Nursing Models and Development Methodical Examination

Question: Discuss about the Nursing Models and Development for Methodical Examination. Answer: Introduction Research is known as the methodical examination and study of equipments and sources to develop facts and reach new conclusions. It helps to shape and enhance peoples understanding about the world around them (Kirkwood Price, 2014). Psychologists, through research findings can easily describe behavior of people that includes how people think and act in certain ways. Research is important for several reasons as it helps to expand knowledge and discovers new areas. According to Henwood (2014), research is important as it is an instrumental in developing and enhancing knowledge that facilitates efficient learning. On the other hand, research also plays a major role in business. Most of the successful companies, especially those companies who are involved in producing consumer goods and services are investing heavily in their research and development departments (Bryman Bell, 2015). However, different business industries such as agriculture, food and beverage, healthcare, computer softw are, construction and aviation also have high research and development expenditure as it leads to product innovation and improved services (Lewis, 2015). Terry Freedman, in this book The Importance of Research for ICT Teachers precisely stated that research allows people to know and understand issues that they did not even know existed (Cohen, 2013). Besides it is also true that conducting research motivates people to explore possibilities to identify current problems and to disclose truths and fabricated ones. In order to maintain the credibility of the research the academic sector heavily depends on the reliability aspects and validity aspects of the research content. The validity represents the degree of accuracy of the measurement of research content. For instance, in a research project the depression can be explored with help of well-designed survey. However, there are no valid measures to evaluate the anxiety. Another simple example can be formed so as to depict the concept of validity. An alarm set for 6.30 a.m. rings at 7 a.m. every day. These particular incident may be considered as reliable but not valid. There are three categories of validity, which are construct validity, content validity as well as criterion-related validity. On the other hand, the reliability refers to the consistency of the measures in contents of the entire research project. For instance, if any respondents perform approximately similar results against any test within a research, the phenomenon would be cons idered as reliability of the test. However, the academic research cannot produce a precise calculation of the test at every time. There are four categories of reliability that have been noticed in academic research, are test-retest reliability, parallel forms reliability, inter-rater reliability as well as internal consistency reliability. Validity Validity in research can be described as the degree to which a research study measures what it intends to quantify (mite Turhan, 2013). Mainly two types of validity are there which are internal and external. Internet validity means the validity of the measurement and test itself where external measurement means the capability to generalize the findings to the target population. Content Validity Content validity demonstrates the degree a theory considers all parts of a particular condition (Noble and Smith, 2015). For instance, a business that needs to assess the quantity of workers, who are happy with their occupations utilizing temperament, must look at that content validity of the scale. It will help the association to guarantee that exceptionally critical components identified with occupation fulfilment are considered. As said by Lakshmi and Mohideen (2013), content validity is likewise viewed as logical validity. The content validity shows the degree to which an appraisal shows all parts of the expressed thought. Content validity is to a great degree divergent from face validity, as face validity alludes not to what the test initially ascertains, but rather to what anyone knows assess. Face validity surveys a test is legitimate to the examinees who take it or not. The Content validity needs the utilization of perceived topic specialists to ascertain whether test charact erized content and more comprehensive measurable tests that does the assessment of face validity (Ary et al., 2013). Content validity is integral to criterion validity, as it is a helpful marker of the favoured quality. In the hindsight, if none of the components of that test is identified with the principal idea, then the estimation will be one-sided. For the most part, content validity is subjective in nature that asks whether a specific component enhances or brings down a test or research program. Face validity needs singular judgment, for example it inquires the members whether they felt that a test was built legitimately and it was valuable or not. In addition, content validity serves to discover a similar answer. It utilizes diverse methodologies that rely upon measurements, ensuring a capable sort of validity (Elo et al., 2014). Because of reviews and tests, each question is sent to a board of master investigators where those examiners rate it. After gathering opinions from those analysts, it is measured that whether the question is essential or irrelevant to evaluate the construct under study. A major example related to content legitimacy is exhibited below. A school needs to enrol another science instructor. In this situation, a board of governors begins to scan through a few applicants. Those governors will then adumbrate a waitlist and will then set a test, which will select a candidate with the best score. However, in the end he proves to be a poor science teacher (Lund et al., 2014). Then the board starts to find out where they went wrong. It was found that most of the questions were related to physics; therefore, the school got a talented physics teacher. However, the requirement was to recruit a science teacher who can teach biology, chemistry and psychology. In this way, the content validity of the test was not good. The score did not speak to the build of "being a capable science instructor." Then the school expert upgraded the test. Then the test was reshaped by the school authority. Then the candidates were asked again to take the test from where the school found