Evidence map›Paper›PMID 36790406›Full record

ArticleLa Medicina del lavoro2023

Psychometric Evaluation of GHQ-12 as a Screening Tool for Psychological Impairment of Healthcare Workers Facing COVID-19 Pandemic.

Anna Comotti, Alice Fattori, Francesca Greselin, Lorenzo Bordini, Paolo Brambilla, Matteo Bonzini

Open access · diamondAbstract read
In one paragraph

Article in La Medicina del lavoro, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
6.6field-weighted citation impact, top 3% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. 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 at 3 institutions in 1 country.

Anna ComottiOccupational Health Unit, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy. anna.comotti@policlinico.mi.it.
Alice FattoriDepartment of Clinical Science and Community Health, University of Milan, Milan, Italy. alice.fattori@unimi.it.
Francesca GreselinDepartment of Statistics and Quantitative Methods, University of Milan Bicocca, Milan, Italy. francesca.greselin@unimib.it.
Lorenzo BordiniOccupational Health Unit, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy. lorenzo.bordini@policlinico.mi.it.
Paolo BrambillaDepartment of Pathophysiology and Transplantation, University of Milan, Milan, Italy and Department of Neurosciences and Mental Health, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy. paolobrambilla.ter@gmail.com.
Matteo BonziniOccupational Health Unit, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy and Department of Clinical Science and Community Health, University of Milan, Milan, Italy. matteo.bonzini@unimi.it.
Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico · ITUniversity of Milan · ITUniversity of Milano-Bicocca · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe General Health Questionnaire (GHQ) is a widely used tool, both in clinical and research settings, due to its brevity and easy administration. Researchers often adopt a dichotomous measurement method, considering a total score above or below a certain threshold. This leads to an extreme simplification of the gathered data and therefore to the loss of clinical details. In a multi-step evaluation study aimed at assessing health care workers' mental health during the Covid-19 pandemic, GHQ-12 proved to be the most effective tool to detect psychological distress compared to other scales adopted. These results led to deepen the understanding of GHQ-12 properties through a statistical study by focusing on items' properties and characteristics.

methodsGHQ-12 responses were analyzed using Item Response Theory (IRT), a suitable method for scale assessment. Instead of considering the single overall score, in which each item accounts equally, it focuses on individual items' characteristics. Moreover, IRT models were applied combined with the latent class (LC) analysis, aiming to the determination of subgroups of individuals according to their level of psychological distress.

resultsGHQ-12 was administered to 990 health-care workers and responses were scored using the binary method (0-0-1-1). We applied the two-parameter logistic (2-PL) model, finding that the items showed different ways of responses and features. The latent class analysis classified subjects into three sub-groups according to their responses to GHQ-12 only: 47% of individuals with general well-being, 38% expressing signs of discomfort without severity and 15% of subjects with a high level of impairment. This result almost reproduces subjects' classification obtained after administering the six questionnaires of the study protocol.

conclusionsAccurate statistical techniques and a deep understanding of the latent factors underlying the GHQ-12 resulted in a more effective usage of such psychometric questionnaire - i.e. a more refined gathering of data and a significant time and resource efficiency. We underlined the need to maximize the extraction of data from questionnaires and the necessity of them being less lengthy and repetitive.

Indexed as

COVID-19PandemicsHumansMental HealthPsychometricsSurveys and Questionnaires

Identifiers

PMID36790406
PMCPMC9987474
OpenAlexW4320857013

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.