Unveiling the Interplay Between Rational, Psychological and Functional Factors in Continuous Glucose Monitoring Early Adoption: Novel Evidence from the Dexcom ONE Case in Italy

Overview

Journal BMC Health Serv Res

Publisher Biomed Central

Specialty Health Services

Date 2024 Jun 18

PMID 38890619

Authors

Francesca Zoccarato

Martina Manzoni

Davide Minotti

Emanuele Lettieri

Andrea Boaretto

Affiliations

Soon will be listed here.

Abstract

Background: The escalating prevalence of diabetes, with its multifaceted complications, poses a pressing challenge for healthcare systems globally. In response, the advent of continuous glucose monitoring (CGM) systems, offering technological solutions for daily diabetes management, presents significant opportunities. However, the widespread adoption faces several barriers, linked both to the technological configuration of the devices and to the psychological dimension of patients. Therefore, this study aims to apply and test a theoretical model that investigates the antecedents of the intention to use Continuous Glucose Monitoring systems.

Methods: The research model was built to unveil the impacts of psychological factors, functional components and rational constructs derived from the Technology Acceptance Model (TAM) on CGM systems sustained adoption. To ensure the comparability of results, we have collected data from people who had used Dexcom ONE Dexcom (San Diego, CA) for the first time for at least one month. Employing Structural Equation Modelling (SEM) techniques, the hypothesized relationships among constructs were assessed.

Results: The analyses confirmed the positive correlation of rational factors to the Intention to Use. Subjective Norm, intended as the physicians' influence, is positively correlated with the Perceived Usefulness. Trend Arrows, albeit being negatively correlated with Perceived Usefulness, have a positive correlation on Perceived Ease Of Use, reinforcing its mediating effect towards Perceived Usefulness. Among psychological factors, Trust in the CGM technology positively correlates with Intention to Use. Health Literacy is negatively correlated to the Intention to Use.

Conclusions: These findings contribute to theoretical and managerial understanding, providing recommendations to enhance the adoption of CGM systems like Dexcom ONE.

Citing Articles

Understanding Psychosocial Barriers to Healthcare Technology Adoption: A Review of TAM Technology Acceptance Model and Unified Theory of Acceptance and Use of Technology and UTAUT Frameworks.

Lee A, Ramasamy R, Subbarao A Healthcare (Basel). 2025; 13(3).

PMID: 39942440 PMC: 11816427. DOI: 10.3390/healthcare13030250.

References

Kang H, Park H, Kim C, Singh-Carlson S . Experiences of Using Wearable Continuous Glucose Monitors in Adults With Diabetes: A Qualitative Descriptive Study. Sci Diabetes Self Manag Care. 2022; 48(5):362-371. DOI: 10.1177/26350106221116899. View

Hirsch I, Nardacci E, Verderese C . Flash Continuous Glucose Monitoring: Implications for Use of Continuous Data in Daily Diabetes Management. Diabetes Spectr. 2019; 32(4):355-367. PMC: 6858083. DOI: 10.2337/ds18-0059. View

Nyblade L, Stockton M, Giger K, Bond V, Ekstrand M, Mc Lean R . Stigma in health facilities: why it matters and how we can change it. BMC Med. 2019; 17(1):25. PMC: 6376713. DOI: 10.1186/s12916-019-1256-2. View

Brew-Sam N, Chhabra M, Parkinson A, Hannan K, Brown E, Pedley L . Experiences of Young People and Their Caregivers of Using Technology to Manage Type 1 Diabetes Mellitus: Systematic Literature Review and Narrative Synthesis. JMIR Diabetes. 2021; 6(1):e20973. PMC: 7886614. DOI: 10.2196/20973. View

Tanenbaum M, Adams R, Lanning M, Hanes S, Agustin B, Naranjo D . Using Cluster Analysis to Understand Clinician Readiness to Promote Continuous Glucose Monitoring Adoption. J Diabetes Sci Technol. 2018; 12(6):1108-1115. PMC: 6232742. DOI: 10.1177/1932296818786486. View

Rodbard D . Continuous Glucose Monitoring: A Review of Successes, Challenges, and Opportunities. Diabetes Technol Ther. 2016; 18 Suppl 2:S3-S13. PMC: 4717493. DOI: 10.1089/dia.2015.0417. View