a reliable and qualified science teacher (Cook et al., 2013). Th erefore, it can be said that this test had a higher rational validity. Criterion Validity Criterion validity, which is also known as criterion related validity, evaluates how well one predicts an outcome for another measure. A test can have this kind of validity that it is valuable for foreseeing execution or conduct in another condition (past, present or potentially future). For example, a competitor takes an assessment test amid the meeting strategy (Jensen, 2013). After taking this test, if it is possible to precisely predict how well that candidate will perform, then this test have criterion validity. In other cases, GRE that graduate students take also includes criteria validity as it helps to predict how well a student will perform in graduate students. Criterion validity is also called as predictive validity that assesses how much the test scores measuring one test condition in tried and true with other rule being measured. For instance, in an achievement test is gone for assessing a typical fifth grader's achievement, then it is huge that both the dialect abilities and science tests are appropriately adjusted for a normal fifth grader (Yin, 2013). The most concerning issue identified with criterion validity is when utilized as a part of the sociologies, pertinent rule factors are difficult to recognize. There are three types of criterion validities available, which are predictive validity, concurrent validity and postdictive validity. If a test can perfectly forecast what it is supposed to predict, then it can be called as predictive validity. For instance, SAT displays predictive validity for performance in college. This kind of validity accumulates scores from the indicator measures at first and after that gathers criterion data (Shepard, 2016). Then again, because of simultaneous legitimacy, indicator and criterion data are gathered in the meantime. It can allude to when a test replaces another test. For example, test for a driver is supplanted by an in-person test with an educator. Postdictive legitimacy can be utilized if the test is an appropriate measure of something that occurred sometime recently. Concurrent validity is another part of criterion validity that alludes to an examination between the referred assessment and a result surveyed in the meantime. Construct Validity Construct validity refers to the capability of an evaluation tool such as survey and a test to actually evaluate the psychological concept being studied. For example, if someone wants to know his heights, he would use a tape and not a bathroom scale as height measurements are showed in inches not in pounds. According to Hulteen et al. (2015), construct validity refers to the degree to which inferences can properly be made from the operationalizations in the study to the theoretical constructs on which those operationalizations were depended. Likewise external validity, construct validity is related to generalizing. However, external validity involves generalizing from study context to other people places or time where construct validity involves from generalizing from measures to the concepts of given program. Construct validity is mostly used in education, social sciences and psychology. It demonstrates that a test is originally evaluating the construct it claims it is measuring. For instance, if one tries to figure out whether an educational program enhances emotional maturity in elementary school age children or not, construct validity will help to evaluate of the research is actually measuring emotional maturity or not (Darawsheh, 2014). However, it is not easy to measure construct validity as. Numbers of measures are needed to properly demonstrate construct validity that includes pilot studies and clinical trials. The biggest reason that it is hard to measure is in the social sciences, lot of subjectivity and most constructs have no original unit of measurement. According to Leung (2015), after World War II, many attempts were made to apply statistics to constructs validity. However, all the solutions were too complicated to use in real life. In some situations, such as clinical trial s, statistical tests like a students test can be used to determine if there is a significant difference between pretests and post tests. Validity in quantitative design Validity is an important aspect that helps to validate quantitative research. As per Lub (2015), validity is the degree to which evidence assists that the interpretations of the data are correct and the manner in which interpretations will be used is proper Hartas, (2015). Therefore, it can be said that validity helps to obtain results that are truthful and believable. In order to determine the validity, researchers normally develop a series of questions and will look for answers in the research of others to understand whether the measurements are precise or not. The significance of validity can be seen however content legitimacy. Content validity takes a gander at whether the instrument appropriately covers all the substance that concerns the variable. In lucid words, it attempts to discover the instrument that covers the whole space identified with the variable. For example, in a nursing course, the guidelines about general wellbeing, an examination with content validity will cover all the substance. The guidelines put an emphasis on the themes that had gotten greater scope (Heale and Twycross, 2015). The conventional criteria for validity entrenched in a positive way. The aspect of positivism has been portrayed by a methodical theory of validity. Within the matrix of positivism, the validity was the outcome and finish of other observational originations, for example, confirm, truth, reality, reason and scientific information. Validity recognizes whether the examination initially assesses and discovers appropriate information or not (Jensen, 2013). It can be said that the validity in quantitative research is construct validity. Construct is the underlying idea, thought, question or theory that guarantees which information should be accumulated and how it must be assembled. Another measure of validity is criterion validity. A paradigm is whatever other instrument that measures a similar variable. Through criterion validity, connections can be led to guarantee the degree to which the different instruments measure a similar variable. There are three ways through which criterion validity can be measured which are