{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T13:38:18Z","timestamp":1780925898149,"version":"3.54.1"},"reference-count":67,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,1,8]],"date-time":"2023-01-08T00:00:00Z","timestamp":1673136000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>The prevalence of neck pain, a chronic musculoskeletal disease, has significantly increased due to the uncontrollable use of social media (SM) devices. The use of SM devices by younger generations increased enormously during the COVID-19 pandemic, being\u2014in some cases\u2014the only possibility for maintaining interpersonal, social, and friendship relationships. This study aimed to predict the occurrence of neck pain and its correlation with the intensive use of SM devices. It is based on nine quantitative parameters extracted from the retrospective X-ray images. The three parameters related to angle_1 (i.e., the angle between the global horizontal and the vector pointing from C7 vertebra to the occipito-cervical joint), angle_2 (i.e., the angle between the global horizontal and the vector pointing from C1 vertebra to the occipito-cervical joint), and the area between them were measured from the shape of the neck vertebrae, while the rest of the parameters were extracted from the images using the gray-level co-occurrence matrix (GLCM). In addition, the users\u2019 ages and the duration of the SM usage (H.mean) were also considered. The decision tree (DT) machine-learning algorithm was employed to predict the abnormal cases (painful subjects) against the normal ones (no pain). The results showed that angle_1, area, and the image contrast significantly increased statistically with the time of SM-device usage, precisely in the range of 2 to 9 h. The DT showed a promising result demonstrated by classification accuracy and F1-scores of 94% and 0.95, respectively. Our findings confirmed that the objectively detected parameters, which elucidate the negative impacts of SM-device usage on neck pain, can be predicted by DT machine learning.<\/jats:p>","DOI":"10.3390\/jimaging9010014","type":"journal-article","created":{"date-parts":[[2023,1,9]],"date-time":"2023-01-09T02:31:30Z","timestamp":1673231490000},"page":"14","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Social Media Devices\u2019 Influence on User Neck Pain during the COVID-19 Pandemic: Collaborating Vertebral-GLCM Extracted Features with a Decision Tree"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1249-009X","authenticated-orcid":false,"given":"Bassam","family":"Al-Naami","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, Faculty of Engineering, The Hashemite University, Zarqa 13133, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bashar E. A.","family":"Badr","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Al-Ahliyya Amman University, Amman 19328, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4249-2923","authenticated-orcid":false,"given":"Yahia Z.","family":"Rawash","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Faculty of Engineering, The Hashemite University, Zarqa 13133, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hamza Abu","family":"Owida","sequence":"additional","affiliation":[{"name":"Department of Medical Engineering, Al-Ahliyya Amman University, Amman 19328, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0893-138X","authenticated-orcid":false,"given":"Roberto","family":"De Fazio","sequence":"additional","affiliation":[{"name":"Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4058-4042","authenticated-orcid":false,"given":"Paolo","family":"Visconti","sequence":"additional","affiliation":[{"name":"Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,8]]},"reference":[{"key":"ref_1","unstructured":"(2022, April 04). 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