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Accepted for/Published in: JMIR mHealth and uHealth

Date Submitted: Jul 2, 2024
Date Accepted: Oct 23, 2025

The final, peer-reviewed published version of this preprint can be found here:

Unraveling the Factors Associated With Digital Health Intervention Uptake: Cross-Sectional Study

Ruotsalainen I, Valtanen M, Kärsämä R, Umer A, Liedes H, Parikka S, Lundqvist A, Aittola K, Manninen S, Pihlajamäki J, Vuorinen AL, Lindström J

Unraveling the Factors Associated With Digital Health Intervention Uptake: Cross-Sectional Study

JMIR Mhealth Uhealth 2025;13:e63896

DOI: 10.2196/63896

PMID: 41364913

PMCID: 12728403

Unraveling the Factors Associated with Digital Health Intervention Uptake: Cross-sectional study

  • Ilona Ruotsalainen; 
  • Mikko Valtanen; 
  • Riikka Kärsämä; 
  • Adil Umer; 
  • Hilkka Liedes; 
  • Suvi Parikka; 
  • Annamari Lundqvist; 
  • Kirsikka Aittola; 
  • Suvi Manninen; 
  • Jussi Pihlajamäki; 
  • Anna-Leena Vuorinen; 
  • Jaana Lindström

ABSTRACT

Background:

For preventing chronic noncommunicable diseases, the reduction of modifiable lifestyle risk factors is a crucial strategy. Digital health interventions (DHIs) hold promises for reducing these major risk factors and reaching large population groups; however, concerns have arisen regarding their health equity.

Objective:

In this study, we investigated the relation of socio-economic factors, health, lifestyle habits, and use of e-services with the uptake of a DHI.

Methods:

In this cross-sectional study, we offered (by mail or SMS) a subgroup (n=6978) of 20 to 74-year-old participants of the population-based Healthy Finland questionnaire survey an opportunity to start using a web-based DHI (BitHabit app), which aims to support adoption of healthy lifestyle habits. Adjusted logistic regression models were used to identify significant predictors of DHI uptake.

Results:

Women (adjusted odds ratio [aOR] 1.69, 95% CI 1.49–1.93), middle-aged individuals (1.47, 1.21–1.79), and those with higher income (aORs between 1.76–1.97) and education (1.10, 1.08–1.12) had higher odds of DHI uptake. Moreover, healthier lifestyle indicated by better diet quality (1.07, 1.04–1.10), less frequent or non-smoking (aORs between 1.59–2.29), sleep (0.58, 0.37–0.86), higher functional capacity (1.06, 1.02–1.11), and good overall current health (1.46, 1.15–1.89) associated with increased likelihood of DHI uptake. Lastly, individuals with better internet connections, higher competence to use e-services (aORs between 2.00–4.10), low concerns about data security (aORs between 1.37–1.76), stronger belief in benefits of digital services (1.04, 1.02–1.05), and reporting to use e-services (aORs between 2.48–6.08) had higher odds of uptake.

Conclusions:

Our findings indicate that those with higher socioeconomic status and better health and lifestyle are more likely to take up DHI. Our research also highlights the impact of digital literacy and positive attitudes towards online services in adopting DHIs. These insights will be valuable in shaping strategies for future DHI initiatives.


 Citation

Please cite as:

Ruotsalainen I, Valtanen M, Kärsämä R, Umer A, Liedes H, Parikka S, Lundqvist A, Aittola K, Manninen S, Pihlajamäki J, Vuorinen AL, Lindström J

Unraveling the Factors Associated With Digital Health Intervention Uptake: Cross-Sectional Study

JMIR Mhealth Uhealth 2025;13:e63896

DOI: 10.2196/63896

PMID: 41364913

PMCID: 12728403

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