Introduction to Psychology: Exam Notes PDF

What is Psychology? - The study of mind, behaviour and the relationship between them. - Key characteristics: o Scientific study of behaviour. o Strong theoretical underpinnings. o Strong research basis. o Emphasis on empirical evidence. - Goals of psychology: o Describe behaviour – what, where and when it happens. o Explain behaviour – why it happens. o Predict behaviour – what will happen next. o Change behaviour – individuals, groups, society. Psychological phenomena - Psychology is a broad field which is primarily concerned with psychological phenomena in any context. - Psychological phenomena can typically be categorised into mental processes and behaviour. - Mental processes can also be thought of as a subjective experience. - Behaviour – usually explicitly observable and often assumed to be a manifestation of a subjective experience. o Example – when a person attends a lecture, they are motivated to learn. - Mental processes/subjective experiences – internal experience which is typically unobservable unless it manifests as a behaviour or is intentionally measured. o Example – excitement during a lecture. - Every day we experience and are confronted by psychological phenomena. Importantly, people can experience these phenomena on more than one occasion: o The phenomenon repeats. o If the phenomenon repeats or occurs consistently under certain conditions, then it is predictable. - If a phenomenon repeatedly occurs then it becomes valuable to understand, explain and predict. - People working in the field of psychology are motivated to understand, explain and predict psychological phenomena. - Psychologists are not the only ones who are interested in repeating and predicting phenomena. - We also experience lots of non-psychological phenomena every day: o Equal and opposite reactions. o Chemical binding. - Much like psychological phenomena, these physical and chemical phenomena have been discovered by science. Psychology as a science Testimonials: - Are worthless for the evaluation of psychological theories and practice. - Easy to generate, positive bias, isolated case, spontaneous remission, placebo effect. - Very effective. - Psychologists are not permitted to use testimonials in their practice. What is science? - The goal of science is to create reasonable explanations (theories) to describe reality. - Scientific theory is based on evidence. - Evidence is gathered and evaluated according to rigid rules which are systematically applied. - This ensures that a scientific theory reflects reality to the best of our ability. - This process is accumulative, continuously evolving, and rigorously evaluated. - Why do we need science? o To discover new knowledge. o To make informed decisions. o To improve methods for research. - Five norms of science: 1. Universalism – the attributes of the researchers are irrelevant; different researchers should reach the same conclusion. 2. Communalism – scientific information must be shared publicly. 3. Disinterestedness – scientists must place aside all personal beliefs. 4. Organised scepticism – science is subject to peer review and replication. 5. Novelty – science should not just be repetition. Converging evidence: - The connectivity principle. - Scientific knowledge is cumulative. - Any new theory must account for new findings as well as old ones. - True sciences show a progressive development of theories over time. - Science is convergent when a series of experiments consistently supports a given theory while collectively eliminating competing explanations. - Convergence in psychology: o Psychological phenomena are complex. o Discoveries in psychology are small parts of a puzzle that gradually start to fit together. Why do we need science in psychology? - We live in a society exquisitely dependent on science and technology, yet 94% of people in the Western World are said to be ‘science illiterate’. - To avoid falling prey to psychological myths, we need to apply the scientific principle in psychology. - We develop research questions and employ the scientific approach to test these research questions. - Critical thinking plays a significant role in this process. Science in psychology: - Allows us to make systematic observations, interpret findings, and systematically apply them. - Maximises rigor, reliability and validity. - Allows us to accommodate previous findings. - Assists in evidence-based practice, improves service provision, and directs health policy. - We adhere to the Scientist-Practitioner Model in psychology. The Scientist Practitioner Model: - Based on premise that science and practice should continually inform one another. - Psychology is dynamic and experimental rather than fixed and prescribed. - Involves development of interlocking skills to foster a career-long process of psychological investigation, assessment and intervention. - A constant effort to increase the component of psychological practice that is based firmly on scientific principles and evidence, and to decrease the component that is based on unsubstantiated speculation, unanalysed experience, intuition or art. It is recognised, however, that science progresses by a fusion of these types of cognitive processes – hypothesis generation often involves creativity and intuition followed by experimental justification. - It is used in the practice and training of: o Clinical psychologists. o Counselling psychologists. o Generally registered psychologists. o Neuropsychologists. o Educational, organisational and sport psychologists. - Science/research   Practice of psychology. - Applications: o Mastery of the knowledge, principles and methods of the basic discipline of psychology. o Training in the conceptual skills required to apply the basic knowledge principles and methods to the problems of professional practice. o Acquisition of specific skills in the use of relevant procedures, technologies and techniques. o Use of validated methods of assessment and treatment. o Keeping up to date with the latest research in your specialist field. o Applying the findings and methods of research to clinical practice. o Performing empirical evaluation of those findings and methods relevant to clinical practice. o Incorporating evaluation of client progress, treatment and intervention efficacy/success. o Avoiding becoming complacent (set in ways) with assessment, diagnoses, and intervention. o Forging links between practice and further research questions. o Adopting a scientific mindset – being open and objective. - Difficulties: o Practitioners tend to be very time poor. o Practitioners may not have engaged with scientific method since their tertiary/post graduate studies, may compromise capacity to discern good quality research. o Some research may require scientific memberships to access. o Might be difficult to identify current research insights about the specific concern/s with which a practitioner is working. Key subfields of Psychology Biological psychology: - Involves the study and measurement of biological or physiological psychological phenomena. - Often requires the use of sophisticated equipment to measure bodily signals, such as: o Heart rate. o Blood flow. o Brain activity and structure (EEG, fMRI, PET). o Sweat activity. o Hormones and neurotransmitters. - A biological psychology phenomena is the lateralised dominance of certain functions. - Your dominant hand can indicate your dominant brain hemisphere: o Left handed – right hemisphere dominance. o Right handed – left hemisphere dominance. - Some have argued that high prenatal testosterone exposure delays left hemisphere development, leading to right hemisphere dominance. This can explain male traits such as strengths in visuospatial skills and weaknesses in language skills. - Handedness is also linked to homosexuality, autism and infant cradling preferences in women. Cognitive psychology: - Involves the study and measurement of mental abilities. - These phenomena largely include: o Sensation and perception. o Learning. o Memory. o Attention. o Intelligence. o Creativity. - Research has shown our short-term memory capacity is around 7 items (+/- 2). - When we are stretched, we tend to use other strategies to encode and retrieve information. - A well-established psychological phenomenon is the serial position effect, which includes the primacy and recency effects. Developmental psychology: - Involves the study and measurement of changes in mental processes and behaviour from birth through to old age. - Usually involves an interest in the following areas: o Parenting. o Childcare. o Preservation of mental abilities in elderly people. - Traditionally, this can be a challenging area to research because of the need to access samples of children and to follow people across their lives. Personality psychology: - Involves the study and measurement of individual differences in human traits. - Researchers have put a lot of effort into developing personality tests to identify certain personality types. - One of the most popular models of personality is the Big Five Factor Personality Inventory: o Agreeableness. o Conscientiousness. o Extraversion. o Neuroticism. o Openness to experience. - The Dark Triad of personality has recently become of huge interest to researchers in psychology: o Narcissism – selfish, arrogant, sensitive, ruthless. o Psychopathy – lack