“First or Second Drop of Blood in Capillary Glucose Monitoring” Article Analysis
The quantitative design of the study
A study published in The Journal of Emergency Nursing article, “First or Second Drop of Blood in Capillary Glucose Monitoring,” observed inconsistent practices in using the first or second drop of blood to measure blood glucose levels accurately varies in the home and ER setting. The study’s purpose was to determine if blood from the first or second blood drop samples, collected from the same site from patients with diabetes type I, would show variation in testing results (Palese, Fabbro, Casetta & Mansutti, 2016).
The study method is described as descriptive with inferential statistical analysis, providing the most reliable evidence from a literature review about differences between blood sugar result variations determined between the use of the first blood drop or second samples (Polit, 2012).
Descriptive research design provides systematic data collection and analysis of information determining the relationship between variables through observing, describing, and documenting (Polit, 2012). Descriptive research is strong in true-to-life situations and can collect large amounts of data. Still, sample groups are not randomly selected but are determined by self-selection and cannot assume groups being compared are similar(Polit, 2012). Because attitude, situations, and behaviors or complex in the real world, difficulty interpreting findings may be difficult due to limitations (Polit, 2012).
Strengths and limitations of the study
Strengths and limitations of the study as described by Palese, Fabrro, Casetta & Mansutti (2016), are:
Strengths
- Two hypotheses were established: 1)There is no difference between the repeated measurement(first or second) obtained from a single subject. 2)Different concentrations of glucose will not affect differences between the first and second drops of blood.
- Sample group: 195 individuals with type 1 diabetes without hypoglycemia and washed hands.
- Study approval: The hospital IRB approved data collection with written consent obtained from study participants.
- Criteria were established: age 18 years and older, normothermia, washed hands, no suspected hypoglycemia.
- Bias avoidance: Same hand and finger use for blood collection from each patient and healthcare providers given education about the procedure, data collection process, and technique.
- Equipment: the same portable glucometers and finger strips used for every patient.
- Defined glucose concentrations: The value determined first and second drops of blood following American Diabetes Association and Literature review guidelines. Blood Sugar Criteria: BG < 179 mg/dL, 180-358 mg/dL and BG >359 mg/dL.
- Environment: controlled outpatient patient clinic setting.
- Data Analysis: Ranking system and data software used to determine statistical analysis with P < 05.
Limitations
- Comparisons: first and second blood drops comparison methods and the gold standard of measurement, as reported in the literature review, were not addressed.
- Blood collection: consecutively obtained from the same site and no use of other glucometers, which differs from the literature review process.
- Sample group: Limited to Diabetics type I individual after breakfast meal consumption and hands washed with soap and water.
- Exclusions: are patients with suspected hypoglycemia and soiled hands, and the complexity of the ER setting was not considered.
- Environment: controlled environment does not reflect conditions encountered in the emergency room, unstable and urgent changes in patient conditions, unclean hands, various times of day, and hypoglycemia.
- Literature review: Database sources, number of articles reviewed, and levels of evidence of literature review lacked identified.
Substantive Response to the Article Analysis
I agree with this post concerning the strengths of the quantitative study being addressed. First, a good quantitative study should have a clearly stated hypothesis. On this issue, the journal article under analysis has two strong hypotheses. Additionally, the study used a sizeable sample of 195 participants. This sample size is large enough to generalize the results in other set-ups. According to Faber and Fonseca (2014), studies should use large sample sizes to detect clinically relevant differences.
Additionally, I agree with the post that seeking study approval from the hospital IRB and obtaining consent from participants is one of the strengths of the article. Clinical studies should be approved by appropriate bodies, and participants should give written consent to take part in the research to avoid ethical and legal implications for researchers. Last month, I read an interesting piece in a scientific journal highlighting the legal and ethical implications of not obtaining approval from relevant bodies and consent from participants. I realized that non-compliance to IRB approval could prevent one from using data collected. I also learned that researchers are bound by a code of ethics to obtain informed consent from participants in a study.
“Effect of Meaningful Recognition on Critical Care Nurses’ Compassion Fatigue” Article Analysis
The quantitative design of the study
The quantitative study, Effect of Meaningful Recognition on Critical Care Nurses’ Compassion Fatigue, is nonexperimental observational research that observed the impact of meaningful recognition on prevention or decreasing the likelihood of nurses experiencing burnout, secondary stress trauma, or compassion fatigue. This study, which is a form of correlation study, has its limitations.
According to Polik & Beck (2017), descriptive correlation studies can be weak in showing the relationship between the cause of a phenomenon due to how, in real life, the behaviors, attitudes, and characteristics of the participants are intertwined in complex ways leading to challenges in interpreting the data. However, if derived from theory and supported by a strong design, the cause inferences could be possible (Polik & Beck, 2017).
Additionally, the sample itself is self-limiting. Meaning, the participants being studied have already been placed in existing groups, such as this study being ICU staff, and not randomly selected but through self-selection (Polik & Beck, 2017). This process of self-selection can create room for bias (Polik & Beck, 2017). According to Polik & Beck (2017), the strengths of this type of study include a large amount of data collected is efficient by being able to uncover multiple variables of interaction in a short period of time and the strong correlation and relation to real-life concepts rather than artificial or idealization components.
Strengths and limitations of the study
The following strengthens, and limitations discussed in this study by Kelly & Lefton (2017) are:
Limitations
- The low response rate to the surveys sent to the participants.
- Survey responder bias was present.
