Influence of mHealth-Based Lifestyle Interventions on Symptoms of Anxiety and Depression of Women With Gestational Diabetes: A Meta-Analysis

Abstract

Background:

Symptoms of anxiety and depression are common in women with gestational diabetes mellitus (GDM). Mobile health (mHealth)-based lifestyle interventions have been shown to be effective in improving glycemic control of these women.

Purpose/Objective:

The aim of the study was to evaluate the influence of mHealth-based lifestyle interventions on symptoms of anxiety and depression in women with GDM.

Design:

A systematic review and meta-analysis or randomized controlled trials.

Setting:

Clinical or community-based settings.

Sample:

Nine studies involving 1,168 pregnant women with GDM were included.

Intervention:

mHealth-based lifestyle interventions.

Measures:

Symptoms of anxiety and depression quantitatively analyzed in clinical scales.

Analysis:

A systematic literature search was performed in electronic databases, including PubMed, Cochrane library, Embase, Web of Science, Wanfang, and China National Knowledge Infrastructure to obtain relevant randomized controlled studies. A random-effects model was used to pool the results by incorporating the impact of the potential heterogeneity.

Results:

Findings revealed that when compared to usual care, women who received mHealth-based lifestyle interventions had significant improvements in symptoms of anxiety (standardized mean difference [SMD]: −0.55, 95% CI [−0.77, −0.33], p < .001; I² = 67%) and depression (SMD: −0.51, [−0.72, −0.29], p < .001; I² = 65%). Sensitivity analyses by excluding one study at a time showed consistent results. Subgroup analyses showed similar results in mHealth achieved by phone, websites, and applications, in mHealth targeting diet and exercise with and without psychological support, in mHealth lead by nurse with and without other clinical specialists, and in studies with different evaluating tools for anxiety and depression.

Conclusions:

mHealth-based lifestyle interventions could significantly improve the symptoms of anxiety and depression in women with GDM.

Keywords

gestational diabetes mellitus mHealth lifestyle intervention anxiety depression meta-analysis

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References

Amoakoh-Coleman

Borgstein

A. B.

Sondaal

S. F.

Grobbee

D. E.

Miltenburg

A. S.

Verwijs

Ansah

E. K.

Browne

J. L.

Klipstein-Grobusch

(2016). Effectiveness of mHealth interventions targeting health care workers to improve pregnancy outcomes in low- and middle-income countries: A systematic review. Journal of Medical Internet Research, 18(8), e226.

Baek

E. S.

Park

H. J.

(2013). Effects of a case management program on self-efficacy, depression and anxiety in pregnant women with gestational diabetes mellitus. Korean Journal of Women Health Nursing, 19(2), 88–98.

Bakker

C. J.

Wyatt

T. H.

Breth

M. C.

Gao

Janeway

L. M.

Lee

M. A.

, et al. (2023). Nurses’ roles in mHealth app development: Scoping review. JMIR Nursing, 6, e46058.

Bidhendi Yarandi

Vaismoradi

Panahi

M. H.

Gare Kymre

Behboudi-Gandevani

. (2021). Mild gestational diabetes and adverse pregnancy outcome: A systemic review and meta-analysis. Frontiers in Medicine, 8, 699412.

Chen

F. J.

Wang

L. Y.

Zeng

D. G.

(2021). Application of remote home care plan in nursing management of patients with gestational diabetes. Cheeloo Journal of Nursing, 27(3), 55–58.

Chen

X. M.

Chen

X. J.

(2019). Application effect of “Internet plus School for Pregnant Women” model in pregnant women with gestational diabetes. Diabetes New World, 19(10), 149–151.

Eberle

Lohnert

Stichling

(2021a). Effectiveness of disease-specific mhealth apps in patients with diabetes mellitus: Scoping review. JMIR Mhealth and Uhealth, 9(2), e23477.

Eberle

Loehnert

Stichling

(2021b). Effectivness of specific mobile health applications (mHealth-apps) in gestational diabtetes mellitus: A systematic review. BMC Pregnancy and Childbirth, 21(1), 808.

Egger

Davey Smith

Schneider

Minder

(1997). Bias in meta-analysis detected by a simple, graphical test. BMJ, 315(7109), 629–634.

10.

Guo

Zhang

Zhou

Chen

L. M.

S. Y.

(2019). Evaluating the effects of mobile health intervention on weight management, glycemic control and pregnancy outcomes in patients with gestational diabetes mellitus. Journal of Endocrinological Investigation, 42(6), 709–714.

