Mental health practice - Essay Example

Qualitative research is typically taken to be exemplified by the social survey and by experimental investigations. Qualitative Research tends to be associated with participant observation and unstructured in depth interviewing. Qualitative data consist of words and observations, not numbers. As with all data, analysis and interpretation are required to bring order and understanding. This requires creativity, discipline and a systematic approach. It is often called content analysis. The aim of Qualitative Data Analysis is that of collating data collected and making it applicable to research and development. The target audience when intelligently tapped yields a plethora of information which needs to be systematically and logically disseminated, sifted and made into a coherent whole. The entire process is not empirical - but highly logical. This data is primarily narrative. It is derived from a number of sources, individualistic and groups. It comprises either spoken words or written words, sometimes both together. Data collection through individuals and groups maybe done through objective Multiple Choice Questions (MCQs) or Frequently Asked Questions (FAQs). There may also be comments, or first hand accounts, eliciting information through phrases or textual paragraphs or by way of individuals one on ones. The last named elicit data in the form of summary or transcription from the spoken word. The same methodology applies to group discussions wherein target of focus groups are subject to detailed questionnaires which provide enormous amount of data. Multiple Choice Questions, Frequently Asked Questions, comments, or first hand accounts eliciting information through phrases or textual paragraphs or by way of Group Discussions all form part of the same methodology Jottings, diary entries, notes and sub notes, observations and journalistic writings are also invaluable sources of data collections. Watch and wait methods which provide field notes, and descriptive accounts are indispensable to data collection. Again, the use of the written word from documents, articles, reports, newspaper clippings are of immense help to the data collector. First hand experiences and stories are again of ample help. Lastly, to lend a semblance of realism one relies on case studies to provide that extra flavour of day to day life. Once the data is in hand, the next step is to make it useful. It is not that all the data collected is of sufficient utility or valuable to be used but it has to be properly read and re read before requisite information can be garnered from it. It is obvious that the spoken word depends largely on the mode of answering questions as well as the mood of both the persons asking and the one answering. Thus a degree of subjectivity creeps in the oral word while the written answers dispense with subjectivity. The data once identified is then analysed to be made attributable to the purpose of collection. In other words, it is made to focus on the job at hand through topics, period of time as well as particular event. Similarly, the data collated in terms of cases individuals or groups runs the risk of the age factor being misrepresented which amounts to a great deal of confusion. In such a scenario greater credence is given to the written word. Often after analysis if it is found that relevant data is rather meager, then data collection has to be done all over again. This can get very tedious. The researcher needs to have an inherent patience while doing field work. Collection of qualitative data can be very difficult and often confusing. An important aspect of collating and analysing data is creating a link between categories created through the commonality of patterns and other similarities. The ultimate object is to garner as much information and similar data as possible Sifting through data obtained by both means, oral and written, individual or group, is a humongous task but is the hallmark of accuracy. It is not enough to simply obtain data, from all the sources available as mentioned above, but to embark on the task of accurately logically interpreting all that collected and making it applicable as an indispensable tool of research. To that effect, the entire gamut of data has to be interpreted through key words and phrases through relationships and words of similar meanings, through antonyms and synonyms, acronyms and abbreviations, through pneumonyms and other similarities to arrive at effective analysed. Inaccuracy, subjectivity, mood swings, circumstances and most importantly the inclination to produce and procure correct useable data are all vagaries with which the spoken word, both for individuals and groups are associated. In general terms larger credibility of existing written, or elicited written data belies the importance of checking and rechecking data collated. Prime Facie all that is collected is not accurate and does not always hold good. But at the same time care should be taken to ensure that bias does not creep in to remove and disregard carefully garnered data. Reproducing the Qualitative data collected after analyzing it entails a huge amount of moral consequences. The amount of confidentiality to be maintained as also the relevance of the data at the time of analysis and final report, even to a great extent the authenticity of the data collected is solely dependent on the researcher. All researchers have to bear in mind the incredible moral consequences of what is constructed through qualitative research. Working with qualitative data is a rich and enlightening experience. It is both a science and art. It involves critical, analytical thinking and creative innovative perspectives (Patton 1990). Quantitative research is the systematic scientific investigation of quantitative properties and phenomena and their relationships. Quantitative research is widely used in both the natural and social sciences.The objective of quantitative research is to develop and employ mathematical models, theories and hypotheses pertaining to natural phenomena. The process of measurement is central to quantitative research because it provides the fundamental connection between empirical observation and mathematical expression of quantitative relationships. Quantitative research is generally approached using scientific methods which include: The generation of models, theories and hypotheses The development of instruments and methods for measurement Experimental control and manipulation of variables Collection of empirical data Modelling and analysis of data Evaluation of results Quantitative research is often an iterative process whereby evidence is evaluated, theories and hypotheses are refined, technical advances are made, and so on. Virtually