convergent validity, divergent validity and predictive validity (Cook et al., 2016). Convergent validity helps to show that a tool is extremely correlated with other tools that are evaluating the same variable. Divergent validity displays when an instrument is ineffectively associated to different devices that are measuring a similar variable and Predictive variable implies that the apparatus must have high connections with future paradigms. For example, a score of high self-viability identified with directing an assignment must foresee the positive possibilities a member have while finishing the errand. Validity in qualitative design As far as qualitative research work, the idea of legitimacy is depicted by a colossal scope of terms. This idea cannot be portrayed as a solitary, settled or all-inclusive idea; nevertheless, "rather a reliant construct, unavoidably stranded in the strategies and aims of specific research procedures and tasks." However, some subjective specialists have contended that the word validity is not relevant for subjective research work (Lewis, 2015). In addition, they have understood that it is imperative to possess some sort of qualifying check or measure for their examination. For example, it is understood that the validity is to a great degree, influenced by the impression of specialists in the review and his decision of worldview supposition. Subsequently, a ton of scientists has set up their own particular ideas of legitimacy. At the same time, they have created or embraced what they consider in legitimate way, for example, quality, rigour and dependability. Discussion identified with quality in subjective research started from the concerns about validity in quantitative establishment. It includes substituting new expression for words, for example, legitimacy to reflect interpretivism originations (McKibbe and Silvia, 2016). While looking for the importance of thoroughness in research, it is found that the utilization of the thought meticulousness in subjective research must be not the same as those in quantitative research by obliging that there is an inclination in subjective research. In this way, new origination meticulousness can be clarified as subjectivity, reflexivity and the social correspondence of talking. Then again, researchers contend that maintaining dependability of an examination report completely relies on upon the issues that are talked about in legitimacy (Smith, 2015). Finding out truth through measures of legitimacy is supplanted by the possibility of dependability. It is solid and sets up trust in the discoveries. With a specific end goal to guarantee legitimacy the initial step ought to be to choose an all around prepared and gifted mediator. A decent arbitrator or facilitator will check individual inclination and desires are at the entryway. Nevertheless, with a decent mediator, it is likewise vital to recognize a decent example. Ensure that members are genuinely individuals from the fragment from which they are enlisted (Hartas, 2015). One noteworthy issue is moral enrolling in subjective research, as information gathered from members who are not illustrative of their fragment will not accomplish appropriate outcomes. Another appropriate technique to elevate legitimacy is to utilize a system known as triangulation. To accomplish this, research is done from more than one point of view. This can appear as utilizing a few mediators, unique areas, and different people assessing similar information (Heale and Twycross, 2015). For the situation for a few candidates, or moment an association may choose to run some concentration amasses in parallel through two different investigates and after that at last think about the outcomes. Legitimacy in subjective research can likewise be checked by a strategy known as respondent approval. This procedure includes testing essential outcomes with members to check whether they are still unique. Another technique through which legitimacy can be built up is to effectively hope to discover elective clarifications (Jensen, 2013). In the event that an analyst can keep out supplementary situations, he will have the capacity to reinforce the legitimacy of the discoveries. With a specific end goal to do that it is essential to make inquiries in an opposite plan. Methods to create legitimacy in subjective research that is talked about can appear to be less substantial and particular than in a portion of the other precise orders. In this situation, solid and appropriate research strategies will ensure that a legitimate level of legitimacy is utilized as a part of subjective research. Reliability Reliability of the research can be considered as the extent while an instrument of the research exhibits consistency as well as stability through the results. There are four categories of reliability measures available in the academic research, which are described below: Test-retest reliability: It is an evaluation of the reliability of the results, which are attained by the test multiple times over a finite period. The results of the test need to be correlated so as to gauge the stability of the test results. For instance, a participant can partake in a test multiple times having an considerable interval. The correlated coefficient would be effective to indicate the results stability. Parallel forms reliability: It is an evaluation of the reliability of the results, which are attained by assessing the data collected from same individuals with different version of tools. However, the tools need to be probing similar knowledge base, skill as well as construct. Two different questionnaires with similar probing capability can be used to conduct the survey with similar participants in a parallel manner. The correlated coefficient would be effective to indicate the results stability. Inter-rater reliability: It is an evaluation of the reliability of the assessment decisions, which are attained from the judges or raters. It is most effective to conduct a practical analysis as in real life the human observers can always interpret the information in a different manner. It is highly useful in the case of subjective consideration of the judgments. Internal consistency reliability: It is an evaluation of the reliability of the different test items, which produces similar results. There are two different categories of internal consistency reliability, which are Average inter-item correlation: It is obtained by taking the average of correlation coefficients of the test