Examining the concept of equity in community psychology with natural language processing.
J Community Psychol
; 49(6): 1718-1731, 2021 08.
Article
in English
| MEDLINE | ID: covidwho-1231854
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.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Natural Language Processing
/
Community Psychiatry
/
Health Equity
/
Community-Based Participatory Research
/
Knowledge Discovery
/
Social Determinants of Health
Limits:
Humans
Language:
English
Journal:
J Community Psychol
Year:
2021
Document Type:
Article
Affiliation country:
Jcop.22603
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