Assessing the Pragmatic Nature of Mobile Health Interventions Promoting Physical Activity: Systematic Review and Meta-analysis.

PRECIS-2 Pragmatic-Explanatory Continuum Indicator Summary-2 RE-AIM Reach, Effectiveness, Adoption, Implementation, Maintenance digital health mHealth meta-analysis mobile health mobile phone physical activity systematic review

Journal

JMIR mHealth and uHealth
ISSN: 2291-5222
Titre abrégé: JMIR Mhealth Uhealth
Pays: Canada
ID NLM: 101624439

Informations de publication

Date de publication:
04 05 2023
Historique:
received: 01 10 2022
accepted: 14 03 2023
revised: 20 02 2023
medline: 8 5 2023
pubmed: 4 5 2023
entrez: 4 5 2023
Statut: epublish

Résumé

Mobile health (mHealth) apps can promote physical activity; however, the pragmatic nature (ie, how well research translates into real-world settings) of these studies is unknown. The impact of study design choices, for example, intervention duration, on intervention effect sizes is also understudied. This review and meta-analysis aims to describe the pragmatic nature of recent mHealth interventions for promoting physical activity and examine the associations between study effect size and pragmatic study design choices. The PubMed, Scopus, Web of Science, and PsycINFO databases were searched until April 2020. Studies were eligible if they incorporated apps as the primary intervention, were conducted in health promotion or preventive care settings, included a device-based physical activity outcome, and used randomized study designs. Studies were assessed using the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) and Pragmatic-Explanatory Continuum Indicator Summary-2 (PRECIS-2) frameworks. Study effect sizes were summarized using random effect models, and meta-regression was used to examine treatment effect heterogeneity by study characteristics. Overall, 3555 participants were included across 22 interventions, with sample sizes ranging from 27 to 833 (mean 161.6, SD 193.9, median 93) participants. The study populations' mean age ranged from 10.6 to 61.5 (mean 39.6, SD 6.5) years, and the proportion of males included across all studies was 42.8% (1521/3555). Additionally, intervention lengths varied from 2 weeks to 6 months (mean 60.9, SD 34.9 days). The primary app- or device-based physical activity outcome differed among interventions: most interventions (17/22, 77%) used activity monitors or fitness trackers, whereas the rest (5/22, 23%) used app-based accelerometry measures. Data reporting across the RE-AIM framework was low (5.64/31, 18%) and varied within specific dimensions (Reach=44%; Effectiveness=52%; Adoption=3%; Implementation=10%; Maintenance=12.4%). PRECIS-2 results indicated that most study designs (14/22, 63%) were equally explanatory and pragmatic, with an overall PRECIS-2 score across all interventions of 2.93/5 (SD 0.54). The most pragmatic dimension was flexibility (adherence), with an average score of 3.73 (SD 0.92), whereas follow-up, organization, and flexibility (delivery) appeared more explanatory with means of 2.18 (SD 0.75), 2.36 (SD 1.07), and 2.41 (SD 0.72), respectively. An overall positive treatment effect was observed (Cohen d=0.29, 95% CI 0.13-0.46). Meta-regression analyses revealed that more pragmatic studies (-0.81, 95% CI -1.36 to -0.25) were associated with smaller increases in physical activity. Treatment effect sizes were homogenous across study duration, participants' age and gender, and RE-AIM scores. App-based mHealth physical activity studies continue to underreport several key study characteristics and have limited pragmatic use and generalizability. In addition, more pragmatic interventions observe smaller treatment effects, whereas study duration appears to be unrelated to the effect size. Future app-based studies should more comprehensively report real-world applicability, and more pragmatic approaches are needed for maximal population health impacts. PROSPERO CRD42020169102; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=169102.

