Evidence map›Paper›PMID 34754633›Full record

ArticleCureus2021

Development and Validation of a Comprehensive Questionnaire to Assess Interpersonal Discord (Bullying, Harassment, and Discrimination) at the Workplace in a Healthcare Setting.

Amandeep Singh, Piyush Ranjan, Tanveer Kaur, Siddharth Sarkar, Ashish D Upadhyay, Upendra Baitha, Prayas Sethi, Ranveer S Jadon, Pankaj Jorwal

Abstract read
In one paragraph

Article in Cureus, 2021. 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

9 authors.

Amandeep SinghMedicine, All India Institute of Medical Sciences, New Delhi, IND.
Piyush RanjanMedicine, All India Institute of Medical Sciences, New Delhi, IND.
Tanveer KaurMedicine, All India Institute of Medical Sciences, New Delhi, IND.
Siddharth SarkarAddiction, All India Institute of Medical Sciences, New Delhi, IND.
Ashish D UpadhyayStatistics, All India Institute of Medical Sciences, New Delhi, IND.
Upendra BaithaMedicine, All India Institute of Medical Sciences, New Delhi, IND.
Prayas SethiInternal Medicine, All India Institute of Medical Sciences, New Delhi, IND.
Ranveer S JadonMedicine, All India Institute of Medical Sciences, New Delhi, IND.
Pankaj JorwalMedicine, All India Institute of Medical Sciences, New Delhi, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective This study was conducted to develop and validate a comprehensive questionnaire to assess bullying, discrimination, and harassment in healthcare settings. Methodology A mixed-method study design was used to develop and validate the questionnaire. In phase I, qualitative approaches were used for the development, which included literature search, focus group discussions (FGDs), following which the construct was developed. In phase II, face validity and construct validity were established using quantitative approaches. Results The final questionnaire consists of 25 items divided into five sections addressing the burden, impact, reasons for underreporting, risk factors, and mitigation strategies. The questionnaire has very good consistency with a Cronbach's alpha score of 0.86. Conclusion This is a comprehensive tool with appropriate psychometric properties with potential use for evaluating the problem of interpersonal discord in the form of bullying, harassment, and discrimination in a healthcare setting.

Indexed as

bullyinghealth personneltoolworkplace discordworkplace violence

Identifiers

PMID34754633
PMCPMC8564218

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.