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Research Data Analysis Portfolio Piece A
Research Data Analysis Portfolio Piece A
The cross-sectional survey study “Prescribing practice and off-label
use of psychotropic medications in post-acute brain injury rehabilitation
centres: A cross-sectional survey” will be analyzed in this article. A
research data summary and result analysis, a summary and interpretation
of statistical data, a critique of research methods, suggestions for
further research in this area, and support of the study’s implications
will be discussed in this article. The research summary and result
analysis will be performed first.
Research Data Summary and Result Analysis
The study, the study’s data, its inferences, and the general impact of the study’s inferences to the future will be analyzed in this section. The research problem in this study is that pharmacotherapy has limited guidance for treating post-acquired brain injury (ABI) (Pisa, et.al., 2015). The research question or objectives of the study are to assess (a) the prevalence of psychotropic medications used; (b) the prevalence of usage of off-label psychotropic medications; and (c) the factors that are associated with usage of atypical antipsychotics (Pisa, et.al., 2015). Participants in the study included 35 out of 40 (87.5%) identified centers with 31
(77.5%) including patient-level data (Pisa, et.al., 2015). The participants in the study were identified centers in the Italian Society for Rehabilitation Medicine and they were not separated into groups (Pisa, et.al., 2015). Structured questionnaires that were filled out by the centers were used to collect the data (Pisa, et.al., 2015). The data was prepared for analysis by calculating the
responses on the questionnaire (Pisa, et.al., 2015). Data analysis was performed with descriptive statistics that were calculated to characterize the different centers (Pisa, et.al., 2015). The results of the study indicate that it is not uncommon for ABI rehabilitation clinics to prescribe off-label psychotropic medications particularly antidepressants and antipsychotics (Pisa, et.al., 2015). Although the data has been summarized the statistics have not been analyzed so there is a detailed look at the statistics of this study later in the article. The inferences and implications of the study of will be discussed next.
Since the results of the study point to an inference that off-label psychotropic medication is practiced in over 50% of the clinics implications are made that more research is needed in this area. The implications of this research are that future research should be concerned with improving the quality of evidence to guide the pharmacological treatment of neurobehavior in ABIs as well as evaluation of the benefits and risks of off-label prescribing (Pisa, et.al., 2015). The inference of this study indicates that there is still extensive research to be performed concerning the use of off-label psychotropic medications for people suffering with ABIs. The study implies that physicians should be very careful when prescribing off-label medications. Next the statistical data will be summarized and interpreted.
Summary and Interpretation of Statistical Data
Interpretation of statistical data is important when studies are meant to be understood by those unfamiliar with research jargon. A cross-sectional survey such as the prevalence study featured in this article is a form of an observational study that includes the collection and analysis of data that was collected at a specific point in time from arepresentative subset or a population (Steinberg, 2011). The centers were characterized by the calculation of descriptive statistics which describe the variables in a study (Salkind, 2012). The numbers of beds and patients are the continuous variables that were used to make categories for the study to be considered scientific (Pisa, et.al., 2015). The study calculated the prevalence of centers using psychotropes for each of the 108 drugs used in 35 centers (Pisa, et.al., 2015). On-label usage of each drug was computed by division of the centers reporting use of that medication by the total number of centers (Pisa, et.al., 2015). The off-label use was computed by the division of the number of centers that reported off-label use of the medication by the reported total number of centers that utilize that medicine (Pisa, et.al., 2015). The frequency of off-label indications for each therapeutic class was calculated by the division of the number of centers who reported individual indication by the number of centers that reported the use of off-label medicating for a minimum of one medication from the same therapeutic class (Pisa, et.al., 2015). The type of study that was performed and the manner in which prevalence was calculated to classify the study as cross-sectional has been described. The next paragraph will further analyze the statistics.