Sections du résumé

BACKGROUND
Mobile health (mHealth) apps can promote physical activity; however, the pragmatic nature (ie, how well research translates into real-world settings) of these studies is unknown. The impact of study design choices, for example, intervention duration, on intervention effect sizes is also understudied.
OBJECTIVE
This review and meta-analysis aims to describe the pragmatic nature of recent mHealth interventions for promoting physical activity and examine the associations between study effect size and pragmatic study design choices.
METHODS
The PubMed, Scopus, Web of Science, and PsycINFO databases were searched until April 2020. Studies were eligible if they incorporated apps as the primary intervention, were conducted in health promotion or preventive care settings, included a device-based physical activity outcome, and used randomized study designs. Studies were assessed using the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) and Pragmatic-Explanatory Continuum Indicator Summary-2 (PRECIS-2) frameworks. Study effect sizes were summarized using random effect models, and meta-regression was used to examine treatment effect heterogeneity by study characteristics.
RESULTS
Overall, 3555 participants were included across 22 interventions, with sample sizes ranging from 27 to 833 (mean 161.6, SD 193.9, median 93) participants. The study populations' mean age ranged from 10.6 to 61.5 (mean 39.6, SD 6.5) years, and the proportion of males included across all studies was 42.8% (1521/3555). Additionally, intervention lengths varied from 2 weeks to 6 months (mean 60.9, SD 34.9 days). The primary app- or device-based physical activity outcome differed among interventions: most interventions (17/22, 77%) used activity monitors or fitness trackers, whereas the rest (5/22, 23%) used app-based accelerometry measures. Data reporting across the RE-AIM framework was low (5.64/31, 18%) and varied within specific dimensions (Reach=44%; Effectiveness=52%; Adoption=3%; Implementation=10%; Maintenance=12.4%). PRECIS-2 results indicated that most study designs (14/22, 63%) were equally explanatory and pragmatic, with an overall PRECIS-2 score across all interventions of 2.93/5 (SD 0.54). The most pragmatic dimension was flexibility (adherence), with an average score of 3.73 (SD 0.92), whereas follow-up, organization, and flexibility (delivery) appeared more explanatory with means of 2.18 (SD 0.75), 2.36 (SD 1.07), and 2.41 (SD 0.72), respectively. An overall positive treatment effect was observed (Cohen d=0.29, 95% CI 0.13-0.46). Meta-regression analyses revealed that more pragmatic studies (-0.81, 95% CI -1.36 to -0.25) were associated with smaller increases in physical activity. Treatment effect sizes were homogenous across study duration, participants' age and gender, and RE-AIM scores.
CONCLUSIONS
App-based mHealth physical activity studies continue to underreport several key study characteristics and have limited pragmatic use and generalizability. In addition, more pragmatic interventions observe smaller treatment effects, whereas study duration appears to be unrelated to the effect size. Future app-based studies should more comprehensively report real-world applicability, and more pragmatic approaches are needed for maximal population health impacts.
TRIAL REGISTRATION
PROSPERO CRD42020169102; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=169102.

Identifiants

pubmed: 37140972
pii: v11i1e43162
doi: 10.2196/43162
pmc: PMC10196895
doi:

Types de publication

Meta-Analysis Systematic Review Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

e43162

Informations de copyright

©Chad Stecher, Bjorn Pfisterer, Samantha M Harden, Dana Epstein, Jakob M Hirschmann, Kathrin Wunsch, Matthew P Buman. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 04.05.2023.

