HMPYC80 Research Methodology (2022 - Semester 1 - Assignment 3)

HMPYC80 – Research Methodology 2022 – Semester 1 – Assignment 3 Question 1: Which of one of the following statements is NOT true about C-studies? C-studies research do NOT ... a) aim to explore or describe without statistical testing and typically use non-random or purposive sampling (NR). b) compare groups or examine relationships between variables by means of some form of statistical hypothesis testing. c) aim to explain phenomena by means of a hypothesis. d) use random sampling (R) as the preferred sampling technique. Question 2: Which one of the following relates to experimental designs? a) Correlational designs. b) Retrospective case study, and group-comparison. c) Quasi-experimental designs. d) Randomised cross-sectional surveys, and replicated randomised cross-sectional surveys.   Question 3: Which one of the following statements does NOT relate to experiments in social science research? a) The researcher will do something (administer an intervention, or manipulate an independent variable, called X) to one of the groups (experimental group) and do something different (or nothing at all) to the other group (control group). b) A retrospective case study design is used whereby data is actively collected in the present. c) The groups are compared or tested for differences between them on a selected outcome, or dependent variables. This is to state that any differences in the outcome (dependent variable) between the groups are due to (or caused by) the intervention or independent variable. d) Three types of experimental designs have been developed to determine the presence of cause-and-effect relationships between different variables. The most significant differences between these types of experimental designs are with regard to: (i) degree of control on the variables being studied (X’s), (ii) degree of randomness, and (iii) presence of a comparison or control group. Question 4: The cross-sectional survey design ... a) is used exclusively in non-experimental studies. b) is an example of a standalone research design. c) is enacted as a carefully designed method for sampling the population of the study, so that the sample represents or targets specific groups of relevance in that population. d) consists of surveys questions that basically tap into the prejudices or "false-facts" that participants hold. Question 5: Threats to external validity include the following: a) History, and maturation or changes in participants. b) Demand factor, the researcher’s expectations, and the Hawthorne effect. c) Statistical regression, participant attrition, and diffusion of treatments. d) Selection, testing, and instrumentation. Question 6: The term "big data" is globally accepted for describing very large sets of information, and the application of specific computational methods for analysing such data by means of programming. Big data is described as data showing certain characteristics, widely regarded as the "Four V’s". Which one of the following statements refers to the veracity of the data? a) Data in the form of media, documents and streaming data that can be structured, unstructured or semi-structured. b) Data sets that are no longer retrospective and static but comprises live, streaming data. c) Large data sets that include pictures and video streams, such as YouTube. d) Legitimate real-time data at all times. Question 7: The benefits of big data related to the integrated health and social care environment do NOT include: a) The issue of privacy and anonymisation is a highly sensitive subject within health and social care and potential for liability hinders biomedical digital research. b) Real-time data giving the provider and service user a real-time synopsis of symptoms c) Better treatment outcomes through improved diagnoses and treatment interventions d) Faster and more efficient response to the slightest emergency from the sensor or from deviations in the collected data Question 8: After establishing a research design for your study, you must identify the most suitable data collection method that fits the design and the circumstances of the research project. Which one of the following statements does NOT relate to how the data will be collected in a quantitative research approach? a) To obtain valid and reliable data you must ensure, before implementing the study, that the measurement procedures and the instruments used have acceptable levels of reliability and validity. Validity and reliability are two of the most important concepts in measurement. b) To increase the validity a researcher can increase the number of items to measure a variable. For example, by using two or more indicators (e.g. two or more questions in a questionnaire) to measure each attribute of a variable. c) Measurement implies observation of complex social phenomena by means of a numerical schema to evaluate or rate statements or items that reflect components of the phenomenon being studied. In simplified terms this means we start with some theoretical construct or phenomenon that we want to observe in human participants. This mostly abstract phenomenon is then broken down into observable indicators after which we attach number values to each indicator that will enable us to quantify our observations. d) Combinations of attributes enable us to measure the phenomenon itself. Most concepts or phenomena dealt with in the social sciences are highly abstract and not easily observable unless they are deconstructed into measurable attributes. So, if