Technology-Enabled Collaborative Care for Diabetes and Mental Health (TECC-DM): Establishing a treatment care pathway in primary care settings

Background: For those living with type 2 diabetes (T2D), mental health issues including distress, anxiety, and depression are common. However, existing models of care require those living with these co-occurring conditions to navigate a fragmented healthcare system across providers, settings, and even sectors to receive adequate physical and mental health services. In a completed co-designed mixed methods explanatory sequential feasibility trial, titled Technology-Enabled Collaborative Care for Diabetes and Mental Health (TECC-DM), existing assets, including widely available technology, were leveraged to integrate T2D and mental health support through weekly virtual health coaching sessions, supported by an interdisciplinary virtual care team over 8 weeks. Primary outcomes included the feasibility and acceptability of the TECC-D model with exploratory outcomes including changes in mental health, substance use, and physical health behaviours collected at baseline, 4, 8, and 12 weeks. 31 adults with T2D and self-identified mental health challenges completed the trial with study findings revealing that the TECC-DM model is feasible and scalable, and that it additionally empowers individuals to take an active role in improving their physical and mental health. Findings also identified that while clinical and professional integration were acceptable and impactful, there was a need to better facilitate access to and treatment through primary care. This includes a need to identify and describe existing practice gaps contributing to barriers to uptake and engagement with personalized T2D self-management care in primary care settings. Objective: With the rapid shift to virtual models of care delivery, there was a need to uncover whom the TECC-DM model best supports, how to identify individuals who may benefit from the program, and how this model could be tailored, linked to, and delivered in primary care settings. Through the mobilization of the TECC-DM feasibility findings, this project served to disseminate (share findings from the co-designed program) and plan (development of an access to treatment pathway to support a future trial; future relationship and capacity building). Methods: To better understand TECC-DM study findings, a mixed methods survey of primary care providers (PCPs) was completed. Distributed through the Smoking Treatment for Ontario Patients (STOP) Program, PCPs included primary care physicians, nurse practitioners, and other allied health professionals from solo practices, family health teams, and community health centres. Partnership: In addition to the TECC-DM study team, a person with lived experience was engaged as a co-researcher in all aspects of this study. This includes development of the survey, analysis and interpretation of findings, and knowledge mobilization. Findings and Next Steps: In conjunction with TECC-DM feasibility findings, survey findings identify that using existing technology and health human resources is an acceptable solution to participants, providers, and partners. Understanding the ways by which individuals with T2D and mental health challenges access (or fail to access) treatment, including barriers to integrated care, is necessary to achieve optimal, whole person care. Leveraging findings from the TECC-DM feasibility trial and these survey findings, our team will further develop the TECC-DM model for full-scale testing.

Authors

Publication Details

Journal
International Journal of Integrated Care
Published
2025-04-09
DOI
https://doi.org/10.5334/ijic.icic24045
Citations
1
Primary Topic
Diabetes Management and Education
Type
article
Field-Weighted Citation Impact
1.29
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Technology-Enabled Collaborative Care for Diabetes and Mental Health (TECC-DM): Establishing a treatment care pathway in primary care settings

Diana Sherifali, Osnat C. Melamed, Carly Whitmore, John Forsythe et al.
1 citations
International Journal of Integrated Care
Diabetes Management and Education
1.29
article

Technology-Enabled Collaborative Care for Diabetes and Mental Health (TECC-DM): Establishing a treatment care pathway in primary care settings

Diana Sherifali, Osnat C. Melamed, Carly Whitmore, John Forsythe, Peter J. Selby, Farooq Naeem
article en
1 citations

Abstract

Background: For those living with type 2 diabetes (T2D), mental health issues including distress, anxiety, and depression are common. However, existing models of care require those living with these co-occurring conditions to navigate a fragmented healthcare system across providers, settings, and even sectors to receive adequate physical and mental health services. In a completed co-designed mixed methods explanatory sequential feasibility trial, titled Technology-Enabled Collaborative Care for Diabetes and Mental Health (TECC-DM), existing assets, including widely available technology, were leveraged to integrate T2D and mental health support through weekly virtual health coaching sessions, supported by an interdisciplinary virtual care team over 8 weeks. Primary outcomes included the feasibility and acceptability of the TECC-D model with exploratory outcomes including changes in mental health, substance use, and physical health behaviours collected at baseline, 4, 8, and 12 weeks. 31 adults with T2D and self-identified mental health challenges completed the trial with study findings revealing that the TECC-DM model is feasible and scalable, and that it additionally empowers individuals to take an active role in improving their physical and mental health. Findings also identified that while clinical and professional integration were acceptable and impactful, there was a need to better facilitate access to and treatment through primary care. This includes a need to identify and describe existing practice gaps contributing to barriers to uptake and engagement with personalized T2D self-management care in primary care settings. Objective: With the rapid shift to virtual models of care delivery, there was a need to uncover whom the TECC-DM model best supports, how to identify individuals who may benefit from the program, and how this model could be tailored, linked to, and delivered in primary care settings. Through the mobilization of the TECC-DM feasibility findings, this project served to disseminate (share findings from the co-designed program) and plan (development of an access to treatment pathway to support a future trial; future relationship and capacity building). Methods: To better understand TECC-DM study findings, a mixed methods survey of primary care providers (PCPs) was completed. Distributed through the Smoking Treatment for Ontario Patients (STOP) Program, PCPs included primary care physicians, nurse practitioners, and other allied health professionals from solo practices, family health teams, and community health centres. Partnership: In addition to the TECC-DM study team, a person with lived experience was engaged as a co-researcher in all aspects of this study. This includes development of the survey, analysis and interpretation of findings, and knowledge mobilization. Findings and Next Steps: In conjunction with TECC-DM feasibility findings, survey findings identify that using existing technology and health human resources is an acceptable solution to participants, providers, and partners. Understanding the ways by which individuals with T2D and mental health challenges access (or fail to access) treatment, including barriers to integrated care, is necessary to achieve optimal, whole person care. Leveraging findings from the TECC-DM feasibility trial and these survey findings, our team will further develop the TECC-DM model for full-scale testing.

International Journal of Integrated CareVol. 25
Openalex Percentile: Top 21%
Diabetes Management and Education
1.29
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.