Chrome Extension
WeChat Mini Program
Use on ChatGLM

The Readability, Understandability, and Suitability of Online Resources for Ostomy Care.

JOURNAL OF WOUND OSTOMY AND CONTINENCE NURSING(2024)

Univ Alabama Birmingham

Cited 0|Views0
Abstract
PURPOSE the purpose of this study was to evaluate the content, readability, understandability, and suitability of online resources for patient specific ostomy care. DESIGN Retrospective cohort study SUBJECT AND SETTING Online websites for ostomy care designed for patients. METHODS Ostomy care websites designed for patients were identified by querying three online search engines. Content areas were established following assessment of all websites by two reviewers. Readability of each website was determined using the Flesch Reading Ease Test and the Simple Measure of Gobbledygook (SMOG) index. Understandability was measured using the Patient Education Materials Assessment Tool (PEMAT), and suitability was determined using the Suitability Assessment of Materials (SAM). Chi-Square and rank sum tests were used to compare these measures across website type and by number of content areas. RESULTS Twenty-three websites met inclusion criteria; 26.1% were for-profit, 13% were government, 26.1% were academic, and 34.8% were non-profit. Nineteen content areas were identified including themes related to pouching, bathing, physical activity, managing output, lifestyle, mental health, and eating. The median number of content areas covered was 8.5 [interquartile range (IQR) 4-13]. The most common content areas were changing/emptying a pouching system (82.6% of websites), preventing/managing peristomal skin irritation (78.3%), eating (60.9%), and odor management (60.9%). Less than 27% of websites had content on irrigation, blockage/constipation, and body image. Readability scores using the Flesch Reading Ease (mean 58, IQR 54.7-69.5) and SMOG Index (mean 9.1, IQR 7.6-9.9) correlated to a high-school or “fairly difficult” reading level. The mean PEMAT measuring understandability was 80 (IQR 78.9-84.0). The mean SAM score checking for suitability (literacy demand, graphics, layout and type, learning stimulation and motivation and cultural appropriateness) was 55% (IQR 48.4%-61.3%), indicating “adequate material.” A greater number of content areas on the websites were associated with worse readability (SMOG and Flesch Reading Ease scores) than websites presenting fewer content areas (P = .001 & P < .001, respectively). CONCLUSIONS We found significant variability in the content, readability, understandability, and suitability of online materials for ostomy care. Websites with more content areas were associated with worse readability.
More
Translated text
Key words
Ostomy care,Ostomy education,Readability,Suitability,Understandability
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest