How continuous glucose monitoring may support behaviour change: perceived mechanisms and app feature…

Abstract

AimsTo understand how users believe continuous glucose monitoring (CGM) changes their behaviour, which app features they credit, and whether endorsing more mechanisms of action (MoAs) is linked to reported diet and physical activity change.

MethodsWe surveyed 112 U.S. adults with type 1 or type 2 diabetes who had used a Dexcom or Abbott Libre CGM within 12 months. Participants rated 26 MoA statements mapped to the Capability, Opportunity, Motivation-Behaviour (COM-B) dominance CIs and ranking frequencies model, identified contributing app features, and reported CGM-attributed diet and physical activity change. Logistic regression examined MoA count and COM-B domains as predictors of behaviour change.

ResultsParticipants (mean age 54.5 years; 60.7% female) reported dietary (82.1%) and physical activity (46.4%) change and endorsed a median of 18 MoAs, most often relating to knowledge, skills and behavioural consequences. Real-time glucose and graphs were attributed to many MoAs. Each additional MoA was associated with higher odds of dietary (OR 1.27, 95% CI 1.15-1.44) and physical activity change (OR 1.27, 95% CI 1.16-1.43). Motivation made the strongest distinct contribution among COM-B domains.

ConclusionsUsers perceive CGM as engaging many behavioural mechanisms; endorsing more was linked to behaviour change. Motivation may be a key target for CGM-based behavioural support.

Similar discrimination, different behaviour under synthetic occlusion: confidence and attribution reproducibility of deep learning models for intraoral ultrasonography
G. Jung, Y.-R. Heo, K.-S. Hu +1
medRxiv3 Nov 2026PreprintCC BYFull textMedical imaging & radiologymedRxiv
Experiences of suicidal behaviour and perceived triggers among young people and caregivers at a tertiary healthcare facility in Kenya
Charlene Gumbo, Muthoni Mathai, John Mburu +5
Frontiers in Psychiatry2 Nov 2026Peer-reviewedCC BY 4.0Psychiatry & mental healthCrossref
Beyond Synovitis: Molecular and Neuroimmune Mechanisms Informing Target-Joint Attribution and Pain Phenotyping for Arthroplasty in Inflammatory Arthritis.
Michal Pruc, Andrzej Bielski, Robert Weglowski +7
International journal of molecular sciences24 Sep 2026Peer-reviewedCC BYFull textPhysiologyEurope PMC
Knowledge, attitude and practice on continuous glucose monitoring and self-monitoring of blood glucose among healthcare professionals across India: A cross-sectional study
Nitin Kapoor, Shehla Sheikh, Sambit Das +3
TouchREVIEWS in endocrinology1 Oct 2026Peer-reviewedCC BYFull textEndocrinology & metabolismEurope PMCPMC
Continuous Glucose Monitoring for Metabolic Phenotyping and Precision Nutrition: Current Evidence, Clinical Applications and Future Perspectives
Liora Colobatiu, Romolica Mihaiu, Alexandra Pusta +1
Diagnostics (Basel, Switzerland)1 Oct 2026Peer-reviewedCC BYFull textGeneral medicineEurope PMC

Cite

BibTeX RIS

BibTeX

@misc{jospe2026continuous,
  title = {{How continuous glucose monitoring may support behaviour change: perceived mechanisms and app feature attribution in a cross-sectional survey}},
  author = {M. R. Jospe and L. C. Bohlen and J. Crawshaw and J. Somerville and E. LaRegina and H. J. Willis and S. K. Gustafson and S. M. Schembre},
  howpublished = {medRxiv},
  year = {2026},
  month = oct,
  doi = {10.64898/2026.10.19.26365948},
  url = {https://www.medrxiv.org/content/10.64898/2026.10.19.26365948v1},
  note = {CC BY-NC-ND},
}

RIS

TY  - UNPB
TI  - How continuous glucose monitoring may support behaviour change: perceived mechanisms and app feature attribution in a cross-sectional survey
AU  - M. R. Jospe
AU  - L. C. Bohlen
AU  - J. Crawshaw
AU  - J. Somerville
AU  - E. LaRegina
AU  - H. J. Willis
AU  - S. K. Gustafson
AU  - S. M. Schembre
PY  - 2026
DA  - 2026/10/19
PB  - medRxiv
DO  - 10.64898/2026.10.19.26365948
UR  - https://www.medrxiv.org/content/10.64898/2026.10.19.26365948v1
AB  - AimsTo understand how users believe continuous glucose monitoring (CGM) changes their behaviour, which app features they credit, and whether endorsing more mechanisms of action (MoAs) is linked to reported diet and physical activity change.  MethodsWe surveyed 112 U.S. adults with type 1 or type 2 diabetes who had used a Dexcom or Abbott Libre CGM within 12 months. Participants rated 26 MoA statements mapped to the Capability, Opportunity, Motivation-Behaviour (COM-B) dominance CIs and ranking frequencies model, identified contributing app features, and reported CGM-attributed diet and physical activity change. Logistic regression examined MoA count and COM-B domains as predictors of behaviour change.  ResultsParticipants (mean age 54.5 years; 60.7% female) reported dietary (82.1%) and physical activity (46.4%) change and endorsed a median of 18 MoAs, most often relating to knowledge, skills and behavioural consequences. Real-time glucose and graphs were attributed to many MoAs. Each additional MoA was associated with higher odds of dietary (OR 1.27, 95% CI 1.15-1.44) and physical activity change (OR 1.27, 95% CI 1.16-1.43). Motivation made the strongest distinct contribution among COM-B domains.  ConclusionsUsers perceive CGM as engaging many behavioural mechanisms; endorsing more was linked to behaviour change. Motivation may be a key target for CGM-based behavioural support.
ER  -

Abstract

Related

Cite