Références

Int J Med Inform. 2014 Jul;83(7):e1-11
pubmed: 23910896
J Orthop Sports Phys Ther. 2003 Apr;33(4):163-5
pubmed: 12723672
J Med Internet Res. 2016 Oct 31;18(11):e287
pubmed: 27806926
Prev Sci. 2019 Aug;20(6):863-872
pubmed: 30788692
J Am Coll Health. 2022 Jan;70(1):89-98
pubmed: 32150514
J Behav Med. 2017 Oct;40(5):712-729
pubmed: 28255750
Mhealth. 2016 Dec 19;2:45
pubmed: 28293615
J Med Internet Res. 2018 Apr 18;20(4):e122
pubmed: 29669703
JMIR Mhealth Uhealth. 2018 Jan 11;6(1):e14
pubmed: 29326093
Implement Sci. 2021 Jan 7;16(1):7
pubmed: 33413489
Int J Behav Nutr Phys Act. 2008 Nov 06;5:56
pubmed: 18990237
CMAJ. 2006 Mar 14;174(6):801-9
pubmed: 16534088
BMJ. 2009 Jul 21;339:b2700
pubmed: 19622552
Int J Environ Res Public Health. 2020 Nov 07;17(21):
pubmed: 33171871
PLoS Med. 2009 Jul 21;6(7):e1000097
pubmed: 19621072
Int J Behav Nutr Phys Act. 2014 Jun 17;11:77
pubmed: 24938641
Am J Public Health. 2012 Sep;102(9):1633-7
pubmed: 22813092
Br J Gen Pract. 2014 Jul;64(624):e384-91
pubmed: 24982490
J Environ Health Sci. 2016 Nov;2(6):
pubmed: 28428979
BMC Med Res Methodol. 2003 Dec 22;3:28
pubmed: 14690550
Women Health. 2020 Feb;60(2):212-223
pubmed: 31113310
JMIR Mhealth Uhealth. 2018 Jan 25;6(1):e28
pubmed: 29371177
Prev Chronic Dis. 2018 Dec 20;15:E162
pubmed: 30576272
Implement Sci. 2017 Sep 6;12(1):111
pubmed: 28877746
Int J Environ Res Public Health. 2018 Dec 13;15(12):
pubmed: 30551555
JMIR Mhealth Uhealth. 2018 Apr 27;6(4):e107
pubmed: 29702473
N Engl J Med. 2017 Nov 23;377(21):2010-2011
pubmed: 29116869
JAMA Netw Open. 2019 May 3;2(5):e194281
pubmed: 31125101
Br J Sports Med. 2022 Dec;56(23):1366-1374
pubmed: 36396151
J Med Internet Res. 2015 Aug 27;17(8):e210
pubmed: 26316499
J Med Internet Res. 2019 Mar 19;21(3):e12053
pubmed: 30888321
Prog Cardiovasc Dis. 2021 Jan-Feb;64:55-63
pubmed: 33129794
Front Public Health. 2022 Nov 10;10:914433
pubmed: 36438245
Int J Behav Nutr Phys Act. 2016 Dec 7;13(1):127
pubmed: 27927218
PM R. 2017 May;9(5S):S106-S115
pubmed: 28527495
J Behav Med. 2017 Feb;40(1):112-126
pubmed: 27722907
J Am Heart Assoc. 2015 Nov 09;4(11):
pubmed: 26553211
Eval Health Prof. 2015 Mar;38(1):3-14
pubmed: 23716732
JMIR Mhealth Uhealth. 2017 Oct 10;5(10):e146
pubmed: 29017991
Health Informatics J. 2016 Sep;22(3):451-69
pubmed: 25649783
Games Health J. 2018 Feb;7(1):1-8
pubmed: 29394109
Curr Opin Cardiol. 2017 Sep;32(5):541-556
pubmed: 28708630
Am J Prev Med. 2020 Feb;58(2):e51-e62
pubmed: 31959326
J Am Heart Assoc. 2018 Jul 2;7(13):
pubmed: 29967221
Implement Sci. 2014 Aug 28;9:96
pubmed: 25163664
Annu Rev Public Health. 2019 Apr 1;40:45-63
pubmed: 30664836
Healthc Inform Res. 2016 Jan;22(1):1-2
pubmed: 26893944
JMIR Mhealth Uhealth. 2018 Aug 24;6(8):e10003
pubmed: 30143477
BMJ. 2019 Aug 28;366:l4898
pubmed: 31462531
JMIR Mhealth Uhealth. 2016 Sep 22;4(3):e109
pubmed: 27658677
JMIR Mhealth Uhealth. 2017 Mar 06;5(3):e28
pubmed: 28264796
J Phys Act Health. 2012 Jan;9 Suppl 1:S5-10
pubmed: 22287448
J Med Internet Res. 2013 Oct 04;15(10):e224
pubmed: 24095951
Ann Behav Med. 2017 Apr;51(2):226-239
pubmed: 27757789
BMC Public Health. 2016 Sep 02;16:925
pubmed: 27590255
JMIR Mhealth Uhealth. 2022 Oct 24;10(10):e35628
pubmed: 36279159
J Med Internet Res. 2015 Nov 10;17(11):e253
pubmed: 26554314
Int J Behav Nutr Phys Act. 2017 Aug 11;14(1):105
pubmed: 28800736
J Med Internet Res. 2016 Dec 19;18(12):e331
pubmed: 27993759
JMIR Mhealth Uhealth. 2018 Nov 12;6(11):e10076
pubmed: 30425028
Digit Health. 2019 Mar 27;5:2055207619839883
pubmed: 30944728
Lancet Glob Health. 2018 Oct;6(10):e1077-e1086
pubmed: 30193830
Sports Med Open. 2018 Sep 3;4(1):42
pubmed: 30178072
Med Sci Sports Exerc. 2012 Jan;44(1 Suppl 1):S68-76
pubmed: 22157777
BMJ Open. 2016 Oct 4;6(10):e012447
pubmed: 27707829
Health Educ Behav. 2013 Jun;40(3):257-65
pubmed: 23709579
Jacobs J Community Med. 2016;2(1):
pubmed: 27034992
PLoS One. 2016 Jun 28;11(6):e0156370
pubmed: 27352250
BMJ. 2015 May 08;350:h2147
pubmed: 25956159
BMJ. 2003 Sep 6;327(7414):557-60
pubmed: 12958120

Auteurs

Chad Stecher (C)

College of Health Solutions, Arizona State University, Phoenix, AZ, United States.

Bjorn Pfisterer (B)

Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.

Samantha M Harden (SM)

Department of Human Nutrition, Foods, and Exercise, Virginia Tech, Blacksburg, VA, United States.

Dana Epstein (D)

College of Health Solutions, Arizona State University, Phoenix, AZ, United States.

Jakob M Hirschmann (JM)

Institute of Sport Sciences, Goethe University, Frankfurt, Germany.

Kathrin Wunsch (K)

Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.

Matthew P Buman (MP)

College of Health Solutions, Arizona State University, Phoenix, AZ, United States.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH