• Example Article: Exelmans, L., & Van den Bulck, J. (2016). Bedtime mobile phone use and sleep in adults. Social Science & Medicine, 148, 93-101. https://doi.org/10.1016/j.socscimed.2015.11.037

• Description: This study investigated the association between using a mobile phone at bedtime and sleep outcomes in a sample of adults. The defining characteristic making this a cross-sectional study is that both the exposure (frequency and type of mobile phone use in bed after lights out) and the outcomes (sleep duration, sleep quality, fatigue, sleep latency) were measured concurrently using surveys administered at a single time point. The researchers recruited a large sample of adults and asked them about their current phone habits and recent sleep experiences. They then analyzed the data to see if higher levels of bedtime phone use were associated with poorer sleep outcomes within that snapshot in time. The study found a significant association, suggesting that bedtime phone use might negatively impact sleep. However, because data were collected simultaneously, it cannot definitively prove that phone use caused poor sleep; it’s possible that people with poor sleep are more likely to use their phones in bed (reverse causality) or that another factor influences both. It provides valuable information on the prevalence of the behavior and its association with sleep issues in the studied population.

In summary, these three study designs represent different approaches along a spectrum of epidemiological investigation. Case reports and series are often initial steps, providing detailed descriptions of novel or unusual occurrences in individuals or small groups, crucial for hypothesis generation. Cross-sectional studies offer a snapshot of a population at a single point in time, useful for measuring prevalence and identifying associations, but limited in determining cause-and-effect relationships (Celentano & Szklo, 2019; Aschengrau & Seage, 2020). Each design contributes uniquely to our understanding of health and disease patterns.

References

Aschengrau, A., & Seage, G. R. (2020). Essentials of epidemiology in public health (4th ed.). Jones & Bartlett Learning.

Celentano, D. D., & Szklo, M. (2019). Gordis epidemiology (6th ed.). Elsevier.

Dufort, E. M., Koumans, E. H., Chow, E. J., Rosenthal, E. M., Muse, A., Rowlands, J., Barranco, M. A., Maxted, A. M., Rosenberg, E. S., Easton, D., Udo, T., Kumar, J., Pulver, W., Smith, L., Hutton, B., Blog, D., & Zucker, H. (2020). Multisystem inflammatory syndrome in children in New York State. New England Journal of Medicine, 383(4), 347-358. https://doi.org/10.1056/NEJMoa2021756