Community Interventions for Public Health

Introduction

Research studies should withstand criticism. The paucity of research information is evident on the impact of clinicians on dietary intake and physical activity improvement, and tobacco use reduction using community intervention methods. Anthony et al. (2016) conducted a study titled “Community Interventions for Health Can Support Clinicians in Advising Patients to Reduce Tobacco Use, Improve Dietary Intake, and Increase Physical Activity.” This research paper critiques the study that was published in the Journal of Clinical Nursing.

Study Problem, Purpose, Hypotheses, and Variables

The study’s purpose and problem are clearly stipulated. From the thorough review of the literature, non-communicable diseases (NCDs) account for most of the global deaths and are more present in both low and middle-income economies (Lozano et al., 2012). Clinicians and their patients can modify the risks of these diseases. The reviewed sources are recent, pertinent to the study, and provided relevant and concise information. Anthony et al. (2016) found that few studies had evaluated the impact of clinicians on the reduction of these risks. Their purpose was to address this problem by carrying out a study to increase the use of interventions to reduce the modifiable risks in low and middle-income countries.

The hypotheses of this study are stated and explained in detail. Anthony and the colleagues hypothesized that community interventions increase clinician preparedness to advise patients on tobacco use cessation, and improvement in dietary intake and physical activity. Independent variables comprise of community interventions like individual and group counseling, self-help materials, and medications (Anthony et al., 2016). The dependent variables are dietary intake, physical activity, and smoking cessation, all of which have a direct relationship with the independent relationship. Therefore, the study explicitly stated and defined both the dependent and independent variables, including their relationship.

Methods

Design

This original community-based nonrandomized control study clearly explains that it utilized a non-experimental control design. The study comprised of the control and intervention groups that completed the surveys (Anthony et al., 2016). However, the full methodology of the Community Interventions for Health programs (CIH) was reported by Duffany et al. (2011). Therefore, the study does not clearly explain the full methodology but refers to another study for more information.

Study Sample and Participants

The study sample and the data collection process are clearly explained. The study was conducted in Kerala in India, Hangzhou city in China, and the Mexico City in settings including health centers, workplaces, schools, and the community (Anthony et al., 2016). Participants comprised of doctors, nurses, and many other allied health professionals. These participants were protected from harm when researchers followed appropriate ethical procedures, including the study approval from relevant institutional review boards in each of the three countries. The authors failed to explain the inclusion and exclusion criteria comprehensively. However, they assert that the specific sampling procedures were given in studies conducted by Anthony et al. (2015) and Dyson et al. (2015). Therefore, the article provides inadequate information on the study sample and the sampling procedure with more detail referred to in previous studies.

Study Reliability and Control of Extraneous Variables

The article conspicuously explains the study’s validity and reliability. The survey that was based on previously validated questionnaires was designed by a development team represented by the three study sites and external consultants (Anthony et al., 2016). Evaluation Coordination Center experts and those from the study sites adapted and translated the surveys. Anthony et al. (2015) further explain that researchers conducted field tests in 2008, between May and June, before making minor revisions. All these improved validity and reliability of the data collection tools. Variables were controlled through the use of control and intervention groups. The two groups were of the same size within the same industry, with participants between the age of 18 and 64 years of age (Anthony et al., 2015). The groups were also independent of each other with similar risks for NCDs during the baseline.

Data Analysis

The article comprehensively explains how data was analyzed. Logistic regression was used in determining the differences between the two groups and time periods, allowing for differences in the baseline of risk factors (Anthony et al., 2016). A difference in difference approach used was similar to that employed by Vanderos et al. (2013) in determining the impact of interventions. Covariates were gender, type of site, and the occupational group.

Results of the Study

The study results supported the research purpose, literature findings, and the study hypotheses. Clinicianns from the intervention group felt more prepared to provide diet and physical activity improvement, and smoking cessation advice than their colleagues in the control group (Anthony et al., 2016). Furthermore, they were less likely than their control group colleagues to take skinfold thickness, hip, height, and waist measurements but more likely to take blood pressure and test blood cholesterol. More resources were available to intervention group clinicians who used complementary medicine less and counseling more than their colleagues in the control group.

Study Implications and Limitations

The article has a section describing the limitations and research implications. The results were acquired from self-reported responses, which is associated with inaccuracies in data recording. The study findings implicate health professional practice in curbing NCDs by reducing the modifiable risks. Clinicians should use the recommended community intervention methods like the CIH program to improve dietary intake, physical activity, and reduce tobacco use in the community. As a result of the benefits of community interventions, I can personally use information from this article in practice.

References

Anthony, D., Dyson, P. A., Lv, J., Thankappan, K. R., Champgane, B., & Matthews, D. R. (2016). Community Interventions for Health can support clinicians in advising patients to reduce tobacco use, improve dietary intake and increase physical activity. Journal of Clinical Nursing, 25(21-22), 3167-3175.

Anthony, D., Dyson, P. A., Lv, J., Thankappan, K. R., Fernández, M. T., & Matthews, D. R. (2015). Reducing health risk factors in workplaces of low and middle‐income countries. Public Health Nursing, 32(5), 478-487.

Duffany, K. O. C., Finegood, D. T., Matthews, D., McKee, M., Narayan, K. V., Puska, P.,… & Yach, D. (2011). Community Interventions for Health (CIH): A novel approach to tackling the worldwide epidemic of chronic diseases. CVD Prevention and Control, 6(2), 47-56.

Dyson, P. A., Anthony, D., Fenton, B., Stevens, D. E., Champagne, B., Li, L. M.,… & the Community Interventions for Health (CIH) collaboration (2015). Successful up-scaled population interventions to reduce risk factors for non-communicable disease in adults: Results from the International Community Interventions for Health (CIH) Project in China, India, and Mexico. PloS One, 10(4), e0120941.

Lozano, R., Naghavi, M., Foreman, K., Lim, S., Shibuya, K., Aboyans, V.,… & AlMazroa, M. A. (2012). Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: A systematic analysis for the Global Burden of Disease Study 2010. The Lancet, 380(9859), 2095-2128.

Vandoros, S., Hessel, P., Leone, T., & Avendano, M. (2013). Have health trends worsened in Greece as a result of the financial crisis? A quasi-experimental approach. The European Journal of Public Health, 23, 727–731.

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