Quali-Quanti Methods for Students PDF

PSYCHOLOGISTS rely on a few methods to measure behavior, attitudes, and feelings. Self-reports, like surveys or questionnaires Observation (often used in experiments or fieldwork) Here’s how the scientific method in quantitative research works, step by step: Generate a theory or hypothesis: The...

PSYCHOLOGISTS rely on a few methods to measure behavior, attitudes, and feelings. Self-reports, like surveys or questionnaires Observation (often used in experiments or fieldwork) Here’s how the scientific method in quantitative research works, step by step: Generate a theory or hypothesis: The researcher makes a prediction about what they think will happen in an experiment or study, focusing on what variables (factors) they need to study. Develop instruments to measure: They create tools like surveys, tests, or devices (like thermometers) to measure the phenomenon they're interested in Design experiments: The researcher sets up experiments to control or change certain variables, which helps in understanding cause-and-effect relationships. QUANTITATIVE METHODS Experimental Design and Analysis Experiments are used to study causal relationships. In an experiment, you manipulate one or more independent variables and measure their effect on one or more dependent variables. A good experimental design involves the following steps: Define Your Variables: Start with a specific research question. Identify the main variables (independent and dependent) and consider extraneous variables. Write Your Hypothesis: Translate your research question into an experimental hypothesis. Design Experimental Treatments: Plan procedures to systematically test your hypothesis. Assign Subjects to Groups: Group participants either between-subjects (different groups experience different treatments) or within-subjects (same group experiences different treatments). Measure Your Dependent Variable: Decide how you’ll measure the outcome. Control Extraneous Variables: Ensure valid conclusions by controlling factors that might influence results. If random assignment isn’t feasible, consider an observational study to minimize bias Posttest-Only Control Group Design posttest-only control group design is a basic experimental design where participants get randomly assigned to either receive an intervention or not, and then the outcome of interest is measured only once after the intervention takes place in order to determine its effect. 1. The treatment and control groups are equivalent at baseline 2. External factors are controlled (use of a control group controls history; use of 1 measurement only controls factors related to the instruments used to measure the outcome 3. Can be used when participants’ anonymity must be kept 4. Not affected by reactions to pretesting (prevention of test-retest effect (a.k.a. sensitization to pretest) 5. Can be done when a pretest is not possible 1. High risk of attrition bias (The absence of a pretest makes it very hard to detect and control this bias.) 2. The effect of the intervention on subgroups is not clear 3. Requires a large sample size 4. Less generalizable than observational designs Low external validity is a general characteristic of experiments a highly controlled study will have a high internal validity (i.e. less bias) In 1993, Topf and Davis used a posttest-only control group design to examine if CCU (Critical Care Unit) noise affects REM (Rapid Eye Movement) sleep. they randomly assigned 70 women with no hearing or sleeping problems to attempt to sleep in one of the following conditions: *noisy environment (the subjects listened to an audiotape recording of CCU sounds): treatment group *quiet environment: control group Note that this experiment was done in a sleep laboratory. Their results showed that CCU sounds can cause poorer REM sleep. Pretest-Posttest Control Group Design pretest-posttest control group design, also called the pretest-posttest randomized experimental design, is a type of experiment where participants get randomly assigned to either receive an intervention (the treatment group) or not (the control group). The outcome of interest is measured 2 times, once before the treatment group gets the intervention — the pretest — and once after it — the posttest. PPCG design has 3 major characteristics: The study participants are randomly assigned to either the treatment or the control group (this random assignment can occur either before of after the pretest). Both groups are exposed to the same conditions except for the intervention: the treatment group receives the intervention, whereas the control group does not. The outcome is measured simultaneously for both groups at 2 points in time — the pretest and the posttest. The pretest-posttest control group is the most commonly used design in randomized controlled trials. Advantages of the pretest-posttest control group design Adding a pretest: Increases the power of the design to detect an effect. Allows studying the effect of the intervention at different sublevels of the pretest. Helps analyzing initial differences between groups (and therefore quantifying their effect on the study outcome). Helps controlling attrition bias i.e. the unequal loss to follow-up of participants between the treatment and the control group which can affect the outcome measured at the posttest. Advantage of using random assignment and having a control group Random assignment and the control group will both limit the effects of: Selection bias: Randomization allows unbiased assignment of participants to treatment options, and therefore makes the study groups comparable. Maturation: Participants are subject to maturation both in the treatment and the control group, therefore, any difference between the outcome of these groups will be due to the effect of the treatment alone and will not be affected by maturation. History: any event that might co-occur with the intervention and has the potential to influence the outcome Participants included in any randomized study might not be typical people in the population i.e. they may not represent well the population of interest, this is because: Not everyone in the population of interest is eligible for the experiment, and not everyone who is eligible can be recruited, and not everyone who is recruited will give us their consent to be included in the study, and not everyone who consented will be randomized. to study the effect of a yoga program on the classroom behavior of autistic children. These children were randomly assigned to either receive the yoga program or their standard morning routine. The study concluded that yoga can significantly improve the classroom behavior of autistic children. But because the researchers used a convenience sample from a particular school and the classrooms that were allowed to participate were hand-picked by administrators, the study outcome may not generalize well to all children with autism. Koenig et al. Solomon Four-Group Design The Solomon four-group design is a type of experiment where participants get randomly assigned to either 1 of 4 groups that differ in whether the participants receive the treatment or not, and whether the outcome of interest is measured once or twice in each group. Solomon four-group design better than a standard two-group design The Solomon four-group design was developed to: Control threats to internal validity: Such as bias and confounding. Something that a standard (two-group) experimental design can control. Control