{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T03:55:37Z","timestamp":1782186937928,"version":"3.54.5"},"reference-count":39,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100005621","name":"Kasetsart University Research and Development Institute","doi-asserted-by":"publisher","award":["FF(KU) 51.67"],"award-info":[{"award-number":["FF(KU) 51.67"]}],"id":[{"id":"10.13039\/501100005621","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fogarty International Center of the National Institutes of Health","award":["U2RTW010088"],"award-info":[{"award-number":["U2RTW010088"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Health Informatics J"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:p>\n                    <jats:bold>Objectives:<\/jats:bold>\n                    This study examined the associations between pesticide exposures, perceived farm stressors, COVID-19-related stressors, and mental health disorders among Thai farmers.\n                    <jats:bold>Methods:<\/jats:bold>\n                    A total of 270 participants were interviewed to assess mental health disorders. Information was also collected on household environments, agricultural activities, and perceived farm- and COVID-19-related stressors. After data preprocessing, 211 samples remained for analysis. Multiple linear regression models were employed as a baseline, and their performance was compared with ensemble tree-based models, which can capture more complex, nonlinear patterns. The Boruta feature selection technique and SHAP scores were used to explain associations between mental health and the independent variables.\n                    <jats:bold>Results:<\/jats:bold>\n                    Lower levels of mental health disorder symptoms were associated with higher levels of personal protective equipment (PPE) use. Certain perceived farm stressors and COVID-19-related stressors were also correlated with mental health outcomes.\n                    <jats:bold>Conclusions:<\/jats:bold>\n                    The findings indicate that greater PPE use and good agricultural practices are associated with reduced symptoms of mental health disorders. This pilot study highlights the potential of machine learning models to explore complex public health issues involving multiple, interrelated factors.\n                  <\/jats:p>","DOI":"10.1177\/14604582251388827","type":"journal-article","created":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T23:53:02Z","timestamp":1761781982000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Application of machine learning to identify key factors influencing agricultural workers\u2019 mental health: A case study of Thai farmers"],"prefix":"10.1177","volume":"31","author":[{"given":"Papis","family":"Wongchaisuwat","sequence":"first","affiliation":[{"name":"Kasetsart University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4256-0512","authenticated-orcid":false,"given":"Veerasit","family":"Kaewbundit","sequence":"additional","affiliation":[{"name":"Kasetsart University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6875-638X","authenticated-orcid":false,"given":"Saisattha","family":"Noomnual","sequence":"additional","affiliation":[{"name":"Mahidol University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,10,29]]},"reference":[{"key":"e_1_3_8_2_2","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph16234849"},{"key":"e_1_3_8_3_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0225661"},{"key":"e_1_3_8_4_2","doi-asserted-by":"publisher","DOI":"10.11606\/s1518-8787.2020054002263"},{"key":"e_1_3_8_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.envres.2016.08.020"},{"key":"e_1_3_8_6_2","doi-asserted-by":"publisher","DOI":"10.1136\/oemed-2012-101005"},{"key":"e_1_3_8_7_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12889-019-6712-6"},{"key":"e_1_3_8_8_2","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph16081327"},{"key":"e_1_3_8_9_2","first-page":"1038","article-title":"The application of artificial neural network in studying landless farmer\u2019s mental health problems","volume":"29","author":"Zhang X","year":"2008","unstructured":"Zhang X, Huang S, Wu X, et al. The application of artificial neural network in studying landless farmer\u2019s mental health problems. Zh\u014dnghu\u00e1 li\u00fax\u00edngb\u00ecng z\u00e1zh\u00ec 2008; 29: 1038\u20131041.","journal-title":"Zh\u014dnghu\u00e1 li\u00fax\u00edngb\u00ecng z\u00e1zh\u00ec"},{"key":"e_1_3_8_10_2","first-page":"10","volume-title":"Depression and risk factors among Iowa farmers","author":"Scarth RD","year":"1997","unstructured":"Scarth RD, Zwerling C, Burmeister LF, et al. Agricultural health and safety. In: Depression and risk factors among Iowa farmers. CRC Press, 1997, p. 10."