11.

Guo

Zhou

Sun

Wang

Zhang

(2021). Application of online-offline integrated medical care management in patients with gestational diabetes. Ginekologia Polska, 92(10), 720–725.

12.

Hamine

Gerth-Guyette

Faulx

Green

B. B.

Ginsburg

A. S.

(2015). Impact of mHealth chronic disease management on treatment adherence and patient outcomes: A systematic review. Journal of Medical Internet Research, 17(2), e52.

13.

Higgins

J. P.

Thomas

Chandler

Cumpston

Page

Welch

V. A.

(2021). Cochrane Handbook for Systematic Reviews of Interventions Version 6.2. The Cochrane Collaboration. https://www.training.cochrane.org/handbook

14.

Higgins

J. P.

Thompson

S. G.

Deeks

J. J.

Altman

D. G.

(2003). Measuring inconsistency in meta-analyses. BMJ, 327(7414), 557–560.

15.

Huang

F. L.

H. Y.

Zhang

S. H.

Zhang

Chen

X. X.

Zhang

C. C.

Zhong

H. X.

Yao

A. M.

Liu

C. Y.

Zhang

N. Z.

Xue

X. W.

(2021). [Effect of mobile health for standardized management on women with gestational diabetes mellitus]. Zhongguo Yi Xue Ke Xue Yuan Xue Bao, 43(4), 551–557.

16.

Huang

Magny-Normilus

McMahon

Whittemore

(2022). Systematic review of lifestyle interventions for gestational diabetes mellitus in pregnancy and the postpartum period. Journal of Obstetric, Gynecologic, and Neonatal Nursing, 51(2), 115–125.

17.

Kusyanti

Wirakusumah

F. F.

Rinawan

F. R.

Muhith

Purbasari

Mawardi

, et al. (2022). Technology-based (Mhealth) and standard/traditional maternal care for pregnant woman: A systematic literature review. Healthcare (Basel, , Switzerland), 10(7), 1287.

18.

Lee

A. Y. L.

Wong

A. K. C.

Hung

T. T. M.

Yan

Yang

(2022). Nurse-led telehealth intervention for rehabilitation (Telerehabilitation) among community-dwelling patients with chronic diseases: Systematic review and meta-analysis. Journal of Medical Internet Research, 24(11), e40364.

19.

Lee

K. W.

Ching

S. M.

Hoo

F. K.

Ramachandran

Chong

S. C.

Tusimin

, et al. (2020). Neonatal outcomes and its association among gestational diabetes mellitus with and without depression, anxiety and stress symptoms in Malaysia: A cross-sectional study. Midwifery, 81, 102586.

20.

Lei

Yan

Chen

H. X.

Shi

X. H.

Zhou

Song

(2021). Application study of online and offline mode in continuing nursing care of gestational diabetes. China Journal of Modern Medicine, 28(26), 237–239.

21.

Mai

X. H.

Mai

Y. L.

(2021). Effect of website based self-management on behavior and blood sugar of women with gestational diabetes. Acta Bengbu Medical University, 20(4), 121–123.

22.

Marcolino

M. S.

Oliveira

J. A. Q.

D’Agostino

Ribeiro

A. L.

Alkmim

M. B. M.

Novillo-Ortiz

(2018). The impact of mHealth interventions: Systematic review of systematic reviews. JMIR Mhealth and Uhealth, 6(1), e23.

23.

Mauriello

L. M.

Van Marter

D. F.

Umanzor

C. D.

Castle

P. H.

de Aguiar

E. L.

(2016). Using mHealth to deliver behavior change interventions within prenatal care at community health centers. American Journal of Health Promotion, 30(7), 554–562.

24.

Mayberry

L. S.

Lyles

C. R.

Oldenburg

Osborn

C. Y.

Parks

Peek

M. E.

(2019). MHealth interventions for disadvantaged and vulnerable people with type 2 diabetes. Current Diabetes Reports, 19(12), 148.

25.

Moon

J. H.

Jang

H. C.

(2022). Gestational diabetes mellitus: Diagnostic approaches and maternal-offspring complications. Diabetes and Metabolism Journal, 46(1), 3–14.

26.

OuYang

Chen

Abdulrahman

A. M.

(2021). Associations between gestational diabetes and anxiety or depression: A systematic review. Journal of Diabetes Research, 2021, 9959779.