There must be statistical analysis in a quantitative study for the study to adhere to protocol. A 95% confidence interval (95% CI) was employed with the odds ratio (OR) to calculate the odds of a patient receiving an unusual antipsychotic agent by using a multivariate unconditional logistic regression (Pisa, et.al., 2015). The confidence interval is a calculation used in statistics that states there is a 95% chance that results are correct to balance errors in calculations (Engineering
Statistics Handbook, n.d.). Odds ratio is used in statistics to quantify the strength of the absence or presence of property A as associated with the absence or presence of property B in any given population (Farlex, 2012). Multivariate statistics is a statistical subdivision that encompasses the simultaneous analysis and observation of multiple outcome variables (Salkind, 2012). Fortunately, the complicated process of unconditional logistic regression is performed by a SAS computer program for statistics (Steinberg, 2011). It sure does seem like a complicated method to scientifically express that off-label medicating of psychotropes occur in more than 50% of the clinics for brain rehabilitation in this study. A critique of research methods will be performed
next.
A critique of research methods
In this section problems noted in research will analyzed to determine why the findings should not be affected by these errors. The generalizability of the results may be limited because they survey occurred in Italian rehabilitation centers; however, the implication that care is necessary when prescribing off-label is not affected by this (Pisa, et.al., 2015). There may have been some errors in reporting as the questionnaires were filled out, but this should not affect the overall results either (Pisa, et.al., 2015). In the study’s limitations Pisa, et.al. (2015) state that drug marketing strategies, national marketing and other factors affect practices for prescribing medication. Since the results of the study indicate that 50% of the center are practicing off-label prescribing the results should not be impacted while the enforcement of the study’s implications should be strengthened. The described process of the study will be critiqued next.
There were some errors noted in the study’s process because it does not go “by the book”. The data was collected on a form, but there was not a designation of the coding strategy noted as a research text implies as a necessary step in study design (Salkind, 2012). Salkind (2012) explains that proposal organization is an important part of the craft of research and that previous research in the study’s area in a vital part of a study; this study featured no previous research.
Hypothesis, null hypothesis, and the acceptance or rejection of null hypothesis is a necessary part of a statistically correct study; nevertheless, these items were not used in this study which may affect the credibility of the study in the scientific community (Steinberg, 2011). It would be unfortunate for this valuable research to lose credibility because the implications of the study may point the way for people with ABIs to regain recovery at a more expedient rate; in fact, these errors should not affect the results of the study. Next suggestions for further research in this area will be discussed.
Suggestions for further research in this area
Knowledge derived from this quantitative research may help sufferers of ABI to recover more efficiently and expediently. Greve & Zink (2009) explain that the initial injury force that causes destruction and distortion is the primary brain injury while the secondary brain injury involves propagation of injury and alterations in cell function through processes like excitotoxicity, disruption of calcium homeostasis, depolarization, and free-radical generation (Greve & Zink, 2009). “Compared to the primary injury, secondary injuries to the brain are more indolent and progressive and may ultimately be the deciding factors in the patient's recovery” (Greve & Zink, 2009. P.98). Greve & Zink (2009) stress that development of therapies that limit secondary brain injury is the best hope for outcome improvement of traumatic brain injury (TBI) patients. More research definitely needs to be done on the prescribing of mind-altering and mind- dumbing psychotropic medications to people with TBIs much less off-label prescribing. It seems like any research that is concerned with the effects of psychotropes on TBIs should have been done before it was prescribed to people in the secondary stages of brain injury. Support of the study’s implications will be discussed next.
Research Data Summary and Result Analysis
The study, the study’s data, its inferences, and the general impact of the study’s inferences to the future will be analyzed in this section. The research problem in this study is that pharmacotherapy has limited guidance for treating post-acquired brain injury (ABI) (Pisa, et.al., 2015). The research question or objectives of the study are to assess (a) the prevalence of psychotropic medications used; (b) the prevalence of usage of off-label psychotropic medications; and (c) the factors that are associated with usage of atypical antipsychotics (Pisa, et.al., 2015). Participants in the study included 35 out of 40 (87.5%) identified centers with 31
(77.5%) including patient-level data (Pisa, et.al., 2015). The participants in the study were identified centers in the Italian Society for Rehabilitation Medicine and they were not separated into groups (Pisa, et.al., 2015). Structured questionnaires that were filled out by the centers were used to collect the data (Pisa, et.al., 2015). The data was prepared for analysis by calculating the
responses on the questionnaire (Pisa, et.al., 2015). Data analysis was performed with descriptive statistics that were calculated to characterize the different centers (Pisa, et.al., 2015). The results of the study indicate that it is not uncommon for ABI rehabilitation clinics to prescribe off-label psychotropic medications particularly antidepressants and antipsychotics (Pisa, et.al., 2015). Although the data has been summarized the statistics have not been analyzed so there is a detailed look at the statistics of this study later in the article. The inferences and implications of the study of will be discussed next.