of empathy or remorse. o Machiavellianism – self-interested, manipulative, lack of morality. Clinical psychology: - Involves the study of causes and treatment of mental disorders, for example: o Depression. o Anxiety. o Schizophrenia. o Autism. - A large effort in clinical work has also been the measurement and classification of symptoms. - They are detailed in the Diagnostic and Statistical Manual (5 th edition) or DSM-V. - Many people associate clinical psychology with cognitive behavioural therapy (CBT) – a technique focusing on changing beliefs and behaviours, usually via highly-structured therapy sessions. - Other approaches, such as interpersonal, emotion-focused and psychodynamic therapies emphasise relationships, emotional processing and the influence of past experiences on current symptoms. - CBT is regarded by some as the ‘gold standard’ for treating common psychological disorders because it has the largest ‘evidence base’ – more research has been done on it. - While CBT has consistently shown modest benefits compared to ‘no treatment’, it does not usually outperform other types of therapy. - Just because CBT is the most researched approach does not necessarily mean it is better than other therapies or more appropriate for some psychological disorders, particularly those with complex presentations. Social psychology: - Involves the study and measurements of how people think about themselves and others, as well as the role of social influence. - Some notable social psychology phenomena include: o Conformity. o Obedience to authority. o Prejudice and stereotypes. o Groupthink. o Influence of the media on attitudes and behaviour. - The bystander effect: o A phenomenon whereby people are less likely to assist in an emergency as the number of bystanders increases. o Explained by a diffusion of responsibility. Educational psychology: - Involves the study and measurement of learning and teaching, usually in very applied settings (e.g. schools and universities). - This field is largely focused on: o Developing and evaluating learning programs. o Curricula development. o Training for teachers. o Academic motivation and achievement. Organisational psychology: - Involves the study and measurement of efficiency, productivity and satisfaction in the workplace. - Organisational psychologists often have an interest in: o Leadership. o Employee selection. o Stress and burnout. o Competition. o Cooperation. o Motivation. - Organisational psychology has become increasingly valuable to companies as it enhances productivity and competitiveness. - The Hawthorne effect: o Discovered in a telephone manufacturing factory located in Hawthorne, West Chicago. o Researchers were interested in the effects of lighting on productivity. o Instead, researchers found that worker productivity was more strongly influenced by the research observation itself, or the awareness of being studied. o Those being intensively observed were more productive. Forensic psychology: - The interaction of the practice or study of psychology and the law. - Forensic psychologists use their knowledge of psychology and the law, and have the forensic skills, to understand legal and justice issues and to generate legally relevant and useful psychological data that enable them to provide services to those who: o Administer law and justice. o Make legally relevant decisions about people in other contexts. o Are involved in situations that have legal and justice implications. - Specific services of forensic psychologists include: o Providing services for litigants, perpetrators, victims and personnel of government and community organisations. o Collecting and reporting evidence of a psychological nature for use in legal and quasi-legal proceedings. o Psychological assessment and report writing; psychological formulation, diagnosis and intervention. o Program evaluation. o Forensic interviewing. o Research. Community psychology: - Community psychology goes beyond an individual focus and integrates social, cultural, economic, political, environmental, and international influences to promote positive change, health and empowerment at individual and systemic levels. - Community psychologists use their knowledge of psychology to provide services to the community when it is faced with challenges; work in partnership with the community to help solve problems and restore individual and collective wellbeing; and specialise in understanding and supporting the needs of communities. - Specific services of community psychologists include: o Assessment of community strengths, needs and opportunities, and evaluation of social networks and resources. o Provision of interventions to address psychosocial needs and strengthen community health and resilience. o Consultation skills to support communities to inform and develop public policies and manage conflict; support staff to develop consultation skills. o Education on psychological factors. o Advocacy on behalf of groups and individuals seeking inclusion, equity and self-determination. - Consumers of the services of community psychologists include: federal, state and local governments; urban, regional, and remote communities; non-government agencies; health and education providers; individuals and groups. Health psychology: - Health psychology concerns the psychology of disease, exercise, substance use, and risky behaviours. - Health psychologists use their knowledge of psychology and health, particularly across the spectrum from wellbeing to illness, to foster health promotion, public health, and clinical assessment and interventions relevant to health and illness. - Health psychologists work across the following areas: o Health promotion. o Lifestyle change (e.g. stress management). o Promotion of exercise and healthy eating behaviours. o Managing diseases or death and dying. o Behavioural strategies relevant to disease prevention (e.g. addiction treatments). o Assessment and treatment of chronic or acute health problems (e.g. pain or sleep disorders where there are relevant psychological factors). Environmental psychology: - Examines the psychological impact of the environment on our behaviour and subjective experiences (e.g. architecture, interior design, landscaping and the effects of climate-related changes). - Environmental psychologists may work alongside or within non-profit organisations, government agencies, businesses, and various non-governmental organisations. - Environmental psychology researchers investigate how people work with and response to the world around them; and apply psychological theories to environment-related behaviours. Sport and exercise psychology: - Sport and exercise psychology uses psychological knowledge, skills and interventions to support athletes to reach peak or optimal performance, consistently, alongside supporting wellbeing. - Beyond an individual focus, sports psychology also focuses on developmental and social aspects of sports participation, and systemic issues associated with sports settings and organisations. - Sport and exercise psychologists use their knowledge of psychology to provide services to the community to enhance personal development and wellbeing from participation in sport and exercise. - Sport and exercise psychologists have specific knowledge of training science and the technical requirements of sport and competition, in particular the rules of important, relevant governing bodies. - Some specific services of sport and exercise psychologists include: o Performance. o Wellbeing. Studying psychology and career pathways Why study psychology? - To understand: o Improve your ability to study, measure and interpret psychological phenomena. - To explain: o Ensure that others benefit from your understanding of psychological phenomena by drawing clear links between causes and outcomes. o Sharing knowledge. - To predict: o Identifying conditions and individuals who are at risk. o Selecting treatments/programs which are most effective for achieving desired outcomes. - To apply: o Carrying out psychological assessments, delivering programs and treatments. o Measuring psychological phenomena to help organisations, employers, health professions improve the outcomes for clients, employees, patients, victims and anybody who is human. o Designing treatments, programs and processes for measuring and influencing behaviour and mental processes. Measuring the Mind Empiricism in psychology Empiricism: - Is a fundamental part of the scientific method. - Philosophical origins (i.e. Vaisheshika darshana, Aristotle, Bacon, Locke, Hume and Descartes). - All hypotheses and theories must be tested with regard to observations rather than resting solely on a priori reasoning, intuition or revelation. - Empirical research (with experiments, established and validated measurement tools, etc.) guides the scientific method in psychology. - Empiricism in psychology: o There are a number of ways we ensure that the science of psychology is empirical. o Examples include:  Well-designed studies (e.g. experimental, correlational).  Sound hypotheses or research questions that are clearly testable.  Clear definitions of variables (i.e. predictors/outcomes).  Use or development of established measured.  