Type of Inquiry
The research study conducted by Guo et al. (2015) is an example of a quantitative inquiry. This categorization is validated by such characteristics of the study as the use of numerical data for analysis and conclusion and the statement of a hypothesis for dismissal or approval by the study findings. Moreover, the researchers collected data using quantitative methods and interpreted the analysis results based on the relationships between variables to find the statistical significance of variables’ dependence.
The Purpose of the Study
The purpose of the conducted research was to measure the influence of the Positive Action program for schools on the improvement of behavior in rural low-income student residents of rural North Carolina. Since such a population is prone to risky behaviors, the study sought to evaluate the effectiveness of the program from a long-term perspective (Guo et al., 2015). In particular, the changes in students’ self-esteem, level of aggression, and internalization were measured.
Sample Description
The sample of the study was selected using probability sampling. In total, 4000 students from rural middle schools were included in the sample, representing two counties, namely intervention county, and comparison county; the ultimate number of participants providing complete data was 1246. The demographic characteristics of the sample included 52% of female and 48% of male participants aged from 9 to 20 years. It was a racially diverse sample with “27 % White, 23 % African American, 12 % mixed race/other, 8 % Latino, and 30 % American Indian” (Guo et al., 2015, p. 2337). The participants were selected intentionally to ensure equal representation in a number of students in each of the two counties.
Research Design
The research design selected for the study was quantitative analysis. It used a quasi-experimental design to compare the behavior of students exposed to the Positive Action program with the behavior of those without the program (Guo et al., 2015). In particular, the researchers used the longitudinal study to measure the data as it changed over the time of three years. The use of quasi-experiment allowed for obtaining a sufficient level of control over the study procedures while maintaining the realistic implementation of the evaluated program.
Data Collection Method
Guo et al. (2015) used quantitative methods of data collection to retrieve necessary information for their variables. The data was collected using surveys to elicit changes in behavior and attitudes. Students were given the School Success Profile, which is a well-established online self-report survey consisting of 195 items “with 22 subscales that measure perceptions and attitudes about school, friends, family, neighborhood, self, health, and well-being” (Guo et al., 2015, p. 2343). The survey was modified to match the purpose of the research.
Data Analysis Method
The collected quantitative data were analyzed using statistical analysis. Guo et al. (2015) applied the “Neyman-Rubin counterfactual framework” to analyze the collected data and identify the correlation between the variables (p. 2347). Within the selected data analysis framework, two propensity score models were used to interpret the data about participants exposed to the program and then to compare them with those retrieved from the comparison group.
Results
The study results allowed for partial proving of the hypothesis on the positive effect of the Positive Action program on students’ aggression level, internalization, self-esteem, and school hassles. The study proved statistical significance of the positive effect of the intervention on self-esteem and school hassles. However, the internalization and aggression indicators’ dependence on the program were statistically insignificant, as evidenced by the analysis of the variables.
Opportunities for Further Research
The study provides a basis for substantial future research on the topic of youth’s risky behaviors at school and the correction of it using specifically designed programs. In particular, one of the possible ways of advancing the findings of the current research in further scholarly inquiry is by comparing the effectiveness of the program between rural and urban students. Moreover, future research on the topic might be conducted to investigate the correlation between family factors and exposure to the program for a better understanding of the influencers on students’ behavior improvement.
Threats
Given the limitations of the study, which include specially assigned counties for comparison and the hindered reliability of the findings of propensity scores, the research results might be characterized by some threats. For example, there is a threat to the internal validity of the findings since the outcomes of the research are applicable only to schools in rural North Carolina and school students aged 9-20 years. Thus, the study has minor drawbacks due to its scope and sample.
Criticism
Overall, the analyzed research study was conducted with precision and a rationally selected set of methods based on available previous research and evidence. The exclusion criteria were diligently addressed, and the choices of sampling, data collection, and data analysis methods were provided. Despite several limitations, the study has contributed to the academic literature on the topic of the minimization of risky behaviors in minors through specifically designed school-based programs.
Implications of the Findings
The theoretical findings of the study might have a practical meaning for the educational facilities in the United States and on a global scale. Since the findings indicated only partial effectiveness of the Positive Action program, decision-makers at a national level might use them to find ways for the improvement of the program. Moreover, educational authorities and facilities abroad might apply the findings to mitigate negative manifestations of risky behaviors in youth.
Reference
Guo, S., Wu, Q., Smokowski, P. R., Bacallao, M., Evans, C. B., & Cotter, K. L. (2015). A longitudinal evaluation of the positive action program in a low-income, racially diverse, rural county: Effects on self-esteem, school hassles, aggression, and internalizing symptoms. Journal of Youth and Adolescence, 44(12), 2337-2358.