threats to external validity: Such as pretest sensitization. Something that a standard (two-group) experimental design cannot control. Pretest sensitization (a.k.a. interaction between pretest and treatment) occurs when the use of a pretest increases or decreases the responsiveness of the participants to the study intervention. For example: Consider a pretest that contains questions that non-deliberately make participants more aware and concerned regarding the consequences of smoking. Such pretest may sensitize participants to make them more responsive to a smoking cessation intervention. Limitation/s: high cost (twice the sample size, time, materials, resources, and personnel/work.) Dehghan et al. investigated VR (Virtual Reality) technology as a method to reduce anxiety in children undergoing surgery. The pretest and posttest measured the anxiety score by using a standardized questionnaire. The intervention used was a VR technique that simulates step- by-step going into an operation room. Results The study concluded that VR technology reduced pre-operative anxiety in children by acting as a distraction method. Research Question: Does a new study technique improve exam scores compared to traditional study methods? Procedure: 1. Participants are randomly assigned to one of four groups: Group 1 receives the new study technique and is pretested, Group 2 receives the new study technique but is not pretested, Group 3 does not receive the new study technique but is pretested, and Group 4 does not receive the new study technique and is not pretested. 2. Pretesting involves assessing participants' current study habits and baseline exam scores. 3. All groups study for the same amount of time. 4. Participants then take the same exam. 5. Post-testing involves assessing participants' exam scores. Results: Comparisons between Group 1 and Group 3 determine the effect of pretesting. Comparisons between Group 2 and Group 4 determine the effect of the new study technique. Comparisons between Group 1 and Group 2 determine the interaction between pretesting and the new study technique. Comparisons between Group 3 and Group 4 serve as a control for any differential attrition or testing effects. MATCHED PAIRS DESIGN matched pairs design is an experimental design where participants having the same characteristics get grouped into pairs, then within each pair, 1 participant gets randomly assigned to either the treatment or the control group and the other is automatically assigned to the other group CONTRAST TO simple randomized experiment, where the list of all participants in the study gets randomized to either the treatment or the control group. MATCHED PAIRS DESIGN WHEN TO USE? to enforce a balance between important participant characteristics that may influence the outcome. Pair-matching benefits studies with small samples sizes where it is difficult to obtain balanced groups by complete random allocation. A. matching is the difficulty to find appropriate matches. B. impractical in certain clinical settings where patients who arrive  at the clinic must be treated immediately C. financially expensive to implement Matching on 1 variable will not be enough in some cases because the pairs will not be close enough Matching on too many variables will lead to overmatching because the selected pairs become too similar example matching individuals on age, gender, BMI and socio-economic factors, this would certainly compromise the ability to study the effect of cholesterol levels on heart disease, since all these matching variables are somewhat related to cholesterol levels. for large sample sizes, matching is not necessary since the study groups are already balanced at baseline just by random assignment Randomized Block Design: randomized block design is a type of experiment where participants who share certain characteristics are grouped together to form blocks, and then the treatment (or intervention) gets randomly assigned within each block. The objective of the randomized block design is to form groups where participants are similar, and therefore can be compared with each other Blocking on gender Santana-Sosa et al. set to study the effect of a 12-week physical training program on the ability to perform daily activities in Alzheimer’s disease patients. And because physical capability differs substantially between males and females, the authors decided to block on gender. 16 patients participated in the study: 10 females and 6 males. Blocking on gender Santana-Sosa et al. When to use it: An unwanted/uninteresting variable affects the outcome. This variable can be measured. Your sample size is not large enough for simple randomization to produce equal groups Blocking reduces the error term, making your statistical model more predictive and more generalizable. Limitations 1. We cannot block on too many variables 2. Difficulty in choosing the number of blocks If you used fewer blocks than you need: You may have a hard time maintaining homogeneity within each block.  If you used more blocks than your sample size allows: You may end up with few participants in each block to be properly randomized to treatment options. Surveys and Questionnaires Questionnaire a tool used in research to gather information from people by asking them a set of questions. It's a way to collect data directly from individuals. Most of the questions in a questionnaire are closed-ended, meaning people choose from a set of provided answers (like multiple-choice). Sometimes, it includes open-ended questions, where respondents can give their own detailed answers. Types of Questionnaires: 1. Questionnaires for separate variables: These ask about things like preferences (what people  like), behaviors (what people do), and facts (basic information like age or job). They collect straightforward information. 2. Questionnaires for scalable factors: These measure things like identities (how people see themselves), traits (personality characteristics), and attributes (qualities or features). These responses might be on a scale (like rating something from 1 to 5) to capture a range of opinions or feelings. Administration Methods: Researchers can use different ways to give out questionnaires, such as: Online (via email or websites) Over the phone In person Through the mail Each method has its advantages depending on the research needs and the group of people being studied. 1. Questionnaires for Separate Variables: Preferences: Example question: “Which type of coffee do you prefer?” Choices: Espresso Latte Cappuccino Behaviors: Example question: “How often do you exercise per week?” Choices: 0 times 1-2 times 3-4 times 5 or more times Facts: Example question: “What is your age?” Choices: Under 18 18-25 26-35 36-50 Over 50 Questionnaires for Scalable Factors: Identities:  Example question: “To what extent do you identify with being environmentally conscious?” Scale: 1 (Not at all) to 5 (Very much) Traits: Example question: “How would you rate your level of introversion or extroversion?” Scale: 1 (Very introverted) to 5 (Very extroverted) Attributes: Example question: “How satisfied are you with your work-life balance?” Scale: 1 (Very dissatisfied) to 5 (Very satisfied) aIn the first type (separate variables), the focus is on gathering factual or straightforward information. In the second type, the goal is to measure feelings, identities, or traits on a scale, giving a range of responses that capture the intensity or degree of an opinion or attribute. Survey a research method used to gather information from a group of people by using tools like questionnaires. The goal is to collect data, analyze it, and draw conclusions that can represent a larger population. Surveys are widely used in scientific, academic, and business research to understand trends, behaviors, or opinions in various fields. Key Points about Surveys: 1. Data Collection with Questionnaires: Surveys use questionnaires (a set of questions) to collect responses from selected participants. These questions help researchers gather the necessary information. 