items with similar probing ability. Split-half reliability: It is obtained by concluding the correlations between two halves of actual scores. Reliability in quantitative design Reliability has a very distinctive role in all kinds of research project including quantitative research study. In the context of quantitative study, most important evaluation is the quality of the study as far as elicitation of the information is concerned. Reliability of the quantitative study can be considered as the way to evaluate the quality with the aim of generating understanding on the quantitative research. However, according to Hartas (2015) the reliability study of the quantitative research project is often considered as irrelevant and confusing. On the other hand, Elo et al. (2014) has contradicted by stating that the reliability is a very influential factor in the context of designing any quantitative study as it would ensure the quality of the data analysis as well as quality judgment of the study. Darawsheh (2014) have been successful to reveal that the paradigm terms of the research project play a very significant role in judging its own quality level. In the quantitative study, the major criterions for quality are transferability or applicability, dependability or consistency, confirmability or neutrality and credibility. Cook et al. (2013) also supported by stating that the thorough assessment of process notes, data reduction products as well as raw data ensures the achievement the data consistency in any research. The examination of the trustworthiness is quite crucial in order to ensure the reliability of the quantitative research. Cohen, Manion and Morrison (2013) has been successful to produce an effective argument stating that the rules of good science must be redefined at the time of judging the quantitative study. However, Bryman and Bell (2015) also contradicted by stating that reliability has no relevance in the context of quantitative research, as it is highly con cerned of the measurement. Therefore, the study is often considered as wasted while the reliability measures are used. Bryman (2015) has been able to successfully reveal the congruence of reliability as well as extend the conceptualization spectrum of the reliability. It has been disclosed that demonstration of any measures between validity and reliability is sufficient to establish another measure, as the existence of each measure is evidence of other. It has been supported by Ary et al. (2013) with the statement, that reliability can be considered as the consequences of the validity measures. Reliability in qualitative design Reliability has a very distinctive role in all kinds of research project including qualitative research study. In the context of qualitative study, most important evaluation is the quality of the study as far as elicitation of the information is concerned. Reliability of the qualitative study can be considered as the way to evaluate the quality with the aim of generating understanding on the qualitative research. However, according to Hartas (2015) the reliability study of the qualitative research project is often considered as irrelevant and confusing. On the other hand, Elo et al. (2014) has contradicted by stating that the reliability is a very influential factor in the context of designing any qualitative study as it would ensure the quality of the data analysis as well as quality judgment of the study. Darawsheh (2014) have been successful to reveal that the paradigm terms of the research project play a very significant role in judging its own quality level. In the qualitative study, the major criterions for quality are transferability or applicability, dependability or consistency, confirmability or neutrality and credibility. Cook et al. (2013) also supported by stating that the thorough assessment of process notes, data reduction products as well as raw data ensures the achievement the data consistency in any research. The examination of the trustworthiness is quite crucial in order to ensure the reliability of the qualitative research. Cohen, Manion and Morrison (2013) has been successful to produce an effective argument stating that the rules of good science must be redefined at the time of judging the qualitative study. However, Bryman and Bell (2015) also contradicted by stating that reliability has no relevance in the context of qualitative research, as it is highly concern ed of the measurement. Therefore, the study is often considered as wasted while the reliability measures are used. Bryman (2015) has been able to successfully reveal the congruence of reliability as well as extend the conceptualization spectrum of the reliability. It has been disclosed that demonstration of any measures between validity and reliability is sufficient to establish another measure, as the existence of each measure is evidence of other. It has been supported by Ary et al. (2013) with the statement, that reliability can be considered as the consequences of the validity measures. Conclusion The above-description can effectively indicate that the reliability as well as validity plays a significant role in the context of measuring the credibility of the entire research project. In order to maintain the credibility of the research the academic sector heavily depends on the reliability aspects and validity aspects of the research content. The validity represents the degree of accuracy of the measurement of research content. There are three categories of validity, which are construct validity, content validity as well as criterion-related validity. On the other hand, the reliability refers to the consistency of the measures in contents of the entire research project. Reliability of the research can be considered as the extent while an instrument of the research exhibits consistency as well as stability through the results. There are four categories of reliability measures available in the academic research, which are test retest reliability, parallel forms reliability, inter -consistency reliability and inter rate reliability. The above study has been also successful to point out that the reliability and validity are highly influential measures for determining the credibility of both quantitative as well as qualitative research. However, in qualitative research the demonstration of validity can effectively prove the effectiveness of reliability. References Ary, D., Jacobs, L. C., Sorensen, C. 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