-
Work and employment: Work and employment are important for health and well-being. We know that many people with a mental health condition do not participate in key activities of society, they are socially excluded, and that being in work can reduce the likelihood of this. The right work, with the right support from employers, colleagues, carers and health and care professionals can actually aid recovery for people with mental health problems. No one is intrinsically unemployable, studies show that, given the right conditions and support, the vast majority of people who are out of work and use mental health services want to return to or to start work. However, people with mental health problems do face significant challenges when trying to access employment. Some of these challenges are shared with other people such as the need to adjust the physical environment, or to mitigate language difficulties or the need for extra support or training. However, often these obstacles are less tangible owing to some differences between mental health problems and other impairments:
- They are not immediately obvious and can develop at any time in a person’s life
- They attract fear and prejudice e.g. myths of incompetence or dangerousness
- They typically fluctuate and it can be difficult to predict when these fluctuations will occur
- They affect a person’s ability to negotiate the social, rather than the physical world of work.
Sources:
P2: Discuss ethical issues relating to research to the health and social care sectors.
When conducting any kind of research in health and social care sector it is very important that researchers adopt an ethical approach.
Ethical issues: ethical concerns relate to the rights of participants in research. Being involved in research can effect on the lives of participants. The researcher has a moral obligation to take this into account when carryout their research.
An appropriate methodology is required when conducting research to ensure that results and any conclusions drawn are:
Authentic:
Researcher aims to add new knowledge and understanding either by:
- Generating new data.
- Or interpreting or applying exiting knowledge in a new way.
Research is based on the principle that the researcher is a neutral observer of a phenomenon and does not distort or alter observations made of the natural world.
However due to pressures on a researcher, such as:
- The needs to produce results by a deadline.
- Wanting to gain prestige for career advancement.
- Inappropriate influence of others (e.g. the sponsors of the research).
There may be a temptation to alter results from those actually recorded. This is unethical and can have serious consequences for the researcher involved.
Validity:
Validity depends on what claims are made about a piece of research and how well the claims are supported by the evidence or results from the research. Various factors, listed below, may affect the validity of research.
- The methods used to conduct the research should be appropriate for the purpose of the research.
Validity is that it refers to the accuracy of the data collected. How far the does the data give a clear, authentic and accurate statement of what the researcher intends to identify.
- The presentations of the findings, for example what arguments are used to explain the relationship between the results and the conclusions, assumptions or bias in the arguments presented, ignoring some results and, or over emphasising others.
- The conclusions should be an automatic outcome from a discussion of the results. Conclusions that have been evaluated against evidence from other sources a part from that being reported have greater validity than those that are not evaluated against exiting knowledge and understanding of the subject. Conclusions that have very little relationships with results reported would have very limited, if any validity.
Reliability:
Reliability is about the extents to which the research can be reproduced. Reliable research when repeated by another researcher using exactly the same methods produces the same results. Researchers often test the reliability of equipment used in experiments before they conduct along, complex series of tests. In Labority, experiments may be repeated several times. Once the scientists have perfected their techniques and equipment, an average value may be use, or if the variations between results are unavailable great, there are many measurements may be required and statistical tests applied to the results. It is much more difficult for social scientists to repeat a survey.
There are many factors that can have an impact on health and social care research.
- Who commissions the research:
Funding is very important when conducting large scale health and social care research. However the group that commissions the research can lead to bias, and unreliably of data/findings. For example when doing research outside agency rather than inside the hospital. Research costs money by taking up professionals time, or because require particular equipment and other resources.
It also requires specialised research skills which an organisation may not have either because they are too small or because they do not have sufficient use for such skills.
- The influence of the media:
The public continues to be influenced by the media e.g. internet, newspapers, and TV. Individuals must remember that the main role of the media is to sell (magazines) etc… and make a profit.
The media loves sensationalism and therefore may not always report the full facts and figures from research findings. It is important for researchers to follow ethical codes when conducting research. Although ethical codes are not legislation, there are a number of pieces of legislation that help to guide the conduct of research.
