Research Report for Philip Kotler’s Incubator on Ayurvedic Center
Dr. Vijay Pithadia
Dr. Vandana S. Parmar
Rationale of the Study
It has been observed that macrocosm is at its selective best, mediating quality control in human reproduction. This is evident from the fact that 50% of the pregnancies with chromosomal frenzy abort fortuitously. As early as 1859, Charles Darwin in his book, "The Origin of Species", stated about natural selection of species. The mankind, homosapiens are the highest evolved and also natures selected best on this earth. Their caretakers are the doctors’ i.e. medical professions. Since time antediluvian health has been an incessant concern of the mankind. Charaka mentioned that diseases and mankind coexisted all along.
In India and perhaps in the whole world, during Arsha period (period of the Rishis), two great universities came into existence, where course included medicine and surgery. One was Banaras and the other was Takshashilla. The cardinal of the medical sections was Sushruta and Atreya, apiece. The universities grew in the Buddhist epoch, producing medical literature not only for students to learn, but also for the teachers to enlighten. During the post - sovereignty era there was a spurt of setting up of private medical colleges without commensurate resources and dictate.
# Systems focus to medical education
A medical institution could be considered as a system. The input is the students; process includes the teaching learning activities and the output is the juvenile medicos, who are the products of an institution. The role of environment in a system is quite significant. The environment in this context is the society at large. We take the students from the society and after training they leave them back to the society. The society would embrace them only if they can take care of it and its needs; hence it is very important that the training imparted to them is a need based one.
A disease is an abnormal condition affecting the body of an organism. It is often construed to be a medical condition associated with specific symptoms and signs. It may be caused by external factors, such as infectious disease, or it may be caused by internal dysfunctions, such as autoimmune. In humans, "disease" is often used more broadly to refer to any condition that causes pain, dysfunction, distress, social problems, or death to the person afflicted, or similar problems for those in contact with the person. In this broader sense, it sometimes includes injuries, disabilities, disorders, syndromes, infections, isolated symptoms, deviant behaviors, and atypical variations of structure and function, while in other contexts and for other purposes these may be considered distinguishable categories. Diseases usually affect people not only physically, but also emotionally, as contracting and living with many diseases can alter one's perspective on life, and their personality.
Death due to disease is called death by natural causes. There are four main types of disease: pathogenic disease, deficiency disease, hereditary disease, and physiological disease.
The definition of a disease includes any pathological process with a specific set of symptoms. The entire body or any part of the body may be affected. Each disease process has an origin, but the source of some diseases is sometimes difficult to determine. General categories of diseases include cancer, viral, bacterial, autoimmune, sexually transmitted, heart, digestive, thyroid, and blood and nerve diseases. Diseases can also be classified as communicable and non-communicable disease.
In many cases, the terms disease, disorder, morbidity and illness are used interchangeably. In some situations, specific terms are considered preferable.
The term disease broadly refers to any condition that impairs normal function. Commonly, this term is used to refer specifically to infectious diseases, which are clinically evident diseases that result from the presence of pathogenic microbial agents, including viruses, bacteria, fungi, protozoa, multi-cellular organisms, and aberrant proteins.
An infection that does not and will not produce clinically evident impairment of normal functioning, such as the presence of the normal bacteria and yeasts in the gut, is not considered a disease; by contrast, an infection that is asymptomatic during its incubation period, but expected to produce symptoms later, is usually considered a disease. Non-infectious diseases are all other diseases, including most forms of cancer, heart, and genetic disease.
Illness and sickness are generally used as synonyms for disease. However, this term is occasionally used to refer specifically to the patient's personal experience of their disease. In this model, it is possible for a person to be diseased without being ill and to be ill without being diseased. Illness is often not due to infection but a collection of evolved responses, sickness behavior, by the body which aids the clearing of infection. Such aspects of illness can include lethargy, depression, anorexia, sleepiness & inability to concentrate.
In medicine, a disorder is a functional abnormality or disturbance. Medical disorders can be categorized into mental disorders, physical disorders, genetic disorders, emotional and behavioral disorders, and functional disorders. The term disorder is often considered more value-neutral and less stigmatizing than the terms disease or illness, and therefore is preferred terminology in some circumstances. In mental health, the term mental disorder is used as a way of acknowledging the complex interaction of biological, social, and psychological factors in psychiatric conditions. However, the term disorder is also used in many other areas of medicine, primarily to identify physical disorders that are not caused by infectious organisms, such as metabolic disorders.
Significance of the study
Aims & Objectives of the study:
The proposed research aims to develop a systematic approach; thereby following objectives can be outlined:
There is no agreement or consensus between writers on how the word should be defined or interpreted. One reason for this is that ‘research’ means different things to different people, for example:
- Children at school research their local environment.
