DepressionNCT05123794
Shortened Depression Assessment Study
An observational study of Depression, run by University of Toronto at 1 site in Canada.
Trial summary
Participants will be asked to fill out an online questionnaire about their demographics information and all 42 items from the Depression Anxiety Stress Scale (DASS-42). A series of machine learning techniques will be applied to the dataset to develop a shortened assessment using the most important demographics and… Read more about this study
- Who is it for?
- Ages 18 to 100 yearsHealthy volunteers can take part
- Conditions the study is for
- Depression
- How many people
- 39,000 participants
- Where
- 1 siteCanada
- Study dates
- 1 Sep 2019to 1 Sep 2021
- Phase
- Observational
- Are there results?
- None posted in the registry
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 to 100 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Participants from all countries worldwide are eligible
Who may be able to join
- Adults aged 18 and above
- Must be able to read English
- Must have access to the Internet worldwide
Who cannot join
- Children aged 17 and under
- Persons who cannot read English
- Persons that do not have access to Internet
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Using the Long to Short Approach to Develop Rapid Depressions Scales
Participants will be asked to fill out an online questionnaire about their demographics information and all 42 items from the Depression Anxiety Stress Scale (DASS-42). A series of machine learning techniques will be applied to the dataset to develop a shortened assessment using the most important demographics and DASS-42 items from the original questionnaire, to predict depression levels indicated by DASS-42.
Read the detailed description
Clinical depression affects 5-10% of the world population each year and is a serious mental health issue globally. There are many traditional psychological scales that assess levels of depression in adults, where their items are often redundant in the information they carry, and their scoring is not necessarily linear to the item scores. Thus, machine learning techniques can help find the redundancy in the items, as well as the nonlinear relationship between the item scores and the final prediction. Using the Depression Anxiety Stress Scale 42 (DASS-42) as the basis, participants will be asked to fill out an online questionnaire about their demographics information (age, gender, country of residence, race, etc.) and all 42 items of DASS-42 to provide a dataset for this study. Feature selection techniques such as MRMR and Gini feature importance were applied to identify the most important features in the dataset. Then, using machine learning methods such as Logistic Regression, XGBoost, and Ensemble models, models will be fitted on the most important features to develop a shortened depression scale (7-9 items consisting of demographics items and DASS items) that accurately predicted the levels of depression (as measured by the AUC, ROC and F1 scores.
- Conditions
- Depression
- Keywords
- Depression Moderate, Depression Severe, Survey Methodology
- Medical subject headings
- Depression
What is being measured
The primary outcome is the main question the study is designed to answer.
Rapid Depression Assessment Tool based on Depression Anxiety Stress Scale 42
Participants filled out an online questionnaire about their demographic information (age, sex, and ethnicity) and all 42 items from the Depression Anxiety Stress Scale (DASS-42). Each item consists of a 4-point Likert scale from 0 to 3, where 0 means "Did not apply to me at all" and 3 means "Applied to me very much, or most of the time". The depression score is the sum of scores for the items in the depression sub-scale. A higher score indicates a more severe level of depression symptoms.
Machine learning techniques were used to develop a shortened assessment (Rapid Depression Assessment Tool) using demographics and 5 DASS-42 items from the original questionnaire, to predict severity levels of depression indicated by DASS-42. The assessment tool calculates the likelihood of moderate depression symptoms and severe depression symptoms given the responses from each item (ranging from 0 to 3). The data was collected and aggregated through a public website.
Measured: All participants completed the same assessments, which took 10-15 minutes
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Nov 2021
- Study start1 Sep 2019
- Primary completion1 Sep 2021
- Study completion1 Sep 2021
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for DepressionStudies of the same condition, open and under way.
- 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
- Retrospective
- Enrolment
- 39,000 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Toronto
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Kang Lee, University of Toronto
- Investigators
- Kang Lee, Study chair, University of Toronto
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05123794
- Sponsor's protocol ID
- 0032755
- Status last verified
- Dec 2023
- First submitted
- 5 Nov 2021
- Last updated
- 8 Dec 2023
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 8 Dec 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Using the Long to Short Approach to Develop Rapid Depressions Scales
- ClinicalTrials.gov ID
- NCT05123794
- Acronym / sponsor ID
- 0032755
- Conditions
- Depression
- Keywords
- Depression Moderate, Depression Severe, Survey Methodology
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 39,000 participants (actual)
- Lead sponsor
- University of TorontoUniversity, hospital or other
- Study start
- 1 Sep 2019 (actual)
- Primary completion
- 1 Sep 2021 (actual)
- Study completion
- 1 Sep 2021 (actual)
- First posted
- 17 Nov 2021 (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.
Participants will be asked to fill out an online questionnaire about their demographics information and all 42 items from the Depression Anxiety Stress Scale (DASS-42). A series of machine learning techniques will be applied to the dataset to develop a shortened assessment using the most important demographics and DASS-42 items from the original questionnaire, to predict depression levels indicated by DASS-42.
Detailed description
Clinical depression affects 5-10% of the world population each year and is a serious mental health issue globally. There are many traditional psychological scales that assess levels of depression in adults, where their items are often redundant in the information they carry, and their scoring is not necessarily linear to the item scores. Thus, machine learning techniques can help find the redundancy in the items, as well as the nonlinear relationship between the item scores and the final prediction. Using the Depression Anxiety Stress Scale 42 (DASS-42) as the basis, participants will be asked to fill out an online questionnaire about their demographics information (age, gender, country of residence, race, etc.) and all 42 items of DASS-42 to provide a dataset for this study. Feature selection techniques such as MRMR and Gini feature importance were applied to identify the most important features in the dataset. Then, using machine learning methods such as Logistic Regression, XGBoost, and Ensemble models, models will be fitted on the most important features to develop a shortened depression scale (7-9 items consisting of demographics items and DASS items) that accurately predicted the levels of depression (as measured by the AUC, ROC and F1 scores.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Ages
- 18 to 100 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Participants from all countries worldwide are eligible
Key inclusion criteria (3 listed)
- Adults aged 18 and above
- Must be able to read English
- Must have access to the Internet worldwide
Key exclusion criteria (3 listed)
- Children aged 17 and under
- Persons who cannot read English
- Persons that do not have access to Internet
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Rapid Depression Assessment Tool based on Depression Anxiety Stress Scale 42
Time frame: All participants completed the same assessments, which took 10-15 minutes
Participants filled out an online questionnaire about their demographic information (age, sex, and ethnicity) and all 42 items from the Depression Anxiety Stress Scale (DASS-42). Each item consists of a 4-point Likert scale from 0 to 3, where 0 means "Did not apply to me at all" and 3 means "Applied to me very much, or most of the time". The depression score is the sum of scores for the items in the depression sub-scale. A higher score indicates a more severe level of depression symptoms. Machine learning techniques were used to develop a shortened assessment (Rapid Depression Assessment Tool) using demographics and 5 DASS-42 items from the original questionnaire, to predict severity levels of depression indicated by DASS-42. The assessment tool calculates the likelihood of moderate depression symptoms and severe depression symptoms given the responses from each item (ranging from 0 to 3). The data was collected and aggregated through a public website.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 Dec 2023.
- Individual participant dataSharing planned: No
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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. This study is not recruiting at the moment.
Kang Lee study chair
University of Toronto
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Depression, run by University of Toronto at 1 site in Canada.
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 3 inclusion and 3 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: finished, as of the sponsor's last update on 8 Dec 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Canada. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Rapid Depression Assessment Tool based on Depression Anxiety Stress Scale 42 (time frame: All participants completed the same assessments, which took 10-15 minutes). 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 8 Dec 2023.