we want to measure levels of depression in human participants, we first need to deconstruct the term depression into its observable characteristics and then attach a numerical value on a scale that enables us to quantify the extent to which the characteristics are present in the participant. Question 9: The types of validity that underpin psychometric instruments or measurements are typically classified as: content, face, criterion and construct validity. Which one of the following options applies directly to construct validity? a) This means moving away from subjective assessments of face validity and providing more objective evidence of validity. This involves multiple measurements and is established by comparing scores on an instrument with an external criterion known to, or believed to, measure the concept, trait or behaviour being studied. External independent criteria are used against which to compare the scores on an instrument. If we test a new instrument for measuring a construct in people, we can also use a well-known standardised measure to compare our new measure with, then we use that other measure as criterion, and this is called "concurrent validity". b) This involves determining the degree to which an instrument successfully measures a theoretical construct. Any measure exists in some theoretical context and should therefore show relationships with other constructs that can be predicted and interpreted within that context. Construct validity involves not only validation of the instrument itself, but also of the theory underlying it. To establish construct validity, the meaning of the construct must be understood and the propositions the theory makes about the relationships between this, and other constructs must be identified. One method is to compare a measure to variables it logically is NOT supposed to correlate with and to variables that we assume it should correlate with. If it works out that way, we have "convergent validity" that represents those variables the measurement strongly correlates with according to expectations. "Discriminant validity" represents variables the measurement instrument correlates poorly with. Another popular method for establishing construct validity is called "factorial validity" or "factor analysis" (DeVellis, 2017, p. 154). Factor analysis is a primary procedure to determine if a scale has internal validity based on the coherence of the underlying factors in a questionnaire. You have to understand whether underlying sets of items (latent variables) match the dimension composed into a scale. Factor analysis can either be "exploratory" or "confirmatory". The procedure determines whether items cluster together in measuring a particular construct. It also identifies items that do not relate well with the dimension of measurement. c) This is concerned with the representativeness or sampling adequacy of the content (e.g. topics or items) of an instrument. A valid measure would provide an adequate or representative sample of all content or elements or instances of the phenomenon being measured. Is the instrument really measuring the concept we assume it is? Does the instrument provide an adequate sample of items that represent the concept being measured? d) It is concerned with the superficial appearance of a measurement procedure. The relevant question in this regard is: Does the measurement technique look as if it measures the variable that it claims to measure? Question 10: A pilot test is done when we develop a draft version of the measure or use a subsection to test before implementing the study to increase reliability. This is done to... a) standardise instructions. b) standardise the conditions under which the test is taken. c) enable timely changes to increase reliability. d) increase the precision of measurement. Question 11: Which one of the following statements about reliability is INCORRECT? a) Reliability is primarily concerned not with what is being measured, but with how well it is being measured every time it is used. b) A psychological measuring instrument can be valid but not reliable. Reliability and validity exist independently from each other. c) The most commonly used reliability measure using survey data is Cronbach’s coefficient alpha. This coefficient ranges between 0 and 1 and figures closer to 1 (0,8–0,9) generally indicate a highly reliable scale. d) Different reliabilities exist such as the test–retest, parallel-form, split-half, internal consistency and interrater agreement methods. Question 12: Practical considerations for collecting quantitative data include the imperative of anonymity. Anonymity is enabled by ensuring the following: a) Participation in any research should be voluntary and a respondent to a questionnaire should be able to withdraw from completing the survey at any time. b) Data collected by means of paper-based questionnaires should be stored in a lockable cabinet until such time as the data can be transferred to an electronic data set. c) There should not be any way that a participant can be identified or if there is identifiable information such as a name, or an email address, participant code or an informed consent form that may mistakenly be attached to the questionnaire, these should be separated from the questionnaire and securely stored separately. d) Electronic data should be stored on a password protected computer, not a memory stick or other storage device that is not protected. Data should only be exchanged with the analyst or statistician. On completion of the study, all research data should be archived for a prescribed period of usually five years or consistent with the organisation’s data storage policy, before it is either destroyed or deleted. Question 13: Which one of the following statements about sampling is NOT correct? a) The following steps can be followed to draw a random sample: 1. Assign a number to every person or item in the population. 