Web-Based and mHealth Technologies to Support Self-Management in People Living With Type 2 Diabetes: Validation of the Diabetes Self-Management and Technology Questionnaire (DSMT-Q)

Abstract

Background: A growing number of web-based and mobile health (mHealth) technologies have been developed to support type 2 diabetes self-management.

Little is known about individuals’ experiences with these technologies and how they support self-management.

Appropriate tools are needed to understand how web-based and mHealth interventions may impact self-management.

Objective: This study aimed to develop an instrument, the Diabetes Self-Management and Technology Questionnaire (DSMT-Q), to assess self-management among people living with type 2 diabetes who use web-based and mHealth technologies.

Methods: A total of 36 candidate questionnaire items, drafted previously, were refined using cognitive debriefing interviews (n=8), expert consultation, and public patient involvement feedback.

Item reduction steps were performed on survey data (n=250), and tests of validity and reliability were subsequently performed.

Results: Following amendments, patients and experts found 21 items relevant and acceptable for inclusion in the instrument.

Survey participants included 104 (41.6%) women and 146 (58.4%) men.

Two subscales with high construct validity, internal consistency, and test-retest reliability were identified: “Understanding individual health and making informed decisions” and “Confidence to reach and sustain goals.” Conclusions: Analyses confirmed good psychometric properties in the DSMT-Q scales.

This tool will facilitate the measurement of self-management in people living with type 2 diabetes who use web-based or mHealth technologies.

Citations

Laura Kelly, Crispin Jenkinson,David Morley. Web-Based and mHealth Technologies to Support Self-Management in People Living With Type 2 Diabetes: Validation of the Diabetes Self-Management and Technology Questionnaire (DSMT-Q). JMIR Diabetes 2020;5(3):e18208

Page last reviewed: 12 June, 2025

Metadata

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Date issued: 2020-07

ISSN: 23714379

ID: 557