2. Generalizing Results: Surveys aim to generalize the findings to a larger group of people, meaning the results  from a specific set of respondents can be used to understand broader trends in the whole population. 3. Quantitative and Qualitative Data: Surveys often use a mix of closed-ended questions (where people choose from set answers) to generate quantitative data (numbers and statistics). They may also include open-ended questions (where people can write their own answers), which give qualitative data (detailed, descriptive information). 4. Participant Selection: The people who take part in the survey (respondents) are chosen carefully, using standardized procedures and screening methods to avoid biases, ensuring the results are reliable and not skewed. Example: A company wants to understand customer satisfaction. They use a survey to ask customers: Closed-ended question: “How satisfied are you with our service?” (rated from 1 to 5) Open-ended question: “What improvements would you suggest?” The company collects this data, analyzes it, and uses it to improve their service based on the general feedback they gathered. Differences and Similarities Between Surveys and Questionnaires Questionnaires are tools made up of a set of questions designed to collect specific answers from respondents. They are essentially instruments for data collection. Surveys, on the other hand, are research methods that use questionnaires to not only collect data but also evaluate, analyze, and interpret it to gain insights. In other words, a survey is a broader process that includes using a questionnaire to gather information and then analyzing that data. Key Differences: (1) Purpose: Questionnaires: Focus solely on gathering data through asking questions.  Surveys: Go beyond just asking questions. They involve designing the survey, selecting participants (sampling), collecting responses, and analyzing the data. (2) Time: Questionnaires: Tend to be faster since they are just a list of questions. Surveys: Take more time because they include multiple steps—such as gathering participants, data collection, and analysis. (3) Cost: Questionnaires: More cost-effective due to their simplicity and shorter time frame. Surveys: More expensive because they are time-consuming and often require analysis tools or software. Key Differences: (4) Questions: Questionnaires: Usually consist of closed-ended questions (where respondents pick from pre-defined answers). Surveys: Include both closed- and open-ended questions, giving respondents more flexibility in their answers and generating richer data. (5) Answers: Questionnaires: Closed-ended questions tend to produce objective (fact-based) answers. Surveys: Can gather both objective and subjective (opinion- based) responses, thanks to the mix of question types. Why the Differences Matter: Questionnaires only provide raw data (the answers from respondents). However, by themselves, these answers may not be insightful unless they are further analyzed. A survey involves aggregating the data from questionnaires, analyzing trends, and drawing conclusions. Therefore, surveys are more useful when you want to make sense of the data to find patterns or predict outcomes. When to Use Questionnaires vs. Surveys: When to use questionnaires: Stand-alone questionnaires are suitable for collecting simple information from individuals, such as: Accepting donations. Creating email lists. Gathering payment details. Conducting job interviews. When to use surveys: Surveys are more appropriate when you want to analyze feedback or evaluate specific aspects, such as: Customer feedback after an experience. Determining the success of a product. Gauging employee satisfaction. Conducting exit interviews. Evaluating brand awareness. Summary: A questionnaire is just a set of questions used to collect raw data. A survey is a complete research method that includes designing a questionnaire, collecting data, and analyzing the results to gain insights. Surveys are more in-depth, while questionnaires are quicker and more straightforward. Longitudi nal Studies Tracking Variables Over Time  a research method where scientists track the same group of individuals over a long period to see how certain variables (like health, behavior, or traits) change over time. This method is often used in psychology to explore long-term relationships between different factors How a Longitudinal Study Works: *Researchers start by deciding what they want to study and who they will observe. They then gather baseline data, which serves as a starting point. *Over the next months, years, or even decades, researchers collect more data from the same group of people. This allows them to track changes and see how those changes relate to the variables they are studying. For example, if researchers want to know how exercise in middle age affects cognitive health in older age, they might recruit people in their 40s and 50s. They'd collect data on their exercise habits and mental performance. Over the years, they would continue to measure these variables to see if physically fit participants show less cognitive decline in their 70s and 80s. Early Examples of Longitudinal Studies: *In the 17th century, King Louis XIV gathered information about his Canadian subjects over time to understand their health and economy. *In the 18th century, Count Philibert de Montbeillard conducted one of the first formal longitudinal studies, measuring his son's growth every six months. *The Genetic Studies of Genius (started in 1921) followed gifted children into adulthood to see if they shared common traits and to disprove the idea that gifted kids were socially awkward. Types of Longitudinal Studies: Panel study: Tracks a cross- section of individuals over time (for example, a group from different backgrounds). Cohort study: Focuses on a group of people who share a specific characteristic (like being born in the same year). Retrospective study: Looks back at historical data (like medical records) to analyze past trends. Benefits of Longitudinal Research: These studies provide deep insights that other methods can't, especially when looking at developmental and lifespan changes. They help scientists understand how certain factors (like genetics or environment) influence personality or behavior over time. for example, studies on identical twins raised together or apart can reveal whether genetics or upbringing has a greater impact on their traits. Challenges and Pitfalls: Cost and time: Longitudinal studies are expensive and take a long time to complete, which often limits the number of participants. Selective attrition: Participants may drop out over time due to illness, moving, or losing interest. This shrinking of the sample size can hurt the study's validity (whether the study accurately reflects the larger population). If the final group doesn't represent the original sample, the results might not apply to a broader population. TAKEAWAYS A longitudinal study is a powerful tool for understanding long- term changes and relationships between variables. However, it requires significant resources, time, and careful planning to ensure the results are meaningful and reliable. WHAT do the following classic studies have in common? Elizabeth Loftus and Jacqueline Pickrell showed that it is relatively easy to “implant” false memories in people by repeatedly asking them about childhood events that did not actually happen to them (Loftus & Pickrell, 1995). ( example of single-variable research David Rosenhan found that confederates who went to psychiatric hospitals claiming to have heard voices saying things like “empty” and “thud” were labeled as schizophrenic by the hospital staff and kept there even though they behaved normally in all other ways (Rosenhan, 1973). Loftus and Pickrell study is an example of single-variable research Rosenhan - qualitative Learning Objectives  1.Define nonexperimental research, distinguish it clearly from experimental research, and give several examples. 