2. Use a random numbers table or suitable software to select the actual sample. 3. Decide on the size of the sample; that is, what percentage of the population should be studied. 4. Identify and list the complete research population. b) By increasing sample size, you will find smaller and smaller effects to be statistically significant until, at very large sample sizes, almost any effect is significant. You must always be aware that sample size can impact on the statistical test by making it either insensitive (at small sample sizes) or overly sensitive (at very large sample sizes). Practices have been developed to statistically determine the size of a sample. Generally called power calculation, the statistical power of a study to produce sufficient effect size is calculated, either by a statistician or by using a power calculator obtainable from the internet. Sample size is influenced by different variables, of which representativeness is one. Using an insufficient number of participants results finding significant results when these are actually not significant. Using overly large samples leads to not finding significant results when these are actually present. c) The issue of the minimum size of a sample is repeatedly addressed in the literature. It is generally stated that the larger the population, the smaller the percentage of the sample from the population needs to be, and vice versa (Neuman, 2014). If the population itself is relatively small, the sample should comprise a reasonably large proportion of the population. Generally speaking, for a population of 100 000 or 200 000 a sample size of 2 000 will suffice. d) Sampling theory is based on the notion that a relatively small set of observations can give an idea of what can be expected in the total population of the intended study. Even if it were theoretically possible to identify, contact and study the entire relevant population, time and cost considerations usually make this a prohibitive undertaking (Bless, Higson-Smith & Sithole, 2014). The use of samples may therefore result, in more accurate information than might have been obtained if you had studied the entire population. This is so because, with a sample, time, money and effort can be concentrated to produce better-quality research, better instruments, more in-depth information, and better-trained interviewers or observers. The quantitative paradigm focuses on probability sampling that comprises a relatively large number of units from the population. Question 14: Systematic sampling ... a) is done by selecting the first case randomly, preferably from a random table. All subsequent cases are selected according to a particular interval, for instance every fifth or tenth case on a list of names, depending on the percentage sample needed. b) is suitable for heterogeneous populations because the inclusion of small subgroups percentage wise can be ensured. Stratification consists of the universe being divided into a number of strata which are mutually exclusive, non-overlapping groups and the members of which are homogeneous with regard to some characteristic such as gender, home language, income, level of education or age. For each stratum, its own sample are then drawn, whether it be simple random sampling or systematic sampling. c) is used when a sampling frame such as a list of names is not available, but only a map of the relevant geographical area. You should attempt to retain areas that are naturally grouped together, such as suburbs or street blocks. Each cluster on its own must represent the whole population, but variation between clusters must be small. Sampling draws cases only from those clusters selected for the sample. This is at least a two-stage procedure where a random sample of clusters is firstly drawn and then a random sample of elements within each cluster is selected. d) is considered to be the easiest of the sampling methods where each individual case in the population theoretically has an equal chance of being selected for the sample, without skipping any number, thus being a bias-free process. You must have an accurate and complete list of all possible respondents. In practice, it is necessary to assign a unique number to each participant within the population. Question 15: One of the questions in a questionnaire asked each respondent to indicate their annual income in rands. What is the measurement level of this variable (annual income)? a) Nominal variable (e.g. region or province, gender, race or ethnic group, marital status, country of citizenship and home language) can be subjected to arithmetical operations such as addition, subtraction, multiplication or division. b) Ordinal variables involve the least precise type of ranking: with these variables, the categories increase in “value” or intensity, but the distance between categories is not a precise mathematical value. Examples of ordinal values include socioeconomic status, disability status, age intervals, income intervals, employment status (e.g. unemployed but not seeking work, unemployed and seeking work, temporary worker, full-time worker, etc.). Ordinal variables can also be created by collapsing