Research Methods Week 1 PDF

**Research Methods Week 1** ***Choosing The Right Research Design*** By the end of this week you should be able to: 1. Summarise and apply the four key values and principles of ethical research conduct outlined by the NHMRC National Statement.  - Research merit and integrity: Merit refers...

**Research Methods Week 1** ***Choosing The Right Research Design*** By the end of this week you should be able to: 1. Summarise and apply the four key values and principles of ethical research conduct outlined by the NHMRC National Statement.  - Research merit and integrity: Merit refers to the quality of the study, and integrity refers to the intentions and conduct of the researchers. For a study to have merit and integrity, it must have potential to contribute knowledge and understanding, improved social welfare and wellbeing. Research must be designed in a way that respect for the participants is not compromised by the aims of research. It must be conducted by people with appropriate qualifications, expertise and competence. Both aims and methodology must be based on thorough evaluation of past research. - Justice: Refers to fair treatment. This incorporates distributive justice (fair distribution of risks and benefits of the research) and procedural justice (fair treatment in the recruitment of participants, and fair ethical review of the research.) There is to be no exploitation of participants and process of recruiting is fair - Beneficence: Refers to minimising harm and balancing risks of harm against potential benefits. Making participants aware of risks, harms and benefits of research. Where risks exist, they must be mitigated to the extent that it is possible to do so, and participants must be informed of those risks before agreeing to participate. At any point during the research should it become apparent that the benefits no longer outweigh the risks, the research must be paused to allow time for procedures to be modified or must be discontinued. - Respect: Recognition of basic human rights and intrinsic values. Respect privacy, confidentiality and cultural sensitivities as well as informed consent. 2. Summarise and apply recommendations for conducting ethical research with vulnerable populations. - Respect the dignity of all research participants, engage with the taxonomy and language of participants, examine assumptions about who is and is not in the sample population, protecting participant identities and data, recognising intersectionality and its impact, acknowledge multiple epistemologies, consider pre-existing research, avoid problematising or pathologizing lived experiences, interrogate researcher to determine whether they are an insider or outsider to the community, informed consent, adequate compensation for participants time and generate theory from lived experiences. 3. Describe the purpose, key characteristics, and common variations of experimental and non-experimental quantitative research designs. - Experimental: used to test cause-effect relationships between variables. They measure if one factor/s influences another by manipulating variables hypothesised to be the casual factor and overserving the resultant effects on other variables hypothesised to be affected by that factor. Includes between groups studies (simple two-groups experiment, experiments with 3 or more groups, factorial experiments), repeated measures/pre-post (simple two condition A-B, A-B-A designs, more than two time points, simultaneous repeated measures) and mixed designs (between groups + repeated measures) - Non-experimental: do not involve the manipulation of an independent variable. Purpose is to measure the extent to which a phenomenon occurs in a population (e.g. prevalence), to investigate relationships between variables, or to test differences between groups when random assignment to groups is not possible. Non-experimental designs are unable to directly draw conclusions about causality due to lack of cause-effect. Common variations of experiments include single variable research, cross-sectional correlational research, longitudinal cohort research and quasi-experimental research. 4. Describe the purpose, key characteristics, and common variations of qualitative and mixed methods designs. - Qualitative: purpose is to gain a deep, nuanced understanding of human experiences, behaviours and the social and cultural contexts in which they occur. Key characteristics include type of data being collected (diary entries, field notes, digital data like social media comments and emails and artefacts such as photographs and artwork), data collection method (1:1 interviews, focus groups, observation, text analysis and interpretation) and data analysis and reflexivity. Common variations include narrative inquiry, phenomenology, grounded theory, ethnography and case studies. - Mixed-methods: combines elements of both quantitative and qualitative research, researchers will collect, analyse, and interpret both quantitative and qualitative data. Can be used to develop new theories, more time consuming but more explanatory. 