all research may involve a combination of quantitative and other analytic approaches and methods. Quantitative research is often contrasted with qualitative research. Although a distinction is commonly drawn between qualitative and quantitative aspects of scientific investigation, it has been argued that the two go hand in hand. Qualitative research is often used to gain a general sense of phenomena and to form theories that can be tested using further quantitative research. Although quantitative investigation of the world has existed since people first began to record events or objects that had been counted, the modern idea of quantitative processes have their roots in Auguste Comte's framework. Statistical methods are used extensively within fields such as economics, social sciences and biology. Quantitative research using statistical methods typically begins with the collection of data based on a theory or hypothesis, followed by the application of descriptive or inferential statistical methods. Causal relationships are studied by manipulating factors thought to influence the phenomena of interest while controlling other variables relevant to the experimental outcomes. In the field of health, for example, researchers might measure and study the relationship between dietary intake and measurable physiological effects such as weight loss, controlling for other key variables such as exercise. Quantitatively based opinion surveys are widely used in the media, with statistics such as the proportion of respondents in favor of a position commonly reported. In opinion surveys, respondents are asked a set of structured questions and their responses are tabulated. In the field of climate science, researchers compile and compare statistics such as temperature or atmospheric concentrations of carbon dioxide. Empirical relationships and associations are also frequently studied by using some form of General linear model, non-linear model, or by using factor analysis. A fundamental principle in quantitative research is that correlation does not imply causation. This principle follows from the fact that it is always possible a spurious relationship exists for variables between which covariance is found in some degree. Associations may be examined between any combination of continuous and categorical variables using methods of statistics. Measurement is often regarded as being only a means by which observations are expressed numerically in order to investigate causal relations or associations. However, it has been argued that measurement often plays a more important role in quantitative research. Quantitative research may involve the use of proxies as stand-ins for other quantities that cannot be directly measured. Thomas Kuhn (1961) argued that results which appear anomalous in the context of accepted theory potentially lead to the genesis of a search for a new, natural phenomenon. He believed that such anomalies are most striking when encountered during the process of obtaining measurements, as reflected in the following observations regarding the function of measurement in science: When measurement departs from theory, it is likely to yield mere numbers, and their very neutrality makes them particularly sterile as a source of remedial suggestions. But numbers register the departure from theory with an authority and finesse that no qualitative technique can duplicate, and that departure is often enough to start a search (Kuhn, 1961, p. 180). ' Psychometrics is the field of study concerned with the theory and technique for measuring social and psychological attributes and phenomena. This field is central to much quantitative research that is undertaken within the social sciences. Quantitative methods are research methods dealing with numbers and anything that is measurable.Counting and measuring are common forms of quantitative methods. The result of the research is a number, or a series of numbers. These are often presented in tables, graphs or other forms of statistics. In psychology, the use of one or other type of method has become a matter of controversy and even ideology, with particular schools of thought within each discipline favouring one type of method and pouring scorn on to the other. Advocates of quantitative methods argue that only by using such methods can the social sciences become truly scientific; advocates of qualitative methods argue that quantitative methods tend to obscure the reality of the social phenomena under study because they underestimate or neglect the non- measurable factors, which may be the most important. The modern tendency (and in reality the majority tendency throughout the history of social science) is to use eclectic approaches. Quantitative methods might be used with a global qualitative frame. Qualitative methods might be used to understand the meaning of the numbers produced by quantitative methods. Using quantitative methods, it is possible to give precise and testable expression to qualitative ideas. Ontology is the department of metaphysics concerned with the nature of being. Ontological assumptions will therefore be completely influenced by faith. Such assumptions quite naturally form the basis of positivism and positivist approaches to any research. Positivism is the philosophical system recognizing only positive facts and observable phenomena. It naturally accepts. Epistemology is the theory of knowledge or grounds of knowledge. Thus, epistemological assumptions form the basis of interpretivist approach to research. Epistemological assumptions will challenge every ontological belief and will want to question every positivist approach of research. While ontological assumptions will naturally believe in the goodness of a product or process, epistemological assumptions will want to interpret every aspect of the same. Ontological assumptions will not question the theoretical basis of a concept or a product or even a research process. The basis of such assumptions is good faith or a simple faith in the data. Epistemological assumptions will want to get to the bottom of the matter and will raise questions about the theoretical basis of the assumption. They want to understand and interpret everything in a framework of methodology Conventional science is based on 'rational positivist' thought. This includes the presumptions that there is a 'real world'. Data can be gathered by observing it. This data is factual. It is truthful and unambiguous. The 'post-positivist', 'interpretivist' philosophy, on the other hand, asserts that these assumptions are unwarranted, According to this philosophy 'facts' and 'truth' are a wild supposition and 'objective' observation is impossible, and that the act of observation-and- interpretation is dependent on the perspective