precise values into ranges. c) Interval level variables, on the other hand, take on numerical values and are usually obtained by measuring or counting. The most common examples in the social sciences include standardised scales (e.g. aptitude, intelligence, social functioning, depression, stress and coping) and self-designed tests with Likert scales, and sometimes with interval ranges. Various standardised scales are available to be used quite effectively for measuring various social conditions and topics of interest in social research. d) The ratio level of measurement is the most mathematically precise measure. A characteristic of a ratio variable is that there is an absolute zero on the scale regardless of the units. This allows for precise comparisons. As a rule, if “zero” can be a legitimate and meaningful response, the variable is a ratio. Question 16: Quantitative research most often uses deductive logic, in which you commence with one or more hypotheses and then collect data to determine whether or not empirical evidence provide support for that hypothesis. Statistical significance is used to test a hypothesis. Which one of the following statements is NOT correct? a) The null hypothesis posits that there is no relationship between the variables or that any relationship we can discern in our data is merely due to chance, or to sampling error. Using a null hypothesis as a starting point forces you to require a high standard of evidence to conclude that your findings do not support the null hypothesis – namely that the evidence must be strong to conclude that the proposition that there is no relationship between variables cannot be supported. b) The second type is the alternative hypothesis. This type of hypothesis probably seems to be the more straightforward, as it posits that there is a relationship between the variables. The point is that an alternative hypothesis becomes more compelling only after we have demonstrated that our evidence does not support the null hypothesis and that any relationship we have discerned between variables is highly unlikely to have been produced at random, or by sampling error. The alternative hypothesis or hypotheses could also specify the direction of the relationship. c) To avoid Type II errors, we may decide to insist on the higher significance threshold of ρ < 0.01. After all, if the 95 per cent significance can still allow one “fluke” sample out of every 20, then, surely, we are on safe ground with 99 per cent significance. The problem here, though, is that we risk upholding the null hypothesis (i.e. that there is no relationship between our variables) when the relationship does actually exist in the population. d) The ability to shift theorising from the sample (e.g. survey participants) to the wider population from which the sample was drawn relies on two important factors, namely: (i) robust sampling practices; and (ii) statistical tests of significance that are usually performed on either the 0.05 or the 0.01 level of significance. The convention in the social sciences is that the 95 per cent confidence level is the lowest acceptable result. Question 17: Quantitative methods of analysis fall into four main categories, namely: (i) descriptive; (ii) association: (iii) causation; and (iv) inference. Which one of the following statements relates to "inference"? a) This involves the use of (i) factor analysis, (ii) path analysis or (iii) regression, to determine the network of relationships between variables. Multivariate analysis is most often used, where three or more variables are compared. These are used both to make estimates of population characteristics from the sample characteristics and to establish whether relationships within a sample can be expected to assist in predicting (other than by chance) relationships in the population from which the sample is drawn. b) These methods are used to report the distributions (or spread) of a sample or population across a wide range of variables (using all four levels of measurement as discussed above). The aim of these methods is to produce a scope of the characteristics of such distributions through (i) frequencies, (ii) measures of central tendency and (iii) measures of dispersion. Univariate analysis focusing on one variable at a time is used. c) These techniques are used to establish whether positions on one variable are likely to be consistently associated with positions on another variable through, depending on the level of measurement and the number of variables analysed, either (i) correlation, (ii) analysis of variance (ANOVA) or (iii) regression. Bivariate analysis comparing two variables is most often used. d) These are performed by indicating measures of significance and indicators of effect size that show the size of that difference. Question 18: Which one of the following statements is INCORRECT with regard to statistical techniques of analysis? a) In normal, or “bell-shaped” distributions (sometimes called a bell-shaped curve or simply a bell curve), approximately 68 per cent of the measurements fall within one standard deviation on either side of the mean (34 per cent within one standard deviation above the mean and another 34 per cent within one standard deviation below the mean), 95 per cent within two standard deviations from the mean, and more than 99 per cent within three standard deviations (with approximately 16 per cent more than one standard deviation above and another 16 per cent more than one standard deviation below the mean). b) Most correlational techniques