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Ahmadzadeh K, Bahrami M, Zare-Farashbandi F, Adibi P, Boroumand MA, Rahimi A. Patient education information material assessment criteria: A scoping review. Health Info Libr J 2023; 40:3-28. [PMID: 36637218 DOI: 10.1111/hir.12467] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Revised: 10/13/2022] [Accepted: 11/03/2022] [Indexed: 01/14/2023]
Abstract
BACKGROUND Patient education information material (PEIM) is an essential component of patient education programs in increasing patients' ability to cope with their diseases. Therefore, it is essential to consider the criteria that will be used to prepare and evaluate these resources. OBJECTIVE This paper aims to identify these criteria and recognize the tools or methods used to evaluate them. METHODS National and international databases and indexing banks, including PubMed, Scopus, Web of Science, ProQuest, the Cochrane Library, Magiran, SID and ISC, were searched for this review. Original or review articles, theses, short surveys, and conference papers published between January 1990 and June 2022 were included. RESULTS Overall, 4688 documents were retrieved, of which 298 documents met the inclusion criteria. The criteria were grouped into 24 overarching criteria. The most frequently used criteria were readability, quality, suitability, comprehensibility and understandability. CONCLUSION This review has provided empirical evidence to identify criteria, tools, techniques or methods for developing or evaluating a PEIM. The authors suggest that developing a comprehensive tool based on these findings is critical for evaluating the overall efficiency of PEIM using effective criteria.
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Affiliation(s)
- Khadijeh Ahmadzadeh
- Health Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.,Student Research Commitee, Sirjan School of Medical Sciences, Sirjan, Iran
| | - Masoud Bahrami
- Department of Adult Health Nursing, Nursing and Midwifery Care Research Center, School of Nursing and Midwifery, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Firoozeh Zare-Farashbandi
- Health Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Payman Adibi
- Gastroenterology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mohammad Ali Boroumand
- Department of Medical Library and Information Sciences, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Alireza Rahimi
- Health Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
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Gordejeva J, Zowalla R, Pobiruchin M, Wiesner M. Readability of English, German, and Russian Disease-related Wikipedia pages: Automated Computational Analysis (Preprint). J Med Internet Res 2022; 24:e36835. [PMID: 35576562 PMCID: PMC9152717 DOI: 10.2196/36835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 04/12/2022] [Accepted: 04/14/2022] [Indexed: 11/13/2022] Open
Affiliation(s)
| | - Richard Zowalla
- Department of Medical Informatics, Heilbronn University, Heilbronn, Germany
- Consumer Health Informatics SIG, German Association for Medical Informatics, Biometry & Epidemiology (GMDS e. V.), Cologne, Germany
- Center for Machine Learning, Heilbronn University, Heilbronn, Germany
| | - Monika Pobiruchin
- Consumer Health Informatics SIG, German Association for Medical Informatics, Biometry & Epidemiology (GMDS e. V.), Cologne, Germany
- GECKO Institute for Medicine, Informatics & Economics, Heilbronn University, Heilbronn, Germany
| | - Martin Wiesner
- Department of Medical Informatics, Heilbronn University, Heilbronn, Germany
- Consumer Health Informatics SIG, German Association for Medical Informatics, Biometry & Epidemiology (GMDS e. V.), Cologne, Germany
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Arslan D, Tutar MS, Kozanhan B. Evaluating the readability, understandability, and quality of online materials about chest pain in children. Eur J Pediatr 2020; 179:1881-1891. [PMID: 32894353 DOI: 10.1007/s00431-020-03772-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 08/01/2020] [Accepted: 08/04/2020] [Indexed: 10/23/2022]
Abstract
An increasing number of individuals use the Internet to obtain health information. However, online health information is unregulated and highly variable. We aimed to assess the readability, understandability, and quality of online information available for "chest pain in children." This analysis was performed in January 2020, by inputting the search term "chest pain in children" into Google. The 180 search results were evaluated/categorized. The readability was assessed using the Flesch reading ease score, the Gunning FOG readability score, the Flesch-Kincaid grade level, the Coleman-Liau score, the Simple Measure of Gobbledygook readability score, the Fry readability score, and the automated readability index (ARI). The quality was assessed through the Journal of the American Medical Association (JAMA) benchmark criteria. The understandability was evaluated by the Patient Education Materials Assessment Tool (PEMAT) for this study. Sixty-five websites were analyzed (academic and hospital websites (n = 30), physicians and health information websites (n = 35)). Among all websites, the average reading grade level was 9.99. There was no statistical difference between the two groups for the average readability level (p: 0.645). The mean PEMAT score for all websites was 65.09%. There was no statistical difference between the two groups for the average PEMAT score (p: 0.945). For both groups, the understandability score was below 70%. The average JAMA benchmark score was 2.43 ± 1.06, with a statistically significant difference between the academic and hospital websites (2.07 ± 0.91) and physician and health information websites (2.74 ± 1.09, p: 0.009).Conclusion: The readability of online materials available for patients regarding "chest pain in children" was significantly higher than the grade 6 recommended by the National Institutes of Health. The current online health information related to pediatric chest pain may be too difficult for the average reader to read. The quality and understandability were not good for both groups. Improving the readability, understandability, and quality of pediatric health-related online materials has the potential to reduce parental anxiety, improve baseline medical knowledge, and even enhance the physician-parent alliance.