Appropriate sample sizes. Scientific theory: - Any scientific collection of data needs to be theory-driven, not just random observations. - Scientific theories are constructed to explain and predict phenomena. - The role of scientific theory: o Provides a conceptual structure that is supported by a large and varied set of data. o Hypotheses are specific predictions derived from theories. o Hypotheses should be falsifiable, meaning that we can reject them via scientific testing. o This allows us to test a theory. - Scientific theories… o Are specific – they must state what will happen (and sometimes what will not happen). o Theories are modified and rejected based upon evidence. o No theory is infallible. - Observation: o Observation is structured so that the results of the observation reveal something about the underlying nature of the world. o Observation alone is not sufficient for the scientific collection of evidence – it must be systematic. Falsifiability: - Scientific theories must always be stated so that the predictions proposed can be demonstrated to be false. - Falsifiability of theory is the logical possibility that it can be contradicted by an observation or the outcome of an experiment. - The notion that something is falsifiable does not mean it is false; rather, that if it is false then some observation or experiment will produce a reproducible result that is in conflict with it. - Sigmund Freud (1856-1939): o Many theoretical and therapeutic contributions. o Examples include:  Development.  Personality.  Subconscious processing.  Psychoanalysis.  Psycho-sexual illness. o Freud’s theories have no predictive ability.  Has no explanatory power – everything is explainable by the theory.  Cannot be falsified, therefore cannot be tested.  Dangerous when we overlook alternative explanations. Verifiability: - Philosophical doctrine suggests that science must be publicly verifiable in order for it to be evaluated. - Science does not exist until it has been submitted to the scientific community for criticism and empirical testing by others. - Wakefield: o 1998 Andrew Wakefield and colleagues published article in The Lancet claiming MMR vaccine was linked to autism. o The results have never been replicated – all evidence shows no causal link between autism and the MMR vaccine. o Vaccination rates are still affected by this research today. - Peer review, scientific publication, and replication are minimal criteria – they are not enough by themselves. - What can we do? o Transparency in experimental methodology, observation and collection of data. o Public accessibility and transparency of scientific communication. o Public availability and reusability of scientific data. o Using web-based tools to facilitate scientific collaboration. Publication and peer review: - Publication of research: o Communicating knowledge and methods for obtaining knowledge. o Important for furthering science. o Methods are corrected and improved. - Peer review: o Research is a continual process that is advanced through collaboration and critique. o Journal articles are critiqued by several scientists prior to publication. o Open Access is the idea that scientific research should be published in such a way that the findings of a study are accessible to all potential users without any barriers. o Conferences are not a quality control. Replication: - The same experiment for the same results. - Replicability viewed as the ‘safeguard for the creep of subjectivity’. - However, replication studies can be difficult to publish. Data and Variables in Quantitative Research The 3 broad research domains: 1. Quantitative research – research involving conducting statistical analyses using numerical data. 2. Qualitative research – research based on rich textual data rather than numerical data. 3. Mixed methods research – the class of research where the researcher mixes or combines quantitative and qualitative research techniques, methods, approaches, concepts or language into a single study. Data: - The translation of phenomena into the real world into something that is deliberately recorded and collected. - Potential data is all around us and we use it every day to help us make decisions. - In scientific disciplines, we develop measurement tools to collect data. - Our perceived environment can be measured in various ways – light, temperature, sound, air quality. Data in psychology: - We use a variety of instruments in psychology to measure subjective experiences and behaviours. - Very often, multiple measurements are used for the same phenomenon. - Examples of instruments used to collect data in psychology include: o Questionnaires (e.g. depression scales). o Tests (e.g. testing aptitude, intelligence). o Observations (i.e. visual evaluations of behaviour). o Archival data (e.g. medical and educational records). o Experimental tasks (e.g. implicit association tasks). o Physiological measures (e.g. heart rate, fMRI). o Interviews and focus groups. Variables: - A phenomenon that can take on different values – it can vary. - Examples of constructs that can be considered variables: depression, psychopathy, aggression and learning. - Variables need to be operationalised before we can measure them. o A process of defining a fuzzy concept so as to make it clearly distinguishable, measurable and understandable in terms of empirical observations. o Our definitions can change across contexts or over time. Basic quantitative models: - The most basic quantitative models only have two variables. - The association between the two can be positive or negative: o Positive relationship – an increase in the values of the first variable is associated with an increase in the values of the second variable. o Negative relationship – an increase in the values of the first variable is associated with a decrease in the values of the second variable. - Psychological models should not be about psychological phenomena. This does not mean that we cannot pair psychological phenomena with other non-psychological variables. Independent or predictor variables: - Variables which are assumed to cause changes in another variable. - Typically occurs before a particular outcome. - In some designs, the researcher knows the values prior to the start of the study; in others, it is measured as part of the study. - Independent variables can have multiple levels (i.e. different magnitudes or groups. Dependent or criterion/outcome variables: - Variables which are thought to change in response to variations in an independent variable. - In all research designs, this variable is being measured as part of the study. Covariates/control variables: - A variable that may also affect the dependent/criterion/outcome variable (usually a weaker association). - Typically not of primary interest to the researcher. - Could be taken into account (measured or controlled (when designing the research). Confounding variables: - The covariate should not be a better independent variable than the one we have chosen. - If the covariate is a more sensible explanation, then it is a confounding variable. - That is, the effect we are supposedly interested in is being confused for the effect of another variable. - This can sometimes mean the association we were originally interested in becomes spurious (i.e. meaningless). Scales of measurement - Data in quantitative research can possess different properties depending on what was measured and how it was measured. - The more properties, the more flexible our options are (i.e. we can perform more manipulations to evaluate and interpret our data. - The scales of measurement are: o Nominal/categorical:  The most limited scale of measurement in quantitative research.  No property of magnitude.  Cannot perform operations (subtraction, addition etc.).  Data with only two categorical options is referred to as dichotomous data.  Examples: biological sex, political preference, eye colour.  o Ordinal:  Property of order but values do not represent magnitude.  Still cannot perform operations.  May still represent categories.  Examples: placing in a competition (1st, 2nd, 3rd). o Interval:  Property of magnitude but not relative magnitude.  Meaningful (equal) differences between intervals.  No true zero point (can have negative values).  Zero does not represent the absence of a property.  Can perform some operations – addition and subtraction, not multiplication and division.  Example – temperature, 12 hour clock. o Ratio:  Property of magnitude (including relative magnitude).  Meaningful (equal) differences between intervals.  True zero point (cannot have negative values).  Zero represents the absence of a property.  Can perform many operations – subtraction, addition, division and multiplication.  The most useful scale of measurement for analysis.  