Community Recreation & Education: Practical Implementation


This report is a clinical search assignment for a PICOT question, which is premised on investigating whether the application or use of community recreation exercises/activities compares to educational campaigns or reduces the risk for health conditions, such as diabetes, stroke, cancer, and hypertension, within two years. The PICOT question also focuses on examining the above issues for obese and overweight adults between 18 and 40 years.

This paper indicates the results of a systematic review of research materials which was aimed at finding a study that offered a practical application for implementing the PICOT idea. In other words, the systematic review helped in identifying evidence-based research that would be pivotal in undertaking the PICOT investigation.

In the first part of this paper, the processes followed in undertaking the systematic review are identified and analyzed. A general overview of the error analysis is also outlined in this segment of the paper to describe the procedures undertaken by the researcher to safeguard the integrity of the search process. The second part of this paper provides a summary of the study selected. In this section, key details describing how the authors of the evidence-based quantitative article undertook their study are outlined.

The details describing the procedures adopted in the investigation, including the sample size, research approach, and population studied, are also explained in this part as well. The third section of this paper provides a detailed analysis of how the evidence gathered from the selected research is applicable to the current (PICOT) investigation.

Comparatively, the outcomes that identify the validity and reliability of findings are explained in the fourth section of the paper, and they explain the procedures undertaken by the researchers to safeguard the integrity of their investigation. The fifth section of this paper explores the possibility of bias in the selected study, while the sixth segment explains the level of evidence of the findings presented in the review. The last section of the report summarizes the main findings of this paper. The first part, which is a systematic review and error analysis, appears below.

Systematic Review and Error Analysis

The systematic review of the investigation was undertaken by using the keywords: “education,” “obesity,” and “exercising.” These words were used to search for articles in the PubMed and the Cochrane databases. Collectively, the two online libraries generated 43 articles. None of the materials from Cochrane were directly related to the central focus of the study, which was understanding the application or use of community recreation exercises and educational campaigns in obesity management.

Alternatively, some of the articles from this database were excluded from the final results because they did not link aspects of education or health coaching with recreation exercises. Comparatively, 12 articles generated from PubMed met this criterion. More importantly, they attempted to draw a link between exercising, health coaching, and the reduction of obesity-related risk factors, such as stroke, cancer, diabetes, and hypertension.

These articles were further narrowed down to those that were randomized. Three articles met this criterion. Additionally, a systematic review process further narrowed down the search process to one article, which was quantitative in nature. Consequently, the other two research studies were excluded from the review because they either had a mixed methods research design or were qualitative in nature. Based on these processes, the exclusion criteria were defined by the nature of the study (randomized or not) and the research design.

As part of the error analysis, an emphasis was made to only include studies from the two reputable databases mentioned above. They are health-based sources of data and are either focused on nursing or public health management. The selected articles for review were also peer-reviewed and contained a detailed discussion of the measures taken by the researchers to safeguard their reliability and credibility. The chosen article that emerged from this review was titled “Frontline Experiences of a Practice Redesign to Improve Self-Management of Obesity in Safety Net Clinics,” and it was written by AuYoung, Duru, Ponce, Mangione, and Rodriguez (2015).

The study’s findings had a confidence level of 95%. This means that the standard margin of error was +/-5%. The same percentages represent both the sampling and non-sampling errors. However, since an approximate confidence level was used, the calculations only took into account the random sampling error. Therefore, the potential sources of bias error are not included in this error analysis. In other words, it is difficult to establish the non-representative sampling design or to quantify the possibility that some of the questions asked were poorly phrased. A summary of the case study is provided below.

Summary of the Case Study Selected

The selected study was undertaken with the aim of understanding the facilitating and limiting factors of self-management obesity. The study was contextualized in three safety-net clinics. The researchers consulted physicians and medical assistants in an attempt to understand their experiences when helping to improve obesity management in primary care settings (AuYoung et al., 2015). The study strived to understand some of the barriers involved in undertaking a “team” approach to managing the condition. The sample population comprised 21 respondents whose views were recruited through interviews and 393 people who gave their opinions about the research topic through patient surveys (AuYoung et al., 2015).

The assessment was done in two phases. The first one was completed during the early implementation of the practice stage, while the second one was undertaken after six months (AuYoung et al., 2015). The 21 respondents who were interviewed in the research were nurses who worked in the three clinics. Before the survey was done, patient groups were analyzed to ascertain their demographic differences and health behaviors (AuYoung et al., 2015). The results of the investigation helped to ascertain the next steps that were taken in the data collection process.

The patient surveys that involved 393 randomized participants investigated obese patient activation and health statuses (AuYoung et al., 2015). The results of the investigation showed that insufficient resources and patient engagement processes influenced the effectiveness of the health practitioners to formulate and implement interventions that helped reduce obesity (AuYoung et al., 2015). This result was observed despite the existence of fairly high patient activation levels.

