Evidence map›Paper›PMID 37333922›Full record

ArticleFrontiers in psychiatry2023

Rasch analyses of the Quick Inventory of Depressive Symptomatology Self-Report in neurodegenerative and major depressive disorders.

Anthony L Vaccarino, Sandra E Black, Susan Gilbert Evans, Benicio N Frey, Mojib Javadi, Sidney H Kennedy, Benjamin Lam, Raymond W Lam, Bianca Lasalandra, Emily Martens and 9 more

2 registry-linked trialsOpen access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT01655706 phase3completednot on this map

Integrated Biological Markers for the Prediction of Treatment Response in Depression

TypeinterventionalSponsorUniversity Health Network, TorontoRan2012 to 2017Enrolled211ConditionsMajor Depressive DisorderArmsescitalopram, aripiprazole
NCT04104373 completednot on this map

The Ontario Neurodegenerative Disease Research Initiative

TypeobservationalSponsorOntario Neurodegeneration Disease Research InitiativeRan2014 to 2018Enrolled522ConditionsAlzheimer Disease, Amyotrophic Lateral Sclerosis, Frontotemporal Dementia, Parkinson DiseaseArmsObservational Cohort
3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Development and initial validation of DESCAQ: A Rasch-based computer-adaptive questionnaire for assessing digital eye strain.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2025
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors at 9 institutions in 1 country.

Anthony L VaccarinoIndoc Research, Toronto, ON, Canada.
Sandra E BlackDr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada.
Susan Gilbert EvansIndoc Research, Toronto, ON, Canada.
Benicio N FreyDepartment of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.
Mojib JavadiIndoc Research, Toronto, ON, Canada.
Sidney H KennedyDepartment of Psychiatry, University of Toronto, Toronto, ON, Canada.
Benjamin LamDepartment of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.
Raymond W LamDepartment of Psychiatry, University of British Columbia, Vancouver, BC, Canada.
Bianca LasalandraIndoc Research, Toronto, ON, Canada.
Emily MartensIndoc Research, Toronto, ON, Canada.
Mario MasellisDepartment of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.
Roumen MilevDepartments of Psychiatry and Psychology, Queen's University, Providence Care, Kingston, ON, Canada.
Sara MitchellDepartment of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.
Douglas P MunozCentre for Neuroscience Studies, Queen's University, Kingston, ON, Canada.
Alana SparksIndoc Research, Toronto, ON, Canada.
Richard H SwartzDr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada.
Brian TanRotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.
Rudolf UherDepartment of Psychiatry, Dalhousie University, Halifax, NS, Canada.
Kenneth R EvansIndoc Research, Toronto, ON, Canada.
Indoc Research · CAUniversity of Toronto · CAHealth Sciences Centre · CAQueen's University · CABaycrest Hospital · CADalhousie University · CASt. Joseph’s Healthcare Hamilton · CASunnybrook Research InstituteUniversity of British Columbia · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Symptoms of depression are present in neurodegenerative disorders (ND). It is important that depression-related symptoms be adequately screened and monitored in persons living with ND. The Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) is a widely-used self-report measure to assess and monitor depressive severity across different patient populations. However, the measurement properties of the QIDS-SR have not been assessed in ND. Aim: To use Rasch Measurement Theory to assess the measurement properties of the Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) in ND and in comparison to major depressive disorder (MDD). Methods: De-identified data from the Ontario Neurodegenerative Disease Research Initiative (NCT04104373) and Canadian Biomarker Integration Network in Depression (NCT01655706) were used in the analyses. Five hundred and twenty participants with ND (Alzheimer's disease or mild cognitive impairment, amyotrophic lateral sclerosis, cerebrovascular disease, frontotemporal dementia and Parkinson's disease) and 117 participants with major depressive disorder (MDD) were administered the QIDS-SR. Rasch Measurement Theory was used to assess measurement properties of the QIDS-SR, including unidimensionality and item-level fit, category ordering, item targeting, person separation index and reliability and differential item functioning. Results: The QIDS-SR fit well to the Rasch model in ND and MDD, including unidimensionality, satisfactory category ordering and goodness-of-fit. Item-person measures (Wright maps) showed gaps in item difficulties, suggesting poor precision for persons falling between those severity levels. Differences between mean person and item measures in the ND cohort logits suggest that QIDS-SR items target more severe depression than experienced by the ND cohort. Some items showed differential item functioning between cohorts. Conclusion: The present study supports the use of the QIDS-SR in MDD and suggest that the QIDS-SR can be also used to screen for depressive symptoms in persons with ND. However, gaps in item targeting were noted that suggests that the QIDS-SR cannot differentiate participants falling within certain severity levels. Future studies would benefit from examination in a more severely depressed ND cohort, including those with diagnosed clinical depression.

Indexed as

depressive symptomsmajor depressive disorderneurodegenerative disorderQIDS-SRRasch measurement theoryvalidity

Identifiers

PMID37333922
PMCPMC10273843
OpenAlexW4379229111

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.