adopted by the observer. Interpretivists criticise even the physical scientists for the narrowness of their assumptions. Their criticisms hold some truth particularly strongly in the social sciences, where the objects of study are influenced by so many factors. These factors are extremely difficult to isolate and control in experimental laboratory settings. The interpretivist approach confronts the difficulties presented by the nature of the research domain, and in particular: the intangibility of many of the factors and relationships; the inherent involvement of the researcher within the research domain; the dependence of outcomes on the researcher's perspective of: the selection and definition of the research domain; the selection and rendition of existing theory; the definition of the research question; the design of the research framework; the selection, definition and operationalisation of variables; and the measurement of variables. This builds up to a requirement that multiple interpretations of the same phenomena must be allowed for, and that no truth is attainable. The epistemological assumption is guided by the interpretivist approach questions everything around. If it is, why is it, how is it Their answers are sought in the framework of methodology to build up the knowledge base of everything. Any idea or research or product or concept can be approached by the positivist attitude which forms the basis of ontological belief or an interpetivist attitude which forms the basis of epistemological approach. It is like two ways of looking at a coin. The positivist approach is guided by the ontological assumption that everything is natural and good and therefore cannot or should not be questioned. The interpretivist approach is guided by the Epistemological assumption which measures the truth of everything in its own methodology and clarifies the knowledge content of the research. The Care Programme Approach (CPA) was introduced in 1991 and is intended to be the basis for the care of people with mental health needs outside hospital. It applies to all people with serious mental health problems who are accepted as clients of specialist mental health services. The CPA also comes into play while someone is a psychiatric hospital in- patient and creates the framework for discharge planning and aftercare. The CPA framework can be used in relation to aftercare which has to be provided in accordance with Section 117 of the Mental Health Act, but the statutory health and social services agencies need specifically to ensure that their Section 117 duties are being fulfilled within any CPA care plan agreed. The CPA also links in with Care Management practised by local authority social services departments, where social services departments are undertaking their duties of assessing needs and purchasing appropriate services, under the NHS and Community Care Act. If the relevant bodies are co-operating, and have consistent procedures, then the CPA, Care Management and (where applicable) Section 117 duties, can all often be integrated into a single process. The CPA process has four stages: 1. A systematic assessment of the person's healthcare and social care needs 2. The development of a care plan agreed by all involved, including the person her/himself and any informal carers, as far as this is possible, and addressing the assessed needs 3. Identifying a key worker, to be the main point of contact with the person concerned and to monitor the delivery of the care plan 4. Regular review of the person's progress and the care plan, with agreed changes to the plan as appropriate. Not everyone who is client of specialist psychiatric services will require an equally full or complex CPA approach. In reality, four levels of the CPA exist: Minimal CPA, which is appropriate for people who: have few healthcare needs need low levels of social support are likely to remain stable. Often the person concerned will only be in touch with the key worker, and the care plan will simply define the expected nature and frequency of contact with that key worker, and set a review date. More Complex CPA, for people who: need a medium level of support may need further continuing assessment are less likely to remain stable. In these cases, the person is likely to receive support from more than one professional discipline, and the care plan will be more complex. Full, multi-disciplinary CPA, for people who: have a severe mental illness are not functioning well socially may represent some risk to themselves or others may be unstable and volatile. The care plan is likely to be very detailed, with arrangements for continuing monitoring , and special attention is required to communication between the various professionals involved. Supervision Register. Where a person represents a significant risk to themselves or others, they may be placed on the Supervision Register. This is a form of at risk register, which aims to ensure that someone at risk is actively followed-up, and to reduce the chances that such a person will slip through the community care net. The CPA exists to ensure that several, perhaps obvious, principles of good practice are realised. These features include: a multi-disciplinary approach to community care provision, following psychiatric admission systematic planning, recording and reviewing of the person's care and support a universal top level system, which integrates other requirements such as Section 117 aftercare, Care Management and the Supervision Register the involvement of users and carers in the creation and review of the care plan identifying a lead person [key worker] to take responsibility for overseeing the delivery of the care plan flexibility of service provision, responding to the person's changing needs ensuring a proactive approach is taken to offering support, in an attempt to ensure that people do not lose touch with services which they have been assessed as needing a swift and appropriate response if a person's mental health deteriorates. Conclusion: Much of the review will have to be measured quantitatively. There can be tests and measurements taken to determine or review the condition of the person whose mental health is affected. The quantitative tests will give epistemological information about the health parameters of the mental patient. That will decide how the patient was before being put on CPA, how he has improved, what the various parameters are as far as mental health records show. But qualitative research, including data collection and observation followed by ontological understanding will have to be called upon to understand value based and therapeutic relationships. After all value based therapy forms the most important underlying factor of any Care Programme Approach. Read More