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Revista de la Facultad de Medicina Humana

versão impressa ISSN 1814-5469versão On-line ISSN 2308-0531

Resumo

CARRILLO, Fiorella Otero; PICOY ROMERO, Pamela Rocio  e  ROJAS, Rubén Espinoza. mpact of addiction to social networks on the mental health of human medicine students, in times of Covid-19. Rev. Fac. Med. Hum. [online]. 2023, vol.23, n.4, pp.62-72.  Epub 30-Nov-2023. ISSN 1814-5469.  http://dx.doi.org/10.25176/rfmh.v23i4.5920.

Objective:

To determine the association of addiction to social networks and the consequences in mental health in human medicine students of the Ricardo Palma University, year 2021.

Materials and methods:

Cross-sectional observational study, with the participation of 454 human medicine students from first to fifth year, chosen by stratified random sampling proportional to size. The instrument was validated, obtaining a Cronbach's Alpha (α=0.90), the questionnaires used were: Addiction to Social Networks (ARS), Depression, Anxiety, Stress Scale (DASS-21) and Pittsburgh Sleep Quality Index (PSQI). In order to evaluate the association between variables, we used crude and adjusted prevalence ratio (PR), using the Poisson regression model with the logarithmic link and with the 95% confidence interval.

Results:

65.4% were women, with an average age of 21.2 years. A significant association was found between high social network addiction and mental health (PRc: 2.59; 95% CI: 1.92-3.50; p: 0.000) and, likewise, between high and medium levels of social network addiction. social and with depression, anxiety, stress (p: 0.000) and sleep quality (p<0.010), respectively. 41%, 49.1% and 9.9% of the students presented low, medium and high addiction to social networks, respectively. 57.5% had depression, 56.4% anxiety, 70.5% stress and 77.3% poor sleep quality.

Conclusions:

There was a strong association between ARS and mental health. Therefore, it is recommended that university students visit mental health specialists quarterly for proper identification, evaluation, and management of the problems generated by ARS.

Palavras-chave : Behavior; addictive; social networking; mental health; students, medical (Source: MeSH NLM).

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