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Trial registered on ANZCTR
Registration number
ACTRN12622000486729
Ethics application status
Approved
Date submitted
16/03/2022
Date registered
28/03/2022
Date last updated
28/03/2022
Date data sharing statement initially provided
28/03/2022
Type of registration
Retrospectively registered
Titles & IDs
Public title
Using speech characteristics to classify suicide risk in telehealth callers
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Scientific title
Using speech characteristics to classify low versus high risk of suicide in 64 male and female telehealth counselling calls
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Secondary ID [1]
306700
0
Nil known
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Universal Trial Number (UTN)
U1111-1275-8186
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Trial acronym
RELIANCE (REaL tIme ANalysis of voiCE)
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Linked study record
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Health condition
Health condition(s) or problem(s) studied:
suicide
325664
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Condition category
Condition code
Mental Health
323013
323013
0
0
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Suicide
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Intervention/exposure
Study type
Observational
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Patient registry
False
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Target follow-up duration
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Target follow-up type
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Description of intervention(s) / exposure
Duration of observation is 1/7/2020 - 30/6/21
Call recordings made to a national telehealth suicide prevention service will be observed throughout the duration of each call. Callers identified as being at high risk of imminent suicide will be identified. Callers will by identified via screening questions ("are you at risk of suicide", and "do you have a plan that you will carry out"). High risk of suicide status will be initially assigned by the responding counsellor using an organisational risk framework, then confirmed retrospectively by a team of Associate Researchers and finally re-confirmed by the student investigator, using the Columbia Suicide Severity Risk rating (ratings 5 and 6). Calls are made form private homes, and in public spaces.
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Intervention code [1]
323146
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Early Detection / Screening
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Comparator / control treatment
Call recordings made to a national telehealth suicide prevention service will be observed throughout the duration of each call. Callers identified as being at low risk of imminent suicide will be identified. Callers will by identified via screening questions ("are you at risk of suicide", and "do you have a plan that you will carry out"). Low risk of suicide status will be initially assigned by the responding counsellor using an organisational risk framework, then confirmed retrospectively by a team of Associate Researchers and finally re-confirmed by the student investigator, using the Columbia Suicide Severity Risk rating (ratings 1 and 2). Calls are made form private homes, and in public spaces.
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Control group
Active
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Outcomes
Primary outcome [1]
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High risk of suicide shall be determined via assessment using the Columbia Suicide Severity Rating Scale (CSSR-S) (Rating 5 and 6) (highest levels)
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Assessment method [1]
330780
0
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Timepoint [1]
330780
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Assessment of high risk of suicide will be made at the conclusion of each call, and after listening to each call recording in full.
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Secondary outcome [1]
407538
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Emotional distress shall be assessed via the Distress Barometer (10 point Likert-style scale, 0=absence of emotional distress; 10 = highest level emotional distress).
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Assessment method [1]
407538
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Timepoint [1]
407538
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Emotional distress shall be assessed at various timepoints across each call recording. Timepoints shall correspond to a variety of emotional distress ratings within each recording.
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Eligibility
Key inclusion criteria
English speaking; call made within Australia; 18+ years
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Minimum age
18
Years
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Maximum age
No limit
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Sex
Both males and females
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Can healthy volunteers participate?
Yes
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Key exclusion criteria
Calls made via teletext or requiring third party translation; speech difficulties (motor articulation); intoxication.
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Study design
Purpose
Screening
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Duration
Cross-sectional
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Selection
Defined population
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Timing
Retrospective
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Statistical methods / analysis
Preprocessing of call recordings will include conversion to alternative format (8kHz; 16-bit PCM) compatible with RStudio. Recordings will be normalised and pre-emphasis applied to attenuate low frequencies and magnify high frequencies.
Analysis will involve:
1. L1-penalised Lasso Regression to reduce the number of extracted speech characteristics.
2. 3-level Mixed Effects Generalised Additive Modelling (GAMM) with speech characteristics extracted at within 40ms (50% overlapping) Blackman-windowed frames (level 1); Annotated Segments with Power Spectral Density characteristics (level 2); and individual callers with identified sex of caller (level 3). Binary regression with logit link will be used to discriminate between low and high risk of suicide response. AR1 autocorrelation will also be applied to level 1 predictors.