The recommendations provided by AuYoung et al. (2015) centered on the need to provide staff with adequate time and resources to execute new responsibilities that would support the management of obesity. It was also established that the involvement of multiple supporters might improve the sustainability levels of health programs (AuYoung et al., 2015).

Application of Evidence to Practice

The findings of the selected article are instrumental to the current practice because they outline the main issues that affect the implementation of obesity management techniques. They also provide a guideline that explains what needs to be done to improve the efficacy of obesity management programs. At the core of the findings are the opportunity to analyze the effectiveness of education programs and exercising (or similar physical activities) in obesity management, as proposed by Dejonghe, Becker, Froboese, and Schaller (2017).

These insights provide the link between the article and the PICOT question because the latter strives to find out how the application (or use) of community recreation exercises/activities compare to educational campaigns focusing on lifestyle changes or reduce the risk of health conditions, such as diabetes, stroke, cancer, and hypertension, within two years.

The selected study also explains the difficulty that health practitioners encounter in integrating educational programs into the lives of people who are suffering from obesity. In other words, as alluded to in the work of Kuhn, Page, Ward, and Worrall-Carter (2014), health assistants are experiencing difficulties integrating health coaching responsibilities into the routine practices of selected patient groups.

Based on some of the limitations of current health interventions, AuYoung et al. (2015) propose the need to look for new ways of formulating more effective interventions to manage obesity. This link shows a close relationship between the study’s findings and the PICOT questions because both of them acknowledge the need to establish the most effective ways of improving obesity management through health coaching and other techniques. The chosen article also helps in meeting this goal by proposing effective ways of sustaining health programs for managing obesity by involving all levels of health staff in the process.

Therefore, the pieces of evidence gathered from the selected article are applicable to the PICOT question because they strive to evaluate the best approaches to improving the management of obesity. They also help to indicate which approach is the best in formulating the most effective interventions. More importantly, the evidence selected from the chosen study is instrumental in understanding which intervention has the highest efficacy because it focuses on the self-management of obesity (AuYoung et al., 2015).

The PICOT question is also hinged on the self-management of obesity because education and exercising are both common practices that health practitioners hope to instill in affected persons to improve their general health outcomes even when there is no one around (Kuhn et al., 2014). Determining the best technique to use in preventing obesity is pivotal in understanding which of the two (education or exercising) could have the most impactful outcomes.

Additionally, the evidence provided in the selected study is important in helping health practitioners to understand the social, economic, and political factors that influence the occurrence of health risk factors, such as cardiovascular diseases, diabetes, and stroke, which are linked with obesity (Kuhn et al., 2014).

More importantly, the evidence obtained from the selected study is instrumental in clarifying the roles of physicians and healthcare service providers in instituting behavior change among people who have a high risk of obesity. In this regard, it is easier to understand the boundaries of healthcare service providers in creating behavior change and how targeted individuals need to adopt better self-management techniques to improve their health outcomes. Collectively, this analysis is instrumental in answering the PICOT research question.

Outcomes Identifying Validity and Reliability of Findings

It is important to establish the reliability and validity of findings in research studies because it is the easiest way of making sure that the information generated is applicable to different health contexts. To safeguard the quality of information obtained from the respondents, AuYoung et al. (2015) sought the approval of the Institutional Review Board (IRB). The patient survey and interview results were communicated to the participating clinics to improve the validity of the findings as well (AuYoung et al., 2015).

Indeed, according to AuYoung et al. (2015), this approach was adopted to improve face validity. The procedure was also employed to help develop recommendations that would further enhance the quality of information generated. One limitation acknowledged by the researchers was that the views presented in the article did not represent the opinions of all healthcare service providers or obese people (AuYoung et al., 2015). They also point out that the random selection of participants in the study was strategically made to eliminate any bias that could emerge from the possibility of the interviewer or researcher only obtaining the opinions of those who wanted to participate in the study (AuYoung et al., 2015).

Follow-up interviews were also done by the researchers to make sure that the information presented in the final paper represented the views of those who gave them. Instances of deviation were corrected by giving preference to the opinions of the respondents over those derived from an interpretation of the same (AuYoung et al., 2015). Collectively, these steps were aimed at improving the quality of information obtained from the study because they centered on ensuring the data obtained were reliable, credible, and valid.

Possibility of Bias

According to Payne and Steakley (2015), it is naïve for researchers to think that bias cannot affect their research findings. Here, bias refers to the prejudiced consideration of a question. To avoid these types of errors, researchers are often advised to avoid the “human influence” in research (Payne & Steakley, 2015). The selected study has some possibilities of bias because the researchers do not explain how they addressed specific areas of vulnerability in the formulation of their findings.

