Critically Appraising Design Elements and Study Validity in Quantitative Studies

Critically Appraising Design Elements and Study Validity in Quantitative Studies

In the study by Schmeer et al. (2019), the statistical power appeared adequate. A large sample size and robust analytical methods support this. The independent variable, family context, was well-defined and operationalized. This created clear contrasts that likely enhanced statistical power. Precision was further improved by controlling for confounding variables such as socioeconomic status, race, and age, reducing potential biases. However, if the hypotheses were not supported, it raises the possibility that statistical conclusion validity might have been compromised. This may be due to issues like measurement errors or unaccounted confounders. These factors could lead to incorrect conclusions despite the rigorous methodology. Therefore, while the study was methodologically sound, any unsupported hypotheses should be interpreted carefully.

There is no categorical focus on intervention fidelity. This is because the study is observational rather than interventional. Therefore, elements such as staff training, monitoring of intervention implementation, and ensuring the delivery and receipt of the intervention were not applicable. The research aimed to examine naturally occurring family contexts and their impact on adolescent sleep patterns. It was not testing the effects of a specific intervention. Subsequently, the study’s strength lies in its observational design, analyzing existing variables rather than implementing and monitoring a controlled intervention. For studies of this nature, ensuring accurate measurement and control of confounding variables is important instead of focusing on intervention fidelity.

In their 2019 study, Schmeer et al. took several steps to minimize selection biases and control for confounding variables. The researchers used a large, diverse sample drawn from the National Longitudinal Study of Adolescent to Adult Health. This ensured that there was broad representation and selection bias was reduced. They used statistical controls for a range of confounding participant characteristics. For instance, socioeconomic status, race, age, and gender. They accounted for these variables by using multivariate regression models. Thus enhancing the equivalence of the groups being compared. Additionally, they conducted sensitivity analyses to test the strength of their findings. These steps collectively were adequate in controlling for potential confounders and minimizing selection biases. They strengthened the validity of the study’s conclusions. However, despite these measures, unmeasured confounding variables may still exist. This is a common limitation in observational studies.

Several design elements were incorporated to address threats to internal validity. The use of longitudinal data from the National Longitudinal Study of Adolescent to Adult Health helped mitigate the impact of history and maturation effects. It enabled tracking of changes over time within the same individuals. Attrition was addressed by employing appropriate statistical techniques to handle missing data. However, the extent to which this was entirely effective depends on the nature and reasons for participant dropout. The researchers aimed to reduce confounding influences that could bias the results. They included a wide range of control variables, such as socioeconomic status, race, and family structure. However, as an observational study, it inherently cannot rule out all potential threats to internal validity. For example, unmeasured confounders or biases arising from self-reported data. Overall, the study demonstrates a high level of internal validity due to its strong design and comprehensive controls. Nonetheless, some limitations typical of observational research remain.

The primary threats to construct validity were related to the accurate measurement and operationalization of the key variables. Key variables included family contexts and sleep patterns. The study’s design was observational rather than interventional. Therefore, issues like matching the conceptualization of an intervention with its operationalization and confounding the intervention with extraneous content did not apply. However, ensuring that the constructs of family contexts, such as family structure and sleep quality, such as duration, were accurately and consistently measured was crucial. The researchers used well-established instruments and longitudinal data to minimize these threats. The setting, drawing on a nationally representative sample, was appropriate and reflective of the general adolescent population in the United States. It was in line with the study’s conceptual framework. Overall, the construct validity of the study appears strong. Careful consideration was given to defining and measuring the central constructs.

Schmeer et al. (2019) provided a detailed description of the study context, enhancing its external validity. The study utilized data from the National Longitudinal Study of Adolescent to Adult Health. This includes a large, nationally representative sample of adolescents in the United States. This broad and diverse sample improves the generalizability of the findings to the wider adolescent population in the United States. The settings and participants were well-described, covering various family contexts and socio-demographic backgrounds. They were typical of those to whom the results are intended to apply. The study’s findings are more likely to apply to similar populations because it captured a wide range of family environments and demographic variables. This supports the external validity of the research.

In their study on family contexts and sleep during adolescence, Schmeer et al. (2019) appear to have appropriately balanced validity concerns. The researchers paid significant attention to internal validity by employing robust statistical methods, controlling for confounding variables, and addressing potential threats to the study’s integrity. However, this focus on internal validity did not come at the expense of external validity. The use of a nationally representative sample and detailed descriptions of the study context and participants enhanced the generalizability of the findings beyond the specific sample studied. By addressing internal and external validity concerns, the researchers ensured that their findings were reliable and applicable to broader populations. This reflects a balanced approach to validity considerations.

References

Schmeer, K. K., Tarrence, J., Browning, C. R., Calder, C. A., Ford, J. L., & Boettner, B. (2019). Family contexts and sleep during adolescence. SSM – Population Health, 7, 100320. https://doi.org/10.1016/

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Critique a quantitative study for design elements and study validity. Use the guidelines for critiquing design elements and study validity, Box 10.1 (p. 223) of your textbook.

Critically Appraising Design Elements and Study Validity in Quantitative Studies

Read the Introduction and Methods section of the assigned quantitative article (refer to the entirety of the article as needed) and write a paper (no more than 4 pages) evaluating the article for critical elements for design and validity. The article may also be found in the Toolkit accompanying the Resource Manual. Be sure to read carefully, and pay attention to grammar, sentence structure, and APA guidelines. Do not be repetitive, just state the facts and be concise. Be sure to refer to the Rubric used to grade this assignment.