27.

Page

M. J.

McKenzie

J. E.

Bossuyt

P. M.

Boutron

Hoffmann

T. C.

Mulrow

C. D.

Shamseer

Tetzlaff

J. M.

Akl

E. A.

Brennan

S. E.

Chou

Glanville

Grimshaw

J. M.

Hróbjartsson

Lalu

M. M.

Loder

E. W.

Mayo-Wilson

McDonald

. . .Moher

(2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71.

28.

Page

M. J.

Moher

Bossuyt

P. M.

Boutron

Hoffmann

T. C.

Mulrow

C. D.

Shamseer

Tetzlaff

J. M.

Akl

E. A.

Brennan

S. E.

Chou

Glanville

Grimshaw

J. M.

Hróbjartsson

Lalu

M. M.

Loder

E. W.

Mayo-Wilson

McDonald

S. . . .

McKenzie

J. E.

(2021). PRISMA 2020 explanation and elaboration: Updated guidance and exemplars for reporting systematic reviews. BMJ, 372, n160.

29.

Rasmussen

Poulsen

C. W.

Kampmann

Smedegaard

S. B.

Ovesen

P. G.

Fuglsang

(2020). Diet and healthy lifestyle in the management of gestational diabetes mellitus. Nutrients, 12(10), 3050.

30.

Rutledge

C. M.

Kott

Schweickert

P. A.

Poston

Fowler

Haney

T. S.

(2017). Telehealth and eHealth in nurse practitioner training: Current perspectives. Advances in Medical Education and Practice, 8, 399–409.

31.

Smyth

Curtin

Tully

Molphy

Breathnach

(2022). Smartphone apps for surveillance of gestational diabetes: Scoping review. JMIR Diabetes, 7(4), e38910.

32.

Sweeting

Wong

Murphy

H. R.

Ross

G. P.

(2022). A clinical update on gestational diabetes mellitus. Endocrine Reviews, 43(5), 763–793.

33.

Wang

Yan

Yuan

Yang

Liu

Zhang

Z.-J.

(2020). The association between gestational diabetes mellitus and cancer in women: A systematic review and meta-analysis of observational studies. Diabetes and Metabolism, 46(6), 461–471.

34.

Whitmore

Bird

McGillion

M. H.

Carter

Chen

Pierazzo

Carroll

S. L.

(2020). Impact of nurse scientist-led digital health interventions on management of chronic conditions. Nursing Outlook, 68(6), 745–762.

35.

Xie

Wang

Xiao

Qiu

Zhang

(2022). Association of gestational diabetes mellitus with overall and type specific cardiovascular and cerebrovascular diseases: Systematic review and meta-analysis. BMJ, 378, e070244.

36.

Luo

Huang

Liu

(2022). Gestational diabetes mellitus and adverse pregnancy outcomes: Systematic review and meta-analysis. BMJ, 377, e067946.

37.

X. L.

F. P.

Wang

Y. P.

(2020). The value of health education on WeChat platform for nursing elderly pregnant women with diabetes. World Latest Medical Information, 20(4), 292–293.

38.

Yeşilçınar

İ.

Kıncı

M. F.

Ünver

H. C.

Sivaslıoğlu

A. A

. (2023). Pregnancy-related anxiety and prenatal attachment in pregnant women with preeclampsia and/or gestational diabetes mellitus: A cross-sectional study. Journal of Clinical Obstetrics and Gynecology, 33(1), 27–35.

39.

Yew

T. W.

Chi

Chan

S. Y.

van Dam

R. M.

Whitton

Lim

C. S.

Foong

P. S.

Fransisca

Teoh

C. L.

Chen

Ho-Lim

S. T.

Lim

S. L.

Ong

K. W.

Ong

P.-H.

Tai

B. C.

Tai

E. S.

(2021). A Randomized Controlled Trial to Evaluate the Effects of a Smartphone Application-Based Lifestyle Coaching Program on Gestational Weight Gain, Glycemic Control, and Maternal and Neonatal Outcomes in Women With Gestational Diabetes Mellitus: The SMART-GDM Study. Diabetes Care, 44(2), 456-463.

40.

Zhang

W. Q.

(2022). Effect of peer support education based on Internet platform on pregnancy outcome of patients with gestational diabetes mellitus and reproductive tract infection. Journal of Bengbu Medical College, 47(11), 1597–1601.