For example, there is a possibility of respondent bias which could have manifested through acquiescence. This issue is characterized by the tendency of some respondents to aimlessly agree with the researcher. Respondents who are prone to this kind of error often agree with ideas proposed by researchers and often do so when they are lazy to interrogate what the interviewers are asking them to answer (Payne & Steakley, 2015). More than 20 interviews were conducted in the selected paper. Some of them could have contained this bias. More importantly, there is no indication that the researchers took extra care to prevent its occurrence.

There is also a possibility that habituation bias occurred in the study. It exists when respondents tend to give standard views in a study (usually to “fit in”) (Payne & Steakley, 2015). The standardization of responses could occur because of a similar wording of questions or the possibility that some respondents could be fatigued from questioning. The selected study involved two phases of questioning.

The possibility of habitual bias occurring could be higher in the second phase of interrogation because some respondents could feel fatigued from the first interview. Additionally, some of them could provide similar responses based on the location of the clinics sampled. Generally, there were three health centers studied. The views given by the three centers could have shown similar patterns of responses because of the habitual bias discussed above. AuYoung et al. (2015) do not explain how they accounted for such an error in the study. Therefore, it is likely to have occurred.

The possibility of confirmation bias occurring in the study is also high. It happens when researchers have already formulated a hypothesis about the study and only use the respondents’ views to support them (Payne & Steakley, 2015). At the same time, they may be inclined to dismiss data that do not align with their hypothesis. Mackey and Bassendowski (2017) say this type of bias is one of the most pervasive and widespread because it affects the data collection and analysis processes. Managing this kind of bias requires researchers to keep monitoring the responses of the participants and challenge preconceived ideas or hypotheses about the research topic.

However, AuYoung et al. (2015) do not explain how such an error was managed or prevented in the study, despite the possibility of its existence. Combined with habitual and confirmation bias, the three types of issues highlighted in this paper explain the possible types of challenges that could have affected the research process. More importantly, they cover the possible types of biases that could occur from the participant and interviewer’s points of view.

Level of Evidence in the Review

Ascertaining the level of evidence in clinical research trials is an important process in finding high-quality data for use in clinical decisions. A critical component of evidence-based medicine is ascertaining the level of evidence gathered. The levels of evidence in clinical trials are determined by the strength of information collected in the studies. The data associated with the selected article is level I because the study was based on a high-quality randomized trial. The information collected was also gathered from multiple studies (interviews and surveys) and with multiple sensitivity analyses (AuYoung et al., 2015).

Additionally, the systematic reviews of evidence gathered in the study exhibited the homogeneity of randomized controlled trials commonly associated with Level I evidence (Mackey & Bassendowski 2017). The implications of having level I data on the research process hinges on the need for clinicians to use the strongest evidence unless there is a clear and compelling reason why this recommendation should not be adopted.


Based on the findings of this study, the chosen research article is applicable to the PICOT research question because it provides an overview of the main implementation issues for managing obesity as a public health issue. More importantly, it provides the context and understanding of the roles and responsibilities of health practitioners and the target audience in health management. Concisely, the self-management approach explained in the study is pivotal in reviewing the efficacy of the PICOT question because it provides a practical application for the implementation of the idea, which is to find out whether education plays a more effective role in preventing obesity, compared to exercising and community recreation activities.

The focus on other health issues, such as stroke and diabetes, in the selected study also draws a strong link with the PICOT question because it similarly centers on the reduction of risk for conditions, such as diabetes, stroke, cancer, and hypertension. Thus the evidence gathered from the article could be instrumental in implementing the PICOT idea.


AuYoung, M., Duru, O. K., Ponce, N. A., Mangione, C. M., & Rodriguez, H. P. (2015). Frontline experiences of a practice redesign to improve self-management of obesity in safety net clinics. The Journal of Ambulatory Care Management, 38(2), 153–163. Web.

Dejonghe, L. A., Becker, J., Froboese, I., & Schaller, A. (2017). Long-term effectiveness of health coaching in rehabilitation and prevention: A systematic review. Patient Education and Counseling, 100(9), 1643-1653. Web.

Kuhn, L., Page, K., Ward, J., & Worrall-Carter, L. (2014). The process and utility of classification and regression tree methodology in nursing research. Journal of Advanced Nursing, 70(6), 1276–1286.

Mackey, A., & Bassendowski, S. (2017). The history and evidence-based practice in nursing education and practice. Journal of Professional Nursing, 33(1), 51-55. Web.

Payne, R., & Steakley, B. (2015). Establishing a primary nursing model of care. Nursing Management, 46(12), 11-13. Web.