Since the results of the study point to an inference that off-label psychotropic medication is practiced in over 50% of the clinics implications are made that more research is needed in this area. The implications of this research are that future research should be concerned with improving the quality of evidence to guide the pharmacological treatment of neurobehavior in ABIs as well as evaluation of the benefits and risks of off-label prescribing (Pisa, et.al., 2015). The inference of this study indicates that there is still extensive research to be performed concerning the use of off-label psychotropic medications for people suffering with ABIs. The study implies that physicians should be very careful when prescribing off-label medications. Next the statistical data will be summarized and interpreted.
Summary and Interpretation of Statistical Data
Interpretation of statistical data is important when studies are meant to be understood by those unfamiliar with research jargon. A cross-sectional survey such as the prevalence study featured in this article is a form of an observational study that includes the collection and analysis of data that was collected at a specific point in time from arepresentative subset or a population (Steinberg, 2011). The centers were characterized by the calculation of descriptive statistics which describe the variables in a study (Salkind, 2012). The numbers of beds and patients are the continuous variables that were used to make categories for the study to be considered scientific (Pisa, et.al., 2015). The study calculated the prevalence of centers using psychotropes for each of the 108 drugs used in 35 centers (Pisa, et.al., 2015). On-label usage of each drug was computed by division of the centers reporting use of that medication by the total number of centers (Pisa, et.al., 2015). The off-label use was computed by the division of the number of centers that reported off-label use of the medication by the reported total number of centers that utilize that medicine (Pisa, et.al., 2015). The frequency of off-label indications for each therapeutic class was calculated by the division of the number of centers who reported individual indication by the number of centers that reported the use of off-label medicating for a minimum of one medication from the same therapeutic class (Pisa, et.al., 2015). The type of study that was performed and the manner in which prevalence was calculated to classify the study as cross-sectional has been described. The next paragraph will further analyze the statistics.
There must be statistical analysis in a quantitative study for the study to adhere to protocol. A 95% confidence interval (95% CI) was employed with the odds ratio (OR) to calculate the odds of a patient receiving an unusual antipsychotic agent by using a multivariate unconditional logistic regression (Pisa, et.al., 2015). The confidence interval is a calculation used in statistics that states there is a 95% chance that results are correct to balance errors in calculations (Engineering
Statistics Handbook, n.d.). Odds ratio is used in statistics to quantify the strength of the absence or presence of property A as associated with the absence or presence of property B in any given population (Farlex, 2012). Multivariate statistics is a statistical subdivision that encompasses the simultaneous analysis and observation of multiple outcome variables (Salkind, 2012). Fortunately, the complicated process of unconditional logistic regression is performed by a SAS computer program for statistics (Steinberg, 2011). It sure does seem like a complicated method to scientifically express that off-label medicating of psychotropes occur in more than 50% of the clinics for brain rehabilitation in this study. A critique of research methods will be performed
next.
A critique of research methods
In this section problems noted in research will analyzed to determine why the findings should not be affected by these errors. The generalizability of the results may be limited because they survey occurred in Italian rehabilitation centers; however, the implication that care is necessary when prescribing off-label is not affected by this (Pisa, et.al., 2015). There may have been some errors in reporting as the questionnaires were filled out, but this should not affect the overall results either (Pisa, et.al., 2015). In the study’s limitations Pisa, et.al. (2015) state that drug marketing strategies, national marketing and other factors affect practices for prescribing medication. Since the results of the study indicate that 50% of the center are practicing off-label prescribing the results should not be impacted while the enforcement of the study’s implications should be strengthened. The described process of the study will be critiqued next.
