Expectations of People With Type 1 Diabetes About Voice-based Interventions to Support Diabetes Distress Management

NCT ID: NCT05517772

Last Updated: 2023-10-25

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

12 participants

Study Classification

OBSERVATIONAL

Study Start Date

2022-06-16

Study Completion Date

2023-05-02

Brief Summary

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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.

Detailed Description

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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:

1. Delineating the properties that an instrument for diabetes distress management must incorporate to be considered adequate by its intended users (e.g. single voice-analysis function exclusively for diabetes distress management vs multiple functions or multiple uses).
2. Determining the attributes (e.g. frequency of use) that could make a digital health solution prone to be integrated by its end-users into their everyday lives.
3. Defining the characteristics likely to make a digital health solution acceptable. These are privacy and security concerns, barriers of use (difficulties with technology, disability) and facilitators of use (technical support, use of plain language).

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.

Conditions

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type1diabetes Diabetes Distress

Study Design

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Observational Model Type

OTHER

Study Time Perspective

CROSS_SECTIONAL

Eligibility Criteria

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Inclusion Criteria

1. Men or women with a Type 1 diabetes diagnosis /caregivers of children diagnosed with T1D
2. Able to speak and read in English, German, or French.

Exclusion Criteria

Unwilling or unable to participate in online interviews.
Minimum Eligible Age

13 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Luxembourg Institute of Health

OTHER_GOV

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Guy A Fagherazzi, PhD

Role: PRINCIPAL_INVESTIGATOR

Luxembourg Institute of Health

Locations

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Luxembourg Institute of Health

Strassen, , Luxembourg

Site Status

Countries

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Luxembourg

References

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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.

Reference Type BACKGROUND
PMID: 34485879 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 29067269 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 35274356 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 34056518 (View on PubMed)

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.

Reference Type DERIVED
PMID: 39753264 (View on PubMed)

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.

Reference Type DERIVED
PMID: 37709324 (View on PubMed)

Other Identifiers

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PSYVOICE

Identifier Type: -

Identifier Source: org_study_id

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