Explaining The Ontological And Epistemological Assumptions Psychology Essay

The processes underlying systematic research are said to be directed by a series of basic beliefs and values. These are so called ‘Inquiry paradigms’, the basic belief systems or world views of the researcher (Goulding, 2002), frame the course of research and its outcomes. Guba & Lincoln made a significant contribution in articulating four differing worldviews of research – positivist, post positivist, critical, and constructivist- based on their ontological, epistemological and methodological assumptions (Hills and Mullet, 2000). These assumptions are not logically defensible but individualistic. Guba (1990) stated “the quantitative inquiry approach is rooted in realist ontology,” comparatively to the qualitative inquiry paradigm, which is based on different ontological and epistemological beliefs.

Wand and Weber (1993:220) refer to ontology as “a branch of philosophy concerned with articulating the nature and structure of the world”. Ontology primarily addresses the question ‘what exists?” and attempts to comprehend the kinds and structures of objects, properties, events, processes and relationships in every area of reality (Smith, 2003). The researcher’s ontological assumption, a personal assumption which is impossible to refute empirically, is their assumed answer to the research question by concept-definitions. That is to say, what the researcher decides they are studying or what should be studied, may that be an entity, agent, behaviour etc and the way in which they perceive the reality of what is being measured. It is the research question or hypothesis in its simplest form. Researchers have to assume that the world they investigate is a world populated by human beings who have their own thoughts, interpretations and meanings. In the MRC-CFAS survey, the concept of ldquocognitive impairment, as an indicator of dementia is a social construct of which the researcher must decide what ‘cognitive function’ consists of and the meanings behind it based on their personal reflection of beliefs about the nature of cognitive function. Researchers have developed their own language and lexicons to help them store and communicate Dementia knowledge, which are characterized by a significant amount of implicit knowledge.

Underlying ontology is epistemology, beliefs about knowledge acquisition. The acquisition of knowledge depends on the interaction between the knower (inquirer) and the known (the object of inquiry) (Tavakoi et al, 2004). Particular ontological beliefs lead us to make particular epistemological assumptions. Epistemological is concerned with deciding what kinds of knowledge are possible, therefore valid and appropriate within our ‘reality’ and often is focused around on propositional knowledge. It separated beliefs and conjecture with acquired knowledge. Epistemology asks the questions ‘What are its sources?’, ‘What is its structure, and what are its limits?’, ‘How can we use our reason, others, and other resources to acquire knowledge’. There are two classical epistemological positions. Empiricism places primary focus on what we experience, or a posteriori knowledge. Empirical processes collect data about the world through our five senses and build up a body of knowledge through a process of induction. Rationalism on the other hand places primary focus on rational reflection. In the MRC-CFAS study, the Researchers measure data with an objectivist epistemology, to find causality, effects, and explanations. The survey method uses repeatable, falsifiable one way mirror observation, in which the researcher is independent and detached from the unit being measured, so they may predict events and test the hypothesis. There is a determined the criteria for knowledge, with quantifiable scales by constructing a fixed instrument (a set of questions). They do not allow the questions to emerge and change, so the object can be researched without being influenced by the researcher. Any possible researcher influence can be anticipated, detected, and accounted for (controlled) i.e. standardisation.

Concisely define: (a) non-response bias, (b) sampling error, (c) validity and (d) reliability.

(5% marks each)

In surveys with low response rates, non-response bias can be a major concern. Non-response refers to the failure to obtain observations on some elements selected for the sample due to unit or item non response (Kish, 1965:532). Non-response may be due to (1) the inability to make contact with the selected (eligible) sample unit; (2) unwillingness of the sampled unit to participate in the survey and (3) other reasons, for example language barrier or some other incapacity . The likelihood for non-response is further compounded when there are multiple stages or components of response, e.g., screener interviews, multiple respondents associated with a case, or more than one waves of data collection (Bose 2001) .Incomplete response may introduce uncertainty as to the accuracy of the findings and raise questions as to whether it is desirable to extrapolate over the non-response element of the survey. Response rates are generally used as indicators of potential bias as low response rates increase the possibility that survey error will bias results. Shiekh and Mattingly, 1981 account that a possible bias as a result of the lost information has to be investigated and its extent estimated.

Sampling error compromises the differences between the sample and the population that are due to the sample that has been selected. By increasing the sample size, the sampling error can be minimized (Erzberger, 1998) A sample is expected to mirror the population from which it comes, however, there is no guarantee that any sample will be precisely representative of the population. Chance may dictate that a disproportionate number of untypical observations will be made.

