Article critique
Below is a critique of a research done to determine factors influencing patient completion of diabetes self-management education. A number of researchers under Care Innovations conducted the research. They aimed at achieving high participation rates in research trials of self-management education.
Method
Research design
A study context method was used evaluate diabetes outcomes where researchers used excising records from two healthcare systems. All those people diagnosed with type 2 diabetes received mailed letters requesting them to participate in the research. Since the purpose of the research was to achieve a high participation rate in research trials, the following design was not 100% effective. Only 82% of people who met the eligibility criteria responded. Alternatively, the researcher would have made an advertisement on social media so that anyone who could be interested could take part in the research. Interpretability of the findings did receive appropriate comparisons. The researchers did not compare the outcomes with those of similar studies because it was realized that screening instruments would have performed a better function.
On the other hand, limited numbers of clinics were used as data collection points. These limited the outcome of group sessions that required different data collection points in order to determine the effect of healthcare center on patient’s completion of diabetes self-managed education. In addition, there was less flexibility in scheduling various sessions because of the limited number of data collection centers, which affected the validity of the results. Biasness is an element that affects the outcome of most studies. In the following research, participants were given a small token of $50 for accepting to take part in the research, but they were not issued with incentives. The small appreciation given to participants helped in improving the validity of the research, but lack of incentives questioned the reliability of data collected (Adams et al, 2013).
Population and sample
623 participants took place in the research although the researchers failed to establish their gender. The method used in selecting samples for different study arms was not given. This led to an error in assigning the sample for each group because they totaled to 622 and not 623 (243+245+134=622). The random assignment could have ensured each study arm get an equal number of participants in order to ensure uniformity. The sampling procedure used represented some type of sample biases because one study arm received almost half the number of participants compared to other two. It was not clear the analysis method used to determine the sample size. A useful sample should be large enough to allow generalization and should be above 10% of the total population. The power analysis method was used to determine the sample size although the sample was less than 10% of the number of people mailed (i.e. 10% of 9,971 mailed participants=997).
Data collection and measurement
The data collection tools chosen by a researcher should be able to achieve the research objectives. Baseline surveys based on demographics, behavioral and psychological measures was used as the main method of data collection. The collection method aimed at measuring the key variables of the research, although other data collection methods such as observation and interviews were ignored that could have given results that are more precise. In addition, researchers used self-administered questionnaires on patients to diagnose depression and its effects. Low scores were obtained from questionnaires because patients were not observed as they answered them that gave room for participants to leave some questions unanswered (Adams et al, 2013).
On the other hand, the researchers only gave a highlight of the specific instruments without providing a deep description of how they were selected and their benefits over other instruments. The selected instruments formed the best choice for a research. For instance, surveys are important in any research because they involve an interaction between the researcher and the participant. Since the purpose of the study was achieve high participation, the data collection instruments used did not represent in full the intended purpose of the research.
Reliability and validity are essential in any research. Reliability is a measure of the degree to which research instruments yield consistent results after a repeated number of trials. Validity is the extent to which a test measures what the researcher wished to achieve. The data collection method used was not 100% valid or reliable. Researchers could have used test-retest technique to access the reliability of the research. In addition, some data collected was not reliable because participants never received enough tutorials on how to use some complicated instruments. Some participants indicated some confusion at some instances when asked the type of education they were engaged in (Adams et al, 2013).
Procedures
The data collection procedure used in any research depicts the strength of results obtained. There was an intervention in data collection procedures, but researchers did not give a full analysis of its implementation. There were instances where some participants failed to attend interventions and their regarded as non-starters. In addition, most participants allocated to intervention groups did not receive all the information required because the procedures were contradicting with what was being intervened. Moreover, the people who were involved in data collection were well trained to handle different diabetes cases. The only problem with the procedure used was that less amount of time was allocated for education programs giving the staff inadequate time to evaluate the participants (Adams et al, 2013).
Result
Data analysis
Descriptive statistical method was used for data analysis. The main elements of descriptive statistics used were proportions, standard deviation, and means. Significance of 0.05 was used to evaluate independent variables. In addition, multiple logistic regression method was used in determining the probabilities. The study used the most effective data analysis tools however; the researchers did not make use of a control experiment. Multiple linear regressions was used in determining continuous variables mean differences instead of using the t-test to determine the effectiveness of the research hypotheses. Moreover, the research did not cater for type I and type II errors because most of the results were biased as the sample size selected did not represent fully the whole population (Adams et al, 2013).
Findings
Results indicated that some participants did not attend any of the three sessions and these contributed to the number of errors made. 40 participants did not participate in any session showing the researchers did not make adequate preparations for the study. The significance of statistics in the study was represented, but some important statistical tools were ignored in result analysis. The amount of the confidence interval achieved was not a representation of the sample size because of poor participant preparation methods (Adams et al, 2013).
Summary assessment
The research achieved its objectives but it was faced by many limitations. The value of the results could be an 80% true because various factors influencing patient completion of self-management education were realized. The research findings provide meaningful evidence that can be utilized in nursing practice. Some of the recommendations given at the end of the research would assist future researchers in developing a perfect study on the same topic.
References
Adams, F. K. et al. (2013). “Factors Influencing Patient completion of Diabetes Self-Management Education”, Diabetes spectrum, 26 (1), 40-45
