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Article ; Online: Examining the concept of equity in community psychology with natural language processing.

Scaccia, Jonathan P

Journal of community psychology

2021  Volume 49, Issue 6, Page(s) 1718–1731

Abstract: ... applied NLP to explore the concept of equity in community psychology. The COVID-19 crisis has made pre ... existing health equity gaps even more salient. Community psychology has a specific interest in working ... laborious. Natural language processing (NLP) uses computer-based algorithms not traditionally implemented ...

Abstract Large amounts of text-based data, like study abstracts, often go unanalyzed because the task is laborious. Natural language processing (NLP) uses computer-based algorithms not traditionally implemented in community psychology to effectively and efficiently process text. These methods include examining the frequency of words and phrases, the clustering of topics, and the interrelationships of words. This article applied NLP to explore the concept of equity in community psychology. The COVID-19 crisis has made pre-existing health equity gaps even more salient. Community psychology has a specific interest in working with organizations, systems, and communities to address social determinants that perpetuate inequities by refocusing interventions around achieving health and wellness for all. This article examines how community psychology has discussed equity thus far to identify strengths and gaps for future research and practice. The results showed the prominence of community-based participatory research and the diversity of settings researchers work in. However, the total number of abstracts with equity concepts was lower than expected, which suggests there is a need for a continued focus on equity.
MeSH term(s) Community Psychiatry/methods ; Community-Based Participatory Research/methods ; Health Equity/statistics & numerical data ; Humans ; Knowledge Discovery/methods ; Natural Language Processing ; Periodicals as Topic ; Social Determinants of Health/statistics & numerical data
Language English
Publishing date 2021-05-18
Publishing country United States
Document type Journal Article
ZDB-ID 1491194-2
ISSN 1520-6629 ; 0090-4392
ISSN (online) 1520-6629
ISSN 0090-4392
DOI 10.1002/jcop.22603
Database MEDical Literature Analysis and Retrieval System OnLINE

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