5. Describe the purpose and key characteristics of systematic approaches to summarising past research (SLRs, meta-analyses). - Systematic literature reviews: critical analysis and synthesis of past research on a topic, which aims to identify what is currently known as well as gaps in current understanding that could be investigated in further research. The purpose of an SLR is to provide a comprehensive, unbiased summary of what existing literature on a topic has found, and the quality of evidence in the existing literature. Key characteristics of SLRs are development of a protocol, systematic search procedures, screening studies against eligibility criteria, extracting and summarising data, evaluation of study quality and reporting procedures. - Meta-analysis: extension of SLRs that include synthesis of past research, meta-analyses take the statistical results of past research and statistically aggregate these results to calculate average magnitude of an effect across all of the studies investigated, quantifying heterogeneity. 6. Evaluate and select an appropriate research approach and design for a research question. - A researcher conducts detailed interviews with unmarried teenage fathers to learn about how they feel and what they think about their role as fathers and summarizes their feelings in a written narrative. (I THINK THIS IS A QUALITATIVE RESEARCH DESIGN) - A researcher measures the impulsivity of a large sample of drivers and looks at the statistical relationship between this variable and the number of traffic tickets the drivers have received. (I THINK THIS IS A NON-EXPERIMENTAL CROSS SECTIONAL DESIGN) - A researcher randomly assigns patients with low back pain either to a treatment involving hypnosis or to a treatment involving exercise. She then measures their level of low back pain after 3 months. (I THINK THIS IS AN EXPERIMENTAL BETWEEN-GROUPS DESIGN) - A college instructor gives weekly quizzes to students in one section of his course but no weekly quizzes to students in another section to see whether this has an effect on their test performance. (I THINK THIS IS AN EXPERIMENTAL BETWEEN GROUPS DESIGN) **The four key ethical values and principles, as outlined in Section 1 of the National Statement are:** **Merit and integrity** Merit refers to the quality of the study, whereas integrity refers to the intentions and conduct of the researchers.  For a study to be deemed to have merit and integrity, it must have the potential to contribute to knowledge and understanding, social welfare, and/or individual well-being. It must be designed and conducted using appropriate facilities and scientifically valid instruments. It must be conducted by people with appropriate qualifications and expertise, who will conduct and report the research honestly and in alignment with recognised ethical principles and will disseminate the results for the benefit of the broader community. Both the aims and methodology of the study should be based on thorough evaluation of previous research. **Justice** Justice essentially refers to fair treatment. This incorporates distributive justice (fair distribution of risks and benefits of the research) and procedural justice (fair treatment in the recruitment of participants, and fair ethical review of the research.) For a study to be deemed to respect the principle of justice, the participants for the proposed research must be appropriate for the topic. The method of recruitment should be fair, and no particular social group should be unfairly burdened by the research. There should be an equal distribution of benefits of participation, and participants should not be coerced or exploited. There should be an equal and fair distribution of the benefits of the research to the broader community. **Beneficience** Beneficience** **refers to minimising harm and balancing the risks of harm against potential benefits.  For a study to meet satisfy the principle of beneficence, the benefits of the research must justify any risk or harm experienced by participants. Where risks exist, they must be mitigated to the extent that it is possible to do so, and participants must be informed of those risks before agreeing to participate. At any point during the research should it become apparent that the benefits no longer outweigh the risks, the research must be paused to allow time for procedures to be modified or must be discontinued. A key point to remember here is that research does not need to be without risk - but the risks of participation must be balanced by the beneficial outcomes. That is, the guideline is not \"do no harm\", but rather \"do only as much harm as can be outweighed by the benefit, and ensure participants understand the risk of that harm\". **Respect** Respect refers to the recognition of the basic, intrinsic value of human beings.  For a study to satisfy the principle of respect, the autonomy, privacy, confidentiality, and cultural sensitivities of participants and their communities must be protected. Participants should be empowered to make their own, informed decision about participating in research wherever possible. **Vulnerable populations**, broadly, refers to groups of that may have diminished ability to fully safeguard their own interests in a research setting, or who experience socioeconomic disadvantage, stigma, or discrimination. This vulnerability can be due to a variety of factors such as age, cognitive development or impairment, power imbalances, dependence on medical care, cultural or linguistic barriers, social or economic disadvantages, a history of social oppression, exploitation or disadvantage, or situational vulnerabilities (e.g., refugee status, incarceration etc).   