There were some errors noted in the study’s process because it does not go “by the book”. The data was collected on a form, but there was not a designation of the coding strategy noted as a research text implies as a necessary step in study design (Salkind, 2012). Salkind (2012) explains that proposal organization is an important part of the craft of research and that previous research in the study’s area in a vital part of a study; this study featured no previous research.
Hypothesis, null hypothesis, and the acceptance or rejection of null hypothesis is a necessary part of a statistically correct study; nevertheless, these items were not used in this study which may affect the credibility of the study in the scientific community (Steinberg, 2011). It would be unfortunate for this valuable research to lose credibility because the implications of the study may point the way for people with ABIs to regain recovery at a more expedient rate; in fact, these errors should not affect the results of the study. Next suggestions for further research in this area will be discussed.
Suggestions for further research in this area
Knowledge derived from this quantitative research may help sufferers of ABI to recover more efficiently and expediently. Greve & Zink (2009) explain that the initial injury force that causes destruction and distortion is the primary brain injury while the secondary brain injury involves propagation of injury and alterations in cell function through processes like excitotoxicity, disruption of calcium homeostasis, depolarization, and free-radical generation (Greve & Zink, 2009). “Compared to the primary injury, secondary injuries to the brain are more indolent and progressive and may ultimately be the deciding factors in the patient's recovery” (Greve & Zink, 2009. P.98). Greve & Zink (2009) stress that development of therapies that limit secondary brain injury is the best hope for outcome improvement of traumatic brain injury (TBI) patients. More research definitely needs to be done on the prescribing of mind-altering and mind- dumbing psychotropic medications to people with TBIs much less off-label prescribing. It seems like any research that is concerned with the effects of psychotropes on TBIs should have been done before it was prescribed to people in the secondary stages of brain injury. Support of the study’s implications will be discussed next.
Support of the study’s implications
prevalent the first three months after ABI or TBI. It seems logical to be able to critically analyze that the prescribing of off-label medications during the most vital time of recovery for TBI is not wise without ample research to discover what these mind-altering drugs may be doing to a delicate recovering brain. A center that is supposed to helping people recover from brain damage should most likely be more careful in what they prescribe to the patients.
A research data summary and result analysis, a summary and interpretation of statistical data, a critique of research methods, suggestions for further research in this area, and support of the study’s implications have been discussed in this article. The author feels that the implications of this study are so vital to patients who are recovering from TBIs that they will be restated: future research should be concerned with improving the quality of evidence to guide the pharmacological treatment of neurobehavior in ABIs as well as evaluation of the benefits and risks of off-label prescribing (Pisa, et.al., 2015). This statement could be broadened to include on-label prescriptions of psychotropic medication to people recovering from brain damage for the benefit of those recovering.
References
Engineering Statistics Handbook. (n.d.). What are confidence intervals? Engineering Statistics Handbook. Retrieved from http://itl.nist.gov/
Farlex. (2012). Odds Ratio. The Free Dictionary by Farlex. Retrieved from
http://
Greve, M. W., & Zink, B. J. (2009). Pathophysiology of Traumatic Brain Injury. Mount Sinai Journal Of Medicine, 76(2), 97-104. doi:10.1002/msj.20104
Pisa, F. E., Cosano, G., Giangreco, M., Giorgini, T., Biasutti, E., & Barbone, F. (2015). Prescribing practice and off-label use of psychotropic medications in post-acute brain injury rehabilitation centres: A cross-sectional survey. Brain Injury, 29(4), 508-516. doi:10.3109/
Salkind, N. J. (07/2012). Exploring Research, 8/e, VitalSource for Capella University. [VitalSource Bookshelf Online]. Retrieved from
https://
Schretlen, David J. & Shapiro, Anne M. (2003). A quantitative review of the effects of traumatic brain injury on cognitive functioning. International View of Psychiatry. Volume 15. Pages 341-349. Retrieved from
http://
Steinberg, W. J. (2011). Statistics Alive!, 2nd Edition. [VitalSource Bookshelf Online]. Retrieved from https://
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