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This study explores the perspectives and needs of people dealing with type 1 diabetes or their carers to co-design a voice-based digital health intervention for supporting diabetes distress management.
New technologies restore people with type 1 diabetes to a certain degree of independence and control over their lives while allowing medical providers to keep an overview of their patient's general health conditions and the evolution of their treatments. Notably, solutions integrating voice-processing technology appeared to be encouraging alternatives for remote monitoring.
Diabetes distress is a common condition in people living with type 1 diabetes. Diabetes distress is associated with poor metabolic control and low quality of life. Because voice analysis involves highly complex methods for processing audio features, this kind of development might also be capable of detecting subtle changes associated with psychological factors, like diabetes distress.
Nevertheless, digital health incorporation into the everyday lives of potential users might also imply a big challenge for many of them.
For this reason, studying the needs of the end-users of technological tools before defining any aspect of their design has become a critical step in developing this kind of technology.
The main objective of Psyvoice is to identify the preferences of people living with type 1 diabetes for voice-based digital health solutions for diabetes distress detection and control.
Secondary objectives are:
To achieve all of these objectives, the investigators will conduct in-depth interviews.
The study will combine qualitative and quantitative methods. The investigators will invite twenty people with a T1D diagnosis or caregivers of children diagnosed with this condition to participate in semi-structured in-depth interviews and questionnaires. The questionnaires will be composed of a Socio-demographic, an e-Health Literacy (eHLQ) questionnaire, and a Diabetes Distress (PAID) scale.
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| Measure | Description | Time Frame |
|---|---|---|
| Semi-structured interviews | Analyzing semi-structured interviews using a qualitative research methods approach will allow extracting the themes that matter for people when expressing preferences regarding digital voice technology. | At baseline |
| Measure | Description | Time Frame |
|---|---|---|
| Patient reported outcomes | Diabetes distress and e-health literacy will be described with a validated self-reported scale | At baseline |
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Inclusion Criteria:
Exclusion Criteria:
Unwilling or unable to participate in online interviews.
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Diabetes clinic and diabetes patient association
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| Name | Affiliation | Role |
|---|---|---|
| Guy A Fagherazzi, PhD | Luxembourg Institute of Health | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Luxembourg Institute of Health | Strassen | 1445 | Luxembourg |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34485879 | Background | Kiriella DA, Islam S, Oridota O, Sohler N, Dessenne C, de Beaufort C, Fagherazzi G, Aguayo GA. Unraveling the concepts of distress, burnout, and depression in type 1 diabetes: A scoping review. EClinicalMedicine. 2021 Aug 28;40:101118. doi: 10.1016/j.eclinm.2021.101118. eCollection 2021 Oct. | |
| 29067269 | Background |
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| ID | Term |
|---|---|
| D003922 | Diabetes Mellitus, Type 1 |
| D003863 | Depression |
| D001008 | Anxiety Disorders |
| ID | Term |
|---|---|
| D003920 | Diabetes Mellitus |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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| Mathiesen AS, Thomsen T, Jensen T, Schiotz C, Langberg H, Egerod I. The influence of diabetes distress on digital interventions for diabetes management in vulnerable people with type 2 diabetes: A qualitative study of patient perspectives. J Clin Transl Endocrinol. 2017 Jul 11;9:41-47. doi: 10.1016/j.jcte.2017.07.002. eCollection 2017 Sep. |
| 35274356 | Background | Hart RI, Kimbell B, Rankin D, Allen JM, Boughton CK, Campbell F, de Beaufort C, Frohlich-Reiterer E, Ware J, Hofer SE, Kapellen TM, Rami-Merhar B, Thankamony A, Hovorka R, Lawton J; KidsAP Consortium. Parents' experiences of using remote monitoring technology to manage type 1 diabetes in very young children during a clinical trial: Qualitative study. Diabet Med. 2022 Jul;39(7):e14828. doi: 10.1111/dme.14828. Epub 2022 Mar 24. |
| 34056518 | Background | Fagherazzi G, Fischer A, Ismael M, Despotovic V. Voice for Health: The Use of Vocal Biomarkers from Research to Clinical Practice. Digit Biomark. 2021 Apr 16;5(1):78-88. doi: 10.1159/000515346. eCollection 2021 Jan-Apr. |
| 39753264 | Derived | Aguirre Vergara F, Pinker I, Fischer A, Seuring T, Tichomirowa MA, de Beaufort C, Kamp SM, Fagherazzi G, Aguayo GA. Readiness of adults with type 1 diabetes and diabetes caregivers for diabetes distress monitoring using a voice-based digital health solution: insights from the PsyVoice mixed methods study. BMJ Open. 2025 Jan 2;15(1):e088424. doi: 10.1136/bmjopen-2024-088424. |
| 37709324 | Derived | Aguirre Vergara F, Fischer A, Seuring T, de Beaufort C, Fagherazzi G, Aguayo GA. Mixed-methods study protocol to identify expectations of people with type 1 diabetes and their caregivers about voice-based digital health solutions to support the management of diabetes distress: the PsyVoice study. BMJ Open. 2023 Sep 13;13(9):e068264. doi: 10.1136/bmjopen-2022-068264. |
| D004700 | Endocrine System Diseases |
| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |
| D001526 | Behavioral Symptoms |
| D001519 | Behavior |
| D001523 | Mental Disorders |