The two most important aspects of precision are reliability and validity. Validity is the extent to which a test measures what it was intended to measure. It is objective and refers the degree to which an observed result can be relied upon and not attributed to random error in sampling and measurement. explicit diagnostic criteria and rule-based classifications, like ICD-10. Internal validity, External Validity, Construct validity, and Conclusion Validity. Validity refers to the agreement between the value of a measurement and its true value the degree to which an observed result, such as a difference between 2 measurements, can be relied upon and not attributed to random error in sampling and measurement.

Reliability refers to the reproducibility of a measurement. You quantify reliability simply by taking several measurements on the same subjects. Poor reliability degrades the precision of a single measurement and reduces your ability to track changes in measurements in the clinic or in experimental studies.

Identify and describe the different types of non-response bias in the study. (10% marks)

There are two types of non-response shown in the MRC CFA study: item and unit non-response. Item non-response occurs when certain questions in a survey are not answered by a respondent. The problem of non-response can be especially important for the population study of cognitive status in the elderly because cognitive compromise is a predictor of non-response. Subjects with dementia are less likely to comply. Non response bias within this study was further confounded by the use of proxies to answer questions. Cross sectional studies often underestimate the true burden of disease. In the MRC CFA paper, this was often deemed by the interviewer acting as an instrument. Unit non-response takes place when a randomly sampled individual cannot be contacted or refuses to participate in a survey. The bias occurs when answers to questions differ among the observed and non-respondent items or units.

What steps have the researchers taken to limit non-response bias? (10% marks)

In the screening stage, stratified random populations, representative of a cross section of the overall population in excess of 65 years were studied, using age standardisation. Participants within the centres were interviewed within their own home or the institution in which the resided. Participants were randomly selected to form a subsample (20%) reflective of the stage 1, the baseline screen of the population. This was referred to as the ‘prevalence screen’. As subjects were selected randomly and not so that were information-rich, this limited selection bias. This would have been referred to as being selected through “snowball” or “chain sampling” (Patton, 1990), which “identifies cases of interest from people who know people who know people who know what cases are information-rich, that is, good examples for study, good interview subjects” (Patton, 1990, p. 182).Post-survey weighting adjustments in an attempt to compensate for non-response error. Investigation into the characteristics of those lost to follow-up after initial enrolment was not reported by the other selected studies.

How representative are the estimates of the prevalence of cognitive impairment reported in this paper? (10%marks).

. The MRC-CFAS study explored the cognitive impairment of respondents that were recruited from an age stratified sample of 6 UK sites, whatever the social background, residential status (community or institutional) or health status. The only selection criterion for initial screening was age, respondents being 65 years old or older. The sample was inclusive of institutionalised subjects who were more likely to show cognitive impairment. The response rates were 82% for the five first centres and 87% in Liverpool, so that there were 18,131 respondents at baseline. Individuals who refused were more likely to have poor cognitive ability but had less years in full-time education and were more often living in their own home though less likely to be living alone. Prevalence was reported as an MMSE score less than 17/18. It recognizes the researcher as the instrument, taking into account the experiences and perspectives of the researcher as valuable and meaningful to the study (Lincoln and Guba, 1985) Such an approach relies on pre-identified variables from tightly defined populations, attempting to fit individual experiences and perspectives into “predetermined response categories” (Patton, 1990, p. 14), allowing no room for research objects or variables to help define the direction of the research

Critically discuss the reliability (20% marks) and validity (20% marks) of the data-collection instruments used to assess the cognitive status of study participants.

Explicit definitions provide, if not a guarantee, at least an indication of adequate reliability, and they make it clear what meaning is being ascribed to the diagnostic terms employed. Measurement of cognitive function is subjective, despite a standard methodology pre-identified variables from gathered from tightly defined population studies. Attempting to fit individual experiences and perspectives into “predetermined response categories” (Patton, 1990, p. 14), allowing no room for research objects or variables to help define the direction of the research. Structured interviews were used, by the introduction of explicit definitions but it is hard to ascertain if the data provided by the MMSE test aligned with the current decision rules in ICD-10 Diagnostic Criteria for Research. The MRC-CFA note that the diagnostic criteria under this definition would not be a feasible measurement instrument for a large population study, as in the study. a standard set of questions is administered to collect reliable information. interviewer leads the respondent, this results in interviewer bias. Bias can be caused by subconscious or conscious gathering of selective data. It includes prompting and giving positive reinforcement to the respondent for providing an answer the interviewer perceives as desirable or “right”. The mini-mental state examination (MMSE) or Folstein test is a brief but systematic 30-point questionnaire used as an instrument for screening cognitive function, validated in a number of population studies (Folstein, 1975). The method used by the MRC CFA mimics the methodology 0f the Canadian Study of Health and Aging (1994). There is inherent bias in using this test as it will not detect subtle memory losses, particularly in well-educated patients. Adjustment must be made in light of social status and education level, otherwise those with low education level may show poor results despite not having cognitive impairment and those with high education and pronounced cognitive results may show favourable results that ultimately mask the problem. In addition, the instrument relies heavily on verbal response and reading and writing. Therefore, patients that are hearing and visually impaired, intubated, have low English literacy, or those with other communication disorders may perform poorly even when cognitively intact. The interviewer in this test also acts as an instrument and although standardisation was used and promting minimise, none scitped behaviours of the interviewer, such as intonation, may have influenced the outcome of questions. It recognizes the researcher as the instrument, taking into account the experiences and perspectives of the researcher as valuable and meaningful to the study (Lincoln and Guba, 1985)

