The Internalized Ableism Inventory: Scale development using a hybrid artificial intelligence and community-based participatory research design.

IF 1.7 4区医学 Q3 PSYCHOLOGY, CLINICAL

Rehabilitation Psychology Pub Date : 2025-09-22 DOI:10.1037/rep0000639

Paul B Perrin, Bryan R Christ, Tiffanie A Vargas, Mia E Dini, Benjamin Ertman, Steph L Cull, Diego Rivera, Bridget Xia, Erin E Andrews-Ash, Linda Mona, Alexander J Gates, Daniel W Klyce

{"title":"The Internalized Ableism Inventory: Scale development using a hybrid artificial intelligence and community-based participatory research design.","authors":"Paul B Perrin, Bryan R Christ, Tiffanie A Vargas, Mia E Dini, Benjamin Ertman, Steph L Cull, Diego Rivera, Bridget Xia, Erin E Andrews-Ash, Linda Mona, Alexander J Gates, Daniel W Klyce","doi":"10.1037/rep0000639","DOIUrl":null,"url":null,"abstract":"Objective: This study (a) used OpenAI's GPT-4 large language model to generate an initial item pool for a potential scale measuring internalized ableism, (b) involved disabled community stakeholders in refining the items and prompting additional artificial intelligence-generated items, and (c) psychometrically validated the scale in a large sample of disabled individuals.Method: Following a series of GPT-4 prompts and iterative community-based participatory research feedback, a tentative item pool of 90 statements was developed. A sample of 409 adults with diverse disabilities completed a survey containing the initial item pool, potentially related scales, and demographic questions.Results: An exploratory factor analysis helped identify the final 51 items and subscale structure, and a confirmatory factor analysis then provided evidence of excellent factor structure fit. The scale contained eight subscales with Cronbach's αs that ranged from .85 to .97, with an overall total score α of .98. The total score and subscales showed consistent convergent validity with other measures of internalized stigma for chronic illness and anger and frustration with disability.Conclusion: This study generated for the first time in the known research literature a nuanced, comprehensive, and psychometrically sound scale based on the integration of both artificial intelligence and community-based participatory research methodology: the Internalized Ableism Inventory. The demonstrated methodology generating it has the potential to modernize psychological scale development approaches. (PsycInfo Database Record (c) 2025 APA, all rights reserved).","PeriodicalId":47974,"journal":{"name":"Rehabilitation Psychology","volume":" ","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12462894/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Rehabilitation Psychology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1037/rep0000639","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PSYCHOLOGY, CLINICAL","Score":null,"Total":0}

引用次数: 0

Abstract

Objective: This study (a) used OpenAI's GPT-4 large language model to generate an initial item pool for a potential scale measuring internalized ableism, (b) involved disabled community stakeholders in refining the items and prompting additional artificial intelligence-generated items, and (c) psychometrically validated the scale in a large sample of disabled individuals.

Method: Following a series of GPT-4 prompts and iterative community-based participatory research feedback, a tentative item pool of 90 statements was developed. A sample of 409 adults with diverse disabilities completed a survey containing the initial item pool, potentially related scales, and demographic questions.

Results: An exploratory factor analysis helped identify the final 51 items and subscale structure, and a confirmatory factor analysis then provided evidence of excellent factor structure fit. The scale contained eight subscales with Cronbach's αs that ranged from .85 to .97, with an overall total score α of .98. The total score and subscales showed consistent convergent validity with other measures of internalized stigma for chronic illness and anger and frustration with disability.

Conclusion: This study generated for the first time in the known research literature a nuanced, comprehensive, and psychometrically sound scale based on the integration of both artificial intelligence and community-based participatory research methodology: the Internalized Ableism Inventory. The demonstrated methodology generating it has the potential to modernize psychological scale development approaches. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

查看原文本刊更多论文

内化残疾量表：使用混合人工智能和基于社区的参与式研究设计的规模开发。

目的：本研究(a)使用OpenAI的GPT-4大型语言模型为测量内化残疾主义的潜在量表生成初始项目池，(b)让残疾人社区利益相关者参与改进项目并提示其他人工智能生成的项目，以及(c)在大量残疾人样本中对量表进行心理测量学验证。方法：通过一系列GPT-4提示和基于社区的参与性研究反馈，开发了一个包含90个语句的暂定题库。409名不同残疾的成年人完成了一项调查，其中包括初始项目库、潜在的相关量表和人口统计问题。结果：探索性因子分析有助于确定最终的51个项目和子量表结构，验证性因子分析提供了良好的因素结构拟合的证据。量表包含8个分量表，Cronbach αs值为。85到。97分，总分α为0.98分。总分和子量表与其他慢性疾病内化污名和残疾愤怒和沮丧的测量方法显示一致的收敛效度。结论：在已知的研究文献中，本研究首次基于人工智能和社区参与式研究方法的整合，生成了一个细致、全面、心理测量学上健全的量表：内化残疾量表。所演示的产生它的方法有可能使心理量表发展方法现代化。（PsycInfo Database Record (c) 2025 APA，版权所有）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Rehabilitation Psychology Multiple-

CiteScore

4.80

自引率

7.40%

发文量

期刊介绍： Rehabilitation Psychology is a quarterly peer-reviewed journal that publishes articles in furtherance of the mission of Division 22 (Rehabilitation Psychology) of the American Psychological Association and to advance the science and practice of rehabilitation psychology. Rehabilitation psychologists consider the entire network of biological, psychological, social, environmental, and political factors that affect the functioning of persons with disabilities or chronic illness. Given the breadth of rehabilitation psychology, the journal"s scope is broadly defined.