In this section of the module, we will focus on ethical frameworks for working with Aboriginal and Torres Strait Islander peoples, culturally and linguistically diverse (CALD) populations, and LGBTQIA+ individuals. **[Core Values of ethical conduct in research with Aboriginal and Torres Strait Islander Peoples and communities (NHMRC, 2018)]** **Spirit and Integrity** - Spirit and Integrity is the core value at the heart of the guidelines. - Spirit refers to respecting the ongoing connection and continuity between Aboriginal and Torres Strait Islander peoples past, present, and future generations. Integrity refers to the integrity of the researchers and respect for Aboriginal and Torres Strait Islanders values and cultures. - To demonstrate spirit and integrity, researchers must demonstrate commitment to upholding all the values outlined in the guidelines. **Cultural Continuity** - **Cultural Continuity **emphasises the role of past, present, and future in shaping collective identity (e.g., the role of historical exploitation in shaping perceptions of the present and future). This value also emphasises the critical role of personal and collective relationships in the social lives of Aboriginal and Indigenous peoples, and bonds between people and the environment. - To demonstrate cultural continuity, researchers must understand the historical experiences that may lead Aboriginal and Torres Strait Islander peoples to perceive research as exploitative. They must recognise the importance of personal and collective relationships and the role these play in the social lives of Aboriginal and Torres Strait Islander peoples and communities. Researchers are expected to engage with communities who are involved in or impacted by the research and this conducting research in ways that do not diminish the cultural distinctiveness or disrespect the intrinsic value or identity of Aboriginal and Torres Strait Islander people and communities. **Equity** - **Equity **is about ensuring fairness and justice in research processes and outcomes. In the context of Aboriginal and Torres Strait Islander research, this means acknowledging the unique position of Aboriginal and Torres Strait Islander Peoples in Australia, including their history of colonisation and dispossession. In research, this translates to actively working to address power imbalances, ensuring that Aboriginal and Torres Strait Islander Peoples have a meaningful voice in all stages of research, and that the benefits of research are equitably shared. It is about recognising the rights of these communities as equal partners in research. - To demonstrate equity researchers must recognise and value Aboriginal and Torres Strait Islander knowledge, wisdom, and resources (e.g., historical, biological, and genetic resources). Benefits of the research should be fairly distributed in Aboriginal and Torres Strait Islander communities to support equity in economic, legal, social, and health status. **Respect** - **Respect **refers to regard for the welfare, rights, knowledge, skills, beliefs, perceptions, customs, and cultural heritage (both individual and collective) of people involved in research. - To demonstrate respect, researchers must have an understanding of the values, norms, needs, interests, and aspirations of communities and individuals involved in the research and self-awareness about one's own attitudes, beliefs, and behaviours. Researchers must demonstrate an understanding of intended and unintended consequences of the research during the development phase, and should reach a research agreement with community members about how the research will be conducted. **Reciprocity** - **Reciprocity **in research means acknowledging and valuing the contributions and knowledge of Aboriginal and Torres Strait Islander communities, and building relationships based on mutual respect, trust, and shared benefits. Researchers are expected to engage in a manner that acknowledges the give-and-take nature of these relationships and to ensure that communities are not just subjects of research but active participants and beneficiaries. - To demonstrate reciprocity, researchers are expected to engage in equitable and respectful engagement with Aboriginal and Torres Strait Islander peoples to include them in the research process. The benefits of the research should be defined by the Aboriginal and Torres Strait Islander peoples involved in or impacted by the research, rather than by the researcher. If the research outcomes are not likely to benefit the community, this must be respectfully discussed with the community. Acknowledge that the benefits to the researcher (employment, professional reputation etc.) may be more immediate and outlast the benefits to the community, **Responsibility** - **Responsibility** involves recognition of the social and cultural responsibilities that are valued by Aboriginal and Torres Strait Islander peoples and communities, and ensuring the research does not impact their ability to engage in these responsibilities. These responsibilities include things such as caring for country, kinship bonds, and maintaining harmony between physical and spiritual realms. - To demonstrate responsibility, researchers must ensure the research does not inflict harm on Aboriginal and Torres Strait Islander individuals or communities, or the things they value. While there may be some risk to the research, the assessment of risk/benefit must take into account the perspectives and values of the people and communities involved. Processes must be established to ensure researchers who cause harm are accountable to the individuals, families, and communities involved in the research. **[Ethical Principles for Research with Gender and Sexually Diverse People and Communities]** 1\. Respect the Dignity of All Research Participants - This is the core principle of this framework. It relates to respecting participants\' dignity throughout the research process, from planning to dissemination by adhering to all of the other principles outlined in this framework. 