Datye K, Tilden D, Parmar A, Goethals E, Jaser S . Advances, Challenges, and Cost Associated with Continuous Glucose Monitor Use in Adolescents and Young Adults with Type 1 Diabetes. Curr Diab Rep. 2021; 21(7):22. PMC: 8575075. DOI: 10.1007/s11892-021-01389-1. View

Carrera A, Lettieri E, Lietti G, Martignoni S, Sgarbossa C, Cafazzo J . Therapies go digital. What drives physicians' acceptance?. PLoS One. 2024; 19(5):e0303302. PMC: 11086840. DOI: 10.1371/journal.pone.0303302. View

Welsh J . Role of Continuous Glucose Monitoring in Insulin-Requiring Patients with Diabetes. Diabetes Technol Ther. 2018; 20(S2):S242-S249. DOI: 10.1089/dia.2018.0100. View

10.

Aleppo G, Webb K . Continuous Glucose Monitoring Integration in Clinical Practice: A Stepped Guide to Data Review and Interpretation. J Diabetes Sci Technol. 2018; 13(4):664-673. PMC: 6610596. DOI: 10.1177/1932296818813581. View

11.

Sorensen K, Van den Broucke S, Pelikan J, Fullam J, Doyle G, Slonska Z . Measuring health literacy in populations: illuminating the design and development process of the European Health Literacy Survey Questionnaire (HLS-EU-Q). BMC Public Health. 2013; 13:948. PMC: 4016258. DOI: 10.1186/1471-2458-13-948. View

12.

Aggarwal A, Pathak S, Goyal R . Clinical and economic outcomes of continuous glucose monitoring system (CGMS) in patients with diabetes mellitus: A systematic literature review. Diabetes Res Clin Pract. 2022; 186:109825. DOI: 10.1016/j.diabres.2022.109825. View

13.

Lee M, Tanenbaum M, Maahs D, Prahalad P . Overcoming Barriers to Diabetes Technology in Youth with Type 1 Diabetes and Public Insurance: Cases and Call to Action. Case Rep Endocrinol. 2022; 2022:9911736. PMC: 8904094. DOI: 10.1155/2022/9911736. View

14.

Carrera A, Zoccarato F, Mazzeo M, Lettieri E, Toletti G, Bertoli S . What drives patients' acceptance of Digital Therapeutics? Establishing a new framework to measure the interplay between rational and institutional factors. BMC Health Serv Res. 2023; 23(1):145. PMC: 9921481. DOI: 10.1186/s12913-023-09090-7. View

15.

Engler R, Routh T, Lucisano J . Adoption Barriers for Continuous Glucose Monitoring and Their Potential Reduction With a Fully Implanted System: Results From Patient Preference Surveys. Clin Diabetes. 2018; 36(1):50-58. PMC: 5774999. DOI: 10.2337/cd17-0053. View

16.

Zheng M, Patel A, Khoja A, Luo Y, Lin W, He Q . Barriers and facilitators of diabetes management by continuous glucose monitoring systems among adults with type 2 diabetes: a protocol of qualitative systematic review. BMJ Open. 2021; 11(10):e046050. PMC: 8559096. DOI: 10.1136/bmjopen-2020-046050. View

17.

Sorgard B, Iversen M, Martensson J . Continuous glucose monitoring in adults with type 1 diabetes: A balance between benefits and barriers: A critical incident study. J Clin Nurs. 2019; 28(17-18):3318-3329. DOI: 10.1111/jocn.14911. View

18.

Schluter S, Freckmann G, Heinemann L, Wintergerst P, Lange K . Evaluation of the SPECTRUM training programme for real-time continuous glucose monitoring: A real-world multicentre prospective study in 120 adults with type 1 diabetes. Diabet Med. 2020; 38(2):e14467. DOI: 10.1111/dme.14467. View

19.

Freckmann G, Link M, Kamecke U, Haug C, Baumgartner B, Weitgasser R . Performance and Usability of Three Systems for Continuous Glucose Monitoring in Direct Comparison. J Diabetes Sci Technol. 2019; 13(5):890-898. PMC: 6955463. DOI: 10.1177/1932296819826965. View

20.

Shah V, Laffel L, Wadwa R, Garg S . Performance of a Factory-Calibrated Real-Time Continuous Glucose Monitoring System Utilizing an Automated Sensor Applicator. Diabetes Technol Ther. 2018; 20(6):428-433. PMC: 6422005. DOI: 10.1089/dia.2018.0143. View