assume that the relationship between variables (if any) is linear. A scatterplot will assist you to identify the type of relationship between variables (linear or non-linear). A linear correlation refers to straight-line relationship between two variables. That simply means the more we have of one variable, the more (in positive correlation) or less (in negative correlation) we have of another variable. The relationship between social support and mental health in those exposed to trauma, or between socioeconomic status and food security, are examples of a linear relationship. c) When two variables or factors are correlated this implies a cause-and-effect relationship between them, for example between smoking and alcoholism. It is possible to conclude the existence and direction of a causal relationship based on an observed positive or negative correlational relationship between factors. d) Multiple regression is a correlational technique that enables you to learn about the relationship amongst several independent variables (sometimes referred to as predictor, regressor or explanatory variables in multiple regression) and one dependent variable (or sometimes referred to as the outcome, target or criterion variable). More specifically, it is used to predict the value of a dependent variable based on known (or assumed) values of two or more independent variables. Question 19: In qualitative research -- where a person or group has a story to tell, a perception or experience to share or holds a specific view a phenomenon, event, situation or context -- the aim of the researcher is primarily to ... a) to generalise the findings of the sample to the general population b) develop an in-depth understanding of the person within context of their situation. c) confirm hypotheses, examine causality and explain relationships between variables and groups. d) access and source compelling samples via random selection of the participants. Question 20: Research design in qualitative research does NOT ... a) consider how to enrich the research by employing different lenses on the same phenomenon, such as triangulation where more than one sampling or data collection method is used and a hermeneutic framework that values inter-subjective interpretations. b) use and obtain (data) saturation to increase rigour by collecting many similar instances of the phenomenon to incrementally build certainty. c) consist of well-developed, rather rigid options, with clearly defined design sets. d) refer to a creative and interactive process where the researcher becomes the primary research instrument with their own research paradigm (ontology and epistemology), culture, ideology, experience, personality, emotions and knowledge. Question 21: Phenomenology originated from the philosophy of Edmund Husserl (1859–1938) who aimed to describe how life is experienced through consciousness. Which of the following statements is NOT true with regard to phenomenology? a) At the root of phenomenology is the intent to understand the concepts, thoughts, ideas and images giving meaning to the structure of various types of experience from a subjective viewpoint, including perception, thought, memory, imagination, emotion, desire and bodily awareness. Phenomenology, in simple terms, refers to the description or interpretation of an individual’s immediate experience through consciousness. b) The researcher is not required to openly and continuously acknowledge their preconditions and assumptions and reflect on the influence these may have on the research process (bracketing). c) The "descriptive" phenomenological research strategy regards experience as intentional, and therefore believe that reality should be consciously observed, described and understood. The focus is on understanding the experiences of participants rather than the interpretation of events in their lives. The aim is therefore not to describe smaller events in a person’s life, but to describe their experiences of a life event, thereby allowing the essence of these experiences to emerge. The lifeworld refers to a person’s conscious experience of everyday life and social action. d) "Hermeneutic" or "interpretative phenomenology" (IPA) regards human beings as actors and as knowers of a phenomenon because they are in the world and therefore already part of it. Hermeneutic (interpretative) phenomenology focuses on the relationship between an individual and his/her lifeworld. Heidegger’s term lifeworld implies that individuals already understand the world and their position within it. In a sense, interpretative phenomenology moves beyond bracketing and description by asking the participant not only to relate the experience but interpret its subjective meaning as well. Question 22: Which one of the options below is a CRITICISM that applies to interpretative grounded theory? a) Glaser and Strauss emphasised that you should remain sensitive to the data for the emergence of theory from the information gathered. To do this they had to take the stance of the positivist ideal of tabula rasa (Lat. “blank slate”), thereby not consulting the literature before the emergence of analytical categories from the data. As Thornberg and Dunne (2019, p. 209) point out, this notion is considered highly problematic by critical theorists with a constructivist orientation. b) In the constructivist approach to grounded theory, it is necessary to grasp the main principles of critical constructivist theory as grounded theory researcher, you are no longer distant and removed from your participants