Evidence map›Paper›PMID 40762192›Full record

ArticleJournal of medical Internet research2025

The Impact of Individual Factors on Careless Responding Across Different Mental Disorder Screenings: Cross-Sectional Study.

Huawei Kuang, Lichao Zhu, Haonan Yin, Zihe Zhang, Biao Jing, Junwei Kuang

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. 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

6 authors.

Huawei KuangSchool of Energy and Constructional Engineering, Shandong Huayu University of Technology, Dezhou, China.ORCID http://orcid.org/0000-0002-6041-4702
Lichao ZhuTencent (China), Shenzhen, China.ORCID http://orcid.org/0009-0002-4219-4117
Haonan YinPaul Merage School of Business, University of California, Irvine, CA, United States.ORCID http://orcid.org/0009-0006-4275-7476
Zihe ZhangSchool of Energy and Constructional Engineering, Shandong Huayu University of Technology, Dezhou, China.ORCID http://orcid.org/0009-0005-6827-4029
Biao JingSchool of Energy and Constructional Engineering, Shandong Huayu University of Technology, Dezhou, China.ORCID http://orcid.org/0009-0003-8603-0584
Junwei KuangDepartment of Industrial Engineering, School of Business Administration, South China University of Technology, No. 381 Wushan Road, Guangzhou, 510641, China, 86 18810889628.ORCID http://orcid.org/0000-0003-1741-7374

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Online questionnaires are widely used for large-scale screening. However, careless responding (CR) from participants can compromise the reliability of screening outcomes. Prior studies have focused on the effects of individual and environmental factors on CR, but the effect of questionnaire type remains underexplored. Objective: This study investigates the individual factors influencing CR in online mental health screening and assesses how the effect of these factors varies across different psychological questionnaires. Methods: This study analyzed data from 24,367 participants across 4 questionnaires (PHQ-9 [Patient Health Questionnaire-9], PSS [Perceived Stress Scale], ISI [Insomnia Severity Index], and GAD-7 [Generalized Anxiety Disorder-7 Scale]). CR was defined as the proportion of items completed in less than 2 seconds per item. We used a multiple linear regression model to examine the effect of individual factors (sex, age, education, smoking, and drinking) on CR across 4 questionnaires. In addition, response times were visualized to identify patterns between careless and careful responders. Results: Females demonstrate lower levels of CR than males when completing the PHQ-9 (β=-.172, 95% CI -0.104 to -0.089; P<.001), PSS (β=-.234, 95% CI -0.162 to -0.14; P<.001), ISI (β=-.207, 95% CI -0.13 to -0.114; P<.001), and GAD-7 (β=-.177, 95% CI -0.108 to -0.093; P<.001). Older participants demonstrated lower levels of CR on the PHQ-9 (β=-.036, 95% CI -0.007 to -0.003; P<.001), ISI (β=-.036, 95% CI -0.007 to -0.003; P<.001), and GAD-7 (β=-.053, 95% CI -0.009 to -0.005; P<.001), but their age was unrelated to CR on the PSS. Interestingly, compared with participants with an associate-level education, those with a high education (bachelor's, master's, or doctoral degree) demonstrated higher levels of CR, especially those with a master's degree (PHQ-9: β=.098, 95% CI 0.136 to 0.188; P<.001 and GAD-7: β=.091, 95% CI 0.125 to 0.178; P<.001). Smokers exhibited varied patterns, with current smokers demonstrating lower levels of CR on the PHQ-9 (β=-.022, 95% CI -0.064 to -0.016; P=.001) and GAD-7 (β=-.014, 95% CI -0.051 to -0.002; P=.03), whereas occasional smokers demonstrated higher levels of CR on the PSS (β=.019, 95% CI 0.010 to 0.050; P=.003) than nonsmokers. Drinkers demonstrated lower levels of CR than nondrinkers, with the strongest effect among occasional drinkers on the PHQ-9 (β=-.163, 95% CI -0.103 to -0.087; P<.001). Analysis of response times revealed that participants tended to spend less time on PHQ-9 and GAD-7 surveys, and CR on PSS and ISI surveys was characterized by skipping questions. Conclusions: The effect of individual factors on CR varies across questionnaire types. These findings offer valuable insights for questionnaire designers and administrators, highlighting the need for targeted intervention.

Indexed as

Mass ScreeningMental DisordersAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedSurveys and QuestionnairesYoung Adultcareless responsedigital healthmental healthonline health screeningquestionnaire

Identifiers

PMID40762192
PMCPMC12323810

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.