},{"key":"e_1_3_8_11_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11205-014-0638-2"},{"key":"e_1_3_8_12_2","doi-asserted-by":"publisher","DOI":"10.1037\/rmh0000121"},{"key":"e_1_3_8_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jrurstud.2020.08.053"},{"key":"e_1_3_8_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.psycom.2022.100036"},{"key":"e_1_3_8_15_2","doi-asserted-by":"publisher","DOI":"10.3390\/su13095186"},{"key":"e_1_3_8_16_2","doi-asserted-by":"publisher","DOI":"10.2147\/RMHP.S302521"},{"key":"e_1_3_8_17_2","doi-asserted-by":"publisher","DOI":"10.1080\/1059924X.2022.2137616"},{"key":"e_1_3_8_18_2","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph192013566"},{"key":"e_1_3_8_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijdrr.2021.102513"},{"key":"e_1_3_8_20_2","doi-asserted-by":"publisher","DOI":"10.1177\/1010539515620631"},{"key":"e_1_3_8_21_2","doi-asserted-by":"publisher","DOI":"10.15344\/2394-4978\/2017\/263"},{"key":"e_1_3_8_22_2","doi-asserted-by":"publisher","DOI":"10.1177\/1048291118759311"},{"issue":"1","key":"e_1_3_8_23_2","first-page":"20","article-title":"Effect of depression prevention programs among rice farmers in Thailand","volume":"2","author":"Kaewboonchoo O","year":"2020","unstructured":"Kaewboonchoo O, Hanklang S, Boonyamalik P, et al. Effect of depression prevention programs among rice farmers in Thailand. Environ Occup Health Pract 2020; 2(1): 20.","journal-title":"Environ Occup Health Pract"},{"key":"e_1_3_8_24_2","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph19159654"},{"key":"e_1_3_8_25_2","doi-asserted-by":"publisher","DOI":"10.3390\/su14031189"},{"key":"e_1_3_8_26_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12889-022-14464-3"},{"key":"e_1_3_8_27_2","doi-asserted-by":"publisher","DOI":"10.1080\/10807039.2024.2310810"},{"key":"e_1_3_8_28_2","doi-asserted-by":"publisher","DOI":"10.3390\/fintech1010006"},{"key":"e_1_3_8_29_2","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v036.i11"},{"key":"e_1_3_8_30_2","volume-title":"Biostatistics: a foundation for analysis in the health sciences","author":"Daniel WW","year":"2013","unstructured":"Daniel WW, Cross CL. Biostatistics: a foundation for analysis in the health sciences. 10th ed. Wiley, 2013.","edition":"10"},{"key":"e_1_3_8_31_2","doi-asserted-by":"publisher","DOI":"10.3390\/bioengineering10070792"},{"key":"e_1_3_8_32_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12913-023-10462-2"},{"key":"e_1_3_8_33_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2022.104855"},{"key":"e_1_3_8_34_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3029154"},{"key":"e_1_3_8_35_2","doi-asserted-by":"publisher","DOI":"10.1017\/S0033291719000151"},{"key":"e_1_3_8_36_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0230389"},{"key":"e_1_3_8_37_2","doi-asserted-by":"publisher","DOI":"10.2196\/42420"},{"key":"e_1_3_8_38_2","doi-asserted-by":"publisher","DOI":"10.1186\/s40359-021-00574-x"},{"key":"e_1_3_8_39_2","doi-asserted-by":"publisher","DOI":"10.1186\/s40708-023-00205-8"},{"issue":"1","key":"e_1_3_8_40_2","first-page":"583","article-title":"Predicting employee attrition: XAI-powered models for managerial decision-making","volume":"13","author":"Baydili \u0130T","year":"2015","unstructured":"Baydili \u0130T, Tasci B. Predicting employee attrition: XAI-powered models for managerial decision-making. Systems 2015; 13(1): 583.","journal-title":"Systems"}],"container-title":["Health Informatics Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/14604582251388827","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/14604582251388827","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/14604582251388827","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T22:29:02Z","timestamp":1777501742000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/14604582251388827"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10]]},"references-count":39,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,10]]}},"alternative-id":["10.1177\/14604582251388827"],"URL":"https:\/\/doi.org\/10.1177\/14604582251388827","relation":{},"ISSN":["1460-4582","1741-2811"],"issn-type":[{"value":"1460-4582","type":"print"},{"value":"1741-2811","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10]]},"article-number":"14604582251388827"}}