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Affiliation(s)
- Derya Arslan
- Department of Pediatric Cardiology, University of Health Sciences Turkey, Konya Education and Research Hospital, 42075, Konya, Turkey.
| | - Mahmut Sami Tutar
- Department of Anesthesiology and Reanimation Clinic, Konya Numune Hospital, Konya, Turkey
| | - Betul Kozanhan
- Department of Anesthesiology and Reanimation Clinic, University of Health Science Turkey, Konya Education and Research Hospital, Konya, Turkey
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Luo A, Xin Z, Yuan Y, Wen T, Xie W, Zhong Z, Peng X, Ouyang W, Hu C, Liu F, Chen Y, He H. Multidimensional Feature Classification of the Health Information Needs of Patients With Hypertension in an Online Health Community Through Analysis of 1000 Patient Question Records: Observational Study. J Med Internet Res 2020; 22:e17349. [PMID: 32469318 PMCID: PMC7293056 DOI: 10.2196/17349] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 02/16/2020] [Accepted: 03/29/2020] [Indexed: 01/17/2023] Open
Abstract
Background With the rapid development of online health communities, increasing numbers of patients and families are seeking health information on the internet. Objective This study aimed to discuss how to fully reveal the health information needs expressed by patients with hypertension in their questions in a web-based environment and how to use the internet to help patients with hypertension receive personalized health education. Methods This study randomly selected 1000 text records from the question data of patients with hypertension from 2008 to 2018 collected from Good Doctor Online and constructed a classification system through literature research and content analysis. This paper identified the background characteristics and questioning intention of each patient with hypertension based on the patient’s question and used co-occurrence network analysis and the k-means clustering method to explore the features of the health information needs of patients with hypertension. Results The classification system for the health information needs of patients with hypertension included the following nine dimensions: drugs (355 names), symptoms and signs (395 names), tests and examinations (545 names), demographic data (526 kinds), diseases (80 names), risk factors (37 names), emotions (43 kinds), lifestyles (6 kinds), and questions (49 kinds). There were several characteristics of the explored web-based health information needs of patients with hypertension. First, more than 49% of patients described features, such as drugs, symptoms and signs, tests and examinations, demographic data, and diseases. Second, patients with hypertension were most concerned about treatment (778/1000, 77.80%), followed by diagnosis (323/1000, 32.30%). Third, 65.80% (658/1000) of patients asked physicians several questions at the same time. Moreover, 28.30% (283/1000) of patients were very concerned about how to adjust the medication, and they asked other treatment-related questions at the same time, including drug side effects, whether to take the drugs, how to treat the disease, etc. Furthermore, 17.60% (176/1000) of patients consulted physicians about the causes of clinical findings, including the relationship between the clinical findings and a disease, the treatment of a disease, and medications and examinations. Fourth, by k-means clustering, the questioning intentions of patients with hypertension were classified into the following seven categories: “how to adjust medication,” “what to do,” “how to treat,” “phenomenon explanation,” “test and examination,” “disease diagnosis,” and “disease prognosis.” Conclusions In a web-based environment, the health information needs expressed by Chinese patients with hypertension to physicians are common and distinct, that is, patients with different background features ask relatively common questions to physicians. The classification system constructed in this study can provide guidance to health information service providers for the construction of web-based health resources, as well as guidance for patient education, which could help solve the problem of information asymmetry in communication between physicians and patients.
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Affiliation(s)
- Aijing Luo
- The Third Xiangya Hospital of Central South University, Changsha, China.,Key Laboratory of Medical Information Research, Central South University, College of Hunan Province, Changsha, China
| | - Zirui Xin
- The Third Xiangya Hospital of Central South University, Changsha, China.,Key Laboratory of Medical Information Research, Central South University, College of Hunan Province, Changsha, China.,School of Life Sciences, Central South University, Changsha, China
| | - Yifeng Yuan
- The Third Xiangya Hospital of Central South University, Changsha, China.,Key Laboratory of Medical Information Research, Central South University, College of Hunan Province, Changsha, China.,School of Life Sciences, Central South University, Changsha, China
| | - Tingxiao Wen
- School of Life Sciences, Central South University, Changsha, China
| | - Wenzhao Xie
- The Third Xiangya Hospital of Central South University, Changsha, China.,Key Laboratory of Medical Information Research, Central South University, College of Hunan Province, Changsha, China
| | - Zhuqing Zhong
- The Third Xiangya Hospital of Central South University, Changsha, China.,Key Laboratory of Medical Information Research, Central South University, College of Hunan Province, Changsha, China
| | - Xiaoqing Peng
- The Third Xiangya Hospital of Central South University, Changsha, China.,Key Laboratory of Medical Information Research, Central South University, College of Hunan Province, Changsha, China
| | - Wei Ouyang
- The Third Xiangya Hospital of Central South University, Changsha, China.,Key Laboratory of Medical Information Research, Central South University, College of Hunan Province, Changsha, China.,School of Life Sciences, Central South University, Changsha, China
| | - Chao Hu
- Key Laboratory of Medical Information Research, Central South University, College of Hunan Province, Changsha, China.,School of Computer Science and Engineering, Central South University, Changsha, China.,Information and Network Center, Central South University, Changsha, China
| | - Fei Liu
- The Third Xiangya Hospital of Central South University, Changsha, China.,Key Laboratory of Medical Information Research, Central South University, College of Hunan Province, Changsha, China.,School of Life Sciences, Central South University, Changsha, China
| | - Yang Chen
- The Third Xiangya Hospital of Central South University, Changsha, China.,Key Laboratory of Medical Information Research, Central South University, College of Hunan Province, Changsha, China.,School of Life Sciences, Central South University, Changsha, China
| | - Haiyan He
- The Third Xiangya Hospital of Central South University, Changsha, China.,Key Laboratory of Medical Information Research, Central South University, College of Hunan Province, Changsha, China.,School of Life Sciences, Central South University, Changsha, China
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