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The sampling utilized in this article is the non-probability, convenience sampling strategy (Kleier, 2014). The research being done is specific to African Americans with diabetes mellitus, and a strength of this type of sampling is that the group of individuals participating is a reflection of the specific research being done. Additional strengths associated with convenience sampling is the cost and effort reduction for the researchers (Brown, 2018). The non-probability convenience group sampled for this study is the best group for researchers to identify the behaviors or self-care for African American clients with diabetes mellitus. A power analysis was completed to identify a sample size of 100 (Kleier, 2014).

Weaknesses associated with this type of study are best described in the photo provided in the lecture, where the convenience sample identifies who is in the study, but due to the convenience of the sample, members of the population are missed (Brown, 2018). Bias reduction methods are identified, which include the Diabetes Attitude Scale, Diabetes Empowerment Scale, the Summary of Diabetes Self-Care Activities, and the Hemoglobin A1C (Kleier, 2014). Despite the use of the bias reduction methods, the research conducted still had a significantly larger population of women participating in the study, 73% of the sample is women compared to 27% being men (Kleier, 2014). This is not an accurate sample based on diabetes rates in Florida, although statistically African American women have more diabetes diagnoses than African American men, the differences are not as significant as the 73% compared to 27% (CDC, 2016).  Based on where the sampling occurred, shopping centers, grocery stores, and churches, that is a possible causation of why the sample size included so many more female participants (Kleier, 2014). In addition to these locations, they may have also sampled more participants in bars, restaurants, and sports events. In addition, the inclusion and exclusion criteria, outside of the A1C, relied on self report, including body weight. Personally, not research article related, I will always say I weigh less than my actual weight. I imagine the weight data collection is possibly inaccurate from the large sample size of women. The results of this study ended up being inconclusive, however it did identify weaknesses in the healthcare system associated with diabetes and proper patient education (Kleier, 2014).

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According to Kleier, the sampling strategy used in this study was a non random, convenience sampling strategy to gather African-American adults with diabetes. Convenience sampling, as a specific non-random method, is not generalizable to the larger target population due to the risk of sampling bias. Strict inclusion or exclusion criteria may be used to reduce convenience, and in this study, participants that consented were expected to complete survey instruments (which asked demographic questions) and provide blood for A1C testing, in order to meet the inclusion criteria. The recruitment of volunteers took place in locations in South Florida where African Americans were highly populated, so places like stores and churches. As stated in the article, the location of recruitment is a limitation because the cultural and educational experience of African Americans that migrated from the Caribbeans may be different from African Americans that are more culturally diverse. In addition, there were 100 participants used in this study, and power analysis was used in order to determine 100 as the minimum sample size needed. Overall, the fact that power analysis was used in this study is a strength, and the sampling method used might have been a weakness despite the attempt to reduce bias. Since the study was targeting the entire African American population, perhaps a random, stratified sampling method would have been more appropriate so that the majority of participants wouldn't be females.

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