Validity

The word “valid” is derived from the Latin validus, meaning strong, and it is defined as “wellfounded and applicable; sound and to the point; against which no objection can fairly be brought” (Kendall and Jablensky, 2003). This is not simply a measurement but questions “the nature of reality” based on epistemological assumption. The construct validity of the MMSE has been well studied (Jefferson et al, 2002:1). Low reported levels of sensitivity, particularly among individuals with mild cognitive impairment, have been reported for the MMSE (Tombaugh & McIntyre, 1992; de Koning et al. 1998) and may be due to the emphasis placed on language items and a lack of items assessing visual-spatial ability (Grace et al. 1995; de Koning et al. 1998; Suhr & Grace, 1999). Relatively few studies have examined the ability of MMSE to differentiate between individuals with dementia (Jefferson et al, 2002). in qualitative research one cannot escape the reality that the researcher is an instrument that filters data through own paradigm

instrument fails to assess abstract thinking,(13) and the task force which developed

criteria for the clinical diagnosis of Alzheimer’s disease recommended the evalu-

ation of cognitive processes such as language skills in conjunction with the MMSE

as part of the diagnostic process.(17) Concerns raised by critics of the “cognitive

paradigm,”(18) relate to whether the MMSE, or other instruments, used singly or

in combination are valid measures of “cognition,” and the extent to which dementia

is susceptible to diagnosis using currently available objective methods.(19) Stockton et al, 1998). he analyses raise questions with regard to the reinterpretation of lack of education, from a confounding factor in prevalence estimates of cognitive impairment to a risk factor for dementia, and support those who have questioned the validity of the one-dimensional cognitive paradigm, and the trend to diagnosis based upon objective assessment with standardized instruments.

One of the assumptions underlying qualitative research is that reality is holistic, qualitative research is that reality is holistic, multi-dimensional, and ever-changing; it is multi-dimensional, and ever-changing; it is not a single, fixed, objective phenomenon not a single, fixed, objective phenomenon waiting to be discovered, observed, and waiting to be discovered, observed, and measured. Then how do we assess the measured. Then how do we assess the validity of what validity of whatis is being observed or being observed or measured? measured?

Investigation into the characteristics of those lost to follow-up after initial enrolment was not reported by the other selected studies

• Screening periods were close together in-depth, structured, in-person interview.

• Interviews in respondent’s homes

• Subjects were asked would them comply with further interviews

• Coding was subject to different codes for ‘don’t know and ‘no answer’ – no assumptions were made

Standardised structured interviews were undertaken in the respondent’s own home at baseline using a computerised interview. The screen interview collected information about demographics including marital status and educational ability, social class, cognitive ability (Mini Mental State Examination ) and organicity symptoms of the Automated Geriatric Examination for Computer Assisted Taxonomy (AGECAT). The mini-mental state examination (MMSE) or Folstein test is a brief but systematic 30-point questionnaire used as an instrument for screening cognitive function, validated in a number of population studies (Folstein, 1975). The method used by the MRC CFA mimics the methodology 0f the Canadian Study of Health and Aging (1994). There is inherent bias in using this test as it will not detect subtle memory losses, particularly in well-educated patients. Adjustment must be made in light of social status and education level, otherwise those with low education level may show poor results despite not having cognitive impairment and those with high education and pronounced cognitive results may show favourable results that ultimately mask the problem. In addition, the instrument relies heavily on verbal response and reading and writing. Therefore, patients that are hearing and visually impaired, intubated, have low English literacy, or those with other communication disorders may perform poorly even when cognitively intact. The interviewer in this test also acts as an instrument and although standardisation was used and promting minimise, none scitped behaviours of the interviewer, such as intonation, may have influenced the outcome of questions. It recognizes the researcher as the instrument, taking into account the experiences and perspectives of the researcher as valuable and meaningful to the study (Lincoln and Guba, 1985)

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