Research Ability Research Articles

A Multi-disciplinary Investigation of Linearization Deviations in Different Regression Models

Aim: This study's objective is to examine linearization deviations in various regression models using a multidisciplinary approach.
 Methods: Curve estimate models' accuracy for each type of data was tested using social, financial, and medical data sets.
 Results: Although the power of a given model reduces with non-normal distributions, linearization in the social sciences is more efficient and has less variation from regression points in parametric equations. However, single-center distributions in the social sciences typically lead to nonparametric distributions. When compared to social sciences and health sciences, the effectiveness of linearization in financial sciences is higher. The original essence of financial techniques and models is frequently present, and they test their presumptions. Financial models and assumptions are more linear than those seen in real life since they correspond to artificial systems that individuals have developed, making them better suited for predetermined formulas. The rise in linearization issues in the field of finance, which has been increasingly common in recent years, is a symptom of this together with behavioral finance. Studies in the realm of health and well-known models were discovered to have the highest linearization deviations. Exponential or growth functions exhibit the highest linearization deviations in processes like growth, proliferation, and the spread of disease or pandemics. The data display considerable departures from normality and linearization, particularly in animal trials with very small statistical units or research conducted on a particular population.
 Conclusion: Despite research on R2's explanatory capacity in regression, there aren't enough studies in various fields that concentrate on R2's departures from linearization. Additionally, no study was located in which the subject's mathematical foundation was examined and cross-compared across various data sets. As a result of this feature, the research represents a field first. The research's ability to pragmatically assess the distinctions between disciplines, made possible by its multi-disciplinary nature, is another unique aspect of the work.

The importance of providing gender-affirming care in pharmacy practice

Transgender and gender diverse (TGD) individuals face bias and discrimination across many health care settings including pharmacy. While there is evidence of successful interventions to increase provider awareness of the needs of TGD individuals in medicine, nursing, and social work, little work has been done by the pharmacy profession to recognize and meet the needs of this population. This commentary examines the gaps in pharmacy practice and pharmacy research with regards to the needs of TGD individuals and looks at allied health fields for potential solutions that can be adapted by the pharmacy profession.We first examine the social pressures that TGD individuals face in multiple social contexts and describe how bias and discrimination spill over into their interactions with providers and health care systems. Solutions for improving pharmacy practice research's ability to identify TGD individuals and their needs follows as a measure that will lead to solutions for improving pharmacy practice. A discussion of TGD individuals' responses to actual and perceived discrimination by pharmacists is discussed next, and why their avoidance of pharmacy care can be problematic to their health. The remainder of the paper focuses on how pharmacy education can train future pharmacists to provide inclusive care to TGD individuals, and how interprofessional education and continuing education can enhance future and practicing pharmacists' ability to provide high quality care to TGD individuals.

Testing the research abilities of student teachers at pre-service training and education

Some academic supervisors claimed the low abilities of pre-service students on conducting a research. This research aims to measure the Research Abilities (RA) of students by developing the instruments to test the knowledge of students on essential components of research, i.e., understandings on the type of research, research design, research problem, hypothesis, variable, type of data, research method, sampling, and data analysis. The instrument is an essay, and multiple-choice test consists of 30 questions divided into four categories, i.e., Research Problems, Hypothesis, and Variables (Q1); Research Method (Q2); Data Analysis (Q3); and Action Research (Q4). About 36 science and non-science students participated voluntarily on the online test, 89% are females, and 14% are science education students. Only 35 data are valid to be analyzed. The result shows that the highest score belongs to a non-science student (24), and the average rating of science students (12.14) is almost equal with non-science ones (12.62). The average score of Q1 is 5.1 of 12, Q2 4.4 of 8, Q3 is 1.1 of 3, and Q4 is 0.9 of 3. The conclusion is students show low performances on RA’s components.

