Authors:
Dexter Dave R. Valdeavilla
;
Nicole Ashley V. Santos
;
Agana Louisse S. Domingo
and
Maria Teresa R. Pulido
Affiliation:
Department of Physics, Mapúa University, Intramuros, Manila City, 1002 and Philippines
Keyword(s):
Biomedical Experiments, Depression, Mental Health, Emerging Issues in Social Networks, Surveys, Case Studies.
Related
Ontology
Subjects/Areas/Topics:
Case Studies
;
Health Engineering and Technology Applications
;
Neural Rehabilitation
;
Neurotechnology, Electronics and Informatics
;
Simulation and Modeling
;
Simulation Tools and Platforms
Abstract:
Depression is a mental illness that negatively affects how a person feels, thinks and acts. In this work, we used an online survey to ask 501 Filipino university-age students on symptoms commonly associated with depression: sadness or isolation, headaches or migraine, anxiety over everyday activities, moodiness or irritability or agitation, chronic fatigue, and low self-esteem or motivation. We learned that all respondents experience at least one symptom weekly. Most respondents (52.7%) experience all six symptoms weekly, with 1 to 3 days a week being the most common frequency. An overwhelming majority attributed such symptoms to academics (92.6%), followed by family (69.5%) and friends (49.5%). Lastly, most (41.9% - 59.7%) believe they have around 1-3 friends with the same symptoms that they experience. The researchers are calling for an increased awareness of mental health issues and good practices, especially within homes and schools, to address the prevalence of depression in uni
versity-age Filipinos. The prevalence of Big Data and the Internet of Things within this particular demographic greatly enhances the ability of mental health professionals and researchers to detect and hopefully address the symptoms of depression.
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