- People research the times of trains from Waterloo to Paris.
- Scientists research the effects of genetically modified food.
- PhD students research and extend knowledge in their subject area.
A useful starting point in answering the question is to see how research is defined in a dictionary. Dictionary definitions use words such as ‘systematic’, ‘careful’, ‘facts’, ‘information’, and ‘investigation’. However, the problem with these definitions is they are not sufficiently rigorous or detailed for our purposes. For example, the word ‘information’ is often used when ‘data’ should be used. From the many definitions offered in research methods textbooks, there is some agreement that research:
- is a process of gathering facts (data)
- is systematic
- reviews, questions and synthesizes existing knowledge
- involves analysis
Research is about process, the approach we take and think the question which arises, synthesis we do, analyze the result and understand the criticality. Superficially the research process appears to be relatively simple - if we carry out the basic steps methodically and carefully, then we should arrive at useful conclusions.
• Research Design
The main different types of research are classified by its purpose, its process and its outcome. These can in turn be broken down further:
- The purpose of the research can be classified as:
- The process of the research can be classified as:
- The outcome of the research can be classified as:
- basic or pure
Purpose of research
- Exploratory research
This is conducted when there are few or no earlier studies to which references can be made for information. The aim is to look for patterns, ideas or hypothesis rather than testing or confirming a hypothesis.
- Descriptive research
This describes phenomena as they exist. It is used to identify and obtain information on the characteristics of a particular issue. The data collected are often quantitative, and statistical techniques are usually used to summaries the information. Descriptive research goes further than exploratory research in examining a problem since it is undertaken to ascertain and describe the characteristics of the issue.
Process of research
There is no consensus about how to conceptualize the actual undertaking of research. There are, however, two main traditions of approaching a research topic – quantitative and qualitative. Each approach demands different research methods.
- Quantitative research
The quantitative approach usually starts with a theory or a general statement proposing a general relationship between variables. With this approach it is likely that the researchers will take an objective position and their approach will be to treat phenomena as hard and real.
· Qualitative research
The alternative tradition is the qualitative approach. Here the investigator views the phenomena to be investigated as more personal and softer.
Outcome of research
- Applied research
Applied research is problem-oriented as the research is carried out to solve a specific problem that requires a decision, for example, the improvement of safety in the workplace, or market research. For our dissertation it is not usually acceptable to carry out applied research as it is very much limited to one establishment or company and we are required to look at issues of wider significance, perhaps to our industry as a whole or to a sector of it. It is important to understand that the dissertation requires carrying out some form of basic research
Basic research is also called fundamentalor pure research, and is conducted primarily to improve our understanding of general issues, without any emphasis on its immediate application. It is regarded as the most academic form of research since the principal aim is to make a contribution to knowledge, usually for the general good, rather than to solve a specific problem for one organization. This may take the form of the following:
- Discovery – where a totally new idea or explanation emerges from empirical research which may revolutionize thinking on that particular topic.
- Invention – where a new technique or method is created. An example of this would be the invention of TQM (total quality management).
- Reflection – where an existing theory, technique or group of ideas is re-examined possibly in a different organizational or social context.
Collecting data is time consuming and expensive, even for relatively small amounts of data. Hence, it is highly unlikely that a complete population will be investigated. Because of the time and cost elements the amount of data we collect will be limited and the number of people or organizations we contact will be small in number. We will, therefore, have to take a sample and usually a small sample.
A probability sampling scheme is one in which every unit in the population has a chance (greater than zero) of being selected in the sample, and this probability can be accurately determined. The combination of these traits makes it possible to produce unbiased estimates of population totals, by weighting sampled units according to their probability of selection. Probability sampling includes:
· Simple Random Sampling,
· Systematic Sampling,
· Stratified Sampling,
· Probability Proportional to Size Sampling,
· And Cluster or Multistage Sampling.
These various ways of probability sampling have two things in common:
- Every element has a known nonzero probability of being sampled and
- Involves random selection at some point.
– Simple Random Sampling & Stratified Sampling shall be used for this research.
Method for Analysis
· Tabulation and Graphical
o Statistical graphics, also known as graphical techniques, are information graphics in the field of statistics used to visualize quantitative data.
Graphical statistical methods have four objectives:
v The exploration of the content of a data set
v The use to find structure in data
v Checking assumptions in statistical models
v Communicate the results of an analysis.
· Trend analysis
In statistics, trend analysis often refers to techniques for extracting an underlying pattern of behavior in a time series which would otherwise be partly or nearly completely hidden by noise. A simple description of these techniques is trend estimation, which can be undertaken within a formal regression analysis.
Today, trend analysis often refers to the science of studying changes in social patterns, including fashion, technology and the consumer behavior.
