Measurement of the Reliability and Quality of Online Surgery Videos with Artificial Neural Networks
Introduction:The effect of the internet on education has started to increase more and more with the Coronavirus disease-2019 (COVID-19) pandemic. Although many researchers have used online resources during the pandemic, their quality and reliability and the way these two aspects could be evaluated o...
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| Format: | Article |
| Language: | English |
| Published: |
Galenos Yayinevi
2022-05-01
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| Series: | İstanbul Medical Journal |
| Subjects: | |
| Online Access: |
http://istanbulmedicaljournal.org/archives/archive-detail/article-preview/measurement-of-the-reliability-and-quality-of-onli/52040
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| _version_ | 1828021983528353792 |
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| author | İdris Kurtuluş |
| author_facet | İdris Kurtuluş |
| author_sort | İdris Kurtuluş |
| collection | DOAJ |
| description | Introduction:The effect of the internet on education has started to increase more and more with the Coronavirus disease-2019 (COVID-19) pandemic. Although many researchers have used online resources during the pandemic, their quality and reliability and the way these two aspects could be evaluated online has remained a problem. This study aims to measure the reliability and quality of online videos about inguinal hernias by using the DISCERN questionnaire and to see if the quality and reliability of these online videos are determined accurately and fast with artificial neural networks (ANNs) by teaching them some easily accessed variables about the videos.Methods:A total of 30 online videos searched on Google with the keywords of “TEP,” and “totally ekstraperitoneal inguinal hernia repair” from February 15 to March 1, 2021 with the approval of the University of Health Sciences Turkey, Başakşehir Çam and Sakura City Hospital Ethical Committee were included in this research (approval number: 303, date: 29.12.2021). The videos were found using the “videos” tab of Google. The DISCERN questionnaire was applied to the videos and the results of the questionnaire were tried to be estimated with ANNs by teaching them some easily accessed variables about the videos. The results of the questionnaire and results of the predictions were compared.Results:A total of 30 videos were evaluated. Benefitting from the scores of the DISCERN questionnaire, a total of three groups were formed with K-means clustering analysis. The scores of the low-quality videos were between 0 and 26.50, of the medium quality videos between 26.50 and 34.9, and of the high-quality ones between 34.9 and 48. In determining the video quality in the ANNs estimation model, “the number of likes” (a video received) was found to be the variable with the highest effect (on the model) with an importance coefficient of 0.245. Its normalized importance was found to be 100%. “Country” with an importance coefficient of 0.060 was found to be the variable with the lowest effect (on the model). Its normalized importance was found to be 24.4%. The median value of the scores obtained from the DISCERN questionnaire was 28, while the median value of the DISCERN scores estimated with the ANNs was 27.50. No statistically significant difference was observed between the distribution of the estimated scores and the scores obtained from the DISCERN questionnaire (p=0.314). Additionally, there was no statistically significant difference between the video groups formed according to the scores of the DISCERN questionnaire, and the video groups formed according to the DISCERN scores that were estimated with the ANNs (p=0.771). A total of 20 videos were found to be low quality with the DISCERN questionnaire, while 19 videos were estimated to have low quality with the ANNs. The number of medium-quality videos was six according to the DISCERN questionnaire and five according to the ANNs. There were a total of four high-quality videos in the DISCERN questionnaire and six in the ANNs. It was observed that the quality group of 86.6% of the videos (26 videos) was predicted accurately with the ANNs.Conclusion:The quality and reliability of most TEP videos on the Internet were quite low. The instruments in the literature make searches retrospectively, and using them is quite time consuming. ANNs seem to be quite successful in estimating the reliability and quality of online videos. The reliability and the quality of the videos could be shown to users fast with online electronic labels developed thanks to the ANNs. |
| first_indexed | 2024-04-10T12:01:25Z |
| format | Article |
| id | doaj.art-7e2210f185934e0b943e161bfbf6d09f |
| institution | Directory Open Access Journal |
| issn | 2619-9793 2148-094X |
| language | English |
| last_indexed | 2024-04-10T12:01:25Z |
| publishDate | 2022-05-01 |
| publisher | Galenos Yayinevi |
| record_format | Article |
| series | İstanbul Medical Journal |
