EconPapers    
Economics at your fingertips  
 

Mobile well-being in pregnancy: suggestions from a quasi-experimental controlled study

Claudia Carissoli, Deborah Gasparri, Giuseppe Riva and Daniela Villani

Behaviour and Information Technology, 2022, vol. 41, issue 8, 1639-1651

Abstract: ‘BenEssere Mamma’ app is a mobile self-help intervention containing mindfulness meditations and ‘savoring the present moment’ exercises for use during pregnancy. The goal of this study is to investigate the effectiveness of this app in enhancing the psychological well-being of healthy childbearing women. A quasi-experimental controlled study was conducted with 74 pregnant women randomly assigned to experimental group (APP – mobile app and antenatal care) or control group (routine antenatal care). Participants were assessed on their psychological well-being before, after the 4 weeks of use of the app, and after the childbirth, using Ryff’s Psychological Well-Being Scale. Women’s acceptance and user experience with the app were also assessed through an ad hoc questionnaire. Experimental group reported an increase in sense of autonomy after intervention and after childbirth, and greater self-acceptance after the childbirth compared to the control group. Results are promising and future investigations are needed to understand if a more interactive or a longer intervention could lead to more effective results and if other populations could benefit of this opportunity. Furthermore, to take advantage of potentialities of mobile apps for promoting well-being in pregnant women, the integration of these tools within a wide public health project is encouraged.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/0144929X.2021.1894484 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tbitxx:v:41:y:2022:i:8:p:1639-1651

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tbit20

DOI: 10.1080/0144929X.2021.1894484

Access Statistics for this article

Behaviour and Information Technology is currently edited by Dr Panos P Markopoulos

More articles in Behaviour and Information Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tbitxx:v:41:y:2022:i:8:p:1639-1651