3. Component-wise Gradient Boosting well be used to automatically classify each recording to either low or high risk of suicide categories. The algorithm will be trained on 70% of the recordings, while the remaining 30% will be used for validation purposes.
The methods used at 2. and 3. will allow for significant non-linearity amongst the predictors by using splines to more accurately model the data.
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Recruitment
Recruitment status
Completed
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Date of first participant enrolment
Anticipated
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Actual
8/07/2021
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Date of last participant enrolment
Anticipated
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Actual
15/07/2021
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Date of last data collection
Anticipated
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Actual
15/07/2021
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Sample size
Target
500
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Accrual to date
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Final
840
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Recruitment in Australia
Recruitment state(s)
ACT,NSW,NT,QLD,SA,TAS,WA,VIC
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Funding & Sponsors
Funding source category [1]
311030
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Charities/Societies/Foundations
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Name [1]
311030
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On The Line
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Address [1]
311030
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PO Box 2339,
Footscray,
Vic 311
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Country [1]
311030
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Australia
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Funding source category [2]
311033
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Government body
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Name [2]
311033
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Australian Federal Police
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Address [2]
311033
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Cnr College Street and Benjamin Way, Belconnen ACT 2617
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Country [2]
311033
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Australia
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Primary sponsor type
University
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Name
Swinburne University of Technology
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Address
John Street
Hawthorn
Vic. 3122
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Country
Australia
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Secondary sponsor category [1]
312353
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None
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Name [1]
312353
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Address [1]
312353
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Country [1]
312353
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Ethics approval
Ethics application status
Approved
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Ethics committee name [1]
310578
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Swinburne University Human Research Ethics Committee
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Ethics committee address [1]
310578
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John Street, Hawthorn Vic. 3122
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Ethics committee country [1]
310578
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Australia
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Date submitted for ethics approval [1]
310578
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01/12/2020
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Approval date [1]
310578
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22/01/2021
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Ethics approval number [1]
310578
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20214340-5805
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Summary
Brief summary
The primary hypothesis of the study is to automatically classify a sample of call recordings obtained from our telehealth partners according to risk of suicide. Risk of suicide is defined as low (levels 1 and 2 on the Columbia Suicide Severity Rating scale, CSSR-S) and High (levels 5 and 6 on the CSSR-R). Call recordings will be sourced from two industry partners including On The Line who administer the Suicide Call Back service and the Australian Federal Police who administer 000 emergency services in the Canberra, Australia region.
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Trial website
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Trial related presentations / publications
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Public notes
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Contacts
Principal investigator
Name
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Prof Denny Meyer
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Address
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Centre for Mental Health
Swinburne University of Technology
John Street
Hawthorn
Vic. 3122
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Country
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Australia
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Phone
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+61 03 9214 4824
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Fax
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Email
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[email protected]
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Contact person for public queries
Name
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Ravi Iyer
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Address
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Centre for Mental Health
Swinburne University of Technology
John Street
Hawthorn
Vic. 3122
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Country
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Australia
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Phone
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+61 456 565 575
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Fax
118147
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Email
118147
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[email protected]
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Contact person for scientific queries
Name
118148
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Ravi Iyer
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Address
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Centre for Mental Health
Swinburne University of Technology
John Street
Hawthorn
Vic. 3122
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Country
118148
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Australia
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Phone
118148
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+61 456 565 575
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Fax
118148
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Email
118148
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[email protected]
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Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
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No/undecided IPD sharing reason/comment
Call recordings contain personally identifiable information and relate to sensitive information being discussed in a counselling context.
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What supporting documents are/will be available?
No Supporting Document Provided
Results publications and other study-related documents
Documents added manually
No documents have been uploaded by study researchers.
Documents added automatically
Source
Title
Year of Publication
DOI
Embase
Using Voice Biomarkers to Classify Suicide Risk in Adult Telehealth Callers: Retrospective Observational Study.
2022
https://dx.doi.org/10.2196/39807
N.B. These documents automatically identified may not have been verified by the study sponsor.
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