Examples: height, weight, exam scores. Discrete versus continuous data: - Discrete: o No immediate values between data values. o Nominal and ordinal measures are discrete. o There cannot be infinite decimals between points of the scale. - Continuous: o There are immediate values between data values. o Common in interval and ratio scales (but not always). o There can be infinite decimals between points of the scale. Reliability and validity Reliability: - Refers to the consistency of measures. o If we were to measure something more than once, would we get the same results? - Measures that are not reliable cannot be trusted. - There are three main types of reliability in research: Type Definition Description Internal consistency Consistency among items in a Test takers’ responses to all items on a scale/subscale measure. should be similar/consistent. Test-retest reliability Consistency over time. Test takers’ responses to items at time 1 should be similar to responses at time 2. Inter-rater reliability Consistency across Multiple observers/raters should provide similar accounts of observers/raters. the same event/occurrence/behaviour. Validity: - Refers to the extent to which a concept or measurement is well founded and corresponds accurately with the world. o Are we actually measuring what we think we are measuring? - Evidence for the validity of a measure builds up over time as it is used repeatedly in research. - There are four main types of validity in research: Type Definition Example (i.e. extraversion measure). Face validity Looks like it is measuring X. Items appear (to the naïve observer) to be measuring extraversion/sociability). Content validity Samples the full breadth of X. Items cover all aspects of extraversion (e.g., talkative and adventurous and active etc.). Criterion validity A test’s correspondence with a concrete Scores on the measure predict current base rate cortical outcome; measured now (concurrent) and in arousal levels; as well as future sociable behaviour at the future (predictive). parties, work, etc. Construct validity Is related to other measures of X People with high scores on this measure also score highly (convergent); and is not related to measures on the NEO-PI extraversion subscale; scores on this of Y and Z (discriminant); does it behave measure are not related to scores on the Beck Depression consistently with theoretical predictions? Inventory or the Neo-PI Openness subscale. - A measure can be reliable but not valid; an unreliable measure cannot be valid. Measures of central tendency and variability Measures of central tendency: - Are one number summaries (the simplest form of statistics). o Mean – sum of the values in the dataset divided by number of values. o Median – midpoint of the dataset. o Mode – most frequent value in the dataset. - The mode is not very popular in psychological measurement. - How do we decide whether to use the mean or median? o Depends on shape of data. o Mean is useful when have nice symmetrical distributions. o It is problematic to use the mean when the data is not symmetrical. o Better to report the median when the data is skewed (i.e. not normally distributed). Measures of variability: - Range – different between the smallest and largest value in the dataset. - Interquartile range – range between the middle 50% of the data. - Variance – sum of the squared deviations of each data point from the mean. - Standard deviation – square root of the variance. - Outlier – a data point that differs significantly from other observations. Knowledge is Power Quantitative research designs Correlational research: - There is no group assignment or manipulation. - Independent and dependent variables are often measured at the same time. o In this design they are typically referred to as predictor and criterion/outcome variables. - Only the strength of the relationship can be determined. - But the potential causal direction could be ambiguous. - Advantages: o Simplest to set up.  No manipulation required (which may be more pragmatic and/or more ethical). o Well-suited to online survey data collections.  May also be conducted in the laboratory. o Venues, equipment and research assistants are often not typically required. o Can be more ecologically valid than experimental studies in a lab (i.e. may translate better to the real world). - Disadvantages: o Causal direction cannot be determined.  Correlation only tells us whether variables are associated, not if one causes another.  Confident conclusions cannot be drawn (i.e. correlation does not imply causation). o Cannot easily rule out other explanations.  Other variables might explain the associations. o Does not advance knowledge as quickly.  Only tells us strength and direction (positive or negative).  Can be less publishable. Quasi-experimental research: - There is group assignment but no manipulation. - It is not always possible to randomly assign participants to groups or levels of an independent variable. o This can be due to the nature of the variable, or due to practical or ethical constraints. - Group assignment is typically based upon some pre-existing characteristics or disposition. o This cannot be randomly decided or manipulated (e.g. gender). - There is sometimes ‘control groups’ created by using self-selection criteria (e.g. non-smokers). o The researcher does not determine this. - Advantages: o Allows us to conduct research here true experimental designs would not be logical, practical or ethical. o Simple to set up. o Well-suited to online survey data collections – may also be conducted in laboratory. o Venues, equipment and research assistants are often not typically required. - Disadvantages: o Causal direction cannot be determined.  Confident conclusions cannot be drawn (i.e. correlation does not imply causation). o Cannot easily rule out other explanations.  Other variables might explain the associations.  Could be other systematic differences between the groups. o Does not advance knowledge as quickly.  Only strength and direction.  Can be less publishable than true experimental research. Experimental research: - There is random condition assignment and a manipulation. o Random assignment occurs in designs where there are more than one group of participants. - Condition assignment should be done at random (i.e. decided by chance). o Equal likelihood of assignment to manipulation or control condition. - Control and/or placebo conditions are used. o Provides a suitable comparison to determine whether the manipulation has yielded a true effect. o In designs with one group of participants, a baseline measurement is used as a control instead. - Causation: o The purpose of experimental research is to explain behaviour by uncovering causal relationships between variables. o Before casual inference, three criteria must be met:  Co-variation – the variables must change together (i.e. they must be correlated).  Temporal ordering – cause must precede effect.  No rival explanations – alternate explanations (plausible rival hypotheses) must be ruled out as possible causes of the effect. - Random assignment: o Equal chance of being in either condition (occurs in experimental designs, but not in correlational or quasi- experimental designs). o There should be no systematic differences between conditions. o If the dependant variable changes in condition 1 then we can be confident that it was due to changes in the independent variable (the manipulation). - Non-random assignment: o Cannot be equal chance of being in either condition. o This leads to two conditions which may have multiple systematic differences. o If the dependant variable is different between the groups we cannot be confident that it was due to differences in the independent variable. o Causal conclusions cannot be drawn because there are many systematic differences between the groups. - Advantages: o Can make causal conclusions.  Still need to be mindful of external validity.  Finding evidence of a causal effect in a group of participants does not ‘prove’ this is true beyond a particular study. o Control groups and random allocation help rule out alternative explanations.  Systematic differences between groups or over time are attributable to the manipulation. o Advance knowledge more quickly.  Temporal direction of associations are clearer.  More publishable. - Disadvantages: o Costly and time consuming.  Venues, equipment and research assistants are often needed to perform a manipulation effectively.  Lower sample sizes as a result. o Manipulations and control groups are associated with ethical challenges (i.e. some manipulations are not ethical). o Often have more ethical considerations to correlational and quasi-experimental designs – usually a by-product of performing a manipulation. Qualitative research designs Qualitative research: - Qualitative research is exploratory. o It aims to understand the underlying reasons, motivations, meanings, etc. behind human behaviour, thoughts and interactions. o It seeks to uncover new insights and perspectives, rather than testing predefined hypotheses. - Qualitative research prioritises rich, descriptive accounts of phenomena. o Aiming to capture the complexity and context underlying the human experience. o Researchers often use quotes and vivid descriptions to convey the depth and nuance of their qualitative findings. - Qualitative research relies on a variety of data collection methods, such as: o Interviews, focus groups, visual data, and analysing written text (e.g. media articles, social media posts, open ended questions on online surveys). o These methods allow researchers to gather rich, detailed data about various experiences, beliefs and attitudes. - Qualitative research often employs an inductive approach where theories and concepts emerge from the data rather than being imposed a priori. - Qualitive research acknowledges the subjective nature of reality and emphasises the role of the researcher in interpreting data. o Researchers actively engage with the data, analysing patterns, themes and relationships to generate meaning and