-
Human right act: It is composed of a series of sections that have the effect of codifying the protections in the European Convention on Human Rights into UK law. All public bodies (such as courts, police, local governments, hospitals, publicly funded schools, and others) and other bodies carrying out public functions have to comply with the Convention rights. This means, among other things, that individual can take human rights cases in domestic courts; they no longer have to go to Strasbourg to argue their case in the European Court of Human Rights. The Act sets out the fundamental rights and freedoms that individuals in the UK have access to. They include:
-
Data protection act: The Data Protection Act 1998 seeks to strike a balance between the rights of individuals and the sometimes competing interests of those with legitimate reasons for using personal information. The DPA gives individuals certain rights regarding information held about them. It places obligations on those who process information (data controllers) while giving rights to those who are the subject of that data (data subjects). Personal information covers both facts and opinions about the individual. Anyone processing personal information must notify the Information Commissioner’s Office (ICO) that they are doing so, unless their processing is exempt. Notification costs £35 / year.
-
Policies act: The purposes of this Act are: To declare a national policy which will encourage productive and enjoyable harmony between man and his environment; to promote efforts which will prevent or eliminate damage to the environment and biosphere and stimulate the health and welfare of man; to enrich the understanding of the ecological systems and natural resources important to the Nation; and to establish a Council on Environmental Quality.
-
Codes of conduct: The Equality Act is the most significant piece of equality legislation for many years. It simplifies streamlines and strengthens the law. It gives individuals greater protection from unfair discrimination and makes it easier for employers and companies to understand their responsibilities. It also sets a new standard for those who provide public services to treat everyone, with dignity and respect. In line with our statutory powers, we have produced Codes of Practice on Employment, Services and Equal Pay. The main purpose of the Codes of Practice is to provide detailed explanations of the provisions in the Act and to apply legal concepts in the Act to everyday situations. This will assist courts and tribunals when interpreting the law and help lawyers, advisers, trades union representatives, human resources departments and others who need to apply the law. As with the Act, the Codes apply to England, Scotland and Wales. The Codes set out clearly and precisely what the legislation means. They draw on precedent and case law and explain the implications of every clause in technical terms. These statutory codes are the authoritative source of advice for anyone who wants a rigorous analysis of the legislation's detail. For lawyers, advocates and human resources experts in particular, they will be invaluable.
For this unit my hypothesis is:
“Many students are choosing to go into full time employment after A_levels rather than university as they do not want to have to re pay a student loan.
It is extremely important that I carry out my research in an ethical fashion throughout. I need to ensure the following ethical consideration.
Theoretically, ethics is concerned with moral principles and values. Practically, these principles and values inform a conceptual framework for decision making. Ethically responsible decisions, at individual and group levels, can go far to minimize society's exposure to hazardous agents and, thereby, promote a healthy environment.
Environmental health advocates call for the ethical right of every person to live and work in an environment free of harmful chemicals. Advocates also seek to promote social justice and responsibility by redressing the disproportionate burden of toxic exposures carried by children and by people at the lower socioeconomic margins of local, national, and global communities. The right to a healthy environment can also be extended to wildlife and entire ecosystems.
How can we - whether as individuals, organizations, governments, or corporations - make our decisions align with values and principles that promote and sustain healthy people, communities, and environments? The sections below provide resources on specific topics that we hope will provide useful information as well as inspiration. We recommend beginning with the section on the precautionary principle, which provides a comprehensive framework for preventing pollution and addressing scientific uncertainty.
P3: compare the difference research methodologies for health and social care
Introduction: in this section I am going to compare methodologies which can be used during research in health and social care. I will discuss the advantages and disadvantages to some of research methodologies.
-
Quantitative data: this is sociological evidence expressed in the form of statistics. This kind of data tries to measure social behaviour and express it numerically. It can be used to identify trends, patterns and links between different social factors like class and gender.
-
Qualitative data: this is data that is expresses in words rather than numbers. Qualitative data tries to express the meanings social actors hold about their social world, usually in the forms of their own words.
Examples of qualitative data and quantitative data:
-
Quantitative data includes official statistics of crime rates.
-
Qualitative data includes media reports, letters and diaries.
