FrailtyDIVANNCT05783401
Digital Voice Analysis as a Measure of Frailty and Distress
An observational study of Frailty and Distress, Emotional, run by University Hospital, Basel, Switzerland at 2 sites in Switzerland.
Trial summary
This study evaluates if it is possible to identify quantitative parameters from audio signals to describe the changes in patient's state in relation to frailty and distress. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Frailty, Distress, Emotional
- What is being tested?
- Data acquisition: Speech acquisition, Data acquisition: G8 Screening tool and Data acquisition: Distress Thermometer
- Type of treatment
- Pill or oral medicine
- How many people
- 100 participants
- Where
- 2 sitesSwitzerland
- Study dates
- 19 Nov 2022to Nov 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patient recruitment will be performed at the different participating clinical sites by the investigator
Who may be able to join
- Active cancer or haemato-oncological malignancy
- Adults (≥ 18 years)
- Ability to understand, speak and read German language fluently
- Ability to provide written consent
- Sufficient or corrected vision to see the images
- Sufficient auditory comprehension for participation in the study based on the therapist's clinical opinion
- Ability to concentrate for 20-30 minutes based on the investigator's clinical opinion
- Signed informed consent to the study
Who cannot join
- Aphonia, dysphonia or other obvious voice alterations of patient's voice
- Life-expectancy shorter ≤ 14 days as judged by a physician or nurse via "surprise question"
- Breathlessness whilst speaking
- Cognitive impairment as judged by physician or Mini-Cog in the G8 screening tool
- Severe physical, emotional or existential suffering because of which the enrollment and participation in the study would result in patient burden, as judged by the treating physicians and their multiprofessional team members
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
Switzerland2 sites, 2 recruiting
- Recruiting
Palliativzentrum Hildegard, Basel
Basel, 4002
Jan Gärtner, Prof. Dr. med., +41 61 319 7575, jan.gaertner@pzhi.ch
Jan Gärtner, Prof. Dr. med.
- Recruiting
Kantonsspital Baselland, Klinik für Onkologie, Hämatologie und Immuntherapie
Liestal, 4410
Marcus Vetter, PD Dr. med., + 41 61 925 2525, marcus.vetter@ksbl.ch
Marcus Vetter, PD Dr. med.
About this study
Official title: Digital Voice Analysis as a Measure of Frailty and Distress. A Feasibility Study (DIVAN)
This study evaluates if it is possible to identify quantitative parameters from audio signals to describe the changes in patient's state in relation to frailty and distress.
Read the detailed description
Frailty is a common clinical syndrome especially in older adults that carries an increased risk for poor health outcomes including falls, incident disability, hospitalization, and mortality. The early detection of frailty is of importance in many patient populations to predict treatment outcomes, identify patient needs and coordinate efficient and meaningful care. An electronic assessment of the degree of distress in patients, who are unable to report, would be important to be able to routinely and objectively identify suffering in these patients. Digital voice analysis (DVA) gathers speech samples from individuals via different kinds of recording devices (smartphone, tablet, etc.) and examines a large variety of specific acoustic parameters such as for example frequency and voice quality features. This study is to analyse the potential to evaluate distress and frailty through digital voice analysis. On the contrary to the existing studies, it is intended to record audio and clinical evaluation data from the same subject multiple times during several weeks to be able to analyse temporal changes. This will allow to not only perform inter-subject but as well intra-subject comparisons of changes in audio features with changes of the patient's wellbeing over time. To make the patient speak as freely and relaxed as possible, the patient will describe different images. Different features will be extracted from the audios and potential candidates for a larger patient study will be identified, if data quantity permits using machine learning algorithms. Therefore this study evaluates if it is feasible to gather digital voice samples for voice analyses from cancer patients alongside conventional assessments for frailty (G8 questionnaire and distress (Distress Thermometer) to conduct first, preliminary analyses for identification of potential correlates between voice features and frailty or distress and between changes over time.
