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Some key points to evaluate the quality of each study (using MMAT) got my attention. Divergences and inconsistencies between findings by different methods are generally not addressed nor explained. The studies also didn't mention explicitly the risk of non-response bias (noncontacts, refusals or reasons).

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For the interviews, the description of size and inclusion criteria are clearly justified(eligibility). Moreover, they are conscious that they work with a small subsample of participants from a larger cohort study, stating that their findings should not be generalized to other populations.

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Great way to integrate methods at three stages: data collection, data analysis and interpretation. Both methods complement each other. For example, the qualitative methods provide information about individuals who are missing from networks identified in the quantitative approach.

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In the qualitative study, the data saturation justification is a little bit random (n=40, how to know? This is always a tricky question for me in qualitative studies).

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As a protocol it is great, with an adecuate rationale for the use of mixed methods and gives a well documented details for qualitative and quantitative methods. For example, I really like Table 1 where objectives are linked with data sources, analysis and goals. However, it is difficult to critically evaluate the full quality of the work as they don't show results and interpretation.

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Wagner et al (2018) present data in a meaningful way using the quantitative network information and quotes from interviews, representing appropriate integration of data for a mixed methods approach

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Wagner et al (2018) present data in a meaningful way using the quantitative network information and quotes from interviews, representing appropriate integration of data for a mixed methods approach

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Present a simple and informative chart to display the mixed methods approach and how this will be integrated for analysis (p440)

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Complicated and difficult to follow statistical analysis section. Also, some further justification of not enrolling patients into both the qualitative and quantitative portions would be helpful

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Appropriate rationale and justification for using a mixed methods design to explore perceptions by black patients and use statistical analysis to compare these to outcomes

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On page 2, Figure 1 foregrounds a useful conceptual model portraying findings from previous research with respect to physician implicit racial bias impacting PO.
On page 3, Figure 2 displays a helpful overview of the explorary sequential mm design. Jo

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Wagner et al. portray  useful insights regarding FSWs/health risks displaying a convergent mm approach. Jo

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Wagner et al. portray  useful insights regarding FSWs/health risks displaying a convergent mm approach. Jo

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Hagiwara et a. offer a very interesting protocol with an exploratory sequential approach. However the methodological choice ( e.g. epistemology & chosen mm paradigm) are downplayed & would benefit from more weighting. Jo

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Hagiwara et a. offer a very interesting protocol with an exploratory sequential approach. However the methodological choice ( e.g. epistemology & chosen mm paradigm) are downplayed & would benefit from more weighting. Jo