Identify and discuss any threats to internal and/or external validity in this study

Comprehensive Article Review


Caverly, T.J., Fagerlin, A, & Wiener, R.S. (2018, January 22). Comparison of observed harms and expected mortality benefit for persons in the Veterans Health Affairs Lung Cancer Screening Demonstration Project. JAMA Internal Medicine.




1. What research questions are addressed in this study and what is their purpose (5 points)?


2. What type of research design was used (experimental, quasi-experimental, correlational) in this study and what led you to your decision (5 points)?


3. Are the instruments in this study valid and reliable, why or why not (10 points)?


4. Discuss the specific results of each of the ANCOVAs (analysis of covariance) done in this study. What was the purpose of”each” of the ANCOVAs? What was the covariate in each and why did they do an ANCOVA in each case (5 points)?


5. In the Tables, results are presented, Please explain the tables and summarize the results (15 points).


6. Explain, in simple language, any significant results of this study (25 points)?


7. Identify and discuss any threats to internal and/or external validity in this study (10 points).


8. If you could redesign this study correcting anything you have found wrong with the research, what would you correct and how would you do it (20 points)?




Risks of Lung Screening Seen Outweighing Benefits in Many with Smoking History Very high false-positive screening rate seen in Veterans Affairs study

Real-world findings from a Veterans Affairs (VA) population reinforce the need for personalized decision-making about lung cancer screening using validated risk-stratification models. Using the Bach risk tool for assessing lung cancer risk in veterans screened at eight academic VA centers (MSKCC, 2018), nearly 5,600 veterans in the lowest risk quintile needed to be screened to prevent one lung cancer death. Meanwhile, the number of false-positive cases per death averted was 2,221. See generally Caverly, Fagerlin, & Wiener, 2018.


Patients in the highest quintiles of lung cancer risk had significantly more lung cancers diagnosed supporting the model’s ability to stratify risk in this population. These findings, recently published in the Journal of the American Medical Association Internal Medicine (Caverly et al., 2018) bolster those from a VA screening trial published last March (Kinsinger et



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