000120075 001__ 120075
000120075 005__ 20240319081014.0
000120075 0247_ $$2doi$$a10.2196/31800
000120075 0248_ $$2sideral$$a128870
000120075 037__ $$aART-2022-128870
000120075 041__ $$aeng
000120075 100__ $$aGarcía Martínez, Claudia
000120075 245__ $$aExploring the Risk of Suicide in Real Time on Spanish Twitter: Observational Study
000120075 260__ $$c2022
000120075 5060_ $$aAccess copy available to the general public$$fUnrestricted
000120075 5203_ $$aBackground:Social media is now a common context wherein people express their feelings in real time. These platforms are increasingly showing their potential to detect the mental health status of the population. Suicide prevention is a global health priority and efforts toward early detection are starting to develop, although there is a need for more robust research. Objective:We aimed to explore the emotional content of Twitter posts in Spanish and their relationships with severity of the risk of suicide at the time of writing the tweet. Methods:Tweets containing a specific lexicon relating to suicide were filtered through Twitter's public application programming interface. Expert psychologists were trained to independently evaluate these tweets. Each tweet was evaluated by 3 experts. Tweets were filtered by experts according to their relevance to the risk of suicide. In the tweets, the experts evaluated: (1) the severity of the general risk of suicide and the risk of suicide at the time of writing the tweet (2) the emotional valence and intensity of 5 basic emotions; (3) relevant personality traits; and (4) other relevant risk variables such as helplessness, desire to escape, perceived social support, and intensity of suicidal ideation. Correlation and multivariate analyses were performed. Results:Of 2509 tweets, 8.61% (n=216) were considered to indicate suicidality by most experts. Severity of the risk of suicide at the time was correlated with sadness (ρ=0.266; P<.001), joy (ρ=–0.234; P=.001), general risk (ρ=0.908; P<.001), and intensity of suicidal ideation (ρ=0.766; P<.001). The severity of risk at the time of the tweet was significantly higher in people who expressed feelings of defeat and rejection (P=.003), a desire to escape (P<.001), a lack of social support (P=.03), helplessness (P=.001), and daily recurrent thoughts (P=.007). In the multivariate analysis, the intensity of suicide ideation was a predictor for the severity of suicidal risk at the time (β=0.311; P=.001), as well as being a predictor for fear (β=–0.009; P=.01) and emotional valence (β=0.007; P=.009). The model explained 75% of the variance. Conclusions:These findings suggest that it is possible to identify emotional content and other risk factors in suicidal tweets with a Spanish sample. Emotional analysis and, in particular, the detection of emotional variations may be key for real-time suicide prevention through social media.
000120075 536__ $$9info:eu-repo/grantAgreement/ES/DGA/B03-20R$$9info:eu-repo/grantAgreement/ES/DGA/B21-20R-GAIAP
000120075 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000120075 590__ $$a8.5$$b2022
000120075 592__ $$a1.547$$b2022
000120075 591__ $$aPUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH$$b8 / 180 = 0.044$$c2022$$dQ1$$eT1
000120075 593__ $$aPublic Health, Environmental and Occupational Health$$c2022$$dQ1
000120075 591__ $$aPUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH$$b15 / 207 = 0.072$$c2022$$dQ1$$eT1
000120075 593__ $$aHealth Informatics$$c2022$$dQ1
000120075 594__ $$a12.3$$b2022
000120075 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000120075 700__ $$0(orcid)0000-0001-6565-9699$$aOliván Blázquez, Bárbara$$uUniversidad de Zaragoza
000120075 700__ $$0(orcid)0000-0001-5549-7649$$aFabra, Javier$$uUniversidad de Zaragoza
000120075 700__ $$0(orcid)0000-0002-1557-7545$$aMartínez Martínez, Ana Belén$$uUniversidad de Zaragoza
000120075 700__ $$0(orcid)0000-0001-5566-9746$$aPérez Yus, María Cruz$$uUniversidad de Zaragoza
000120075 700__ $$0(orcid)0000-0002-1690-4130$$aLópez Del Hoyo, Yolanda$$uUniversidad de Zaragoza
000120075 7102_ $$11006$$2255$$aUniversidad de Zaragoza$$bDpto. Fisiatría y Enfermería$$cÁrea Enfermería
000120075 7102_ $$14009$$2740$$aUniversidad de Zaragoza$$bDpto. Psicología y Sociología$$cÁrea Psicología Social
000120075 7102_ $$14009$$2730$$aUniversidad de Zaragoza$$bDpto. Psicología y Sociología$$cÁrea Psicología Básica
000120075 7102_ $$14009$$2735$$aUniversidad de Zaragoza$$bDpto. Psicología y Sociología$$cÁrea Psicolog.Evolut.Educac
000120075 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000120075 773__ $$g8, 5 (2022), e31800$$tJMIR public health and surveillance$$x2369-2960
000120075 8564_ $$s472108$$uhttps://zaguan.unizar.es/record/120075/files/texto_completo.pdf$$yVersión publicada
000120075 8564_ $$s2446118$$uhttps://zaguan.unizar.es/record/120075/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000120075 909CO $$ooai:zaguan.unizar.es:120075$$particulos$$pdriver
000120075 951__ $$a2024-03-18-15:26:22
000120075 980__ $$aARTICLE