and need to continuously examine your personal background, feelings, power and status not to impose these on the study. You need to realise that your interactions with participants are integral to the research process. Such a step back allows us the conceptual distance needed to produce a critical consciousness. Critical consciousness counters the passive acceptance of externally imposed research methods that tacitly certify and justify current modes of knowledge in a decontextualised, reductionistic manner, inscribed by dominant modes of power (Kincheloe et al., 2018, p. 432). c) The principle of reflexivity, defined as constant adjustment of own assumptions through critical self-reflection, has become a major issue in constructivist orientated research (Lincoln et al., 2018, p. 246). The first assumption is that if you reflect self-consciously about your role and actions as researcher – and include these in your fieldnotes and research journals – your research will be the more credible (Rossman & Rallis, 2017, p. 82). This process entails a deeply reflexive examination of values, meanings, language and research actions or “methodological self-consciousness”. d) Although most scholars see grounded theory as an inductive strategy, some insist that it uses both deductive and inductive reasoning (abduction) in the theoretical coding process since you compare your knowledge of theory with the data collected and the codes and categories you created (Charmaz, Thornberg & Keane, 2018, p. 751). Constructivist grounded theorists acknowledge the use of abduction to relate substantial theory to empirical data (Charmaz, 2014). They simultaneously employ techniques of induction, deduction and verification or validation in developing theory. Question 23: Heron's (1996, pp. 172–176) views on different kinds of knowing on the continuum of the arts and the science state a version of knowing that involves "knowing through feeling and imaging and having an empathic resonance with another person or situation". Which type of knowing does this entail? a) Propositional knowing. b) Experiential knowing. c) Positive knowing. d) Presentational knowing. Question 24: Which one of the following statements about narrative inquiry in qualitative research is NOT true? a) Jordaan (2020; pp. 106–107) unpacks this line of thinking by showing how narratives or storytelling, and not natural science, has been the ancient and oldest way to convey knowledge from one generation to the next. This, he claims, shows that the narrative mode of knowing comes naturally and could be regarded as a peculiarly human instinct. b) The philosopher Daniel Dennett’s (1993) statement: “Spiders weave webs, beavers build dams and humans tell stories”. This notion is supported by Bochner (2014, p. 239) who states: "As social beings, weave storied lives [...] Our identities – who we are and what we do –originate in the tales passed down to us and the stories we take on as our own. In this sense, stories constitute 'our medium of being' [...] Storytelling is both a method of knowing – a social practice – and a way of telling about our lives." c) For humans are relational beings, the telling of stories about ourselves and our culture comes naturally, and in doing this the focus moves from analysis and controlling social problems to understanding, caring and opening up dialogues on difficult issues (Bochner & Riggs, 2014, p. 206). Storytelling can also be viewed as a natural way for indigenous communities and some ethnic groups to convey knowledge. d) Objective sciences with its rules of proof, logical deduction and inference are the most ancient form of human storytelling. Question 25: There are various core elements of autoethnography. To which aspect does the "-graphy-" refer? a) Personal experience. b) Cultural beliefs, values, and practices. c) Representation of the research process. d) Embodied reflexivity. Question 26: There are at least five contemporary data collection methods in qualitative research, namely: (i) participant observation; (ii) document study; (iii) the use of secondary data; (iv) visual sources and (v) interviewing. What should you consider when "leaving the field" in the (i) "participant observation" data collection method? a) You should never be too involved with respondents, though you should be able to feel comfortable in their presence. b) When you reach a point of data saturation where further data collection becomes repetitive, and few new insights come to the fore. c) You should preferably begin the relationship on a rather unobtrusive note, instead of being too involved from the start. d) Some respondents might see you as an intruder and will do their best to make you feel unwelcome in their community. Question 27: There are at least five contemporary data collection methods in qualitative research, namely: (i) participant observation; (ii) document study; (iii) the use of secondary data; (iv) visual sources and (v) interviewing. In the (ii) "document study" data collection method: a) Primary sources are seen as the original written material of the author’s own experiences and observations, while secondary sources consist of material that is derived from someone else or previously published works as the original source. b) Existing research data with a different aim is "reworked". This is also called the use of secondary data. c) A history of events or experiences can be studied by direct observation or direct interviewing. d) Visual sources such as ethnographic mapping, microethnography, rephotography, photovoice, autophotography