insights. - Researchers immerse themselves in the data, allowing patterns to emerge through analysis and constructing themes across the dataset. - Qualitative research is flexible and iterative. o Allowing researchers to adapt their approach based on emerging insights and new questions that arise during the research process. o Researchers may revise their methods, refine their research questions, or explore unexpected avenues as they delve deeper into the data. - Qualitative research usually pays close attention to the social, cultural and historical context in which phenomena occur. o Researchers seek to understand how context shapes people’s experiences and perspectives, recognising that meaning is often embedded within broader social structures and relationships. - The main qualitative research designs used in psychology: o Thematic analysis – two main types: inductive and deductive. o Content analysis – four main types: summative, conventional, directed and mixed. o Grounded theory – three main types: systematic, emergent and constructive. o Phenomenology – three main types: descriptive, hermeneutic and interpretative. o Discourse analysis – two main types: Foucauldian and discursive psychology. Thematic analysis: - A process of organising textual data into patterns that are meaningful to the question or aims underpinning the research. - Recurring concepts within the data are identified by tagging similar ideas using codes, similar codes are then grouped together to form themes. - Doing a thematic analysis is an active process as the researcher shapes the themes that are identified in the analysis. - Themes can capture explicit information within the data, or can be more interpretive, identifying deeper meanings within the data. - There are two main approaches to thematic analysis: o Inductive – themes are developed from the data. o Deductive – themes are identified based on a particular theory. Content analysis: - Process of describing phenomena through the application of systematic coding processes. - While content analysis is commonly thought of as a purely descriptive and simplistic approach to qualitative research, it is flexible and can be approached inductively or deductively, used with an array of data sources (e.g. textual, visual), and is most unique in its potential to allow for quantification of qualitative data. - There are four main approaches to content analysis: o Summative – process of coding and counting key words to quantitatively summarise important patterns within the data. o Conventional – process of coding in order to describe and interpret patterns emerging from the data to generate new understandings of a concept or phenomenon. o Directed – process of using codes derived from theory to identify patterns within the data to extend that theory or relate findings to a body of research literature. o Mixed – a combined approach that allows for quantification of codes within data (summative content analysis) and interpretive content analysis (either directed or conventional content analysis). Grounded theory: - Qualitative research approach used to develop theory that is ‘grounded’ in the data collected. - Key characteristics of the approach are the simultaneous collection of data, analysis and theory building to identify and illuminate the social processes underlying the phenomenon of interest. - Theoretical sampling is used to guide data collection. - The analysis of data is based on constant comparison combined with memo writing. - Data collection ceases when theoretical saturation has been reached. - Grounded theory has evolved since its inception in the 1960s, and there are currently three main approaches (systematic, emergent and constructive). Phenomenology: - Qualitative research approach that aims to capture rich descriptions of ‘lived experience’. - A key characteristic of the approach is the use of bracketing of the researcher’s preconceptions to focus on the lifeworld of the individual. - There are currently three main approaches to phenomenological research (descriptive, hermeneutic and interpretative). Discourse analysis: - Focuses on how the particular words people use create particular meaning. - Conversations, interviews, news articles, blogs, academic texts and policy documents are examples of materials that we can subject to a discourse analysis. - This qualitative technique focuses on exploring how words create meaning and the consequences (e.g. for particular people or groups) of using particular words to describe a phenomenon. - There are two types of discourse analysis commonly used in psychology (discursive psychology and Foucauldian discourse analysis). Quality assurance procedures in qualitative research: 1. Researcher reflexibility – researchers should engage in reflexibility, reflecting on their own biases, assumptions and perspectives that may influence the research findings and process, as well as implement techniques to mitigate/manage the impact of these biases. o By acknowledging and addressing their subjectivity, researchers can enhance the rigor and transparency of the study. 2. Audit trails – when conducting the research, researchers should maintain detailed audit trails documenting the research process, including any decisions made during data collection, analysis and interpretation. o Audit trails facilitate transparency and accountability by allowing other researchers to trace the steps taken in the research process and evaluate the trustworthiness of the findings. 3. Methodological transparency – when writing the research paper, researcher should also provide detailed descriptions of the research methods, procedures, and data analysis techniques used in the study throughout the write up so: a. Readers can evaluate the credibility and trustworthiness of the findings. b. Researchers can replicate the study. 4. Member checking – member checking involves seeking feedback from participants to verify the accuracy and credibility of the findings. o Researchers may present preliminary findings to participants and invite them to provide feedback, corrections or additional insights. o Member checking enhances the trustworthiness of the study by ensuring that participants’ perspectives are accurately represented. 5. Peer debriefing/triangulation – peer debriefing involves seeking input and feedback from colleagues or peers who are knowledgeable about qualitative research methods. o Researchers may engage in regular discussions, peer reviews, and cross coding of data to reflect on the research process, address methodological challenges, ensure consistency and enhance the rigor of the study. 6. Data saturation – data saturation refers to the point at which no new information or themes emerge from the data, indicating that theoretical saturation has been reached. o Researchers should strive to achieve data saturation by collecting sufficient data and systematically analysing the data until thematic saturation is achieved. o Data saturation enhances the credibility and depth of the findings by ensuring that all relevant themes and insights have been explored. Qualitative research – advantages: - Provides rich, contextualised descriptions of complex phenomena. - Elicits participants’ own categories of meaning. - Captures dynamic processes. - May develop new theories. - Can challenge the status quo and identify new directions of inquiry. - May reveal potential variables or hypotheses to be tested in future research. Qualitative research – disadvantages: - Longer time for both data collection and analysis compared to quantitative research. - Many researchers are trained in quantitative methodologies but not qualitative methodologies. - Have to be careful to manager researcher subjectivity/bias. - It is often more difficult to compare findings across qualitative studies. - Qualitative researcher cannot account for cause and effect relationships. - May be seen as less credible by administrators/funding bodies. - Due to the nature of qualitative data collection, may need to consider additional ethical dilemmas, power dynamics and potential harm to participants and/or researchers. Criteria for assessing quantitative and qualitative research: Category Quantitative Qualitative Truth value Internal validity Credibility Applicability External validity/generalisability Transferability Consistency Reliability/replicability Dependability Neutrality Objectivity Confirmability Mixed methods research designs Key decisions when choosing a mixed methods design: - Mixed levels designs are chosen based on: o The level of interaction between the quantitative and qualitative strands – independent or interactive. o The priority of the strands – equal, quantitative focus or qualitative focus. o The timing of the strands – concurrent, sequential or multiphase combination timing. o Where and how you want to mix the strands – mixing during interpretation, during data analysis (merging), during data collection (connecting) or at the level of design (i.e. mixing due to theory). The major mixed methods research designs: 1. Convergent parallel design – the researcher collects quantitative and qualitative data concurrently, analyses the two data sets separately, and mixes the two datasets by merging the results during interpretation (sometimes during data analysis). 