Diabetes, obesity & metabolism · 2026
Barriers and Enablers to Diabetes Technologies Use Among Individuals With Type 1 Diabetes: A Scoping Review.
Scoping ReviewСтатьяНазвание и аннотация: Перевод в очереди
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Palermo Laura, Senga Joyeuse, Fakembe Patience, Zhu Xi, Walsh Chris, Leslie Brenna, Shulman Rayzel, Presseau Justin, Dogba Maman Joyce, Banerjee Ananya, Rabasa-Lhoret Rémi, Nakhla Meranda, Brazeau Anne-Sophie, Lovblom Leif Erik, Witteman Holly O, Lipscombe Lorraine L, Weisman Alanna
Аннотация
BACKGROUND: Advanced diabetes technologies are standard of care for people with Type 1 diabetes (T1D). However, inequitable access contributes to disparities in outcomes.
PURPOSE: To characterise barriers and enablers to the use of advanced diabetes technologies among individuals with T1D and to synthesise these determinants using the Theoretical Domains Framework.
DATA SOURCES: EMBASE, Cochrane, PubMed, and MEDLINE were systematically searched from January 1, 2000, to September 30, 2025.
STUDY SELECTION: We included studies of any design examining characteristics associated with the use of insulin pumps, continuous glucose monitors (CGM), or automated insulin delivery (AID) in T1D.
DATA EXTRACTION: Two reviewers independently screened and extracted data using a standardised tool. Determinants were categorised as non-modifiable or potentially modifiable barriers or enablers. Modifiable determinants were mapped to TDF domains to enable theory-informed synthesis.
DATA SYNTHESIS: Of 3081 citations identified, 303 studies (1 864 469 participants) were included. Non-modifiable determinants most frequently associated with technology use included racial/ethnic minority status (n = 90), age (n = 53), sex (n = 36), and socioeconomic status (n = 40). Potentially modifiable determinants clustered primarily within six TDF domains, most commonly Environmental Context and Resources, Social Influences, Knowledge, Skills, Beliefs about Consequences, and Emotions. Within these domains, key barriers included financial constraints (n = 117), provider gatekeeping and clinic processes (n = 43), and physical burden or body image concerns (n = 41). Key enablers included supportive patient-provider relationships and shared decision-making (n = 42), patient education and knowledge of device benefits (n = 40), and proactive provider engagement (n = 24).
LIMITATIONS: A large proportion of abstracts (35.3% overall; 70.6% of interventions), potential publication bias, exclusion of grey literature, predominance of US-based studies (62.4%), and few AID-only studies (6.9%) may limit generalisability.
CONCLUSIONS: Barriers to diabetes technology use map to key TDF domains, with structural factors predominating. Multilevel interventions targeting health system processes, provider practices, and education are needed to improve equitable uptake.
PURPOSE: To characterise barriers and enablers to the use of advanced diabetes technologies among individuals with T1D and to synthesise these determinants using the Theoretical Domains Framework.
DATA SOURCES: EMBASE, Cochrane, PubMed, and MEDLINE were systematically searched from January 1, 2000, to September 30, 2025.
STUDY SELECTION: We included studies of any design examining characteristics associated with the use of insulin pumps, continuous glucose monitors (CGM), or automated insulin delivery (AID) in T1D.
DATA EXTRACTION: Two reviewers independently screened and extracted data using a standardised tool. Determinants were categorised as non-modifiable or potentially modifiable barriers or enablers. Modifiable determinants were mapped to TDF domains to enable theory-informed synthesis.
DATA SYNTHESIS: Of 3081 citations identified, 303 studies (1 864 469 participants) were included. Non-modifiable determinants most frequently associated with technology use included racial/ethnic minority status (n = 90), age (n = 53), sex (n = 36), and socioeconomic status (n = 40). Potentially modifiable determinants clustered primarily within six TDF domains, most commonly Environmental Context and Resources, Social Influences, Knowledge, Skills, Beliefs about Consequences, and Emotions. Within these domains, key barriers included financial constraints (n = 117), provider gatekeeping and clinic processes (n = 43), and physical burden or body image concerns (n = 41). Key enablers included supportive patient-provider relationships and shared decision-making (n = 42), patient education and knowledge of device benefits (n = 40), and proactive provider engagement (n = 24).
LIMITATIONS: A large proportion of abstracts (35.3% overall; 70.6% of interventions), potential publication bias, exclusion of grey literature, predominance of US-based studies (62.4%), and few AID-only studies (6.9%) may limit generalisability.
CONCLUSIONS: Barriers to diabetes technology use map to key TDF domains, with structural factors predominating. Multilevel interventions targeting health system processes, provider practices, and education are needed to improve equitable uptake.