2.Explain when a researcher might choose to conduct nonexperimental research as opposed to experimental research. Non Experimental Design type of research design that relies on observation and measurement rather than experimentation with randomly assigned participants observes and analyzes phenomena in their natural context to gather inform Observation: Researchers analyze events that have already occurred. No Controlled Experiments: Ethical or practical reasons prevent controlled experiments. Existing Samples: Researchers use existing samples or participants. No Direct Intervention: Researchers do not directly intervene in the sample environment When to Use Nonexperimental Research (1) When the research question focuses on a single variable. (e.g., How accurate are people’s first impressions?). What are the average weekly exercise habits of adults in a metropolitan city? (2) When there is a non-causal statistical relationship between variables. (e.g., Is there a correlation between verbal intelligence and mathematical intelligence?). Is there a relationship between sleep quality and anxiety levels in college students? (3) The research question can be about a causal relationship, but the independent variable cannot be manipulated or participants cannot be randomly assigned to conditions or orders of conditions (e.g., Does damage to a person’s hippocampus impair the formation of long- term memory traces?). Does childhood trauma affect adult mental health outcomes? (4) The research question can be broad and exploratory, or it can be about what it is like to have a particular experience (e.g., What is it like to be a working mother diagnosed with depression?). What are the key factors that contribute to resilience in individuals facing significant life stressors? three broad categories: single-variable research, correlational and quasi-experimental research, and qualitative research. SINGLE-VARIABLE RESEARCH The study by Loftus and Pickrell described at the beginning of this chapter is also a good example of single-variable research. The variable was whether participants “remembered” having experienced mildly traumatic childhood events (e.g., getting lost in a shopping mall) that they had not actually experienced but that the research asked them about repeatedly. In this particular study, nearly a third of the participants “remembered” at least one event. single-variable research can answer interesting and important questions. it cannot do- is answer questions about statistical relationships between variables. CORRELATIONAL RESEARCH AND QUASI EXPERIMENTAL RESEARCH - it focuses on a statistical relationship between two variables but does not include the manipulation of an independent variable, random assignment of participants to conditions or orders of conditions, or both. This kind of research takes two basic forms: correlational research and quasi-experimental research. In correlational research, the researcher measures the two variables of interest with little or no attempt to control extraneous variables and then assesses the relationship between them. Workplace stressors, psychological well-being, resilience, and caring behaviours of mental health nurses: A descriptive correlational study Psychological well-being was moderately high, but lower for nurses indicating consumer/carer-related stressors as their most stressful challenge. There were weak to moderate (r = 0.306 to r = 0.549) positive relationships between workplace resilience and psychological well-being, and no relationship between resilience and caring behaviours. Workplace resilience was lower (P < 0.05) for less experienced nurses compared with those with >5 years’ experience, and lower for younger nurses compared with those aged ≥40 years. Foster, K., Roche, M., Giandinoto, J. A., & Furness, T. (2020). Workplace stressors, psychological well‐being, resilience, and caring behaviours of mental health nurses: A descriptive correlational study. International journal of mental health nursing, 29(1), 56-68. In quasi-experimental research the researcher manipulates an independent variable but does not randomly assign participants to conditions or orders of conditions. For example, a researcher might start an antibullying program (a kind of treatment) at one school and compare the incidence of bullying at that school with the incidence at a similar school that has no antibullying program. qualitative. the data are usually nonnumerical and therefore cannot be analyzed using statistical techniques Rosenhan’s study of the experience of people in a psychiatric ward was primarily qualitative. The data were the notes taken by the “pseudopatients”—the people pretending to have heard voices—along with their hospital records. Rosenhan’s analysis consists mainly of a written description of the experiences of the pseudopatients, supported by several concrete examples. To illustrate the hospital staff’s tendency to “depersonalize” their patients, he noted, “Upon being admitted, I and other pseudopatients took the initial physical examinations in a semipublic room, where staff members went about their own business as if we were not there” (Rosenhan, 1973, p. 256). Qualitative Qualitative data has a separate set of analysis tools depending on the research question. thematic analysis would focus on themes that emerge in the data or conversation analysis would focus on the way the words were said in an interview or focus group. Non Experimental Design (Internal Validity) internal validity is the extent to which the design of a study supports the conclusion that changes in the independent variable caused any observed differences in the dependent variable. Key Takeaways *Nonexperimental research is research that lacks the manipulation of an independent variable, control of extraneous variables through random assignment, or both. *There are three broad types of nonexperimental research. Single-variable research focuses on a single variable rather than a relationship between variables. Correlational and quasi-experimental research focus on a statistical relationship but lack manipulation or random assignment. Qualitative research focuses on broader research questions, typically involves collecting large amounts of data from a small number of participants, and analyses the data nonstatistically. *In general, experimental research is high in internal validity, correlational research is low in internal validity, and quasi-experimental research is in between. Qualitative Research? the process of collecting, analyzing, and interpreting non- numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality. non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis “Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.” Qualitative Research Designs Phenomenology aaa research approach that seeks to understand the essence of a particular phenomenon through a detailed exploration of individual experiences. It is especially beneficial for exploring personal experiences such as emotions, perceptions, and awareness. When to Use: When you aim to understand the essence of lived experiences regarding a particular phenomenon.  