2\. Engage with the Taxonomy and Language of Participants - Researchers are encouraged to use and respect the taxonomy and language that participants identify with, rather than imposing pre-existing categories. This approach respects participants\' right to self-identify and enriches the research. For example, respecting and using pronouns and other identifying terms participants self-identify as. 3\. Examine Assumptions about Who is and is not in the Sample Population - This principle advises researchers to assume the presence of gender and sexually diverse individuals in any sample, whether the research specifically aimed to recruit these individuals or not. It is recommended that researchers establish ways for participants to disclose themselves and participate fully in the research, and have their participation documented (e.g., when measuring gender identity, ensure participants have the option to report their identity rather than simply providing binary male/female options). 4\. Assume that Binarised Cisgender Heteronormativity will have an Impact on the Lived Experiences of Gender and Sexually Diverse Research Participants - Binarised cisgender heteronormativity is the assumption that binary gender identity (i.e., male vs female), cisgender identity (alignment of sex assigned at birth and gender identity), and heterosexuality are the norm, and the experiences of people who fit this category are the norm. - Researchers should consider the need for and have strategies in place to protect participant identity, especially in contexts where gender and sexual diversity might be criminalised or stigmatised, as this may both make people reluctant to participate and also place them at risk if their participation is identified. 5\. Recognise Intersectionality and Its Impact - This principle involves acknowledging the interdependent nature of various social categories of identities and oppressions. Researchers are encouraged to consider intersectionality in their design, analysis, and dissemination of findings in order to understand the complexity of experiences that arise from intersectionality. 6\. Acknowledge Multiple Epistemologies - This principle recognises that each person has their own understanding based on their experiences, and that gender and sexually diverse ways of knowing may differ from cisgender heterosexual perspectives. Participants\' interpretation of research questions and their experiences of the world may differ to the researcher's understanding. 7\. Appreciate that Information from Gender and Sexually Diverse Persons and Communities Acts Indigenously - Researchers should respect and accurately interpret the meanings conveyed by participants, involving consultation groups in the design and dissemination of research. Researchers may lack the cultural understanding to accurately interpret the meaning of information conveyed by participants 8\. Avoid Problematising or Pathologising the Lived Experiences of Gender and Sexually Diverse Research Participants - This principle stresses the importance of recognising resilience and resourcefulness, rather than focusing solely on difficulties or challenges experienced by gender and sexually diverse individuals. 9\. Interrogate Researcher (or Ethics Panel Member) Assumptions and Experiences - Researchers and ethics panel members should reflect on their assumptions about sexually and gender diverse people and communities, whether they are insiders or outsiders to the community, to avoid imposing normative assumptions. 10\. If a Participant is (Legally) a Young Person or Other Dependent Person, Prioritise the Informed and Voluntary Consent of the Research Participant Over the Need for the Consent of a Guardian - This principle emphasises respecting the autonomy of young or dependent participants, even if you do not have the consent of their parent/guardian. - This principle may seem a bit controversial, as it's essentially saying to disregard the need for a legal guardian to provide informed consent for a minor. The NHMRC National Statement (2023) identifies some circumstances in which the need for parental consent can be waived (see sections 4.2.8 and 4.2.9) -- these require the researcher to demonstrate that the child is mature enough to understand the research and consent, that the risk of participation is low, and can only occur if the child is estranged from their parents, or it is in the best interests of the child not to seek consent (e.g., "outing" them may put them at risk). 11\. Ensure Adequate Compensation for the Time Participants Commit to the Research Project - Participants\' expertise and time should be fairly recognised, including appropriate compensation for their contribution to the research. 