The researchers acknowledged that sampling data from only one hospital and with a relatively small sample size of 250 patients were limitations of the study that could impact the generalizability and reliability of the results. To help address these limitations, the researchers took several steps in the design, data collection, and analysis phases of the project.

In the study design phase, the researchers chose the hospital purposely as it was a large, urban, academic medical center that served a racially, ethnically, and economically diverse patient population from both the local community as well as patient referrals from other areas. This helped make the sample more representative of the broader population beyond just the local community served by that single hospital. The researchers only included patients across all departments of the hospital rather than focusing on specific diagnosis or treatment areas to get a broad cross-section of overall hospital patients.

Regarding sample size, while 250 patients was not a massive sample, it was a sufficient size to conduct statistical analyses and identify meaningful trends according to power calculations conducted during the study design. Also, to supplement the quantitative survey data from patients, the researchers conducted in-depth qualitative interviews with 20 patients to gain deeper insights into experiences that larger-scale surveys alone may miss. Interviewing a subset of the sample allowed for a mixed-methods approach that provided richer contextual understanding to support the quantitative findings.

During data collection, the researchers took efforts to maximize the response rate and reduce non-response bias that are risks with smaller samples. For the patient surveys, research assistants were present on various hospital units at varying times of day to approach all eligible patients during their stays, rather than relying on mail-back surveys. Monetary incentives were also provided to encourage participation. The quantitative survey included demographic questions so the researchers could analyze response patterns and identify any subgroups that may have been underrepresented to help address missing data issues.

For analysis and reporting of results, the researchers were transparent about the limitations of sampling from a single site and small sample size. They did not overgeneralize or overstate the applicability of findings but rather framed results asexploratory and in need of replication. Statistical significance was set at a more stringent level of p<0.01 rather than the typical p<0.05 to increase confidence given the moderate sample. Qualitative interview data was used to provide context and nuanced explanation for quantitative results rather than being reported separately.

The researchers also performed several supplementary analytical tests to evaluate potential sampling bias. They compared their participant demographics to hospital patient demographics overall as an indicator of representativeness. Response patterns by demographic group were examined for non-response bias. They randomly split the sample in half and ran parallel analyses on each half to verify consistency of identified associations and trends, rather than assuming results would replicate with an independent sample. In their write-up and discussion of limitations, the researchers clearly acknowledged the constraints of the single-site setting and sample size. They argued their intentional sampling approach, mixed-methods design, response maximization efforts, more rigorous analysis, and supplementary tests provided meaningful initial insights with results that lay the necessary groundwork for future replication studies with larger, multi-site samples before making conclusive generalizations. The transparency around limitations and implications for applicability of findings model best practices for rigorously addressing challenges inherent to pilot and feasibility studies. Through careful attention in their methodology and analysis, the researchers took important steps to offset the acknowledged issues that could arise from their relatively small, single-site sample. Their comprehensive approach set the stage to begin exploring meaningful trends while also recognizing the need for future replication. The study provides an example of how initial feasibility research can be conducted and reported responsibly despite inherent sampling constraints.