2. Embedded design – researcher collects and analyses quantitative and qualitative data within a quantitative research design, qualitative research design or research procedure; collection and analysis of secondary dataset can occur before, during and/or after the primary methods. 3. Explanatory sequential design – researcher starts by collecting and analysis quantitative data, then collects and analyses qualitative data in a second phase as a follow-up to the quantitative results, before connecting the phases by using the quantitative results to shape the qualitative research questions, sampling and data collection. 4. Exploratory sequential design – researcher collects and analyses qualitative data first followed by quantitative data, before analysing the qualitative data and uses the results to build the subsequent quantitative phase, and then connects the phases by using the qualitative results to shape the quantitative phase by specifying research questions and variables, developing an instrument and/or generating a typology. 5. Multiphase design – researcher examines an overall objective and implements an iteration of connected quantitative and/or qualitative studies, building each new study on what was learned previously; this is to address a set of incremental questions that advance one overall programmatic objective. Mixed methods research – advantages: - Allows researchers to gain a more comprehensive understanding of the research problem by combing the strengths of both qualitative and quantitative methods. - This approach provides a more holistic view of the phenomenon under investigation – the investigator gains a better understanding of the problem and yields more complete evidence – in terms of depth and breadth. - Employing multiple methods in research can also strengthen the confidence in our findings, also known as triangulation. Mixed methods research – disadvantages: - Designing and conducting mixed methods research can be challenging due to the complexity involved in integrating qualitative and quantitative methods. o Researchers need expertise in both types of methods, as well as knowledge of how to effectively integrate them. - Mixed methods research typically requires more time, resources and expertise compared to studies employing only qualitative or quantitative methods. o Collecting, analysing and interpreting data from multiple sources can be labour-intensive and costly. - It can also be difficult to converge two sets of different data (e.g. knowing how to make sense of discrepant results). Sampling methods and participant organisation Main sampling methods: - Convenience sampling: o Usually volunteers in the near vicinity. o Most common sampling methods. o Undergraduate psychology students are a typical example. o Offers poor generalisation to the wider population (e.g. external validity). o Used in qualitative, quantitative and mixed methods research. - Purposive sampling: o When participants are selected on the basis of the characteristics of the population they belong to and the objectives of the study. o Individuals are deliberately chosen to represent population of interest (e.g. depressed individuals). o Can only be generalised/transferred to similar populations. o Used in qualitative, quantitative and mixed methods research. - Random selection: o Each individual in the population has equal chance of being selected to participate. o Offers best opportunity to generalise to the wider population. o Impossible to achieve in practice. o Mainly used in quantitative research. - Stratified sampling: o A sample which has proportions reflecting the population of interest. o E.g. a population where there are 60% men and 40% women, research may ensure their sample has similar proportions of men and women. o Mainly used in quantitative research. - Theoretical sampling: o A procedure from grounded theory where participants are selected on the basis of whether or not they will contribute to theory development. Between-participants and within-participants designs: - In addition to sampling considerations, researchers typically need to make a decision about how the participants will be organised. o In experimental and quasi-experimental designs, this means choosing between a between-participants design or a within-participants design. o The notion of between versus within participants is not relevant for correlational designs because there is no group/condition assignment. - Between-participants design – when two (or more) groups or conditions are made up of different individuals. o Quasi-experimental designs are usually between-participants (e.g. comparing scores across gender). o Experimental designs can be either or within-participants (sometimes can be both). - Within-participants design – when two (or more) conditions are made up of the same individuals. o Often referred to as repeated-measures designs (e.g. comparing depression before and after treatment). o These designs are usually experimental (i.e. there is often a manipulation occurring between each of the repeated measurements). Between-participants designs Within-participants designs Advantages - In experimental designs, this can - Can reduce (extraneous) variability prevent carry-over effects (i.e. when between conditions (i.e. make it easier participation in one condition can affect to detect actual differences because of the other). less extra variability which occurs because of individual differences. - Random (not systematic) variability is less likely to introduce differences to the measurement of the dependent variable. - Lower sample sizes needed. Disadvantages - Can introduce increased (extraneous) - In experimental designs, this can lead to variability between conditions (i.e. make carry-over effects (i.e. when it harder to detect actual differences participation in one condition can affect because of extra variability which occurs the other). because of individual differences). - Random (not systematic) variability can introduce differences to the measurement of the dependent variable (even if two people have the same amount of dependent variable. Cross-sectional versus longitudinal designs: - Cross sectional designs: o Data (for both variables of interest and outcomes) are measured at one point in time. o May have a form of between-participants design where changes are captured across different groups to compare differences).  E.g. difference across individuals in developmental areas, epidemiological factors and psychological factors. o Advantages:  Collect data from different groups at the same time.  Cheaper and quicker than longitudinal studies.  Tolerance to attribution. o Disadvantages:  Non-equivalent groups.  Maturation cannot be properly evaluated.  Cohort effects – things change in education settings etc. may lead to differences in generational experiences. - Longitudinal designs: o Collecting data over a long period of time. o A form of repeated-measured (within-participants) design. o Collected from the same individuals across a portion of their lifespan. o Well suited to tracking slow changes in factors. Possible to make causal conclusions. o Long term consequences can be observed. o Cause and effect can be observed. o Advantages:  Same as within-participants designs.  Lower extraneous variance – more sensitivity for finding effects.  Establish cause and effect (comorbidity – what occurred first?). o Disadvantages:  Vulnerable to attribution (which can bias the findings).  Participants become familiar with measurement instruments.  Expensive, time consuming and often impractical. Other study designs: - Field designs: o High levels of control can hurt external validity, o Field studies intentionally abandon attempts at control to improve the generalisation of findings to the real world. o Data is collected in real world environments. o Unpredictable. - Case studies: o A single individual is studied in detail.  Typically utilised in situations where the population of interest is unique or rare.  Individuals with damage to specific brain regions, or with rare diseases. o Findings cannot be generalised very far (e.g. often only to those with similar impairments). o May be useful for understanding healthy functioning. o Famous example – Phineas Gage. Common issues when designing research Common issues in quantitative research: - When considering any quantitative design, we need to be mindful of the possible issues that could threaten internal and external validity and develop strategies to mitigate such threats, such as: o Researcher control:  Level of control a researcher has over their variables is often associated with the integrity of the data.  By holding all other variables constant (e.g. temperature, noise, researcher) the effect of the IV on the DV can be better measured/estimated.  Extraneous variance (error) is reduced.  Achieved using standardised procedures.  Higher control is assumed to enhance internal validity.  Increasing levels of control comes at a high price. - Comparison/control groups: o When a comparison condition is used to determine whether true changes have occurred in the manipulation condition (e.g. placebo, waiting lists). o Researchers need to carefully consider the design of their control conditions:  The control group/condition usually needs something to do to stimulate elements of the manipulation condition but without introducing a confound.  The control needs to share something in common with the manipulation to make it a fair comparison.  