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Schipp J, Hendrieckx C, Braune K, Knoll C, O'Donnell S, Ballhausen H, Cleal B, Wäldchen M, Lewis DM, Gajewska KA, Skinner TC, Speight J. Psychosocial Outcomes Among Users and Nonusers of Open-Source Automated Insulin Delivery Systems: Multinational Survey of Adults With Type 1 Diabetes. J Med Internet Res 2023; 25:e44002. [PMID: 38096018 PMCID: PMC10755653 DOI: 10.2196/44002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 06/10/2023] [Accepted: 10/23/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Emerging research suggests that open-source automated insulin delivery (AID) may reduce diabetes burden and improve sleep quality and quality of life (QoL). However, the evidence is mostly qualitative or uses unvalidated, study-specific, single items. Validated person-reported outcome measures (PROMs) have demonstrated the benefits of other diabetes technologies. The relative lack of research investigating open-source AID using PROMs has been considered a missed opportunity. OBJECTIVE This study aimed to examine the psychosocial outcomes of adults with type 1 diabetes using and not using open-source AID systems using a comprehensive set of validated PROMs in a real-world, multinational, cross-sectional study. METHODS Adults with type 1 diabetes completed 8 validated measures of general emotional well-being (5-item World Health Organization Well-Being Index), sleep quality (Pittsburgh Sleep Quality Index), diabetes-specific QoL (modified DAWN Impact of Diabetes Profile), diabetes-specific positive well-being (4-item subscale of the 28-item Well-Being Questionnaire), diabetes treatment satisfaction (Diabetes Treatment Satisfaction Questionnaire), diabetes distress (20-item Problem Areas in Diabetes scale), fear of hypoglycemia (short form of the Hypoglycemia Fear Survey II), and a measure of the impact of COVID-19 on QoL. Independent groups 2-tailed t tests and Mann-Whitney U tests compared PROM scores between adults with type 1 diabetes using and not using open-source AID. An analysis of covariance was used to adjust for potentially confounding variables, including all sociodemographic and clinical characteristics that differed by use of open-source AID. RESULTS In total, 592 participants were eligible (attempting at least 1 questionnaire), including 451 using open-source AID (mean age 43, SD 13 years; n=189, 41.9% women) and 141 nonusers (mean age 40, SD 13 years; n=90, 63.8% women). Adults using open-source AID reported significantly better general emotional well-being and subjective sleep quality, as well as better diabetes-specific QoL, positive well-being, and treatment satisfaction. They also reported significantly less diabetes distress, fear of hypoglycemia, and perceived less impact of the COVID-19 pandemic on their QoL. All were medium-to-large effects (Cohen d=0.5-1.5). The differences between groups remained significant after adjusting for sociodemographic and clinical characteristics. CONCLUSIONS Adults with type 1 diabetes using open-source AID report significantly better psychosocial outcomes than those not using these systems, after adjusting for sociodemographic and clinical characteristics. Using validated, quantitative measures, this real-world study corroborates the beneficial psychosocial outcomes described previously in qualitative studies or using unvalidated study-specific items.
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Affiliation(s)
- Jasmine Schipp
- The Australian Centre for Behavioural Research in Diabetes, Carlton, Australia
- Section for Health Services Research, Institute of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Christel Hendrieckx
- The Australian Centre for Behavioural Research in Diabetes, Carlton, Australia
- School of Psychology, Deakin University, Burwood, Australia
| | - Katarina Braune
- Department of Paediatric Endocrinology and Diabetes, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
- Dedoc Labs GmbH, Berlin, Germany
| | - Christine Knoll
- Department of Paediatric Endocrinology and Diabetes, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Shane O'Donnell
- School of Sociology & School of Medicine, University College Dublin, Dublin, Ireland
| | - Hanne Ballhausen
- Department of Paediatric Endocrinology and Diabetes, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
- Dedoc Labs GmbH, Berlin, Germany
| | - Bryan Cleal
- Diabetes Management Research, Steno Diabetes Center Copenhagen, Copenhagen, Denmark
| | - Mandy Wäldchen
- School of Sociology & School of Medicine, University College Dublin, Dublin, Ireland
| | | | - Katarzyna A Gajewska
- Diabetes Ireland, Dublin, Ireland
- School of Public Health, University College Cork, Cork, Ireland
| | - Timothy C Skinner
- The Australian Centre for Behavioural Research in Diabetes, Carlton, Australia
| | - Jane Speight
- The Australian Centre for Behavioural Research in Diabetes, Carlton, Australia
- School of Psychology, Deakin University, Burwood, Australia
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