When your research question focuses on the commonalities of experiences among a group of individuals. When exploring deep, personal insights into how people perceive and make sense of their experiences. Characteristics: In-depth interviews with individuals who have directly experienced the phenomenon. Analysis focuses on identifying themes and essence of experiences. Example: Investigating the lived experiences of college students coping with severe anxiety. Example: The Experience of Burnout in Healthcare Workers Research Question: How do healthcare workers experience and interpret burnout? Objective: To explore the personal and professional experiences of burnout among healthcare workers. Methodology: 1. Participants: A diverse sample of healthcare workers from different disciplines (e.g., nurses, doctors, therapists) experiencing burnout.  2. Data Collection: Conducting detailed, open-ended interviews to gather rich, descriptive accounts of their experiences. 3. Data Analysis: Using Moustakas’ phenomenological analysis approach, which involves horizonalization (highlighting significant statements), developing clusters of meaning, and creating a composite description of the phenomenon. Findings: The study might uncover themes such as: Emotional Exhaustion: Participants often feel drained and overwhelmed by their work demands. Depersonalization: A sense of detachment from patients and a feeling of reduced personal accomplishment. Impact on Personal Life: Burnout significantly affects their relationships and personal well-being. Recovery and Resilience: Some healthcare workers identify strategies that help them cope and recover, such as peer support, mindfulness practices, and institutional support. Implications: The insights gained can help healthcare organizations develop better support systems and interventions to prevent and mitigate burnout among their staff, ultimately leading to improved patient care and worker satisfaction. descriptive qualitative study sattempts to systematically describe a situation, problem, phenomenon, service or programme. It focuses on discovering the who, what, and where of events or experiences and gaining insights from informants regarding a poorly understood phenomenon It is also used when more information is required to aid the development and refinement of questionnaires in research projects aiming to gain firsthand knowledge of patients’, relatives’ or professionals’ experiences with a particular topic An example is the study by Cao et al. 2022 that explored the state of education regarding end-of-life care from the perspectives of undergraduate nurses. The findings showed that the undergraduate curriculum related to end- of-life care was disjointed and cultural attitudes toward disease and death impede the undergraduate nurses’ learning and knowledge translation of end-of-life care. When to use: Exploring Complex Phenomena, Understanding Context, Gathering Detailed Descriptions, Developing Theories or Hypotheses, Exploring New Areas, Patient or Participant Perspectives, Evaluating Programs or Interventions, Generating Rich Data for Further Analysis.  Healthcare Research: Understanding patients' experiences with chronic illness. Education: Exploring teachers' perceptions of a new curriculum. Social Work: Describing the lived experiences of homeless individuals. Marketing: Capturing consumer attitudes towards a new product. The Impact of Caregiving on Family Members of Individuals with Alzheimer's Disease Research Question: What are the experiences of family members who provide care for individuals with Alzheimer's disease? Objective: To describe the emotional, physical, and social impacts of caregiving on family members. Methodology: Participants: Family members who are primary caregivers for individuals diagnosed with Alzheimer's disease. Data Collection: In-depth interviews focusing on the daily caregiving experiences, challenges, and coping strategies. Data Analysis: Content analysis to systematically categorize and describe the experiences shared by caregivers. Findings: Common themes might include: Emotional Burden: Feelings of sadness, frustration, and helplessness associated with caregiving responsibilities. Physical Strain: Reports of physical exhaustion and health issues arising from the demands of caregiving. Narrative inquiry AAqualitative research that seeks to understand how individuals make meaning of their lives and the world around them through studying their stories and 23 experiences. This qualitative research focuses on marginalised populations, usually individuals or small groups and aims 24 to give voice to their perspective. This approach helps people learn more about the participants’ culture, historical experiences, identity, and lifestyle and is often recorded as a biography, life history, 25 artifacts or traditional story. It captures a wealth of story data, including emotions, beliefs, images, and insights about time. An example is the study by Gordon et al. 2015 which explored medical trainees’ experiences of leadership and followership in the interprofessional healthcare 28 workplace. The findings showed that participants most often narrated experiences from the position of 28 follower. Their narratives illustrated many factors that facilitate or inhibit the development of leadership 28 identities. Traditional medical and interprofessional  hierarchies persist within the healthcare workplace, and wider healthcare systems can act as barriers to distributed 28 leadership practices. When to Use: When your focus is on the stories of individuals and how they make sense of their experiences through storytelling. When you want to explore the chronological or thematic aspects of individual experiences. When investigating how personal and social narratives shape identities and behaviors. Characteristics: Collection of detailed personal stories. Analysis of the structure, content, and context of narratives. Example: Studying personal stories of overcoming anxiety among first-generation college students. Case Study SCase study aids researchers in giving a holistic, detailed account of a single case (or more) as it occurs in its real- 30 life context. The purpose of a case study is to understand complex phenomena and to explore new 29 research questions in a real-world setting. There are three main types of qualitative case study design: intrinsic  case study, instrumental case study and collective case 31 study. An intrinsic case study is often conducted to learn about a 31 one-of-a-kind phenomenon. This type of case study focuses on a single case or a small number of cases and 30,31 explores a specific phenomenon or issue in depth. The researcher needs to define the phenomenon’s distinctiveness, which separates it from all others. the