Identifying the suicidal ideation risk group among older adults in rural areas: Developing a predictive model using machine learning methods.

Kim, Junglyun; Gwak, DongHyeon; Kim, Seonhee; Gang, Moonhee

Kim, Junglyun; Gwak, DongHyeon; Kim, Seonhee; Gang, Moonhee.

Afiliación

Kim J; College of Nursing, Chungnam National University, Daejeon, South Korea.
Gwak D; Department of Biobehavioral Nursing Science, University of Florida, Gainesville, Florida, USA.
Kim S; College of Nursing, Chungnam National University, Daejeon, South Korea.
Gang M; Nursing Department, Songwon University, Gwangju, South Korea.

J Adv Nurs ; 79(2): 641-651, 2023 Feb.

Article en En | MEDLINE | ID: mdl-36534434

Asunto(s)

Depresión; Ideación Suicida; Humanos; Anciano; Estudios Transversales; Factores de Riesgo; Aprendizaje Automático; Dolor

Palabras clave

aged; depression; loneliness; machine learning; nurses; pain; rural population; suicidal ideation

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Depresión / Ideación Suicida Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Humans Idioma: En Revista: J Adv Nurs Año: 2023 Tipo del documento: Article País de afiliación: Corea del Sur

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