Evidence map›Paper›PMID 35099198›Full record

ArticlePsychological assessment2022

Measuring empathy in groups with high schizotypy: Psychometric evaluation of the Interpersonal Reactivity Index.

Kelsey A Bonfils, Julia M Longenecker, Lillian A Hammer, Lauren Luther

Abstract read
In one paragraph

Article in Psychological assessment, 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
–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

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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.

  1. Trial
  2. Review
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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

4 authors.

Kelsey A BonfilsSchool of Psychology.ORCID 0000-0002-8556-5961
Julia M LongeneckerVISN 4 Mental Illness Research Education and Clinical Center (MIRECC).ORCID 0000-0003-2713-4853
Lillian A HammerSchool of Psychology.ORCID 0000-0001-8580-5227
Lauren LutherPsychology Department.

Funding

Stuart T. Hauser Research Training Program in Biological and Social Psychiatry.T32MH016259 · NIMH · JUDGE BAKER CHILDREN'S CENTER · PI Marek Kubicki, Martha E. Shenton · 1985 to 2026
$8.4M
NIMH NIH HHSNIMH NIH HHS T32 MH016259VA Pittsburgh Healthcare System; VISN 4 Mental Illness Research, Education, and Clinical Center (MIRECC)
6 · The paper itself

Abstract

Empathy is integral for interpersonal interactions and formation and maintenance of a strong social network. There is wide agreement that empathy is a multidimensional construct, and it is commonly measured with the Interpersonal Reactivity Index (IRI). The IRI is used widely across healthy and clinical populations, yet insufficient evidence exists on whether the IRI is appropriate for use in groups characterized by high levels of schizotypy. This study sought to examine the factor structure and psychometric characteristics of the IRI when used in a sample of participants with high schizotypy. Nine hundred forty-one undergraduates completed the IRI; 218 met criteria for high schizotypy. Confirmatory factor analysis (CFA) was used to test eight a priori factor structures, and scores from the best fitting model were correlated with relevant measures. Of the eight models tested, a two-factor model including the Perspective-Taking and Empathic Concern subscales evidenced the best fit. The original four-factor structure did not meet criteria for adequate fit in our sample. IRI subscale scores correlated with emotional intelligence. Results suggest that a two-factor structure of the IRI is the strongest path forward for use in high schizotypy samples. This approach, in addition to being psychometrically sound, has the added benefit of being a more brief and targeted assessment that aligns well with contemporary models of empathy. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Indexed as

EmpathySchizotypal Personality DisorderFactor Analysis, StatisticalHumansInterpersonal RelationsPsychometrics

Identifiers

PMID35099198
PMCPMC12997407

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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.