Poorly matched stimuli can undermine internal validity (i.e. we can’t be sure that the relationship really exists because there are other systematic differences in stimuli characteristics). - Piloting is important for selecting and trialling procedures. o Test stimuli on a small sample first, then ensure the stimuli is suitable for research purposes, ensure the stimuli is representative, then ensure that it is equivalent on some properties. o Low risk test to see whether a manipulation is likely to be effective. - Blind and double-blind procedures: o Blind – the participant or researcher do not know which condition they are in/delivering. o Double blind – both the participant and researcher are unaware which condition they are in/delivering. - Practice and order effects: o Practice effects – can be problematic in repeated-measures designs. o Order effects – can be problematic in all signs. o Counteracted by either:  Counterbalancing – if half the participants complete the instruments in the reverse order then any order effects will hopefully cancel out.  Randomisation – if there are lots of measures or we are not sure what order effects might occur. - Participant preconceptions and expectations: o Expectancy/reactance effects – participants’ pre-existing ideas about the study might lead them to respond in systematically similar way. o Hawthorne effect – knowledge that one is being observed can lead participants to respond in systematically similar ways. o Demand characteristics – properties of environmental cues or measures/scales being used can lead participants to respond in systematically similar ways. - Attrition – when participants drop out during a study. - Self-report – one of the biggest challenges we face in psychology is an over-reliance on self-report when measuring variables. o In many cases self-report is the only means to capture the variable of interest. o Self-report is vulnerable to response bias (any response that is not the true level of the phenomena. o This is one form of measurement error. - Education in qualitative research methods in psychology is recent and still relatively limited. - Choosing a qualitative research design or analysis – sometimes the design or analysis chosen is a bad fit for the overall research aims or research description. - Combing multiple analysis types together – when reading qualitative papers, always check for congruency between the overall method chosen and the actual analysis employed. - Sample size: o Too small sample size casts doubt over saturation. o Too big sample size casts doubt over deep analysis. o Quality of information per case is more important than number of cases. o Sample size is dependent on the type of analysis and purpose of the research. - Perspective management in data collection and analysis. o Data collection – quality is improved when researchers recognise and are transparent about the influence of their perspectives upon data collection and appropriately limit that influence to obtain clearer representations of their phenomenon. o Analysis – quality is increased when researchers consider how their perspectives have influenced or guided the analysis of their data in order to enhance their perceptiveness in their analysis. Meta-analytic thinking - A new way of thinking about the meaning of data, requiring that we change our views of the individual empirical study. - Follows the assumption that all studies are consistent – individual studies are just sampling variations of the same result. - If most studies on a set of variables point to the same conclusion, then we can be reasonably confident that the effect is real. - A researcher should: o Report results so that they can easily be incorporated into future meta-analysis. o View their own study as a modest contribution to the body of previous research. - Meta analytic thinking therefore is ‘forest’ thinking, whilst the single study mindset is ‘tree’ thinking. - Approaches that use meta-analytic thinking – narrative reviews, systematic reviews. Critical thinking Myths in psychology - Science must begin with myths and with the criticism of myths. - These are misconceptions that enjoy widespread belief among a significant portion of the population. - These misconceptions emerge either from misinterpreting statements, or from selective attention. - As a scientific discipline, in psychology we aim to meticulously distinguish empirical evidence from fictional beliefs. - The most erroneous stores are those we think we know best – and therefore never scrutinise or question. - Myths in psychology can be very harmful. Sources of myths: - Word of mouth: o Myths are often spread verbally, like urban legends. o Sometimes there are also partial truths to the, o Hearing a claim repeatedly can lead us to believe it is true. - Selective memory: o We rarely (if ever) perceive reality as it actually is. o We tend to attribute relationships that do not exist, over-attending to aspects we find interesting. o Many myths result from cognitive illusions and the tendency to over-attend to relationships that are unusual. - Causation from correlation: o It is incorrect to assume that just because two things are relation, one must cause the other. - Post hoc, ergo propter hoc: o Means ‘after this, therefore because of this’. o We often assume that because A precedes B, then A must cause B. - Biased examples: o The nature of the world means we are often only exposed to a limited population. - Reasoning by representativeness: o Evaluating the similarity between two things based on their superficial resemblance to each other, taking a ‘shortcut’ – this is called the representative heuristic. - Partial truths: o Some myths are based on the truth, but have been misinterpreted or manipulated. Heuristics - Heuristics are one way that myths are perpetuated throughout society. - Heuristics are types of cognitive shortcuts that help us to make quick judgements about the world – like a mental ‘rule of thumb’. - Heuristics are strategies that use readily accessible information. - In psychology, they are simple and efficient rules that have become hard-coded by evolution. - Useful when a quick decision is required or limited information is available, but usually lead to systematic errors and cognitive biases. - Types of heuristics: o Thinking heuristics. o Judgement heuristics. o Memory heuristics. Thinking heuristics Conjunction fallacy: - The probability of two events together cannot be greater than the probability of the events by themselves. - Occurs when it is assumed that specific conditions are more probable than a single general one. Confirmation bias: - Favour information that confirms our beliefs. - Is particularly active when searching for, recalling or interpreting information. - Confirmation bias appears to be a system judgement – our default reaction is to look for information consistent with our preconceived understandings. - We tend to formulate and think of our decisions in terms of choosing rather than rejecting. - The compatibility principle – we look for information based on what we are being asked to do (accept or reject). Illusory correlation: - Perceiving a relationship when one does not exist – people generally misperceive random events as related. - Illusory correlation forms the basis of many stereotypes. Fundamental attribution error: - The tendency to over-value dispositional or personality (internal) based explanations for observed behaviours. - We place an undue emphasis on internal characteristics rather than considering the external factors in the situation. - When we look at other we see personality traits that explain their behaviour, but when we look at ourselves we see circumstances that explain our behaviour. We explain by permanent, enduring traits that would better explained by circumstance and context. - Explanations: o Just world theory – attribute failures to dispositional causes rather than situational (uncontrollable) meets need to believe that the world is fair and controllable. o Culture – enhanced individualism in Western cultures – tend to emphasise the individual over situational factors and more prone to fundamental attribution error. o Salience of the person – the person is the primary reference point and the situation is overlooked. Self-serving bias: - Tendency is attribute events incorrectly, often talking personal credit for positive outcomes and blaming negative outcomes on external events. - A common form of cognitive bias. The Baader-Meinhof phenomenon: - The faulty impression that something happens more frequently than it really does. - This usually occurs when we are learning something new – suddenly, this new thing seems to appear more frequently, when in reality it is only our awareness of that has increased. - Also known as the frequency/recency illusion. Stereotypes: - A false assumption that the members of a group share the same characteristics. - A form of categorisation that helps to simplify and systematise information so that information is more easily identified, recalled, predicted and reacted to. - Stereotypes, prejudice and discrimination are related, but different concepts. - Stereotyping is cognitive and often occurs without conscious awareness, whereas prejudice is the affective component of stereotyping and discrimination is one of the behavioural