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Longitudinal Research

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...

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Alcohol Avoidance Training as a Mobile App for Problem Drinkers: Longitudinal Feasibility Study.

Melissa C Laurens^1,2, Marcel E Pieterse¹, Marjolein Brusse-Keizer³

¹Centre for eHealth and Well-being Research, University of Twente, Enschede, Netherlands.

JMIR Mhealth and Uhealth

|April 15, 2020

Summary

A mobile app for alcohol avoidance training (cognitive bias modification) significantly reduced weekly alcohol consumption by 7.8 units after 3 weeks. This mHealth intervention shows promise for problem drinkers seeking more control over their alcohol use.

Keywords:

alcohol approach bias cognitive bias modification mobile alcohol avoidance training

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Area of Science:

Behavioral Psychology
Digital Health Interventions
Substance Use Research

Background:

Alcohol use is linked to automatic approach tendencies.
Cognitive bias modification (CBM) shows therapeutic potential.
A mobile app was developed to improve access and engagement for alcohol avoidance training.

Purpose of the Study:

Assess adherence to a mobile health (mHealth) app for alcohol avoidance.
Evaluate changes in weekly alcohol consumption pre- and post-training.
Examine user experience with the mHealth app.

Main Methods:

1082 participants used the Breindebaas app for 3 weeks, with at least two sessions weekly.
Training involved swiping away from alcoholic beverage images and towards non-alcoholic ones.
Adherence, alcohol use, and user satisfaction were assessed via online questionnaires post-training and at 3-month follow-up.

Main Results:

Significant reduction in weekly alcohol consumption by 7.8 units after 3 weeks (P<.001).
Further reduction of 6.2 units observed at 3-month follow-up (P<.001).
Positive user feedback on the app's design; 79% adherence rate (>=4 sessions).

Conclusions:

A mobile CBM app can meet the needs of problem drinkers.
Preliminary findings indicate potential for reducing alcohol use via mHealth.
Further research with controlled studies is warranted to confirm these results.