Suicidal attempt and suicidal ideation during the COVID-19 pandemic compared to previous years

Jerónimo, Miguel A.; Piñar, Sergio; Samos, Pilar; Gonzalez, Ana M.; Bellsolà, M.; Sabaté, A.; León, Jordi; Aliart, Xavier; Martín, Luis M.; Aceña, R.; Pérez, Ví­ctor; Córcoles, D.

doi:10.1016/j.rpsm.2021.11.004

Cited by 20 publications

(9 citation statements)

References 25 publications

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“…Esto iría en contra de la actual teoría de la paradoja de género, donde las mujeres tienen más intentos/ideación suicida que los hombres, pero estos últimos lo llevan a cabo de manera efectiva en mayor proporción 25 . La situación de pandemia en una sociedad comparable a la de Argentina no ha demostrado invertir esta tendencia de disparidad de género 26 .…”

Section: Discussionunclassified

Determinantes del puntaje PHQ 9 para síntomas depresivos mayores en trabajadores de la salud durante la pandemia de COVID-19 mediante técnicas de <i>machine learning</i>

Battioni¹,

Scatularo²,

Bellia³

et al. 2024

ACM

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Introducción y objetivos: La pandemia por coronavirus 2 del síndrome respiratorio agudo grave (SARS-CoV-2) ha generado efectos psicológicos y sociales negativos en el personal de salud según se evidenció en la encuesta IMPPACTS-SAC20. Nuestro objetivo es determinar qué dominios del Patient Health Questionnaire (PHQ 9) tienen más influencia en el diagnóstico de depresión mayor e identificar subpoblaciones con elevada prevalencia de esta enfermedad. Métodos: Subanálisis de la encuesta IMPPACTS-SAC20. Se utilizaron técnicas de machine learning no supervisado para realizar un análisis factorial y generar subgrupos de casos similares en cuanto a su desempeño en el puntaje PHQ 9. Resultados: Se incluyeron 1,221 encuestados que respondieron el puntaje PHQ 9. El análisis factorial demostró la presencia de dos dimensiones principales (neurastenia y autopercepción negativa) que explican el 67.2% de la varianza del cuestionario (prueba KMO 0.911, Bartlett p < 0.001). La combinación de ambas dimensiones en un análisis jerárquico generó 9 clusters. Los grupos 5, 4, 2 y 1 explican el 93% de los casos de depresión mayor. Los grupos 5 y 4 presentaron valores más elevados de neurastenia, y los grupos 2 y 1 de autopercepción negativa. Los grupos 6, 7 y 8 en su conjunto presentaron una prevalencia de depresión mayor del 0.6%. Conclusión: La implementación de técnicas de machine learning detectó dos dimensiones dentro del puntaje PHQ 9, la neurastenia y la autopercepción negativa. Se evidenciaron subgrupos de alta prevalencia de depresión mayor, cuyas principales características clínicas fueron el sexo femenino, el consumo de alcohol, el tabaquismo y la intención suicida.

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Section: Discussionunclassified

Determinantes del puntaje PHQ 9 para síntomas depresivos mayores en trabajadores de la salud durante la pandemia de COVID-19 mediante técnicas de <i>machine learning</i>

Battioni¹,

Scatularo²,

Bellia³

et al. 2024

ACM

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“…Intentional intoxication may or may not correspond to suicide cases; however, there are no data in this study to inform how many suicide cases occurred in the two years under study. However, the results of a study conducted in Barcelona indicate that there was an increase of 43.2% in suicide thoughts and attempts during the pandemic compared with the 2018–2019 period, reaching a maximum increase of 573.8% in people under 18 years of age in the month of May 2021 [ 32 ]. Also, the “Report of specific developed activities of CODUs” for 2020 shows that suicidal behaviors increased in the second half of 2020, with an expected trend of gradual increase according to the phases of crisis response mechanisms [ 16 ].…”