instrumental case study employs a specific instance (some of which may be superior to others) to acquire a more extensive understanding of an issue or 30,31 phenomenon. An instrumental case study uses a single case or a small number of cases to explore a broader research question or problem The collective case study researches numerous instances concurrently or sequentially to obtain a more comprehensive understanding of a specific 30,31 subject. This type of case study analyses multiple cases to understand a phenomenon or issue from different perspectives ssThe data collection techniques used in a case study include interviews, observations, or written or visual materials. Data can be collected from various sources, including the case, documents or records, and other relevant individuals. An example of a case study is the study by Lemmen et al. 2021, which aimed to provide insight into how adopting positive health (PH) in a general practice affects primary 32 care professionals’ (PCP) job satisfaction. The findings of the study identified three themes regarding PCPs’ adoption of PH and job satisfaction, namely adopting and adapting Positive Health, giving substance to Positive Health in practice, and changing financial and 32 organisational structures. Thus, the PCPs adopted PH, which supported PCPs to express, legitimise, and promote 32 their distinctive approach to care work and its value. PH also enabled PCPs to change their financial and organisational structures, freeing time to spend on patients and their own well-being. The changes made by the practice increased the job satisfaction of the PCPs When to Use: When you need an in-depth, holistic understanding of a single case or a small number of cases. When exploring a phenomenon within its real-life context, especially when the boundaries between phenomenon and context are unclear. When your research involves complex issues that can be best understood through detailed examination. Characteristics: Multiple data sources: interviews, observations, documents, and artifacts. Can focus on individuals, groups, organizations, or events. Example: A detailed study of a university's support program for students with anxiety disorders. Case Study 1: The Impact of Trauma on Childhood Development Research Focus: Examining the psychological and developmental effects of early childhood trauma on a young child. Execution: Participant Selection: Case Subject: A 7-year-old child who has experienced significant trauma (e.g., abuse or loss of a parent). Criteria: Confirmed traumatic event, observable psychological symptoms, and willingness of guardians to participate. Data Collection Methods: Interviews: Conduct structured and unstructured interviews with the child, parents, and teachers. Observations: Observe the child in different settings such as at home, in school, and during therapy sessions. Psychological Assessments: Use standardized tools to measure anxiety, depression, attachment styles, and developmental milestones. Data Analysis: Qualitative Analysis: Thematic analysis of interview transcripts and observational notes to identify patterns and themes. Quantitative Analysis: Scoring and interpreting psychological assessments to provide a comprehensive profile of the child’s psychological state. ETHNOGRAPHY the study of culture and entails the observation of details of everyday life as they naturally unfold in the real world. It is commonly used in anthropological research focusing on 33 the community. It generally involves researchers directly observing a participant’s natural environment over 33 time. A key feature of ethnography is the fact that natural settings, unadapted for the researchers’ interests, are used. the natural setting or environment is as important as the participants, and such methods have the advantage of explicitly acknowledging that, in the real world, environmental constraints and context influence behaviours and outcomes Ethnography focuses on the lived culture of a group of people, that is, the knowledge they use to generate and interpret social behaviour Ethnography often involves a small number of cases or a community, ethnic or social groups. The researcher enters the lived experience of participants in the field and spends considerable time with them to understand their way of life. This research approach increases the strength of the data An example of ethnographic research is the study by Hinder and Greenhalgh, 2012. The study sought to produce a richer understanding of how people live with diabetes and why self-management is challenging for some. The study revealed that self-management involved both practical and cognitive tasks (e.g. self-monitoring, menu planning, medication adjustment) and socio- emotional ones (e.g. coping with illness, managing relatives’ input, negotiating access to services or 36 resources). Self-management was hard work and was enabled or constrained by economic, material and socio- cultural conditions within the family, workplace and 36 community. Although this study is old, it provides insight into some of the challenges associated with 36 diabetes. While more devices have helped with diabetes in recent years, some of these challenges may still exist. When to Use: When studying cultures, communities, or social groups in depth. When you need a holistic understanding of cultural practices, rituals, and daily life. When you want to immerse yourself in the field to observe and interact with participants over an extended period. Characteristics: Long-term fieldwork and immersion. Focus on cultural context and participant perspectives. Example: Examining the cultural practices and social dynamics within a college fraternity or sorority. Mental Health Practices in Indigenous Communities Research Focus: Understanding traditional mental health practices and beliefs in an Indigenous community. Execution: 1. Participant Selection: 1. Community: Select an Indigenous community with distinct traditional mental health practices. 2. Participants: Community members, including elders, healers, and individuals seeking mental health support. 2. Data Collection Methods: 1. Participant Observation: Spend extended time in the community, observing and participating in daily activities and mental health rituals. 2. Interviews: Conduct in-depth, semi- structured interviews with community members, focusing on their understanding of mental health, causes of mental illness, and traditional healing practices. 3. Focus Groups: Facilitate group discussions to gather diverse perspectives on mental health practices within the community.  