Diet and multiple sclerosis: Behaviour change techniques in the digital health application levidex

Area of Science:

• Digital health interventions
• Behavior change science
• Multiple Sclerosis management

Background:

• Multiple Sclerosis (MS) is a chronic central nervous system disease impacting patients' quality of life.
• People with MS (PwMS) exhibit high motivation for lifestyle changes, particularly dietary behavior.
• A prior study demonstrated the digital health application (DiGA) levidex improved diet quality in early MS.

Purpose of the Study:

• To analyze the diet-related behavior change techniques (BCTs) employed within the levidex DiGA.
• To understand how levidex facilitates dietary behavior modification in individuals with MS.

Main Methods:

• Utilized the Behavior Change Technique Taxonomy version 1 (BCTTv1) for coding.
• Employed independent double-coding with a third rater for disagreements and assessed inter-rater reliability.
• Linked identified BCTs to theoretical mechanisms of action (MoAs) using an interactive tool.

Main Results:

• Achieved high inter-rater reliability (79.01% agreement, kappa 0.78).
• Identified 28 distinct BCTs with 202 total codings related to dietary behavior.
• The most frequent BCTs included 'instruction on how to perform the behavior,' 'information about health consequences,' and 'credible source,' linked to 24 MoAs.

Conclusions:

• Levidex effectively employs a wide array of BCTs focused on skill-building and credible information to encourage healthy dietary habits.
• BCT taxonomy coding is a viable method for analyzing the components of digital health interventions.
• Connecting intervention outcomes to specific BCTs enhances understanding and can inform future nutrition-focused digital health strategies.