There are a number of advantages of quantitative data which are:
-
Test hypothesis: numerical data allows hypothesis to be tested.
-
Study trends: numerical data allows for trends to be identified.
-
Reliable: quantitative methods can be repeated by other researchers with constituent results.
-
Make comparisons: numerical data is easy to compare.
-
Establish causality: numerical data allows casualty to be shown.
-
Easy to analyse: numerical data is easy to analyse.
-
Representative: large scale social survey methods aim to generalise to larger group to which the sample belongs.
-
Objective: the scientific methods of quantitative research mean that the investigations should be free from personal and political opinion and prejudice.
However there are also a number of disadvantages for quantitative data.
-
Lack of depth: quantitative methods sometime do not give people opportunity to say what they really mean.
-
No meaning: any meanings and feelings are hidden beside the numerical data.
-
No focus on the individual: data is summarised collectively and does not look at individual responses.
-
Distorts reality: as data is summarised collectively and statistically. The true picture can be distorted.
- When comparing a quantitative and qualitative data, qualitative data also has its advantages.
-
Close to reality: individual responses give a good reflection of how people feel about issues, often reflecting reality.
-
More personal: qualitative data focuses on individual responses.
-
In depth feelings and meanings: qualitative research tries to achieve what is called “veteran” _ they try and see the word through the eyes of those involved.
-
Health workers not imposing their view of the word: individual responses are reflected in the data, rather than a collective summary.
-
Rich description: detailed responses can be obtained from individuals.
- However unlike quantitative data, qualitative data has the following disadvantages:
-
Subjective: outcome of research can be affected by personal opinions, experiences and biases of researcher.
-
Unreliable: qualitative research methods e.g. observations often depend on personal relationships being established between the respondent and the researchers and are difficult to be repeated by other researchers with similar results.
-
Not measurable: qualitative data includes feelings and opinions which are not measurable statistically.
-
Not scientific: qualitative data research methods do not follow scientific methodology.
-
Cannot generalise: samples studied by qualitative methods tend to be small because the methods are more time consuming and therefore the sample is less likely to generalise to the larger group to which the sample belongs.
-
Mis_inteppration: researchers involved in qualitative research methods e.g. observations may mis_interpret what they see and hear.
Researchers can base their findings on secondary data or primary data:
-
Secondary data: exits prior to and independent from the researchers own research.
-
Primary data: data collected by the researchers themselves. Fresh and original data.
- What are the advantages and disadvantages of secondary data?
Sources of primary data:
I shall now discuss the advantages and disadvantages of the various primary data sources in more detail.
-
Questionnaires: is a tool for measuring attitudes, beliefs and stereotypes that people hold toward issues, topics and other people.
Advantages:
- Get to know exactly what you want.
- Provides quantitative data-easy to analyse.
- Larger samples can be studied.
- Replicable and reliable.
Disadvantages:
- People may not answer truthfully.
- Researcher bias in the framing of the question.
- May not have them all returned.
-
Interviews: A meeting of people face to face, esp. for consultation.
Advantages:
- Get to know more detail than with questionnaires.
- Can provide both quantitative and qualitative data.
- Answers can be followed up with more questions to gain more information.
- Questions can be clarified if they are not fully understood.
Disadvantages:
- Can be time consuming.
- Researchers bias in the framing of questions.
- Presence of interviewer may affect the responses.
-
Laboratory experiments: the Laboratory experiments is a controlled experiment focuses on one aspect of social behaviour.
Advantages:
- Replicable and reliable.
- Control over independent variable.
- Controlled environment can establish cause and effect relationships.
Disadvantages:
- Artificial environment.
- Ethical issues.
- Behaviour changes as a result of the researcher presence or the knowledge of being the subject of an experiment. Hawthorne effect.
-
Field experiments: sometimes the researcher will adapt or create a real-life situation to test a research aim. Although they will not be able to control all the possible influences on the outcome of the experiment, one or more variables will be controlled.
Advantages:
- Results generalizable to the real world.
- Real life situations in natural settings.
- Researchers can focus on specific aspects of social life.
Disadvantages:
- Results on applicable to the field studied.
- Lack of control over variables.
