Impact of Awareness of Bias and Confounding in Epidemiologic Literature  WEEK 6: Critiquing Sources of Error in Population Research to Address Gaps in Nursing Practice

Awareness of bias and confounding in research would greatly influence how I approach treating these patients. Enzenbach et al. (2021) showed that selection bias in population studies often results in participants who are better educated, more financially stable, and healthier than non-participants. This means research on MTBI interventions might not accurately represent older adults with multiple health problems or those from disadvantaged backgrounds. When working with older MTBI patients, I need to consider that their experiences and needs differ substantially from those in research studies.

The research by Khalili et al. (2021) revealed significant discrepancies between self-reported substance use and biological test results, highlighting how underreporting bias affects data collection. With older MTBI patients, this is particularly relevant as they might minimize cognitive difficulties or mental health symptoms due to fear of losing independence or facing stigma. Without recognizing these reporting tendencies, I could easily miss essential symptoms or comorbidities that would impact their treatment plan and recovery.

Two Strategies researchers can use to Minimize Bias in studies 

Researchers can implement improved recruitment methods to minimize bias. As Enzenbach et al. (2021) suggested, considering "the extent of the assessment, the interest in the research topic, and health problems of potential participants can help increase participation and reduce selection bias. Creating multiple pathways for recruitment through community centers, support groups, and healthcare facilities would help researchers engage a more diverse and representative sample of older adults with MTBI.

Another effective strategy is using multiple data collection methods rather than relying solely on self-reporting. Khalili et al. (2021) demonstrated that combining self-reports with objective measures provides more accurate information. In MTBI research, this might mean supplementing patient reports with neuropsychological testing, interviews with family members, and biological markers to create a more comprehensive picture of each patient's condition.

Effects on Bias Result Interpretation

Without minimizing these biases, research results can be seriously misinterpreted. Selection bias might produce treatment protocols that work well for higher-functioning patients but fail to address the needs of those with complex health profiles. As Enzenbach et al. (2021) noted, "frequencies of major health conditions in the general population will likely be underestimated, potentially leading to inadequate care for the most vulnerable patients.

Reporting bias could cause researchers to underestimate symptom severity or miss critical comorbid conditions. Khalili et al. (2021) found only "fair and moderate agreement" between self-reported substance use and objective testing results (p. 1), highlighting how sensitive information is often underreported. For MTBI patients, this could mean significant emotional or cognitive symptoms go unaddressed in treatment recommendations.

By recognizing these biases and working to minimize them, mental health professionals can develop more inclusive and effective interventions for older adults with MTBI.

                                                     References

Enzenbach, C., Wicklein, B., Wirkner, K., & Loeffler, M. (2021). Evaluating selection bias in a population-based cohort study with low baseline participation: The LIFE-Adult-Study. BMC Medical Research Methodology, 19(135), 1-14. https://doi.org/10.1186/s12874-019-0779-8Links to an external site.

Karr, J. E., Iverson, G. L., Isokuortti, H., Kataja, A., Brander, A., Öhman, J., & Luoto, T. M. (2021). Preexisting conditions in older adults with mild traumatic brain injuries. Brain Injury, 1-9. https://doi.org/10.1080/02699052.2021.1976419Links to an external site.

Khalili, P., Esmaeili Nadimi, A., Baradaran, H. R., Janani, L., Rahimi-Movaghar, A., Rajabi, Z., Rahmani, A., Hojati, Z., Khalagi, K., & Motevalian, S. A. (2021). Validity of self-reported substance use: Research setting versus primary health care setting. Substance Abuse Treatment, Prevention, and Policy, 16(66), 1-13.