12\. Generate Theory from the Lives of Research Participants - The final principle highlights the importance of generating theory based on participants\' lived experiences, especially for indigenous and racialised gender and sexually. This means to take what you have learned about the lived experience of your participants, and use this to inform theory, rather than trying to apply existing theory that may not be appropriate for this population. **Quantitative research** is research that involves data that can be represented by numbers and analysed statistically. For example, a study that involves giving participants a questionnaire to rate their experience of symptoms of depression on a scale from 1(*never experience*) to 5(*frequently experience*), and then measure if there is a change in their mean symptom ratings over time is a quantitative study.  Experimental research is used to test **cause-effect relationships** between variables. That is, they measure if one factor (or factors) influences another. Experimental studies test cause-effect hypotheses by **manipulating **variables hypothesised to be the causal factor and observing the resultant effects on other variables hypothesised to be affected by that factor. A variable that is manipulated is referred to as an** independent variable**, whereas the variable that is influenced is referred to as the **dependent variable.** **Between-Groups Experimental Designs** A between-groups (also known as independent groups) experimental design involves dividing participants into separate groups, where each group is subjected to different conditions or treatments corresponding to different levels of the independent variable (or multiple independent variables). If there are differences observed between the groups, these can be attributed to the different conditions to which they were exposed.  **Simple two-group experiments** The simplest version of a between-group experiment is a two-group experiment. This typically involves **one experimental group**, which is exposed to the experimental manipulation, and a **control group** which is not.  [Example]: [Ackerman et al. (2010)](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3005631/) tested whether holding a heavy object would influence judgments of seriousness. Participants were randomly assigned to a condition in which they held either a heavy or light clipboard while evaluating a hypothetical job applicant\'s résumé. The study found that those holding the heavy clipboard rated the applicant as more serious about the position compared to those with the light clipboard. This suggests that physical experiences can influence cognitive judgments. **Experiments With Three or More Groups** Three-group experiments extend on the simple two-group design by adding a third condition. This is done to help rule out alternative explanations for an effect. The third condition might be a second experimental condition or a second control condition. [Example]: In Study 1 of [Baumeister et al. (2005)](https://primoapac01.hosted.exlibrisgroup.com/permalink/f/1bk433u/TN_cdi_openaire_primary_doi_dedup_d1a1ae31ec78a54fc06aff353cdeb0d7), the researchers wanted to test if anticipated social exclusion would influence self-regulation (the dependent variable). Self-regulation was operationalised as willingness to consume a healthy but unpleasant-tasting beverage. Anticipated social exclusion was manipulated by randomly allocating participants to three groups. The first group was given false feedback that they would most likely end up alone in life (social-exclusion group). The second group was given false feedback that they would most likely spend their lives surrounded by people who cared about them (social-inclusion group). The third group received no feedback about their future social life but were told they would experience accidents/injuries (control). The results indicated that participants in the social-exclusion group drank significantly less of the unpleasant-healthy drink than participants in both the social-inclusion and control groups, which the researchers interpret as impaired self-regulation. By including both a social-inclusion group who are induced to think about a positive future and a control group that imagines a negative future that does not involve social exclusion, the researchers can rule out if effects are simply due to imaging a negative future, rather than specifically imagining one involving social exclusion.  **Factorial experiments** An experiment with a factorial design is one in which a researcher tests the effect of **more than one independent** variable at a time, as well as how those independent variables may interact to influence the dependent variable.  The term \"factorial\" refers to the fact that the experiment includes two or more factors (independent variables) which are each set at different levels. Example: [Garbararski et al (2014)](https://doi.org/10.1007/s11136-014-0861-y) wanted to test if two factors influenced how participants rated their general health. The first factor was order of response options to general health questions (ordered from poor-excellent, or excellent-poor). The second was whether the general health questions were asked before or after questions about specific health concerns. This results in four groups, as seen below. **Repeated measures** (aka pre-post) studies involve **measuring a single group of participants at multiple time points** to measure whether their behaviour changes from one time point to another. In experimental repeated measures designs, this will involve measuring the dependent variables before the experimental manipulation is introduced, and then again after it has been introduced.  **Simple two condition (A-B) design** In this design, participants are initially observed at one time point (A) and then again at another timepoint (B) to observe the difference. The conditions at each timepoint are systematically manipulated by the researcher. For example, the dependent variable may be measured at baseline condition (A), and then an experimental manipulation is introduced, and a second measurement is taken (B) to see if this can result in a change in participants\' behaviour.  [Example:] A study might first measure participants\' stress levels at baseline (A), then introduce a relaxation technique (B), and subsequently measure stress levels again to assess if the relaxation technique reduced stress.  **A-B-A designs** This design extends on the A-B design by adding another phase after the experimental manipulation which reverts back to baseline conditions (A). The sequence is baseline (A), manipulation (B), and return to baseline (A). This allows researchers to assess if any changes observed during the intervention phase revert back once the intervention is withdrawn. If so, this provides further evidence that the manipulation was indeed the cause of change, rather than simply something like time passing.  [Example:] We might measure participants\' baseline stress levels (A), introduce a relaxation technique and measure stress (B), then wait some time for the relaxation technique to wear off and measure stress again (A). **Other designs with more than two time points** Some repeated measures studies will expose participants to multiple different levels of an independent variable to see if behaviour changes in response to different variations of an experimental manipulation.  For example, imagine a study that wants to see if exposure to music influences concentration. They could measure participants\' concentration in a quiet room, and then again in a room with music (an A-B design), or they could measure their concentration when listening to different kinds of music (e.g., a cappella, blues, classical, dance). Another variation of this may be a study including follow-up measurements for an experimental manipulation that is delivered over an extended period of time. For example, a study may be interested in testing if a new therapeutic treatment is effective at reducing symptoms of generalised anxiety disorder. They may take baseline measurements of anxiety, then test anxiety levels again 3 weeks into treatment, then again 6 weeks into treatment (etc) to examine if effects change over time. **Simultaneous repeated measures** Rather than having discrete conditions, repeated measures studies may involve alternating back and forth between conditions. For example, a study may be interested in how quickly participants respond to images of animals compared to humans. One option is to have participants perform a reaction time task responding to animals, and then another responding to humans (A-B design). Another is to have a single task in which they are presented with randomly alternating images of animals and humans, and then the researcher extracts their response times to each category and analyses these separately. Mixed designs combine elements of between-groups and repeated-measures experimental designs. This means they include multiple groups of participants who are measured at multiple time points. These reduce the confounding effects of pre-e A mixed experimental design addresses the limitations of both between-groups and repeated measures designs. In between-groups designs, the primary concern is that differences in the dependent variable might be due to pre-existing differences between the groups, rather than the experimental manipulation itself. On the other hand, repeated measures designs are susceptible to time-related effects, where changes in the dependent variable might be attributed to the passage of time rather than the experimental manipulation. By incorporating elements of both between-groups and repeated measures, mixed designs mitigate these issues, allowing for a more comprehensive and reliable assessment of the experimental manipulation\'s impact. [Example of a mixed-experimental design:] Crossover studies include two or more groups of participants who experience the same conditions but in different orders. For example, [Lu et al. (2021)](https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2021.668384/full) tested the effects of a new internet-based CBT program for depression. All participants completed baseline measures of depression symptoms. One group then received 4 weeks of internet-based CBT, while the second group were placed on a waitlist for the same duration. After four weeks, the groups switch (i.e., crossover), so the first group moves to a waitlist, while the second receives internet-based CBT. All participants then completed follow-up measures of depression 3-months later. **Expectancy Effects** The expectations of both the researchers and the participants can influence the way participants behave. This is especially the case in situations in which they are aware of the hypotheses, and of the group/condition the participant is in. We call these experimenter-expectancy effects. **Experimenter-expectancy effects (aka Rosethall or Pygmalian Effects): **A researcher can unintentionally influence the participants\' behaviour through the way they interact with them (e.g., smiling when the participant does what they are expecting they will). These subtle cues are called demand characteristics. **[Strategies for controlling expectancy effects]** 1. **Single-blind procedures:** ensuring participants are unaware of which experimental group they are in (or for repeated measures studies, which condition they are experiencing), and are unaware of the hypotheses of the study. This can help prevent placebo effects. 