- Conditions
- Frailty, Distress, Emotional
- Being tested
- Data acquisition: Speech acquisition, Data acquisition: G8 Screening tool, Data acquisition: Distress Thermometer
- Keywords
- Frailty monitoring, Distress monitoring, Digital voice analysis (DVA), Machine learning, Distress Thermometer, G8 geriatric screening tool
- Medical subject headings
- Frailty
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Data acquisition: Speech acquisitionOther
Speech test with synchronized audio and video recording. The speaking exercises and the audio and video recording will be done using a tablet computer and an application developed in-house. Freely available images showing different scenes will be integrated and displayed on the tablet to be described by the patient. The goal is to have at least two and maximum four of them described with several sentences by each patient per session. Parameters will be extracted from the patient's audio data to estimate the changes in distress and frailty.
Data acquisition: G8 Screening toolDiagnostic test
The G8 screening tool consists of seven items dealing with food intake, weight loss, mobility, neuropsychological problem, body mass index, prescription drug, and self-perception of health, from the Mini-Nutritional Assessment (MNA) questionnaire and was developed specifically for elderly cancer patients. The total G-8 score lies between 0 and 17. A higher score indicates a better health status.
Data acquisition: Distress ThermometerDiagnostic test
The distress thermometer (DT) is a measure of psychological distress in cancer patients. The instrument is a self-reported tool using a 0-to-10 rating scale.
| Study group | Role | What they receive |
|---|---|---|
| Cohort A: palliative care center | Patients from a palliative care center (Palliativzentrum Hildegard, Basel) Receives: Other: Data acquisition: Speech acquisition; Diagnostic Test: Data acquisition: G8 Screening tool; Diagnostic Test: Data acquisition: Distress Thermometer | |
| Cohort B: mid-size cancer center | Patients from a mid-size cancer center (Tumorzentrum Baselland) Receives: Other: Data acquisition: Speech acquisition; Diagnostic Test: Data acquisition: G8 Screening tool; Diagnostic Test: Data acquisition: Distress Thermometer |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change of mean fundamental frequency extracted from the patient's audio data
Change of mean fundamental frequency extracted from the patient's audio data to estimate the changes in distress and frailty.
Measured: during a 16-week period for each patient
Change of first few formants (F1, F2)
Change of first few formants (F1, F2) extracted from the patient's audio data to estimate the changes in distress and frailty.
Measured: during a 16-week period for each patient
Change of jitter (variation in F0 from cycle to cycle)
Change of jitter (variation in F0 from cycle to cycle) extracted from the patient's audio data to estimate the changes in distress and frailty.
Measured: during a 16-week period for each patient
Change of shimmer (variation in peak-to-peak amplitude)
Change of shimmer (variation in peak-to-peak amplitude) extracted from the patient's audio data to estimate the changes in distress and frailty.
Measured: during a 16-week period for each patient
Change of skewness
Change of skewness extracted from the patient's audio data to estimate the changes in distress and frailty.
Measured: during a 16-week period for each patient
Change of kurtosis
Change of kurtosis extracted from the patient's audio data to estimate the changes in distress and frailty.
Measured: during a 16-week period for each patient
Change of voice strength (volume) of the vowel
Change of voice strength (volume) of the vowel extracted from the patient's audio data to estimate the changes in distress and frailty.
Measured: during a 16-week period for each patient
Change of duration of length of the answer
Change of duration of length of the answer extracted from the patient's audio data to estimate the changes in distress and frailty.
Measured: during a 16-week period for each patient
Change of verbal fluency
Change of verbal fluency extracted from the patient's audio data to estimate the changes in distress and frailty.
Measured: during a 16-week period for each patient
Change of word duration of individual words
Change of word duration of individual words extracted from the patient's audio data to estimate the changes in distress and frailty.
Measured: during a 16-week period for each patient
Change of duration of the breaks between the words
Change of duration of the breaks between the words extracted from the patient's audio data to estimate the changes in distress and frailty.
Measured: during a 16-week period for each patient
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Mar 2023
- Study start19 Nov 2022
- Primary completionNov 2025 (estimated)
- Study completionNov 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for FrailtyStudies of the same condition, open and under way.