1Data Analysis: Thematic Analysis: Identify and analyze themes related to mental health beliefs, practices, and the role of healers in the community. Narrative Analysis: Explore the stories and experiences shared by community members to understand the cultural context of mental health. Findings: Holistic Approach: Mental health is seen as interconnected with physical, spiritual, and social well- being. Role of Healers: Traditional healers play a central role in diagnosing and treating mental health issues, often using rituals, herbs, and spiritual guidance. Community Support: Strong emphasis on community support and collective responsibility for individuals' mental well-being. Implications: Insights can inform culturally sensitive mental health interventions and policies that respect and integrate traditional practices. ACTION RESEARCH involves a cyclical process of planning, action, observation, and reflection to improve practice or address a problem. The goal of action research is to generate new knowledge and understanding about a specific issue while at the same time taking action to improve the situate Action research is guided by the desire to take action, so it is not a design. A type of action research is participatory 38 action research. At its core, this is a collaborative, self- reflective enquiry undertaken by researchers and participants to understand and improve upon the practices in which they participate and the situations in which they 38 find themselves. The goal is for the participant to be an 39 equal partner with the researcher. The reflective process is inextricably tied to action, impacted by knowledge of history, culture, and the local context, and is rooted in social connections The study by Doherty and O’Brien, 2021 explored midwives’ understandings of burnout, professionally and personally, in the context of contemporary maternity care 42 in Ireland. Multiple factors influenced midwives’ views and understandings of burnout. PAR provided a platform for midwives to examine their ideas and views on burnout with the collaborative support of their midwifery colleagues, via cycles of action and reflection, which is necessary to develop and maintain change. Midwives characterised burnout as continuous stress and tiredness, with an accompanying decline in their coping capacities, motivation, empathy, and/or efficacy. Burnout is unique to the person and is primarily induced and irrevocably tied to 42 excessive workload in midwifery. Example: Improving Student Mental Health in a High School Problem Identification: A high school has noticed an increase in student anxiety and depression. The school counselor and psychology teacher decide to conduct action research to address this issue. Planning: Goal Setting: The goal is to reduce anxiety and depression among students and improve their overall mental health. Data Collection: Initial data is gathered through surveys to assess the levels of anxiety and depression. Focus groups with students, teachers, and parents provide qualitative insights. Action: Interventions: Implement mindfulness sessions during homeroom periods. Introduce a peer support program where trained students provide support to their peers. Organize workshops for teachers on recognizing and responding to signs of mental distress. Resource Allocation: Allocate time and resources for training teachers and peer supporters. Observation: Monitoring: Regularly monitor student attendance at mindfulness sessions and peer support groups. Feedback Collection: Conduct follow-up surveys and interviews to gather feedback from students, teachers, and parents on the effectiveness of the interventions. Reflection: Data Analysis: Analyze the survey and interview data to determine changes in anxiety and depression levels. Evaluation: Evaluate which interventions were most effective and why. Reflect on any challenges faced during implementation. Adjustment: Modify Interventions: Based on feedback and data analysis, make necessary adjustments to the interventions. For example, if peer support is more effective than mindfulness sessions, increase the focus on peer support. Cycle Repeat: Repeat the cycle to further refine and improve the interventions, ensuring continuous improvement in student mental health. Reporting: Share Findings: Present the findings to the school administration, teachers, parents, and possibly at educational psychology conferences. Publish Results: Consider publishing the research in a relevant journal to contribute to the broader field of educational psychology. GROUNDED THEORY Grounded theory first described by Glaser and Strauss in 1967, is a framework for qualitative research that suggests that theory must derive from data, unlike other forms of research, which 43 suggest that data should be used to test theory. It is a qualitative research process that entails developing theories based on evidence that has been collected from the 43 participants. Grounded theory may be particularly valuable when little or nothing is known or understood about a problem, situation, or 44 context. The main purpose is to develop a theory that explains patterns and correlations in data and may be utilised to understand and predict the phenomenon under investigation interviews, focus groups, questionnaires, surveys, transcripts, letters, government reports, papers, grey literature, music, artefacts, videos, blogs and memos, then analysing it to identify patterns and relationships (1) An example is the study by Malau-Aduli et al., 2020; the study had two main aims – (1) to identify the factors that influence an International Medical Graduate’s (IMG) decision to remain working in regional, rural, and remote areas; (2) to develop a theory, grounded in the data, to explain how these factors are prioritised, evaluated and used to inform a decision 48 to remain working in RRR areas. The findings revealed that the IMG decision-making process involved a complex, dynamic, and iterative process of balancing life goals based on life stage. Many factors were considered when assessing the balance of three primary life goals: satisfaction with work, family, and lifestyle. (2) Another example is the study by Akosah-Twumasi et al. 2020 which explored the perceived role of sub-Saharan African migrant parents living in Australia in the career decision-making 49 processes of their adolescent children. The study showed that the majority of SSA immigrant parents continued to parent in the same manner as they did back 49 home. Interestingly, some parents modified their parenting approaches due to their perceptions of the host 49 nation. However, due to their apparent lack of educational capacity to educate their children, other parents who would otherwise be authoritative turned into trustworthy figures When to Use: When your goal is to develop a theory grounded in data collected from participants. When existing theories do not adequately explain the phenomenon. When you want to derive a theory based on the iterative collection and analysis of data. Characteristics: Iterative process of data collection, coding, and analysis. Focus on generating new theories. Example: Developing a theory on how college students develop resilience to anxiety through campus activities. QUALITATIVE DATA COLLECTION METHODS (1) Interview transcripts: Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings. When to Use: When you need in-depth, detailed information about individuals' experiences, thoughts, feelings, or perspectives. When exploring complex topics where personal context and meaning are important. When you want to clarify, elaborate, or expand on quantitative findings. Types: Semi-structured Interviews: Use when you have specific topics to explore but want the flexibility to follow up on interesting responses. Structured Interviews: Use when you need to ensure that all respondents answer the same questions, maintaining consistency. Unstructured Interviews: Use when you want to allow respondents to express themselves freely and explore topics that arise naturally during the conversation. Example: Conducting semi-structured interviews with students to understand their personal strategies for managing anxiety. Qualitative Research Title: "Exploring the Lived Experiences of Individuals with Anxiety Disorders: A Phenomenological Study" Observations: The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices. 