2. **Double-blind procedures**: ensuring both participants and researchers are unaware of which experimental group they are in (or for repeated measures studies, which condition they are experiencing), and are unaware of the hypotheses of the study. This can help prevent both placebo and experimenter-expectancy effects. 3. **???No-treatment control conditions??**: sometimes a control condition will involve an activity or be exposed to an alternative stimulus so that procedures are as similar as possible between groups (i.e., so they complete the study in the same amount of time, exert the same effort etc). For example, a study investigating the effect of classical music on exam performance may include a control group would listen to dance music (this way both experience audio stimulation while completing the exam). Participants can mistake these active-control conditions for an active manipulation, and may change their behavior and placebo effects can occur as a result. Including a no-treatment condition (e.g., waitlist, no activity, no stimulus etc) and comparing this to a control condition that helps to identify if placebo effects occur in active-control conditions. 4. **Standardisation of procedures**: ensuring all researchers follow a set protocol that specifies how to interact with the participants. This may include scripts to ensure all participants receive identical instructions and prevents subtle changes in wording that could influence participant behaviour. **Carryover Effects** In repeated-measures designs, it\'s possible that changes that occur across time points may be due to the fact that the participants are measured multiple times, rather than due to the experimental manipulations. These are referred to as **carryover effects. For example:** - **Practice effects** occur when completing a task multiple times results in improved performance (e.g., participants may respond faster the second time they complete a reaction-time task because they\'ve had a chance to practice it).  - **Fatigue effects** occur when tiredness or boredom result in worse performance at subsequent timepoints compared to baseline.  - **Context or priming effects** occur when experiencing one condition changes behaviour in a subsequent condition (e.g., completing the same task multiple times may make it easier for participants to guess the hypothesis of the study, and change their behaviour).  **[Strategies for addressing carryover effects: ]** **Counterbalancing:** Counterbalancing is a procedure in which participants are divided into groups, and each group completes the study in a different order. For example, Group 1 may first be exposed to the control conditions at Time 1, and then exposed to the experimental manipulation at Time 2, while Group 2 may first be exposed to the experimental manipulation at Time 1, and then to control conditions at Time 2. To achieve this, the study must use a mixed design. When there are more than two conditions, you may have more groups so that all possible orders of conditions are covered. E.g., imagine a study with four conditions: exposure to a cappella music (A), blues music (B), classical music (C), and dance music (D).  **Non-experimental quantitative research **refers to study designs that **do not involve the manipulation of an independent variable**.  The purpose of non-experimental research is to measure the extent to which a phenomenon occurs in a population (i.e., prevalence), to investigate relationships between variables, or to test differences between groups when random assignment to groups is not possible. [The defining characteristics of non-experimental research] 1. Non-experimental studies **do not involve active manipulation** of variables by the researcher. 2. Non-experimental studies are used to d**escribe the extent to which a phenomenon exists or the extent to which variables co-occur naturally in the world** in the absence of manipulation. **Single Variable Research** Single variable research is, as the name implies, interested in studying one variable at a time. This kind of research can answer questions about average levels of variables in a population (e.g., average age of residents in aged care facilities), and the prevalence of a phenomenon (e.g., what proportion of university students are engaged in full-time paid employment?). Example: [Ortega et al. (2009)](https://doi.org/10.1007/s00420-008-0339-8) measured how many participants reported experiences of bullying in their workplace, and the proportion of bullying perpetrated by different agents (e.g., managers, coworkers etc). **Cross-sectional Correlational Research** Correlational research aims to measure relationships between variables without any active manipulation to change them by the researcher. That is, to what extent do two or more variables naturally co-occur in the world? This kind of research involves taking measurements of different variables from the same group of participants at the same point in time and measuring the degree of covariance between them.  This is useful for situations in which you are interested in variables that cannot be manipulated (e.g., age, personality traits, experience of psychological disorders, etc.), and times when you want to analyse continuous variables, rather than group differences.  