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Digital Footprints of Distress: An Analysis of Mental Health Search Patterns Across Socioeconomic Spectrums in Alabama Counties

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Wisdom, Well-Being, Win-Win (iConference 2024)

Part of the book series: Lecture Notes in Computer Science ((volume 14598))

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Abstract

Mental healthcare access continues to be a significant challenge in the United States, with marked disparities across socioeconomic divides. As technology and algorithms increasingly play pivotal roles in healthcare access, understanding unique symptom manifestations in socioeconomically disadvantaged communities is crucial. In this context, we embarked on a comprehensive analysis of mental health search patterns in Alabama counties, leveraging Google search data. Distinct trends emerged between socioeconomically advantaged and disadvantaged areas. The advantaged regions predominantly showed clinically specific searches, suggesting a higher degree of mental health literacy or more considerable access to healthcare professionals. Residents in disadvantaged areas primarily utilized generalized mental health symptom terms, such as anxiety and depression, hinting at a potential awareness or resource gap. A similar pattern was evident for somatic symptoms, with the disadvantaged showing a preference towards generalized and pain-related terms. This trend could signify disparities in access to specialized care or inappropriate clinical treatments, raising concerns like potential opioid misuse. Additionally, counties with higher population density had more mental health-related searches, while predominantly African American counties showed fewer, suggesting potential cultural or linguistic barriers. Our findings emphasize the potential of refining search engines to cater to diverse user needs and the importance of tailored health campaigns for marginalized communities. However, potential ethical challenges, such as unintentional exacerbation of existing biases, must consistently be recognized. Future research will elevate this analysis to a national scope, considering the effects of significant global occurrences, such as the COVID-19 pandemic, on search behaviors.

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Notes

  1. 1.

    https://www.countyhealthrankings.org/

  2. 2.

    For a full description of the method Google used to create this dataset, see: https://storage.googleapis.com/gcp-public-data-symptom-search/COVID-19%20Search%20Trends%20symptoms%20dataset%20documentation%20.pdf.

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Authors and Affiliations

  1. School of Library and Information Studies, The University of Alabama, Tuscaloosa, USA

    Hengyi Fu

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  1. Hengyi Fu
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Correspondence to Hengyi Fu .

Editor information

Editors and Affiliations

  1. iSchool organization, Berlin, Germany

    Isaac Sserwanga

  2. University of Tsukuba, Tsukuba, Japan

    Hideo Joho

  3. Jilin University, Changchun, China

    Jie Ma

  4. Stockholm University, Kista, Sweden

    Preben Hansen

  5. Wuhan University, Wuhan, China

    Dan Wu

  6. University of Tsukuba, Tsukuba, Japan

    Masanori Koizumi

  7. University of California, Los Angeles, CA, USA

    Anne J. Gilliland

Appendix A

Appendix A

Alcoholism, Amnesia, Anxiety, Arthralgia, Attention deficit hyperactivity disorder, Auditory hallucination, Avoidant personality disorder, Back pain, Blurred vision, Binge eating, Bruxism, Cataplexy, Chest pain, Compulsive behavior, Compulsive hoarding, Chronic pain, Clouding of consciousness, Confusion, Dementia, Depression, Depersonalization, Dizziness, Dry eye syndrome, Dysphoria, Dyspareunia, Excessive daytime sleepiness, Eye strain, Fatigue, Fibromyalgia, Headache, Hypersomnia, Hyperventilation, Generalized anxiety disorder, Guilt, Hypochondriasis, Impulsivity, Insomnia, Itch, Lightheadedness, Major depressive disorder, Manic Disorder, Mood disorder, Mood swing, Muscle weakness, Myalgia, Nausea, Night sweats, Night terror, Pain, Palpitations, Panic attack, Paranoia, Psychosis, Photophobia, Rumination, Self-harm, Sensitivity to sound, Sleep deprivation, Shortness of breath, Suicidal ideation, Shyness, Sleep disorder, Tachycardia, Tinnitus, Tremor, Vertigo, Weakness, Weight gain, Yawn.

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Fu, H. (2024). Digital Footprints of Distress: An Analysis of Mental Health Search Patterns Across Socioeconomic Spectrums in Alabama Counties. In: Sserwanga, I., et al. Wisdom, Well-Being, Win-Win. iConference 2024. Lecture Notes in Computer Science, vol 14598. Springer, Cham. https://doi.org/10.1007/978-3-031-57867-0_9

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  • DOI: https://doi.org/10.1007/978-3-031-57867-0_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-57866-3

  • Online ISBN: 978-3-031-57867-0

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