The study you analyzed provides critical insight into the attitudes and influence of health conditions of the mothers in their early postpartum. I agree with your statement that self-efficacy is the “essential psychological variable in long-term breastfeeding.” The research results suggested that a stronger desire to feed exclusively develops in women with positive birth experiences. You were right by emphasizing that the differences in samples’ conditions were identified using inferential statistics, t-test, and one-way ANOVA. Using these approaches is beneficial for promoting exclusive feeding and expanding the knowledge in further studies. Brockway et al. (2017) claim that “Breastfeeding self-efficacy is a modifiable factor that practitioners can target to improve breastfeeding rates in mothers of full-term infants” (p. 497). However, the alternative perspective can be applied to the study’s results and gathered information if analyzed with other statistical tools.
Aside from the benefits of breastfeeding self-efficacy, the research revealed the negative influence of artificial supplements implementation. With the linear regression with predictor variables, the scientists could also try the reverse approach of measuring the results by the response variables. It would eliminate the requirement of t-tests and ANOVA for submitting the outcomes, as their validity is questionable in such studies (Weissgerber et al., 2018). I explored several healthcare and biomedical studies where ANOVA and t-tests were applied only because they were the most common and the simplest to use for results confirmation. Based on the research design you studied, statistical tools implementation, and my experience in analyzing similar scientific works, the suggestion is to look for more complex data gathering and sample selecting strategies. Applying more concrete criteria to the participants and adding response variables would determine the range of breastfeeding self-efficacy and the outcomes.
Pre-hypertension measures, such as Swedish massage, are necessary for health as an act of care and profound prevention practice. You were right by mentioning that such procedures are essential for decreasing the risk of heart disease development. The research you analyzed has been designed by selecting women with proper conditions, tracking their blood pressure, and assigning a massage course to a randomized part of the group. You correctly claimed that “the data was analyzed using descriptive and inferential statistical methods such as chi-square and t-test through SPSS software.” Such a strategy is beneficial for the studies that contain intervention and dependent variables. It also submits the advantage of Swedish massage appliances related to the prevention of pre-hypertension’s side effects and reducing clients’ blood pressure (Givi et al., 2018). I agree with you that the study aimed to provide a workable non-pharmacological way of managing pre-hypertension for women, and its design shows the profound evidence-based practice for nurses.
Although research with intervention and randomizing groups provides beneficial results, it can be conducted from an alternative perspective. Indeed, diversifying the sample group by applying more participants with a history of pre-hypertension and experience in Swedish massage would make the study’s results more reliable. Furthermore, the chi-square test used for the association between two categorical responses would be helpful in evaluating several pairs of sets (Shih & Fay, 2017). The results measured more detailed that just by comparing intervention to the control group would expand the evidence. I have experience participating in a study about an exam structure for the students’ efficiency, and it revealed that the results differ from subject to subject. Consequently, I suggest that more groups of dependant variables need to be included to explore the impact of a Swedish massage.
References
Brockway, M., Benzies, K., & Hayden, K. A. (2017). Interventions to improve breastfeeding self-efficacy and resultant breastfeeding rates: a systematic review and meta-analysis. Journal of Human Lactation, 33(3), 486-499.
Givi, M., Sadeghi, M., Garakyaraghi, M., Eshghinezhad, A., Moeini, M., & Ghasempour, Z. (2018). Long-term effect of massage therapy on blood pressure in prehypertensive women. Journal of Education and Health Promotion, 7, 54. Web.
Shih, J. H., & Fay, M. P. (2017). Pearson’s chi‐square test and rank correlation inferences for clustered data.Biometrics, 73(3), 822-834.
Weissgerber, T. L., Garcia-Valencia, O., Garovic, V. D., Milic, N. M., & Winham, S. J. (2018). Meta-Research: Why we need to report more than ‘Data were Analyzed by t-tests or ANOVA.’ Elife, 7, e36163.