- More trials run by University Hospital, Basel, SwitzerlandThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University Hospital, Basel, Switzerland
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Marcus Vetter, PD Dr. med., Principal investigator, Kantonsspital Baselland, Klinik für Onkologie, Hämatologie und Immuntherapie
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05783401
- Sponsor's protocol ID
- 2022-01461; th23Vetter
- Acronym
- DIVAN
- Status last verified
- Jan 2025
- First submitted
- 13 Mar 2023
- Last updated
- 17 Jan 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 17 Jan 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Digital Voice Analysis as a Measure of Frailty and Distress. A Feasibility Study (DIVAN)
- ClinicalTrials.gov ID
- NCT05783401
- Acronym / sponsor ID
- DIVAN / 2022-01461; th23Vetter
- Conditions
- Frailty, Distress, Emotional
- Keywords
- Frailty monitoring, Distress monitoring, Digital voice analysis (DVA), Machine learning, Distress Thermometer, G8 geriatric screening tool
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 100 participants (estimated)
- Lead sponsor
- University Hospital, Basel, SwitzerlandUniversity, hospital or other
- Study start
- 19 Nov 2022 (actual)
- Primary completion
- Nov 2025 (estimated)
- Study completion
- Nov 2025 (estimated)
- First posted
- 24 Mar 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study evaluates if it is possible to identify quantitative parameters from audio signals to describe the changes in patient's state in relation to frailty and distress.
Detailed description
Frailty is a common clinical syndrome especially in older adults that carries an increased risk for poor health outcomes including falls, incident disability, hospitalization, and mortality. The early detection of frailty is of importance in many patient populations to predict treatment outcomes, identify patient needs and coordinate efficient and meaningful care. An electronic assessment of the degree of distress in patients, who are unable to report, would be important to be able to routinely and objectively identify suffering in these patients. Digital voice analysis (DVA) gathers speech samples from individuals via different kinds of recording devices (smartphone, tablet, etc.) and examines a large variety of specific acoustic parameters such as for example frequency and voice quality features. This study is to analyse the potential to evaluate distress and frailty through digital voice analysis. On the contrary to the existing studies, it is intended to record audio and clinical evaluation data from the same subject multiple times during several weeks to be able to analyse temporal changes. This will allow to not only perform inter-subject but as well intra-subject comparisons of changes in audio features with changes of the patient's wellbeing over time. To make the patient speak as freely and relaxed as possible, the patient will describe different images. Different features will be extracted from the audios and potential candidates for a larger patient study will be identified, if data quantity permits using machine learning algorithms. Therefore this study evaluates if it is feasible to gather digital voice samples for voice analyses from cancer patients alongside conventional assessments for frailty (G8 questionnaire and distress (Distress Thermometer) to conduct first, preliminary analyses for identification of potential correlates between voice features and frailty or distress and between changes over time.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Cohort A: palliative care center | – | Other: Data acquisition: Speech acquisition, Diagnostic Test: Data acquisition: G8 Screening tool, Diagnostic Test: Data acquisition: Distress ThermometerPatients from a palliative care center (Palliativzentrum Hildegard, Basel) |
| Cohort B: mid-size cancer center | – | Other: Data acquisition: Speech acquisition, Diagnostic Test: Data acquisition: G8 Screening tool, Diagnostic Test: Data acquisition: Distress ThermometerPatients from a mid-size cancer center (Tumorzentrum Baselland) |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patient recruitment will be performed at the different participating clinical sites by the investigator
Key inclusion criteria (8 listed)
- Active cancer or haemato-oncological malignancy
- Adults (≥ 18 years)
- Ability to understand, speak and read German language fluently
- Ability to provide written consent
- Sufficient or corrected vision to see the images
Key exclusion criteria (5 listed)
- Aphonia, dysphonia or other obvious voice alterations of patient's voice
- Life-expectancy shorter ≤ 14 days as judged by a physician or nurse via "surprise question"
- Breathlessness whilst speaking
- Cognitive impairment as judged by physician or Mini-Cog in the G8 screening tool
- Severe physical, emotional or existential suffering because of which the enrollment and participation in the study would result in patient burden, as judged by the treating physicians and their multiprofessional team members