3. Observations When to Use: When studying behaviors, interactions, or processes in their natural settings. When you need to understand the context and environment of the phenomenon. When you want to capture non-verbal cues and actions that might not be revealed through interviews. Types: Participant Observation: Use when the researcher is actively involved in the setting. Non-participant Observation: Use when the researcher observes without involvement, maintaining a distance. Diaries or journals: Written accounts of personal experiences or reflections. Focus Groups: Focus groups involve the gathering of a small group of individuals to discuss a particular topic or issue. Researchers using focus group methods typically facilitate a discussion among the group, allowing participants to share their perspectives and experiences. Focus groups are used to gather data from a group of people who share similar characteristics or experiences. The moderator of the focus group asks open- ended questions and encourages group discussion. When to Use (FGD): When you want to explore group dynamics and interactions. When the topic benefits from collective discussion and varying viewpoints. When you want to generate a broad range of ideas and opinions in a short time. Characteristics: Group discussions guided by a facilitator. Useful for gathering perceptions, attitudes, and beliefs. Example: Conducting focus groups to gather diverse perspectives on the effectiveness of university mental health services. Oral History: Oral history is a research method that involves the collection and analysis of people’s personal narratives. Researchers conduct interviews with individuals who have lived through specific historical events or who have expertise in a particular field. The data collected through these interviews can provide insights into personal experiences and perspectives. Secondary Sources Secondary data collection involves gathering data from existing sources, such as published literature, government reports, and archival data. Secondary data can be useful in qualitative research for providing context and background information on a topic, as well as for comparing and contrasting findings from primary data sources. SAMPLE SIZE AND SAMPLING TECHNIQUE the ideal sample size depends on the questions being asked, the theoretical framework, the study design, the type of data that is gathered, the available resources, and the amount of time The goal of a qualitative study is not to generalise the findings to a larger population but rather to provide a detailed and in- depth understanding of the specific case or cases being studied. The minimum number and types of sample units needed in qualitative research cannot be predetermined using calculations 50 or power analyses. The basic methodological principle in qualitative research is to achieve saturation, which means you keep sampling until you stop learning new details or insights about the phenomenon under investigation In general, you should keep asking participants until the area of interest is saturated and until you hear nothing new.. A systematic review of empirical results showed that qualitative studies that had 9-17 interviews or 4-8 focus group discussions reached saturation It entails the deliberate, purposeful recruitment of individuals who can offer in-depth, precise details on the topic being 53 studied. There are numerous purposive sampling techniques. Examples include typical, extreme or deviant, critical, maximum variation and homogenous sampling Typical case highlights or illustrates what is normal, typical or average in a case. The purpose is to describe what is typical to those who are unfamiliar with the concept or phenomenon Extreme or deviant is used when researchers want to explore deviations or outliers from the norm regarding a particular subject critical case involves exploring one case to provide insight into other similar cases. The maximum variation sampling technique is used if the research aims to uncover core and shared elements/ themes that cut across a diverse sample while simultaneously offering the opportunity to identify divergent opinions homogenous sampling focuses on people of similar backgrounds and experiences. It reduces variation and is mainly used for focus group discussions An example of purposive sampling is the study by Adu et al., 2019 which investigated the common gaps in skills and self-efficacy for diabetes self-management and explored other factors which serve as enablers of and barriers to achieving optimal diabetes self- 55 management. The study utilised a maximum variation purposive sampling technique to recruit participants into the 55 study. Figure 4.3 illustrates purposive sampling, where researchers wish to explore the perceptions of people living with diabetes. Diabetic patients were approached and recruited into the study. is a technique used to recruit participants who are representative of the population from which they are selected but chosen because they are easily accessible and convenient to the researchers rather than being randomly selected this may include utilising geographic location, association with a facility/contact and resources that make participant recruitment convenient This sampling technique saves time and effort but has low credibility. For example, this study by Obasola and Mabawonku, 2018 used convenience sampling to select 1001 mothers attending maternity clinics at health facilities in Nigeria THEORETICAL SAMPLING Theoretical sampling is a data collection process controlled by a 43 theory generation process. It involves the simultaneous collection, coding and analysis of data to identify the next stage of data collection and where to find the participants to develop the emerging theory It is the principal strategy for the grounded theory 43 approach. According to theoretical sampling, new goals for data collection are determined by the information gathered from the previous sample For example, the study by Ligita et al. 2019 utilised theoretical sampling in the study that sought to generate a theory to explain the process by which people with diabetes learn about their disease in Indonesia. The study was conducted in three phases, with a total of twenty-six participants. In the first phase, participants were recruited via purposive sampling, and data from the first phase led to further data gathering. Theoretical sampling was used to select the next data from 17 participants based on the data analysis. Phase three was directed via theoretical sampling, with two new participants recruited into the study. In Figure 4.5, two examples of how theoretical sampling was used in the study have been highlighted Snowball sampling – This technique is used when it is hard to reach potential participants e.g. members of minority groups. The researcher initially contacts a few potential participants and asks them to provide contact details of people or refer people they know who meet the selection 60 criteria. These identified or named individuals are then recruited into the study. A simple way to consider this technique is to think of how a small snowball rolls down a hill and gets bigger as it gathers more snow SSAn example is the study by Kaplan, Korf and Sterk, 1987 which describes the temporal and social contexts of 61 Heroin-using populations in two Dutch cities. While the article may be several years old, the graphical presentation and description of the snowballing technique are still valid