- Difficult to repeat in the same condition.
- Ethical issues.
-
Participant observations: this research methods involves the researcher joining a social group and by participating in its activities, directly experiencing their social world. Used by interpertivist researcher, the emphases is on uncovering the meanings social actors hold about their social world.
Advantages:
- Study of a one or small number of groups.
- Possible to study deviant groups.
- Appropriate for non_literate societies.
Disadvantages:
- Getting too involved.
- Ethical issues.
- Difficulty of recording data.
- Time consuming.
-
Non_participant observations: with this method, the researcher stands back from the group they are observing and does not participate in its activities, simply observing what is happening. The group is being observed May or may not be aware of the presence of the observer.
Advantages:
- More accurate than asking people about their behaviour.
- Observe behaviour in natural environment.
- Small scale detailed research.
Disadvantages:
- Only possible to study small samples.
- Ethical issues.
- Difficultly of recording data.
- Time consuming.
-
Case studies: these are one-off studies of a particular sample of social behaviour, often involving a range of different research methods.
Advantages:
- Study of a one or small number of groups.
- Obtain in depth information of small group.
Disadvantages:
- Getting too involved.
- Ethical issues.
- Difficulty of recording data.
- Time consuming.
Covert observation: observation is covert when those being observed are not aware of the research intention of the researcher. They may be aware of the researcher presence but not of the real reason for observing the group.
Overt observation: observation is overt when the group being observed is aware of the presence and intention of the researcher. The research purpose is usually understood those being observed.
The information above, clearly highlight the fact that there are a variety of different methodologies aware able to gather health and social care information, all of these have their advantages and disadvantages.
P4: plan a research project.
M2: justify the research methodologies chosen for the project.
My hypothesis is: “Many students are choosing to go into full time employment after A_levels rather than university as they do not want to have to re pay a student loan.”
In order to for any research to be successful the researcher must have a research plan. Before starting the research he/she must consider the following:
7 Different types of sampling
Snowball sampling is a method in which a researcher identifies one member of some population of interest, speaks to him/her, then asks that person to identify others in the population that the researcher might speak to. This person is then asked to refer the researcher to yet another person, and so on.
Snowball sampling is very good for cases where members of a special population are difficult to locate. For example, several studies of Mexican migrants in Los Angeles have used snowball sampling to get respondents. The method also has an interesting application to group membership - if you want to look at pattern of recruitment to a community organization over time, you might begin by interviewing fairly recent recruits, asking them who introduced them to the group. Then interview the people named, asking them who recruited them to the group. The method creates a sample with questionable representativeness. A researcher is not sure who is in the sample. In effect snowball sampling often leads the researcher into a realm he/she knows little about. It can be difficult to determine how a sample compares to a larger population. Also, there's an issue of who respondents refer you to - friends refer to friends, less likely to refer to ones they don't like, fear, etc.
This method of sampling is at first glance very different from SRS. In practice, it is a variant of simple random sampling that involves some listing of elements - every nth element of list is then drawn for inclusion in the sample. Say you have a list of 10,000 people and you want a sample of 1,000.
Creating such a sample includes three steps:
- Divide number of cases in the population by the desired sample size. In this example, dividing 10,000 by 1,000 gives a value of 10.
- Select a random number between one and the value attained in Step 1. In this example, we choose a number between 1 and 10 - say we pick 7.
- Starting with case number chosen in Step 2, take every tenth record (7, 17, 27, etc.).
- Random sampling:
The most widely known type of a random sample is the simple random sample (SRS). This is characterized by the fact that the probability of selection is the same for every case in the population. Simple random sampling is a method of selecting n units from a population of size N such that every possible sample of size and has equal chance of being drawn. An example may make this easier to understand. Imagine you want to carry out a survey of 100 voters in a small town with a population of 1,000 eligible voters. With a town this size, there are "old-fashioned" ways to draw a sample. For example, we could write the names of all voters on a piece of paper, put all pieces of paper into a box and draw 100 tickets at random. You shake the box, draw a piece of paper and set it aside, shake again, draw another, set it aside, etc. until we had 100 slips of paper. These 100 form our sample. And this sample would be drawn through a simple random sampling procedure - at each draw, every name in the box had the same probability of being chosen.
