What demographic variables were measured at the nominal level of measurement in the Oh et al. (2014) study?
The data estimated in answer variants such as “yes” or “no,” or multiple choice questions instead of numbers are called nominal measurements. The variables such as incidence of fractures, addiction to alcohol and smoking, and daily exercises were estimated. The types of bones’ thickness were stated as “normal,” “osteopenia,” and “osteoporosis.”
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What statistics were calculated to describe body mass index (BMI) in this study? Were these appropriate?
The Body Mass Index (BMI) is traditionally calculated through the division of weight in kilograms by height in meters. Although in the current study the height was estimated in centimeters, it can be converted to meters by dividing by 100. Thus, the assessment of BMI in the study was provided properly. Moreover, the intervention and control groups did not have a meaningful diversity in BMI values.
Were the distributions of scores for BMI similar for the intervention and control groups?
The BMI rate was comparable for intervention and control groups. The average BMI for the intervention group was 24.7 (SD = 2.5); while that for the control group was 23.38 (SD = 3.32). The conclusion can be made that the two averages overlapped. Besides, there was no considerable disparity between the t score and the chi-squared score.
Was there a significant difference in BMI between the intervention and control groups?
The study results did not reveal any statistically meaningful disparity for the intervention and control groups in major characteristics. The evidence to it is the value of p which was estimated as p=0.485 for the calculation with 40 degrees of freedom. This value is not regarded as meaningful.
Based on the sample size of N = 41, what frequency and percentage of the sample smoked? What frequency and percentage of the sample were non-drinkers (alcohol)?
Among 41 participants of the experiment, 40 did not drink alcohol. Thus, the percentage was calculated in the following way: 40/41*100=97.6%. As for smoking, none of the participants smoked. Consequently, the percentage of non-smokers was estimated like 41/41*100=100%.
What measurement method was used to measure the bone mineral density (BMD) for the study participants?
The bone mineral density (BMD) was evaluated by a DEXA scanning method. The application of this method is broad since it is considered to have high-quality standards. Moreover, its observational error is less than 1%.
What statistic was calculated to determine differences between the intervention and control groups for the lumbar and femur neck BMDs? Were the groups significantly different for BMDs?
The average BMD score was computed. It was needed to prove the discrepancy between BMD scores of intervention and control groups. The t-statistic criterion of the discrepancy of averages was computed to reveal the statistical difference. Degrees of freedom were used to assess a t-statistic criterion. The t-value was discovered at the rate of 0.0526, and the p-value for this result was 0.958. For t=0.055, the value of p is 0.956. These values of p are not recognized as significant since the maximum meaningful score of p is 0.05.
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The researchers stated that there were no significant differences in the baseline characteristics of the intervention and control groups (see Table 2). Are these groups heterogeneous or homogeneous at the beginning of the study? Why is this important in testing the effectiveness of the therapeutic lifestyle modification (TLM) program?
The method of random selection was applied to choose the participants for both intervention and control groups. It was the best method since the homogeneous groups were necessary for this study. The major characteristics of both groups were established. However, these specifications were not substantially different for intervention and control group. The TLM testing demanded this procedure. In case the groups were not homogeneous, the diversity revealed in the rates of BMD could be conditioned by the groups’ diversity and not related to the TLM intervention.
Oh et al. (2014, p. 296) stated that “the adherence rate to the TLM program was 99.6%.” What is the importance of intervention adherence?
It is considered that the statistical meaningfulness of the research findings and, as a result, their explanation, could be under the impact of participants’ adherence. Poor adherence or its absence conditions poor statistical significance of the research results. Moreover, it can cause the reduction between researches. The findings obtained during such research could not be treated as reliable. The study by Oh et al. (2014) stated adherence of 99.6% which proves the reliability of the research results.
Was the sample for this study adequately described?
The sample characteristics significant for this study were weight, height, the BMI, age, addiction to smoking or drinking or its absence, and background of fractions. The conclusion can be made that the sample description was not thorough. It could be complemented with some other significant characteristics such as race. It could add to the reliability of the experiment results since it may have a substantial impact on the BMD. Besides, the relevant information on the sample summary of the groups could be useful. The information on procedures concerning the control group could be mentioned. These factors could also have the impact on the results of the experiment.
Oh, E. G., Yoo, J. Y., Lee, J. E., Hyun, S. S., Ko, I. S., & Chu, S. H. (2014). Effects of a Three-Month Therapeutic Lifestyle Modification Program to Improve Bone Health in Postmenopausal Korean Women in a Rural Community: A Randomized Controlled Trial. Research in Nursing & Health, 37(4), 292–301. Web.