and photo elicitation are used. Question 28: There are at least five contemporary data collection methods in qualitative research, namely: (i) participant observation; (ii) document study; (iii) the use of secondary data; (iv) visual sources and (v) interviewing. During (v) interviewing -- which of the following interview types yields transcripts that are generated during the interviewing process and also automatically keeps an audit trail? a) Focus group interviews. b) Direct interviewing. c) Email interviewing. d) Telephonic interviews. Question 29: Yarning is a conversational process that involves the telling and sharing of stories and information. Yarning is culturally ascribed and cooperative; yarns follow language protocols and result in some acquisition of new meaning (Walker, Fredericks, Mills & Anderson, 2014, p. 1217). There are four different types of yarns or stories. Which yarn is applied where the conversation of the researcher with participants is deliberate and intentional -- with a planned beginning and end -- yet relaxed? (This type of yarning is undertaken freely, it is culturally appropriate and non-exploitative. As the researcher, you take the position of learning from the indigenous peoples and would not interrupt a participant with direct questioning.) a) Social yarning. b) Therapeutic yarning. c) Research topic yarning. d) Collaborative yarning. Question 30: Which of the following statement does NOT apply to culturally responsive interviewing? a) Do not consider cultural groups as monolithic. The risk is a generalisation (which you do not want to do in qualitative research) and it may introduce stereotypes to the interviewing relationship. When interviewing participants, you should challenge yourself to identify the nomothetic qualities (the commonalities among participants), as well as the idiographic qualities (the unique and individual traits of participants). b) It is important not to read or study any material related to the cultural context of the research so that you can be as neutral and objective as possible (as a "tabula rasa"). c) People do not only communicate through language. Folklore, myths, rituals, symbols and proverbs are also used to share important information. Participants may also prefer a more conversational manner of interviewing to a researcher–participant interview context. d) When working across cultures, it would be to your advantage to work from a stance of not knowing. You should be open to learn from participants and discuss issues instead of making assumptions. Question 31: This does NOT apply to sample size in qualitative research: a) Sample size is seen by Mertens and Wilson (2012, pp. 435–380) as more complicated than in quantitative research and there are no real hard and fast rules for selecting a sample in qualitative research. b) You must always remember that quality, to gain in-depth and saturated data, rather than quantity or width, is the main emphasis of qualitative studies. The intent remains not to generalise but to clarify the particular and the specific. c) Mertens and Wilson (2012, p. 436) give an estimation of sample sizes for the various qualitative approaches, such as one or multiple cases for case study research, approximately six participants in the case of phenomenological studies and 30 to 50 interviews for studies in narrative or grounded theory designs. However, some researchers state that repetition leading to data saturation can begin after 13 to 15 cases in some instances. Ultimately, the data saturation principle is the most important factor in qualitative research. d) Sample size depends largely on probability sampling in qualitative research. Question 32: In qualitative data analysis the concepts of transferability, dependability, confirmability and credibility, as dimensions of credible qualitative research, are widely regarded as important measures of trustworthiness. Which one of the following statements in this regard is FALSE? a) Transferability of research findings refers to the extent to which a study’s findings can be applied in other contexts and studies. As the alternative to external validity or generalisability in quantitative studies, in qualitative research you ask whether the findings of the research can be transferred from a specific situation or case to another. b) Dependability relies on positivist notions of an unchanging universe where inquiry could, quite logically, be replicated. The social world is assumed to be relatively unchanging. c) Confirmability implies that other researchers are able to confirm the origins of the derived findings and conclude that they would come to the same or similar conclusions by following the same methods. d) Credibility is the alternative to internal validity in quantitative research, in which the goal is to demonstrate that the study was conducted in such a manner that the research participants were accurately identified and described. Researchers ask if there is a match between research participants’ views and researchers’ reconstruction and their representation of them. Question 33: This is done by systematically maintaining documentation of the researchers’ continuous critical analysis of all decisions and actions taken during the research process, as well as their thinking and feelings about their conceptual framework, research questions, methods, values and biases. By doing this the credibility of the findings are increased. a) Triangulation. b) Crystallization. c) Member checking. d) Audit trail.