A framework for understanding cancer comparative effectiveness research data needs

ObjectivesRandomized controlled trials remain the gold standard for evaluating cancer intervention efficacy. Randomized trials are not always feasible, practical, or timely and often don't adequately reflect patient heterogeneity and real-world clinical practice. Comparative effectiveness research can leverage secondary data to help fill knowledge gaps randomized trials leave unaddressed; however, comparative effectiveness research also faces shortcomings. The goal of this project was to develop a new model and inform an evolving framework articulating cancer comparative effectiveness research data needs. Study Design and SettingWe examined prevalent models and conducted semi-structured discussions with 76 clinicians and comparative effectiveness research researchers affiliated with the Agency for Healthcare Research and Quality's cancer comparative effectiveness research programs. ResultsA new model was iteratively developed and presents cancer comparative effectiveness research and important measures in a patient-centered, longitudinal chronic care model better reflecting contemporary cancer care in the context of the cancer care continuum, rather than a single-episode, acute-care perspective. ConclusionImmediately relevant for federally funded comparative effectiveness research programs, the model informs an evolving framework articulating cancer comparative effectiveness research data needs, including evolutionary enhancements to registries and epidemiologic research data systems. We discuss elements of contemporary clinical practice, methodology improvements, and related needs affecting comparative effectiveness research's ability to yield findings clinicians, policy makers, and stakeholders can confidently act on.

Research on the teaching reform of physiology experiment to enhance the research capacity of the eight-year program medical students

Eight-year medical education is to train medical personnel with high research abi lity and innovative ability, while the experimental teaching, as an important part of physiology teaching, plays an important role in training students in observation, problem-solving skills and practical ability. This article mainly discusses our exploration and practice of teaching in physiology experiment for eight-year program medical students from teaching contents and organization of class teaching, in order to fully increase the studying enthusiasms and meet the scientific mind of these students. Key words: Physiology; Experimental teaching; Research capacity; Eight-year medical program

Making R&D Pay

Getting more commercial payback from R&D is high on the agenda of top executives in many industries. One major company in Australia has been experimenting with a new approach managing research. Though it is still too early declare final victory, there are clear signs that the changes are paying off. The secret has been converting from a functional cost a professional client mentality. This has involved shifting management of R&D away from a research push a market pull approach. Achieving this change meant the organization had build new skills in client service and development, as well as in commercially-oriented project management. This article describes both the reasons for the change and a number of the specific actions that led a radically new way of running research. Why Change? Several years ago, the central reseach facility of one of Australia's largest companies was a classic laboratory in the woods. Located on the outskirts of Melbourne on a grassy, tree-lined site, the lab was a great distance -- physically and spiritually -- from the six operating divisions that were meant share its resources. Inside the foyer were large posters describing a discovery that had occurred 30 years earlier. For 15 years, the R&D function had been run by a scientist who had excellent connections the academic community but few relationships with business managers within the company. As is common in many groups, the laboratory's prevailing culture was defensive, bureaucratic, and hierarchical. Lengthy documents written about the achievements of blamed operating divisions for failing capitalize on the discoveries. Researchers who worked there had a shop floor mentality --timesheets were strictly maintained, the cafeteria opened for only 45 minutes during the day, and heating was cut off at 4.30 p.m. Late nights spent poring over experiments were not only a myth, but a physical impossibility. Costs were tightly controlled and requisitions from the store were parsimoniously doled out. With 200 researchers, this lab was one of the largest commercial facilities in Australia -- but its relevance was increasingly questioned by the business managers. Back in head office, the operating divisions were strikingly uninvolved with R&D -- even in projects that were ostensibly done on their behalf. Managers complained that the researchers' role was to invent things and that their hit rate was far too low. Projects were poorly defined, the relevance of their objectives unclear. Open cynicism flourished about research's ability deliver. Budgets for R&D were based on history: division managers allocated money as though was a charity rather than a vital part of their business. Half of the central facility's budget was funded corporately, and corporate center accountants arbitrarily allocated those charges back the divisions based on sales rather than usage, further adding the barely hidden hostility. At the same time, operating divisions were becoming more aware of the importance of new products. Lower tariff barriers and more imports were threatening profits. The new mission statement for the company emphasized its dependence on science and technology gain competitive advantage. Operating divisions blamed their arm's-length relationship with the function for the new product development vacuum. Many believed that the only way get results was split up the central group and take control of their own researchers. To resolve the debate, the company formed a team with McKinsey answer several questions: should the lab be split up and absorbed by the operating divisions or kept as a central facility? If kept whole, what changes should be implemented improve return on the dollar? Getting the Facts The challenge for the team was get beyond received opinion by developing a fact-based understanding of the issues. …