Critical Analysis of a Quantitative Study- Design and Validity Evaluation

Critical Analysis of a Quantitative Study- Design and Validity Evaluation

The article by Schmeer et al. (2019) investigates the influence of family contexts on adolescent sleep patterns, contributing to understanding how familial factors impact health outcomes during this critical developmental period. This critique evaluates the study’s design elements and validity using the guidelines provided by Polit and Beck (2021).

Statistical Power and Operationalization of Variables

Statistical power is the ability of a study to obtain statistically significant results when there are true differences in the population. Unlike conceptualization, operationalization focuses on how the variables are measured and used in the study. Schmeer et al. (2019) conducted research using a large sample size, which increases the statistical power. Family contexts— the independent variables— were defined in terms of the following indicators, inter alia: Family structure such as single-parent vs. family type (especially two-parent households), socioeconomic status, and family stress. These were established using valid tools, setting up clear contrasts that may have possibly boosted the degree of power. Sample selection bias was minimized through strict inclusion criteria, while multivariate analyses to control for confounding variables, including age, gender, and ethnicity, helped increase accuracy. The synthesis of the variable’s definition and measurement provides strong evidence of statistical conclusion validity, according to Polit and Beck (2021).

Intervention Fidelity

Intervention fidelity is defined as the extent to which an intervention is delivered in the manner intended. This includes ascertaining that the intervention is standardized and that all the participants are treated similarly (van der Laan et al., 2019). Since the study is merely observational, the process must be standardized to achieve consistency in the data collected. Under the section on Methodology, they indicate that they used standardized and validated survey instruments in an attempt to minimize measurement error (Schmeer et al., 2019). However, the article does not present details about the training of the staff involved in data collection or the monitoring of the processes of data collection, which may cause variability. It is essential to make sure that all the researchers and data collectors adhere to these processes so that the study is both faithful and accurate (van der Laan et al., 2019).

Selection Bias and Control of Confounding Variables

Selection bias occurs when the participants selected for a study do not represent the target population. Controlling confounding variables involves adjusting for factors that could influence the outcome (Millard et al., 2022). The study adopted a cross-sectional research design that engaged representative samples of adolescents, reducing selection bias (Schmeer et al. March 2019). The lack of comparability between groups may be a limitation of this paper. However, the authors used multivariate analyses to reduce several confounding factors. This appears sufficient; however, deeper elucidations of how subjects were sampled to further eliminate selection bias could prove useful, especially in the report.

Internal Validity

Internal validity is the extent to which a study can establish a causal relationship between variables (van der Laan et al., 2019). Schmeer et al. (2019) addressed several threats to internal validity. The longitudinal design helped mitigate maturation effects by tracking changes over time. The researchers also accounted for attrition by using statistical methods to handle missing data, though more detail on attrition rates and handling would be beneficial. They did not extensively cover potential historical effects, where external events might influence sleep patterns. Despite minor concerns, the internal validity appears strong due to the robust methodological framework and controls (Polit & Beck, 2021).

Construct Validity

Construct validity refers to how well a test measures the concept it intends to measure (Clark & Watson, 2019). The study conceptualizes family contexts and their impact on adolescent sleep. The measures of family structure, SES, and family stress align well with the theoretical framework. Potential threats to construct validity could arise if the measures don’t fully capture the constructs or if participants interpret survey questions differently. Ensuring that instruments are valid and reliable across diverse populations is crucial (Schmeer et al., 2019).

External Validity

External validity refers to the extent to which study findings can be generalized to other settings, populations, and times (Lesko et al., 2020). Schmeer et al. (2019) provide a detailed context for their study, which enhances its external validity. The diverse sample, including various family structures and socioeconomic backgrounds, supports generalizability to a broader adolescent population. A weakness of the study is that it relies on self-reported data from respondents, which may be prone to social desirability biases. The use of variables such as actigraphy in future studies can enhance external credibility (Schmeer et al., 2019).

Balance of Validity Concerns

Managing validity includes identifying the threats of validity (internal, external, construct, and statistical conclusion validity) while not overemphasizing one aspect to the extent of undermining the others (Lesko et al., 2020). Schmeer et al. (2019) were successful in addressing various types of validity concerns in a good manner. To achieve internal validity, they used strict controls and a large sample size for the study. There are minor threats to construct and external validity, but they do not compromise the study’s solidity to a large extent. Concern for statistical controls and the sample population shows that the study is thorough in its quest for validity. For future studies, more efforts could be made to explore history effects and offer additional fundamental training and screenings for data gathering to boost fidelity (Schmeer et al., 2019).

Conclusion

In their systematic review, Schmeer et al. (2019) provide significant information about family contextual factors regarding adolescents’ sleep. The argument for the generalizability of the study’s findings is that it had high statistical power that minimized errors, provided clear and explicit definitions of the variables under investigation, and was attentive to potential confounding variables. These include minor threats to the construct and external validity of the study. However, they can be overshadowed by the study’s major assets. Future research may improve the validity of history effects and methods of gathering data and including other sleep observation measures. All in all, it offers a great addition to the understanding of the family context and its influence on health-related outcomes among adolescents within the framework of various validity considerations.

References

Clark, L. A., & Watson, D. (2019). Constructing validity: New Developments in Creating Objective Measuring Instruments. Psychological Assessment, 31(12), 1412–1427. https://doi.org/10.1037/pas0000626

Lesko, C. R., Ackerman, B., Webster-Clark, M., & Edwards, J. K. (2020). Target Validity: Bringing Treatment of External Validity in Line with Internal Validity. Current Epidemiology Reports, 7(3), 117–124. https://doi.org/10.1007/s40471-020-00239-0

Millard, L. A. C., Fernández-Sanlés, A., Carter, A. R., Hughes, R. A., Tilling, K., Morris, T. P., Major-Smith, D., Griffith, G. J., Clayton, G. L., Kawabata, E., Davey Smith, G., Lawlor, D. A., & Borges, M. C. (2022). Exploring The Impact of Selection Bias In Observational Studies of COVID-19: A Simulation Study. International Journal of Epidemiology, 52(1), dyac221. https://doi.org/10.1093/ije/dyac221

van der Laan, D. M., Langendoen-Gort, M., Nijpels, G., Boons, C. C. L. M., Elders, P. J. M., & Hugtenburg, J. G. (2019). Implementation fidelity of an intervention program to enhance adherence to antihypertensive medication in Dutch community pharmacies. International Journal of Clinical Pharmacy, 41(4), 1031–1046. https://doi.org/10.1007/s11096-019-00845-z

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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. 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.

Critical Analysis of a Quantitative Study- Design and Validity Evaluation

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.