- Only one style of recognition was assessed d/t how known this recognition program was within the nation. However, they did ask if nurses receive any other form of recognition. Other than thank you notes and “Nurse week” recognition, none were identified by the nurses despite hospitals reporting having these types of programs, such as a clinical ladder, in place.
- The sample utilized was narrow due to the researchers wanting to increase participation by the participants and could have limited the study. The sample was chosen by those hospitals with stronger leadership and cultures that wanted to participate in the DAISY Award program.
Strengths
- The nurses that participated in the study worked in the same area, medical, surgical, medical-surgical, cardiovascular, neurological, and trauma ICU units. Therefore, they had similar patient experiences.
- Large sample size: 726 participants from 24 different hospitals.
- Demographic differences were minimal other than the hospitals participating in the DAISY Award program had a higher percentage of white nurses.
- The study was approved by institutional review boards (IRB) at Arizona State University and the participating sites that did not accept the university’s IRB.
- Data analyzed by using a data software, linear regression analysis was used on each Professional Quality of Life instrument outcome to assess for predictions.
- Cross-validation (dividing groups randomly into two groups and applying the linear regression model to analyze all variables at the same time for each group) confirmed the model of study and predictors of α level of 0.05.
Substantive Response to the Article Analysis
I agree with this post that correlational studies have numerous limitations. According to Asamoah (2014), correlational studies are not well understood, and thus most researchers use this approach wrongly. Hence the results obtained are unreliable, unrealistic, and irrelevant. One of the limitations noted in the post is the low response rate to the surveys sent to participants. This aspect means that researchers may not get a big enough sample size and data to make reasonable conclusions. Additionally, responders to the surveys were subject to bias, and thus the results obtained may not be reliable.
Therefore, I agree with the post that these issues limit the study. At one point, I was involved in carrying out a study, and when the results came in, we established a trend of bias in the majority of the responses given by participants. We wasted a lot of time trying to figure out what would be admitted as non-biased results. Therefore, I understand when biased results are classified as study limitations. On the other hand, the study sample was large, with 726 participants from 24 different hospitals. I agree that this is one of the strengths of the study because the results can be extrapolated and generalized in other set-ups.
“Assessing Learning Styles of Graduate Entry Nursing Students as a Classroom Research Activity” Article Analysis
The quantitative design of the study
The selected quantitative article is “Assessing Learning Styles of Graduate Entry Nursing Students as a Classroom Research Activity: A Quantitative Research Study.” By Gonzales and her team. The study is quantitative because it has used numerous amount of numerical data and statistical measurements. The design of this study is descriptive, and the data is collected using the method of participation. In this study, 202 graduate students were participated voluntarily (Gonzalez et al.,2017). The benefit of this type of research is data can be collected from a large group of participants as well as from large geographic areas.
This type of research is suitable for educational research because educational research and experiences may have huge numbers of variables that cannot be controlled, and many educational pieces of research may require observations and descriptions.
Strengths and limitations of the study
The main limitation or disadvantage of the descriptive research is the truthfulness of participants. Sometimes participants may not work naturally and may be influenced by internal or external biases or interests which may affect the outcome of the research. Another problem is the confidentiality of the participants. Data are collected through interviews, face-to-face interactions, and observations, but in this situation, the participants may not be convinced that their privacy is protected. So, data collectors should be skilled at convincing participants.
Substantive Response to the Article Analysis
I agree with the reason given in this post explaining why the study is quantitative. According to Ingham-Broomfield (2014), quantitative studies use objective measurements and employ mathematical, numerical, or statistical data analysis methods. However, I can’t entirely agree with the general analysis of the journal article as written in this post. First, the post does not address the journal article directly. On the contrary, the post is focused on the general aspects of descriptive studies. For instance, instead of stating the strengths of the study, the student talks of the benefits of using descriptive studies.
Additionally, the limitations given here are not for this particular journal article. The student gives the main limitation of descriptive studies. However, while the lack of truthfulness among participants may be a weakness of descriptive studies, it is not stated clearly if this was a limitation in this particular study. The student can do better by raising issues specific to the journal article by Gonzalez et al. (2017).
References
Asamoah, M. K. (2014). Re-examination of the limitations associated with correlational research. Journal of Educational Research and Reviews, 2(4), 45-52.
Faber, J., & Fonseca, L. M. (2014). How sample size influences research outcomes. Dental Press Journal of Orthodontics, 19(4), 27–29.
Gonzales, L. K., Glaser, D., Howland, L., Clark, M. J., Hutchins, S., Macauley, K., &… Ward, J. (2017). Assessing Learning Styles of Graduate Entry Nursing Students as a Classroom Research Activity: A quantitative research study. Nurse Education Today, 4855-61. Web.
Ingham-Broomfield, B. (2014). A nurses’ guide to quantitative research. Australian Journal of Advanced Nursing, 32(2), 32-38.
Kelly, L. A., & Lefton, C. (2017). Effect of meaningful recognition on critical care nurses’ compassion fatigue. American Journal of Critical Care, 26(6), 438-444. Web.
Palese, A., Fabbro, E., Casetta, A., & Mansutti, I. (2016). First or Second Drop of Blood in Capillary Glucose Monitoring: Findings from a Quantitative Study. JEN: Journal of Emergency Nursing, 42(5), 420-426. Web.
Polit, D. F., & Beck, C. T. (2012). Nursing Research-Generating and Assessing Evidence for Nursing Practice (10th ed.) [Electronic].
Polit, D. F., & Beck, C. T. (2016). Resource manual for nursing research: Generating and assessing evidence for nursing practice (10th ed.). Philadelphia, PA: Lippincott Williams & Wilkins.