“Invalid Data Skews Understanding of Risky Behavior Among LGBQ Students”

By | August 17, 2023



A recent analysis of high school surveys conducted by the CDC suggests that federal data on LGBQ student health may contain exaggerated or untruthful responses, potentially skewing understanding of risky behavior among teens. After accounting for invalid data, the disparities in drug use were not as pronounced as initially thought. However, the disparities in being bullied and considering suicide remained consistent. The study highlights the need for safeguards in data collection to ensure data quality and address mental health disparities. Other research has also found issues with invalid data in various populations and surveys. The Conversation reported

The Centers for Disease Control and Prevention (CDC) conducts surveys on high school students’ health, particularly focusing on lesbian, gay, bisexual, and questioning (LGBQ) students. However, recent analysis has revealed that the data collected may contain a significant amount of inaccurate or exaggerated responses, potentially distorting people’s understanding of risky behavior among teenagers. These inaccuracies affect certain responses more than others. The findings of this analysis are crucial as they highlight the importance of ensuring accurate data collection to avoid misleading conclusions.

The CDC surveys in question were administered during the 2018-2019 school year and involved over 12,800 high school students. These students were asked to identify their sexual orientation and respond to questions regarding their health and well-being. To address the issue of invalid data, a machine-learning algorithm was employed to detect response patterns that indicated extreme or untruthful answers.

After accounting for potentially invalid responses, the disparities in drug use, including steroids, injected drugs, cocaine, ecstasy, and pain medication without a prescription, were found to be less pronounced. Prior to considering the invalid data, it appeared that LGBQ boys used injected drugs four times more frequently than heterosexual boys. However, after accounting for the likely invalid data, no significant difference was observed between the two groups in terms of injected drug use.

While some outcomes were susceptible to invalid data, such as drug use, others remained unaffected. For instance, LGBQ boys and girls were still found to be about twice as likely to experience bullying and two to three times more likely to consider suicide, even after accounting for potentially invalid responses. These findings emphasize that not all outcomes are equally impacted by invalid data.

The Youth Risk Behavior Survey is vital in providing valuable information on the health and behaviors of high school students, particularly in relation to sexual behaviors, drug use, and suicide risk. Therefore, it is crucial to address the stigmatization faced by LGBTQ+ individuals to reduce mental health disparities. Neglecting to check for invalid data may lead researchers to prioritize other differences that may not be as significant or deserving of attention and resources.


To ensure the quality of data collection efforts, policymakers and researchers must implement safeguards. It is essential to recognize that invalid data can disproportionately affect minority populations and low-incidence outcomes, such as heroin use. This issue extends beyond youth surveys and has been observed in studies examining public health behaviors during the COVID-19 pandemic and surveys on sexual orientation among adults.

In response to the study’s findings, the CDC provided a general FAQ page on validity and reliability but did not specifically address the concern raised by the research regarding the disproportionate effect of invalid data on minorities.

Research in various fields, including studies on adoptees, disabled individuals, racial or ethnic minorities, immigrants, and transgender individuals, has also highlighted the issue of invalid data. Even surveys on sexual orientation among adults have encountered invalid responses, casting doubt on the accuracy of the collected information.

In conclusion, it is crucial to conduct data collection endeavors with utmost care to ensure accuracy and prevent misleading conclusions. Addressing the ongoing stigmatization faced by LGBTQ+ individuals is vital in reducing mental health disparities. Policymakers and researchers must prioritize data quality and implement measures to mitigate the impact of invalid responses..

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