Stratified Random Sampling
In this form of sampling, the population is first divided into two or more mutually exclusive segments based on some categories of variables of interest in the research. It is designed to organize the population into homogenous subsets before sampling, then drawing a random sample within each subset. With stratified random sampling the population of N units is divided into subpopulations of units respectively. These subpopulations, called strata, are non-overlapping and together they comprise the whole of the population. When these have been determined, a sample is drawn from each, with a separate draw for each of the different strata. The sample sizes within the strata are denoted by respectively. If a SRS is taken within each stratum, then the whole sampling procedure is described as stratified random sampling.
In some instances the sampling unit consists of a group or cluster of smaller units that we call elements or subunits (these are the units of analysis for your study). There are two main reasons for the widespread application of cluster sampling. Although the first intention may be to use the elements as sampling units, it is found in many surveys that no reliable list of elements in the population is available and that it would be prohibitively expensive to construct such a list. In many countries there are no complete and updated lists of the people, the houses or the farms in any large geographical region
Availability sampling is a method of choosing subjects who are available or easy to find. This method is also sometimes referred to as haphazard, accidental, or convenience sampling. The primary advantage of the method is that it is very easy to carry out, relative to other methods. A researcher can merely stand out on his/her favorite street corner or in his/her favorite tavern and hand out surveys. One place this used to show up often is in university courses. Years ago, researchers often would conduct surveys of students in their large lecture courses. For example, all students taking introductory sociology courses would have been given a survey and compelled to fill it out. There are some advantages to this design - it is easy to do, particularly with a captive audience, and in some schools you can attain a large number of interviews through this method.
The primary problem with availability sampling is that you can never be certain what population the participants in the study represent. The population is unknown, the method for selecting cases is haphazard, and the cases studied probably don't represent any population you could come up with.
However, there are some situations in which this kind of design has advantages - for example, survey designers often want to have some people respond to their survey before it is given out in the "real" research setting as a way of making certain the questions make sense to respondents.
Social research is often conducted in situations where a researcher cannot select the kinds of probability samples used in large-scale social surveys. For example, say you wanted to study homelessness - there is no list of homeless individuals nor are you likely to create such a list. However, you need to get some kind of a sample of respondents in order to conduct your research. To gather such a sample, you would likely use some form of non-probability sampling. To reiterate, the primary difference between probability methods of sampling and non-probability methods is that in the latter you do not know the likelihood that any element of a population will be selected for study.
Quota sampling is designed to overcome the most obvious flaw of availability sampling. Rather than taking just anyone, you set quotas to ensure that the sample you get represents certain characteristics in proportion to their prevalence in the population. Note that for this method, you have to know something about the characteristics of the population ahead of time. Say you want to make sure you have a sample proportional to the population in terms of gender - you have to know what percentage of the population is male and female, then collect sample until yours matches. Marketing studies are particularly fond of this form of research design. The primary problem with this form of sampling is that even when we know that a quota sample is representative of the particular characteristics for which quotas have been set, we have no way of knowing if sample is representative in terms of any other characteristics. If we set quotas for gender and age, we are likely to attain a sample with good representativeness on age and gender, but one that may not be very representative in terms of income and education or other factors. Moreover, because researchers can set quotas for only a small fraction of the characteristics relevant to a study quota sampling is really not much better than availability sampling. To reiterate, you must know the characteristics of the entire population to set quotas; otherwise there's not much point to setting up quotas.
Purposive sampling is a sampling method in which elements are chosen based on purpose of the study. Purposive sampling may involve studying the entire population of some limited group (sociology faculty at Columbia) or a subset of a population (Columbia faculty who have won Nobel Prizes). As with other non-probability sampling methods, purposive sampling does not produce a sample that is representative of a larger population, but it can be exactly what is needed in some cases - study of organization, community, or some other clearly defined and relatively limited group.
My research plan summarised:
Hypothesis: “Many students are choosing to go into full time employment after A_levels rather than university as they do not want to have to re pay a student loan.”