Psychosocial Outcome Improvement Observed in Diabetes Patients Using Automated Insulin Delivery


Addressing a lack of quantitative data on AID, this study used validated measures in a real-world setting to corroborate the psychosocial benefits seen in prior qualitative research.

Adult type 1 diabetes patients using open-source automated insulin delivery (AID) report having comparatively better psychosocial outcomes versus patients not implementing AID systems, according to recent findings, after adjusting for clinical and sociodemographic data.1

These findings resulted from a new real-world study conducted to better quantify data from prior findings on AID and psychosocial outcomes for type 1 diabetes, which were viewed by the investigators as more qualitative.

The research was led by Jasmine Schipp, from the Australian Centre for Behavioural Research in Diabetes in the city of Carlton, Australia. Schipp and colleagues noted that there had not, on a larger scale, been an analysis of person-reported outcome measures (PROMs) on pros and cons of AID system use and that this had been an opportunity missed.2

“Thus, our aim was to compare the psychosocial outcomes of adults with type 1 diabetes using and not using open-source AID systems through the completion of validated PROMs in a multinational web-based survey,” Schipp and colleagues wrote.

Background and Findings

The research team’s design had been partially formed thanks to the ‘Outcomes of Patients’ Evidence with Novel, Do-it-Yourself Artificial Pancreas Technology Project Consortium’ (OPEN). This was made up of a team of various disciplines, including social scientists, physicians, data scientists, developers of open-source AID, public health researchers, and more.

Many of those involved with OPEN had experience in type 1 diabetes and in the utilization of AID. This smaller study was a segment of the overall research conducted thanks to OPEN.

The investigators subjected adult participants with diagnoses of type 1 diabetes with assessments associated with their diabetes-specific quality of life, their overall emotional state of mind, their quality of sleep, their positive well-being, their satisfaction with the treatment, distress related to diabetes, their potential fears regarding hypoglycemia, and the overall impact of COVID-19 on their life quality.

The research team sought to compare outcome measure scores reported by study participants between those utilizing and those not utilizing the open-source AID. The team accomplished this by using independent groups, 2-tailed t tests, and Mann-Whitney U tests.

The investigators carried out an assessment of covariance to account for the potential confounders involved in this research. The analysis covered sociodemographic as well as clinical characteristics that showed differences based upon the implementation of open-source AID.

The study subjects were found by the team thanks to their utilization of diabetes community platforms found on the Internet. Some of these platforms were Facebook groups that supported the open-source AID community, and the team also used the OPEN international health care professional network and the OPEN project Facebook and Twitter (X) accounts.

Overall, the research team ended up involving 592 eligible subjects, all of which had been required to fill out at least 1 questionnaire. This population was made up of 2 cohorts, the first of which had 451 participants that used the open-source AID systems and had a mean age of 43 (41.9% of which were women).

The other cohort was made up of 141 subjects labeled as ‘nonusers,’ with a mean age 40 and 63.8% of which were women. The subjects in the user group for open-source AID were found to show notably enhanced levels of general emotional well-being as well as enhanced levels of subjective sleep quality.

The user arm of the study also was shown by the investigators to have improvement in diabetes-specific Quality of Life (QoL), as well as similar improvements in positive well-being and satisfaction with treatment. They found the AID user arm also had far lower levels of diabetes distress, hypoglycemia fear, and perceptions of the COVID-19 pandemic’s impact on their QoL.

Such differences, which the research team noted were characterized by medium-to-large effects (Cohen d=0.5-1.5), were found to have stayed statistically significant between both of the 2 cohorts even when the team adjusted for sociodemographic and clinical data.

“This study indicates that validated PROMs can quantify the sentiments previously expressed qualitatively (or using unvalidated single items) by the community,” they wrote. “Further research is needed to examine the reasons for these differences.”


  1. Schipp J, Hendrieckx C, Braune K, Knoll C, et al. 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:e 44002. doi: 10.2196/44002
  2. Vallis M, Holt RIG. User-driven open-source artificial pancreas systems and patient-reported outcomes: a missed opportunity? Diabet Med. 2022;39(5):e14797 [CrossRef] [Medline].
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