Evidence map›Paper›PMID 35581321›Full record

ArticleScientific reports2022

Development of computer adaptive testing for measuring depression in patients with cancer.

Ken Kurisu, Masayuki Hashimoto, Tetsuro Ishizawa, Osamu Shibayama, Shuji Inada, Daisuke Fujisawa, Hironobu Inoguchi, Haruki Shimoda, Shinichiro Inoue, Asao Ogawa and 5 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 47% 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

15 authors at 7 institutions in 1 country.

Ken KurisuDepartment of Stress Sciences and Psychosomatic Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
Masayuki HashimotoDepartment of Psychosomatic Medicine, Sunagawa City Medical Center, Sunagawa, Hokkaido, Japan.
Tetsuro IshizawaDepartment of Stress Sciences and Psychosomatic Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
Osamu ShibayamaDepartment of Stress Sciences and Psychosomatic Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
Shuji InadaDepartment of Stress Sciences and Psychosomatic Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
Daisuke FujisawaDepartment of Neuropsychiatry and Palliative Care Center, Keio University School of Medicine, Tokyo, Japan.
Hironobu InoguchiDepartment of Psycho-Oncology, National Cancer Center, Tokyo, Japan.
Haruki ShimodaDepartment of Hygiene and Preventive Medicine, School of Medicine, Iwate Medical University, Iwate, Japan.
Shinichiro InoueDepartment of Neuropsychiatry, Okayama University, Okayama, Japan.
Asao OgawaDepartment of Psycho-Oncology, National Cancer Center Hospital East, Kashiwa, Chiba, Japan.
Tatsuo AkechiCenter for Psycho-Oncology and Palliative Care, Nagoya City University Hospital, Nagoya, Aichi, Japan.
Ken ShimizuDepartment of Psycho-Oncology, Cancer Institute Hospital, Tokyo, Japan.
Yosuke UchitomiInnovation Center for Supportive, Palliative and Psychosocial Care, National Cancer Center, Tokyo, Japan.
Yutaka MatsuyamaDepartment of Biostatistics, School of Public Health, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Kazuhiro YoshiuchiDepartment of Stress Sciences and Psychosomatic Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan. kyoshiuc-tky@umin.ac.jp.
The University of Tokyo · JPKeio University · JPNagoya City University Hospital · JPNational Cancer Center Hospital East · JPOkayama University · JPSunagawa City Medical Center · JPThe Cancer Institute Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The usefulness of depression scales for patients with cancer based on item response theory (IRT) and computer adaptive testing (CAT) has not yet been fully explored. This study thus aimed to develop an IRT-based tool for measuring depression in patients with cancer. We analyzed data from 393 patients with cancer from four tertiary centers in Japan who had not received psychiatric treatment. They answered 62 questions across five categories regarding their psychiatric status over the previous week. We selected 28 items that satisfied the assumptions of IRT, fitted a graded response model to these items, and performed CAT simulations. The CAT simulation used an average of 6.96 items and showed a Pearson's correlation coefficient of 0.916 (95% confidence interval, 0.899-0.931) between the degree of depression estimated by simulation and that estimated using all 28 items. The measurement precision of CAT with only four items was superior to that of the estimation using the calibrated Patient Health Questionnaire-9. These results imply that this scale is useful and accurate for measuring depression in patients with cancer.

Indexed as

DepressionNeoplasmsComputersHumansPatient Health QuestionnairePersonal SatisfactionPsychometricsReproducibility of ResultsSurveys and Questionnaires

Identifiers

PMID35581321
PMCPMC9114408
OpenAlexW4280646002

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.