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The Prejudice towards People with Mental Illness (PPMI) scale: structure and validity

Overview of attention for article published in BMC Psychiatry, September 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)

Mentioned by

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1 news outlet
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1 tweeter
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1 Facebook page
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1 Redditor

Citations

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8 Dimensions

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53 Mendeley
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Title
The Prejudice towards People with Mental Illness (PPMI) scale: structure and validity
Published in
BMC Psychiatry, September 2018
DOI 10.1186/s12888-018-1871-z
Pubmed ID
Authors

Amanda Kenny, Boris Bizumic, Kathleen M. Griffiths

Abstract

Although there is a substantial body of research on the stigma associated with mental illness, much of the extant research has not explicitly focused on the concept of prejudice, which drives discriminatory behaviour. Further, research that has investigated prejudice towards people with mental illness has conceptual, theoretical and psychometric limitations. To address these shortcomings, we sought to develop a new measure, the Prejudice towards People with Mental Illness (PPMI) scale, based on an improved conceptualisation and integration of the stigma and prejudice areas of research. In developing the new scale, we undertook a thematic analysis of existing conceptualisations and measures to identify a pool of potential items for the scale which were subsequently assessed for fidelity and content validity by expert raters. We tested the structure, reliability, and validity of the scale across three studies (Study 1 N = 301; Study 2 N = 164; Study 3 N = 495) using exploratory factor, confirmatory factor, correlational, multiple regression, and ordinal logistic regression analyses using both select and general community samples. Study 1 identified four factors underlying prejudice towards people with mental illness: fear/avoidance, malevolence, authoritarianism, and unpredictability. It also confirmed the nomological network, that is, the links of these attitudes with the proposed theoretical antecedents and consequences. Studies 2 and 3 further supported the factor structure of the measure, and provided additional evidence for the nomological network. We argue that research into prejudice towards people with mental illness will benefit from the new measure and theoretical framework.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 13 25%
Student > Doctoral Student 6 11%
Student > Ph. D. Student 5 9%
Researcher 4 8%
Student > Master 4 8%
Other 10 19%
Unknown 11 21%
Readers by discipline Count As %
Psychology 23 43%
Medicine and Dentistry 4 8%
Social Sciences 4 8%
Engineering 2 4%
Nursing and Health Professions 1 2%
Other 6 11%
Unknown 13 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 August 2020.
All research outputs
#1,853,098
of 16,948,032 outputs
Outputs from BMC Psychiatry
#704
of 3,701 outputs
Outputs of similar age
#47,317
of 283,419 outputs
Outputs of similar age from BMC Psychiatry
#1
of 1 outputs
Altmetric has tracked 16,948,032 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,701 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has done well, scoring higher than 80% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 283,419 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them