Correlational research can also be used to measure if one or more variables is able to predict another. For example, [March et al., (2020)](https://doi.org/10.1016/j.paid.2020.110084) measured the extent to which different personality traits predicted engagement in intimate partner cyberstalking.  **Quasi-Experimental Research** **Quasi-experimental** research involves comparing groups of participants; however, those groups are not randomly allocated. Rather, participants are **sorted into groups based on pre-existing characteristics**. Because there is no random allocation, this is not an experimental design (i.e., no active manipulation by the researcher has occurred). This design is used when random allocation is not possible. For example, imagine a researcher is interested in differences between adolescents and adults -- it's not possible to randomly allocate participants to these groups because we cannot change their age. Instead, they must sort participants into groups based on their reported age. **Case-control studies **are a common example of quasi-experimental designs. These designs involve the initial recruitment of a case group based on a particular characteristic, followed by the recruitment of a control group of participants who are matched to the case participants based on other characteristics. The purpose is to have two groups who are as similar as possible in all aspects except the primary characteristic the research is interested in studying.  For example, [Fortuyn et al. (2010)](https://doi.org/10.1016/j.genhosppsych.2009.08.007)investigated differences in the prevalence of mood disorders in children with and without narcolepsy. It is not possible to manipulate narcolepsy, or randomly allocate participants to either a group with or without narcolepsy. Instead, they used a case-control method in which they first recruited a group of children with narcolepsy, and then recruited a control group without narcolepsy who were age- and sex-matched to the children in the narcolepsy group. **Common Approaches to Qualitative Research** **Narrative Inquiry** The aim of narrative research is to explore and interpret the stories or narratives that individuals use to describe their experiences. Narrative inquiry focuses on the storytelling process and the meanings people ascribe to their life experiences. It involves analysing the structure and content of stories to understand how individuals perceive and make sense of their experiences. **Phenomenology** Phenomenology aims to understand and describe the meaning of individuals\' lived experiences concerning a particular phenomenon. In short, the aim is to understand and describe the participants\' experiences from the participants\' own perspective. **Grounded Theory** The aim of the grounded theory approach is to develop new theory. This is an inductive approach that involves collecting data from participants about their experiences of a phenomenon, and then using this as the basis to generate new theory. **Ethnography** Ethnography is an approach that aims to explore and describe cultural phenomena as experienced and interpreted by individuals within a specific culture or social group. Ethnographic research often involves the researcher immersing themselves within the natural environment of the participants to observe them within the sociocultural context in which they exist, from the perspective of an observer also involved in that context. It focuses on understanding the customs, rituals, and everyday practices of the group being studied. **Case Study** To provide an in-depth, comprehensive understanding of a phenomenon by the examination of a single case or a small number of cases, often within their real-life context. Case studies provide a holistic description of both the experience of a specific phenomenon experienced by an individual or small group, and the context surrounding that case. This is often used to develop or record rare phenomena. **When to Use an SLR** 1. Your aim is to provide a comprehensive, unbiased assessment of what is currently known and unknown about a phenomenon.  2. You want to evaluate the quality of evidence in an existing body of literature. 3. It is not possible to combine the results from past research quantitatively. **When to Use A Meta-Analysis** 1. When you are interested in calculating the average magnitude of an effect across all of the studies that have investigated it. 2. You are interested in quantifying heterogeneity (i.e., how much the effect varies across different studies). 3. You want to identify statistically if there are specific conditions under which the effect does or does not occur. 4. It is possible to combine the results from past research quantitatively. **The AIATSIS research ethics framework The AIATSIS research ethics framework is structured around four principles:** 1\. Indigenous self-determination Recognition and respect Engagement and collaboration Informed consent Cultural capability and learning 2\. Indigenous leadership Indigenous led research Indigenous perspectives and participation Indigenous knowledge and data 3\. Impact and value Benefit and reciprocity Impact and risk 4\. Sustainability and accountability Indigenous lands and waters Ongoing Indigenous governance Reporting and compliance[\ ](https://moodle.federation.edu.au/course/view.php?id=95865&section=3)