736
JAMA Pediatr. 2014 May;168(5):407-13
pubmed: 24589566
J Pediatr Psychol. 2009 Jun;34(5):495-510
pubmed: 19029142
J Adolesc Health. 2017 Dec;61(6):669-677
pubmed: 28822682
Arch Pediatr Adolesc Med. 2005 Dec;159(12):1173-80
pubmed: 16330743
Paediatr Perinat Epidemiol. 1997 Jan;11(1):2-20
pubmed: 9018723
Behav Res Ther. 2016 Apr;79:35-45
pubmed: 26950257
J Clin Psychol. 2004 Mar;60(3):269-83
pubmed: 14981791
Epidemiol Rev. 2010;32:56-69
pubmed: 20354039
J Pediatr Psychol. 2014 Sep;39(8):918-31
pubmed: 24952359
Public Health. 2012 Sep;126 Suppl 1:S4-S10
pubmed: 22784581
Diabetes Care. 2014 Jun;37(6):1759-66
pubmed: 24855158
Expert Rev Neurother. 2012 Jul;12(7):861-9; quiz 870
pubmed: 22853793
J Am Med Inform Assoc. 2016 Jan;23(1):230-9
pubmed: 26186934
Clin Rehabil. 2016 Oct;30(10):1004-1015
pubmed: 26370148
PLoS One. 2015 Mar 18;10(3):e0119895
pubmed: 25786025