{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T12:02:56Z","timestamp":1781611376087,"version":"3.54.5"},"reference-count":32,"publisher":"BMJ","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BMJ Health Care Inform"],"published-print":{"date-parts":[[2018,7]]},"abstract":"<jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Internet use among the elderly is influenced by various demographic backgrounds, social life and health factors.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>This study aims to identify the impact of several demographic features on 60- to 79-year-old individuals\u2019 intention to use the Internet.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec sec-type=\"method\">\n                  <jats:title>Method<\/jats:title>\n                  <jats:p>Finland population data (<jats:italic>N<\/jats:italic> = 2508) from the 2012 IKIPOSA project was used with two cohorts: 60s group (<jats:italic>n<\/jats:italic> = 1515) and 70s group (<jats:italic>n<\/jats:italic> = 990). Descriptive statistic and two binomial logistic regressions have been used with the unadjusted effect and Forward LR method to measure each predictor\u2019s contribution to the model. In addition, a preliminary analysis to measure the multicollinearity was performed.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Result<\/jats:title>\n                  <jats:p>Of the 18 independent variables, only nine predictors, namely, age, education, financial situation, having children, entrepreneurship, a leadership position, a higher level white-collar worker and a lower level white-collar worker, were significant factors in predicting the Internet use. Meanwhile, gender, having grandchildren, living alone, marital status, house location and type, stay-at-home mother or father, blue-collar worker, agricultural entrepreneur and social relations satisfaction were not significant predictors. The most significant predictors were education and age, which contributed 19% and 10%, respectively, to the model. Other significant predictors, lower level white-collar worker, higher level white-collar worker and financial situation, had less impact with only around 6%.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>Education and age were influential factors among elderly to use the Internet in their later life. Certain work experiences affect elderly people\u2019s engagement with the Internet after retirement.<\/jats:p>\n               <\/jats:sec>","DOI":"10.14236\/jhi.v25i3.868","type":"journal-article","created":{"date-parts":[[2018,10,18]],"date-time":"2018-10-18T10:47:09Z","timestamp":1539859629000},"page":"132-133","source":"Crossref","is-referenced-by-count":9,"title":["Influence of previous work experience and education on Internet use of people in their 60s and 70s"],"prefix":"10.1136","volume":"25","author":[{"given":"Muzawir","family":"Arief","sequence":"first","affiliation":[{"name":"Doctoral Student, Department of Health and Social Management, Faculty of Social Sciences and Business Studies, University of Eastern Finland, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sari","family":"Rissanen","sequence":"additional","affiliation":[{"name":"Professor, Department of Social Sciences, Faculty of Social Sciences and Business Studies, University of Eastern Finland, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaija","family":"Saranto","sequence":"additional","affiliation":[{"name":"Professor, Department of Health and Social Management, Faculty of Social Sciences and Business Studies, University of Eastern Finland, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2018,7,1]]},"reference":[{"key":"2025072913391247000_25.3.132.1","doi-asserted-by":"publisher","DOI":"10.4135\/9781446278918.n14"},{"key":"2025072913391247000_25.3.132.2","unstructured":"United Nations; Department of Economic and Social Affairs; Population Division. 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