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Related Experiment Video

Updated: Jun 18, 2026

Mindfulness in Motion (MIM): An Onsite Mindfulness Based Intervention (MBI) for Chronically High Stress Work Environments to Increase Resiliency and Work Engagement
12:22

Mindfulness in Motion (MIM): An Onsite Mindfulness Based Intervention (MBI) for Chronically High Stress Work Environments to Increase Resiliency and Work Engagement

Published on: July 1, 2015

Adherence in Internet-based interventions.

Silje C Wangberg1, Trine S Bergmo, Jan-Are K Johnsen

  • 1Norwegian Centre for Telemedicine, University Hospital of North Norway, Tromsø, Norway.

Patient Preference and Adherence
|November 19, 2009
PubMed
Summary
This summary is machine-generated.

Internet interventions show high dropout rates early on. Tailored emails and automated follow-ups can improve adherence for online health programs.

Keywords:
Internet-based interventionsadherenceattritionself-efficacytailoring

Related Experiment Videos

Last Updated: Jun 18, 2026

Mindfulness in Motion (MIM): An Onsite Mindfulness Based Intervention (MBI) for Chronically High Stress Work Environments to Increase Resiliency and Work Engagement
12:22

Mindfulness in Motion (MIM): An Onsite Mindfulness Based Intervention (MBI) for Chronically High Stress Work Environments to Increase Resiliency and Work Engagement

Published on: July 1, 2015

Area of Science:

  • Digital Health
  • Health Behavior Research
  • Intervention Science

Background:

  • Internet-based interventions offer a scalable platform for health promotion.
  • Low user adherence remains a significant challenge in digital health initiatives.
  • Understanding adherence patterns is crucial for optimizing online health programs.

Purpose of the Study:

  • To report adherence rates from three distinct Internet-based health trials.
  • To identify baseline covariates associated with user adherence.
  • To evaluate strategies for improving adherence in online interventions.

Main Methods:

  • Collected adherence data and baseline characteristics from three trials: diabetes self-management, smoking cessation, and personal health record.
  • Measured adherence through web usage logs and authentication SMS message logs.
  • Analyzed relationships between baseline variables and adherence rates.

Main Results:

  • High early dropout rates were observed across all three trials.
  • Self-efficacy, smoking-related social factors, age, gender, and education influenced adherence.
  • Tailored email communications enhanced user engagement for up to five months.

Conclusions:

  • Substantial attrition necessitates accurate pretrial sample size estimation using attrition curves.
  • Automated email follow-ups are recommended to increase adherence in Internet-based interventions.
  • Personalizing interventions based on baseline covariates like self-efficacy can improve effectiveness.