| spelling | doaj.art-7e2210f185934e0b943e161bfbf6d09f2023-02-15T16:16:35ZengGalenos Yayineviİstanbul Medical Journal2619-97932148-094X2022-05-01232798410.4274/imj.galenos.2022.5549213049054Measurement of the Reliability and Quality of Online Surgery Videos with Artificial Neural Networksİdris Kurtuluş0 University of Health Sciences Turkey, Başakşehir Çam and Sakura City Hospital, Clinic of General Surgery, İstanbul, Turkey Introduction:The effect of the internet on education has started to increase more and more with the Coronavirus disease-2019 (COVID-19) pandemic. Although many researchers have used online resources during the pandemic, their quality and reliability and the way these two aspects could be evaluated online has remained a problem. This study aims to measure the reliability and quality of online videos about inguinal hernias by using the DISCERN questionnaire and to see if the quality and reliability of these online videos are determined accurately and fast with artificial neural networks (ANNs) by teaching them some easily accessed variables about the videos.Methods:A total of 30 online videos searched on Google with the keywords of “TEP,” and “totally ekstraperitoneal inguinal hernia repair” from February 15 to March 1, 2021 with the approval of the University of Health Sciences Turkey, Başakşehir Çam and Sakura City Hospital Ethical Committee were included in this research (approval number: 303, date: 29.12.2021). The videos were found using the “videos” tab of Google. The DISCERN questionnaire was applied to the videos and the results of the questionnaire were tried to be estimated with ANNs by teaching them some easily accessed variables about the videos. The results of the questionnaire and results of the predictions were compared.Results:A total of 30 videos were evaluated. Benefitting from the scores of the DISCERN questionnaire, a total of three groups were formed with K-means clustering analysis. The scores of the low-quality videos were between 0 and 26.50, of the medium quality videos between 26.50 and 34.9, and of the high-quality ones between 34.9 and 48. In determining the video quality in the ANNs estimation model, “the number of likes” (a video received) was found to be the variable with the highest effect (on the model) with an importance coefficient of 0.245. Its normalized importance was found to be 100%. “Country” with an importance coefficient of 0.060 was found to be the variable with the lowest effect (on the model). Its normalized importance was found to be 24.4%. The median value of the scores obtained from the DISCERN questionnaire was 28, while the median value of the DISCERN scores estimated with the ANNs was 27.50. No statistically significant difference was observed between the distribution of the estimated scores and the scores obtained from the DISCERN questionnaire (p=0.314). Additionally, there was no statistically significant difference between the video groups formed according to the scores of the DISCERN questionnaire, and the video groups formed according to the DISCERN scores that were estimated with the ANNs (p=0.771). A total of 20 videos were found to be low quality with the DISCERN questionnaire, while 19 videos were estimated to have low quality with the ANNs. The number of medium-quality videos was six according to the DISCERN questionnaire and five according to the ANNs. There were a total of four high-quality videos in the DISCERN questionnaire and six in the ANNs. It was observed that the quality group of 86.6% of the videos (26 videos) was predicted accurately with the ANNs.Conclusion:The quality and reliability of most TEP videos on the Internet were quite low. The instruments in the literature make searches retrospectively, and using them is quite time consuming. ANNs seem to be quite successful in estimating the reliability and quality of online videos. The reliability and the quality of the videos could be shown to users fast with online electronic labels developed thanks to the ANNs. http://istanbulmedicaljournal.org/archives/archive-detail/article-preview/measurement-of-the-reliability-and-quality-of-onli/52040 discerntotally ekstraperitoneal hernia repairquality and the reliability of videostepartificial neural networks |
| spellingShingle | İdris Kurtuluş Measurement of the Reliability and Quality of Online Surgery Videos with Artificial Neural Networks İstanbul Medical Journal discern totally ekstraperitoneal hernia repair quality and the reliability of videos tep artificial neural networks |
| title | Measurement of the Reliability and Quality of Online Surgery Videos with Artificial Neural Networks |
| title_full | Measurement of the Reliability and Quality of Online Surgery Videos with Artificial Neural Networks |
| title_fullStr | Measurement of the Reliability and Quality of Online Surgery Videos with Artificial Neural Networks |
| title_full_unstemmed | Measurement of the Reliability and Quality of Online Surgery Videos with Artificial Neural Networks |
| title_short | Measurement of the Reliability and Quality of Online Surgery Videos with Artificial Neural Networks |
| title_sort | measurement of the reliability and quality of online surgery videos with artificial neural networks |
| topic | discern totally ekstraperitoneal hernia repair quality and the reliability of videos tep artificial neural networks |
| url |
http://istanbulmedicaljournal.org/archives/archive-detail/article-preview/measurement-of-the-reliability-and-quality-of-onli/52040
|
| work_keys_str_mv | AT idriskurtulus measurementofthereliabilityandqualityofonlinesurgeryvideoswithartificialneuralnetworks |