Both the above method of analysis shall be used by me for the research
· Sources Of Data
· Primary Data Collection
In primary data collection, we collect the data using methods such as interviews and case-studies. The key point here is that the data we collect is unique to us and our research and, until we publish, no one else has access to it. There are many methods of collecting primary data and the main methods include:
- focus group interviews
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The primary data, which is generated by the above methods, may be qualitative in nature (usually in the form of words) or quantitative (usually in the form of numbers or where we can make counts of words used).
Focus group interviews
A focus group is an interview conducted by a trained moderator in a non-structured and natural manner with a small group of respondents. The moderator leads the discussion. The main purpose of focus groups is to gain insights by listening to a group of people from the appropriate target market talk about specific issues of interest.
Observation involves recording the behavioral patterns of people, objects and events in a systematic manner. Observational methods may be:
- structured or unstructured
- disguised or undisguised
- natural or contrived
- Participant, with the participant taking a number of different roles.
Structured or unstructured
In structured observation, the researcher specifies in detail what is to be observed and how the measurements are to be recorded. It is appropriate when the problem is clearly defined and the information needed is specified.
In unstructured observation, the researcher monitors all aspects of the phenomenon that seem relevant. It is appropriate when the problem has yet to be formulated precisely and flexibility is needed in observation to identify key components of the problem and to develop hypotheses. The potential for bias is high. Observation findings should be treated as hypotheses to be tested rather than as conclusive findings.
The term case-study usually refers to a fairly intensive examination of a single unit such as a person, a small group of people, or a single company. Case-studies involve measuring what is there and how it got there. In this sense, it is historical. It can enable the researcher to explore, unravel and understand problems, issues and relationships. It cannot, however, allow the researcher to generalize, that is, to argue that from one case-study the results, findings or theory developed apply to other similar case-studies. The case looked at may be unique and, therefore not representative of other instances. It is, of course, possible to look at several case-studies to represent certain features of management that we are interested in studying. The case-study approach is often done to make practical improvements. Contributions to general knowledge are incidental.
Sampling theory says a correctly taken sample of an appropriate size will yield results that can be applied to the population as a whole. There is a lot in this statement but the two fundamental questions to ensure generalization are:
1. How is a sample taken correctly?
2. How big should the sample be?
The answer to the second question is ‘as large as possible given the circumstances’. It is like answering the question ‘How long is a piece of string’? It all depends on the circumstances. Whilst we do not expect you to normally generalize your results and take a large sample, we do expect that you follow a recognized sampling procedure, such that, if the sample was increased generalization would be possible. You therefore need to know some of the basics of sampling. This will be done by reference to the following example.
The theory of sampling is based on random samples – where all items in the population have the same chance of being selected as sample units. Random samples can be drawn in a number of ways but are usually based on having some information about population members. This information is usually in the form of an alphabetical list – called the sampling frame. Three types of random sample can be drawn – a simple random sample (SRS), a stratified sample and a systematic sample.
Simple random sampling
Simple random sampling can be carried out in two ways – the lottery method and using random numbers.
The lottery method involves:
- transferring each person’s name from the list and putting it on a piece of paper
- the pieces of paper are placed in a container and thoroughly mixed
- the required number are selected by someone without looking
- The names selected are the simple random sample.
This is basically similar to a game of bingo or the national lottery. This procedure is easy to carry out especially if both population and sample are small, but can be tedious and time consuming for large populations or large samples. The random number method involves:
- Allocating a number to each person on the list (each number must consist of the same number of digits so that the tables can be read consistently).
- Find a starting point at random in the tables (close your eyes and point).
- Read off the digits.
- The names matching the numbers are the sample units.
Simple random number sampling is used as the basis for many other sampling methods, but has two disadvantages:
- A sampling frame is required. This may not be available, exist or be incomplete.
- The procedure is unbiased but the sample may be biased. For instance, if the 90 people are a mixture of men and women and all men were selected this would be a biased sample.
Secondary Data Collection
All methods of data collection can supply quantitative data or qualitative data. Quantitative data may often be presented in tabular or graphical form. Secondary data is data that has already been collected by someone else for a different purpose.
Secondary data can be used in different ways:
- We can simply report the data in its original format. If so, then it is most likely that the place for this data will be in our main introduction or literature review as support or evidence.
Most research requires the collection of primary data. Unfortunately, many dissertations do not include secondary data in their findings section although it is perfectly acceptable to do so, providing we have analyzed it. It is always a good idea to use data collected by someone else if it exists – it may be on a much larger scale than we could hope to collect and could contribute to our findings considerably.
This study has some limitations which future research can build on: limitations concerning the implementation issues of, concerning the usages etc.
Expected contributions & coverage:
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