Trial Review

Did you know?

The ANZCTR now automatically displays published trial results and simplifies the addition of trial documents such as unpublished protocols and statistical analysis plans.

These enhancements will offer a more comprehensive view of trials, regardless of whether their results are positive, negative, or inconclusive.

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been endorsed by the ANZCTR. Before participating in a study, talk to your health care provider and refer to this information for consumers
Trial registered on ANZCTR


Registration number
ACTRN12623000219684p
Ethics application status
Not yet submitted
Date submitted
13/02/2023
Date registered
2/03/2023
Date last updated
15/10/2023
Date data sharing statement initially provided
2/03/2023
Type of registration
Prospectively registered

Titles & IDs
Public title
The use of a voice recording app for diagnosis of Parkinson's disease for people living in rural and remote communities. A comparative study between people with early to mid-stage Parkinson's disease and age-matched healthy volunteers.
Scientific title
A comparative clinical study of a voice recording app for the diagnosis of Parkinson's disease for people living in rural and remote communities. A comparative study between people with early to mid-stage Parkinson's disease and age-matched healthy volunteers.
Secondary ID [1] 308491 0
Nil known
Universal Trial Number (UTN)
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Parkinson's disease 328301 0
Condition category
Condition code
Neurological 325351 325351 0 0
Parkinson's disease

Intervention/exposure
Study type
Observational
Patient registry
False
Target follow-up duration
Target follow-up type
Description of intervention(s) / exposure
Participants are requested to repeat sounds which are recorded on a mobile device (Tablet). Voice sounds include the voicing of the letters "oooooo" "mmmmm", "aaaaaa" "pppppp". The duration of the experiment is less than 5 minutes. The participant's recorded voice sounds are immediately saved electronically along with their #ID and sent directly to RMIT for secure storage and analysis.
Data collection sessions for participants diagnosed with Parkinson's disease will be conducted face-to-face from the participating Neurology clinic in Dandenong as well as Goulburn Valley Health (GVH), Shepparton, Victoria.
All experiments are conducted by the researchers from the School of Engineering, RMIT University or by a Movement disorders Nurse at GVH.
Intervention code [1] 324935 0
Early Detection / Screening
Intervention code [2] 324936 0
Diagnosis / Prognosis
Comparator / control treatment
Voice recordings of healthy age-matched controls.
Control group
Active

Outcomes
Primary outcome [1] 333219 0
Analysis of the dynamics of the voice using 2 parameters of measurement in combination - amplitude, and frequency assessed using the app recordings.
Timepoint [1] 333219 0
Assessed after a single session
Secondary outcome [1] 416198 0
Nil
Timepoint [1] 416198 0
Nil

Eligibility
Key inclusion criteria
1.People diagnosed with Parkinson's disease, as evidenced by Unified Parkinson's disease Rating Scale (UPDRS) scores consistent with minimal to moderate disease
2.Healthy age-matched controls
Minimum age
18 Years
Maximum age
No limit
Sex
Both males and females
Can healthy volunteers participate?
Yes
Key exclusion criteria
For Parkinson''s disease participants - diagnosed with other neurodegenerative diseases or stroke

For healthy controls - diagnosis of any neurodegenerative disease or stroke

Study design
Purpose
Screening
Duration
Cross-sectional
Selection
Defined population
Timing
Prospective
Statistical methods / analysis
Sample size is calculated using a large effect size of 0.8 based on previous studies reported in a systematic review reported by our team (1.).
Statistical methods used for evaluation will be based on group differences (Independent-samples-t test / MANOVA or non parametric equivalent as required).

1.Ngo, Q.C., Motin, M.A., Pah, N.D., Drotár, P., Kempster, P. and Kumar, D., 2022. Computerized analysis of speech and voice for Parkinson's disease: A systematic review. Computer Methods and Programs in Biomedicine, p.107133.)

Recruitment
Recruitment status
Not yet recruiting
Date of first participant enrolment
Anticipated
13/11/2023
Actual
Date of last participant enrolment
Anticipated
20/11/2026
Actual
Date of last data collection
Anticipated
20/11/2026
Actual
Sample size
Target
60
Accrual to date
Final
Recruitment in Australia
Recruitment state(s)
VIC

Funding & Sponsors
Funding source category [1] 312733 0
University
Name [1] 312733 0
RMIT University
Country [1] 312733 0
Australia
Primary sponsor type
University
Name
RMIT University
Address
RMIT University, GPO Box 2476, Melbourne VIC 3001 Australia
Country
Australia
Secondary sponsor category [1] 314352 0
None
Name [1] 314352 0
Nil
Address [1] 314352 0
Nil
Country [1] 314352 0

Ethics approval
Ethics application status
Not yet submitted
Ethics committee name [1] 312029 0
RMIT HREC
Ethics committee address [1] 312029 0
GPO Box 2476, Melbourne VIC 3001 Australia
Ethics committee country [1] 312029 0
Australia
Date submitted for ethics approval [1] 312029 0
11/10/2023
Approval date [1] 312029 0
Ethics approval number [1] 312029 0

Summary
Brief summary
Speech impairment is an early sign of Parkinson’s disease. Analysis of features of voice may be used as a diagnostic tool for the detection of Parkinson’s disease and in the assessment of its severity. In addition, people living in rural and remote communities often have difficulties in accessing specialist physicians for both diagnosis and continued assessment of Parkinson’s disease. The ultimate aim of this work is to develop an automated diagnostic tool for the assessment of speech impairments associated with Parkinson’s disease that may be used remotely. Patients will be able to record their voice on their personal device. Voice recordings will be analysed and the recorded voice and analysis sent to the specialist physician.
The aim of this study is to ascertain features of the voice that are most useful in identifying differences in voice features between Parkinson’s disease patients and healthy age-matched controls using a mobile device. The hypothesis is that Parkinson’s disease patients will exhibit significantly different voice features compared with healthy age-matched controls.
Trial website
Trial related presentations / publications
Public notes

Contacts
Principal investigator
Name 123234 0
Prof Dinesh Kumar
Address 123234 0
RMIT University
GPO Box 2476, Melbourne VIC 3001 Australia
Country 123234 0
Australia
Phone 123234 0
+61 399251954
Fax 123234 0
Email 123234 0
[email protected]
Contact person for public queries
Name 123235 0
Dinesh Kumar
Address 123235 0
RMIT University
GPO Box 2476, Melbourne VIC 3001 Australia
Country 123235 0
Australia
Phone 123235 0
+61 399251954
Fax 123235 0
Email 123235 0
[email protected]
Contact person for scientific queries
Name 123236 0
Dinesh Kumar
Address 123236 0
RMIT University
GPO Box 2476, Melbourne VIC 3001 Australia
Country 123236 0
Australia
Phone 123236 0
+61 399251954
Fax 123236 0
Email 123236 0
[email protected]

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
No/undecided IPD sharing reason/comment
Saved data will not be identifiable except for participant grouping (healthy or Parkinson's disease)


What supporting documents are/will be available?

Doc. No.TypeCitationLinkEmailOther DetailsAttachment
18266Study protocol    Directly from researchers conducting the study
18267Informed consent form    Directly from researchers conducting the study
18268Ethical approval    Directly from researchers conducting the study



Results publications and other study-related documents

Documents added manually
No documents have been uploaded by study researchers.

Documents added automatically
No additional documents have been identified.