Section: Discussionmentioning

confidence: 99%

Characterization of Potential Intoxications with Medicines in a Regional Setting

et al. 2023

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The Portuguese Poison Information Center (from Portuguese—CIAV) is a call center that offers medical assistance in case of possible intoxication with any kind of product, including medicines. This center´s main goal is to inform and guide the general public and health professionals. This work aimed to analyze and compare data corresponding to the telephone calls from the Algarve region (South of Portugal), received by CIAV during 2019 and 2020, regarding potential intoxications with medicines. To this end, data provided by CIAV on possible cases of medication intoxication in the Algarve region were collected, including the number of calls received, the place of origin of the call, the age group and sex of the intoxicated individual, the route of exposure to the drug, the circumstances of contact with the substance, the existence of symptoms, and the drug or drugs involved in the potential intoxication. The results showed that the number of cases slightly decreased in 2020 (n = 1261) compared with 2019 (n = 1340), with a high number of cases of intoxication in children between one and four years old in both years (21.2%; n = 152 in 2019; 16.4%; n = 115 in 2020). The drugs belonging to the locomotor system group (paracetamol and ibuprofen) were the main drugs involved, followed by the central nervous system pharmacotherapeutic group, namely benzodiazepines (diazepam and alprazolam). Paracetamol was the main drug responsible for the calls to CIAV (n = 71 in 2019; n = 63 in 2020), while for the remaining drugs there were fluctuations in their positions between both years. In some cases, this swinging may be explained by the possible changes in therapy due to potential interactions with drugs used for the treatment of symptoms of COVID-19 or perhaps related to misleading information released by the media about the use of some drugs, such as ibuprofen, during lockdown periods. Although there has been a decrease in calls to report possible drug intoxication in the Algarve region, the profile of calls was very similar. Paracetamol was the drug with the highest number of reported cases and the group of psychotropic drugs showed the largest increase between 2019 and 2020.

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“…The previous trend combines with what was recorded by the National Survey of Health and Nutrition (ENSANUT) 2018, in which it refers that 5% of the population over 10 years old has ever thought about committing suicide, more specifically in the adolescent population (10 to 19 years old) 4% in men and 7% in women, and in the young population (20 to 29 years old) 4% in men and 5% in women. It has been analyzed that the impact of the pandemic on the suicide spectrum can be economic, social and biological (Conejero et al, 2020), with psychological consequences that could impact suicide rates during the pandemic and even after (Sher, 2020), as has been verified in the significant increase in the number of consultations due to suicide ideas and attempts (Jerónimo et al, 2021), or in the increase in mortality due to suicide, even in countries with a relatively small impact of COVID -19 (Watanabe and Tanaka, 2022). With this panorama, it is necessary to test models that explain suicidal risk, which allow guiding prevention and clinical supported on theoretical empirical bases about suicide.…”

Section: Introductionmentioning

confidence: 99%

Suicide risk model based on the interpersonal theory of suicide: evidence in three regions of Mexico

2023

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Background: Reports of suicidal behavior have increased in Mexico for years. In order to develop a more adequate suicide prevention strategy, it is necessary to understand its predictive factors, so the purpose of this research was to propose a model of suicidal risk in young people, taking into account one of the most current theories on the subject, Joiner's interpersonal theory. Method: A non-probabilistic sample of young people with suicidal ideation from three regions of Mexico was obtained by online survey (N=411), with mean age of 17.89 years (SD. 1.2), 336 women (81.8%), and 75 men (18.2%). Results: First, a multiple linear regression model was created to predict suicidal risk based on thwarted belongingness and perceived burden with 17% explained variance; then a second model was generated with the same variables and including other factors associated with suicide such as self-injury desires, impulsivity and suicide attempts, in addition to variables associated with family conflicts, improving the explained variance to 34%. Lastly, two properly adjusted structural equation models were obtained, one focused on suicidal risk (R2=.21; RMSEA=.026; CFI=.99) and the other on ideation (R2=.18; RMSEA=.070; CFI=.98). Conclusions: The main factors that explain suicidal risk are depressive symptoms, perceived burden and desires for self-injury. Further research on the effect of painful experiences as factors that could predict suicide attempt is suggested.

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Suicidal attempt and suicidal ideation during the COVID-19 pandemic compared to previous years

Cited by 20 publications

References 25 publications

Determinantes del puntaje PHQ 9 para síntomas depresivos mayores en trabajadores de la salud durante la pandemia de COVID-19 mediante técnicas de <i>machine learning</i>

Determinantes del puntaje PHQ 9 para síntomas depresivos mayores en trabajadores de la salud durante la pandemia de COVID-19 mediante técnicas de <i>machine learning</i>

Characterization of Potential Intoxications with Medicines in a Regional Setting

Suicide risk model based on the interpersonal theory of suicide: evidence in three regions of Mexico

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