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Data acquisition: Speech acquisitionSpeech test with synchronized audio and video recording. The speaking exercises and the audio and video recording will be done using a tablet computer and an application developed in-house. Freely available images showing different scenes will be integrated and displayed on the tablet to be described by the patient. The goal is to have at least two and maximum four of them described with several sentences by each patient per session. Parameters will be extracted from the patient's audio data to estimate the changes in distress and frailty. | Other | Cohort A: palliative care center, Cohort B: mid-size cancer center |
| Data acquisition: G8 Screening toolThe G8 screening tool consists of seven items dealing with food intake, weight loss, mobility, neuropsychological problem, body mass index, prescription drug, and self-perception of health, from the Mini-Nutritional Assessment (MNA) questionnaire and was developed specifically for elderly cancer patients. The total G-8 score lies between 0 and 17. A higher score indicates a better health status. | Diagnostic test | Cohort A: palliative care center, Cohort B: mid-size cancer center |
| Data acquisition: Distress ThermometerThe distress thermometer (DT) is a measure of psychological distress in cancer patients. The instrument is a self-reported tool using a 0-to-10 rating scale. | Diagnostic test | Cohort A: palliative care center, Cohort B: mid-size cancer center |
Primary outcome
Change of mean fundamental frequency extracted from the patient's audio data
Time frame: during a 16-week period for each patient
Change of mean fundamental frequency extracted from the patient's audio data to estimate the changes in distress and frailty.
Change of first few formants (F1, F2)
Time frame: during a 16-week period for each patient
Change of first few formants (F1, F2) extracted from the patient's audio data to estimate the changes in distress and frailty.
Change of jitter (variation in F0 from cycle to cycle)
Time frame: during a 16-week period for each patient
Change of jitter (variation in F0 from cycle to cycle) extracted from the patient's audio data to estimate the changes in distress and frailty.
Change of shimmer (variation in peak-to-peak amplitude)
Time frame: during a 16-week period for each patient
Change of shimmer (variation in peak-to-peak amplitude) extracted from the patient's audio data to estimate the changes in distress and frailty.
Change of skewness
Time frame: during a 16-week period for each patient
Change of skewness extracted from the patient's audio data to estimate the changes in distress and frailty.
Change of kurtosis
Time frame: during a 16-week period for each patient
Change of kurtosis extracted from the patient's audio data to estimate the changes in distress and frailty.
Change of voice strength (volume) of the vowel
Time frame: during a 16-week period for each patient
Change of voice strength (volume) of the vowel extracted from the patient's audio data to estimate the changes in distress and frailty.
Change of duration of length of the answer
Time frame: during a 16-week period for each patient
Change of duration of length of the answer extracted from the patient's audio data to estimate the changes in distress and frailty.
Change of verbal fluency
Time frame: during a 16-week period for each patient
Change of verbal fluency extracted from the patient's audio data to estimate the changes in distress and frailty.
Change of word duration of individual words
Time frame: during a 16-week period for each patient
Change of word duration of individual words extracted from the patient's audio data to estimate the changes in distress and frailty.
Change of duration of the breaks between the words
Time frame: during a 16-week period for each patient
Change of duration of the breaks between the words extracted from the patient's audio data to estimate the changes in distress and frailty.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 Jan 2025.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Marcus Vetter, PD Dr. med. principal investigator
Kantonsspital Baselland, Klinik für Onkologie, Hämatologie und Immuntherapie
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Frailty and Distress, Emotional, run by University Hospital, Basel, Switzerland at 2 sites in Switzerland.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 8 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 17 Jan 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Switzerland. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Marcus Vetter, PD Dr. med. (+41 61 925 2525, marcus.vetter@ksbl.ch), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change of mean fundamental frequency extracted from the patient's audio data (time frame: during a 16-week period for each patient). The study lists 11 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 17 Jan 2025.