components of prejudicial reactions. Judgement heuristics Availability heuristic: - Predicting the frequency of an event based on how easily an example can be provided. - Operate on the notion that if something can be recalled, it must be important or more likely to be true. Representativeness heuristic: - Judging the probability of a hypothesis based on how much the hypothesis resembles available data. - Judge something by intuitively comparing it to our mental representation of a category. Anchoring effect: - Cognitive bias that describes the tendency to rely too heavily on the first piece of information offered (i.e. the anchor) when making decisions. - People start with an implicitly suggested reference point (anchor) and then subsequent judgments are made by adjusting around that anchor. Forer/Barnum effect: - Tendency for people to give high accuracy ratings to descriptions of their personality that are supposedly tailed to them, but are vague enough to be about anyone. - Is manifested in response to statements that are called ‘Barnum statements’ – characteristics made about a person that they find valid even though they are generalisations that could apply to almost anyone. Just world theory: - The belief that people get what they deserve. - Very prevalent in health research. - Is a psychological defence mechanism. Memory heuristics The misinformation effect: - Loftus and Palmer (1974) found that exposure to misleading information between the encoding of an event and its subsequent recall causes impaired memory. - Participants watched a short movie of car crashes. Thinking critically What is critical thinking? - A purposeful, self-regulatory judgement that results in interpretation, analysis, evaluation and interference, as well as explanations of the evidential, conceptual, methodological, criteriological or contextual considerations that judgement is based upon. - A kind of thinking in which you question, analyse, interpret, evaluate and make a judgement about what you read, hear, say or write. Its about making reliable judgements about reliable information. - Critical thinking skills are skills needed to be developed – it requires practice in order to become better at applying critical thinking skills. o Not about being innately smart or about learning everything. o Not about pulling everything apart or focusing on faults. Critical thinking in research: - In good thinking: search is sufficiently thorough for the question; search and inference are fair to all possibilities under consideration, and confidence is appropriate to the amount of search that has been done and the quality of the inferences made. - This pattern of thinking involves searching for alternative perspectives (other than your initial/preferred one), integrating across these, and making appropriate adjustments to your confidence level. - Extraordinary claims: o David Hume proposed ‘extraordinary claims require extraordinary evidence’. o The more a claim predicts what we already know, the more persuasive the evidence for this claim must be. o This concept is central to the scientific method and is a key issue for critical thinking, rational thought and scepticism. - Occam’s razor: o Also known as the principle of parsimony (i.e. the simplest route). o Involves ‘shaving off’ unnecessary complex explanations to arrive at the simplest explanation. o The simplest explanation is one which also accounts for the most information. - Testability and falsifiability – scientific theories must be both testable and falsifiable. - Replicability – when the findings of a study are able to be duplicated consistently – replication increases confidence in the findings. - Correlation is not causation – a common mistake is to conclude that when two things are related, one must cause the other. - Ruling out rival hypotheses – cannot just accept findings at face values in line with our theory – we have to challenge and consider other explanations. Think critically – ability versus willingness: - Ability: o Understanding what critical thinking is – how we define it and why it is valuable. o Learning critical thinking skills and strategies. - Willingness: o Being open to utilise critical thinking skills when evaluating evidence. o Considering alternative perspectives and possibly being proven wrong. - Effective critical thinking requires both ability and willingness. o Just having the ability to think critically is not sufficient. Willingness is usually the hurdle. Why thinking critically can be difficult: - Limited resources: o It can be very costly to be thinking critically about everything we see, hear and consume all the time – how can we be selective about when critical thinking will be valuable?  Start thinking sceptically and assume that most things will not be absolute – a possible warning sign is if information is delivered in an absolute way.  Identify complexity – it is important to have an appropriate level of confidence; if you haven’t thought about it or gathered information on it, admit that you don’t know. o A strategy that may help with this – identify when it is most important to think critically. - Motivated reasoning: o Sometimes we are motivated to believe certain things and our reasoning can then be biased. o If it a strongly held belief or has a lot hinging on it, it can be difficult to be open to change. o A strategy that may help with this – using the split mind approach:  If your belief is strongly supported, it will stick around even if you are open-minded.  Being open-minded might even help you adopt stronger, better-supported views and hone your critical thinking. Applying critical thinking: - Critical thinking is a set of skills that allow us to evaluate claims in a scientific, open-minded fashion. Good habits Bad habits - Being fair and open-minded when considering - Biased to prefer own side. different views. - Only superficial understandings; does not care - Trying to understand things deeply; being to learn more. curious. - Accepting without questioning. - Questions assumptions, evidence and - Jumping to conclusions. limitations. - Being overly confident. - Persistent, thorough, careful. - Recognises own limitations, admits when wrong or doesn’t know. - Evaluating evidence: Considerations Authority What are the authors’ qualifications? What field do they work in? What have they published in this area? What organisation are they part of? What is the reputation of that organisation? Any interests? Purpose What was the content written for? What was the intent? Does it aim to be evidence-based? Objective? Is it an argument? Is an idea or product being sold to the reader? Evidence What evidence is being included? Where has it come from? Is this evidence trustworthy? Are claims being made and are these supported? Are references being used? If so, can you corroborate these? - Lateral thinking: o A form of fact-checking to find more information on claims being made across different sources. o Read ‘across’ – check information as you read; this can be done by opening lots of tabs, or having a few sources (websites, books, articles etc.) opened at once. o Checking a range of sources from a range of authors with a range of different interests/purposes. - The ‘split-mind’ approach: o When we have the resources available to do so, and in situations where we think it would be valuable to think critically, we can employ the split-mind approach. o This is a helpful strategy that encourages us to keep a fair and open mind. o One half of you is actively agreeing, extending, applying, making connections, refuting criticisms, etc. o The other half of you is actively disagreeing, questioning, thinking of counter examples, problems, etc. The importance of active thinking: - Failures of critical thinking contribute to many negative outcomes: patient deaths, lost revenues, job loss etc. - In this digital age, we are witnessing an information overload and not all of the information we consume is correct, beneficial or useful. - It is important to be able to effectively evaluate information. - Critical thinking in psychology research is important because psychology is important to life (e.g. coping with stress) and being able to think critically about research is essential to many ventures in academia and beyond. Social psychology - Examines the influence of social processes on people’s thoughts, feelings and behaviours. - How our behaviour is influenced by the presence of other people. - Also considers similarities and differences in thoughts, feelings and behaviours across cultures. Conformity, obedience and social norms Conformity and obedience: - Conformity – the adjustment of individual behaviours, attitudes and beliefs to a group standard, which can be impacted by: o Ambiguity of the situation. o Unanimity and size of the majority. o Minority influence. - Obedience – behaviour change in response to a demand from an authority, which can be impacted by: o Experimenter status and prestige. o Behaviour of others or of the learner. o Level of privacy/anonymity. o Personality characteristics (e.g. authoritarianism and empathy). Asch’s conformity experiment: - In Asch’s (1956) conformity experiment, students were asked to judge which of three comparison lines was the same length as a standard line. - They performed this task for multiple trials, using a different set and comparison lines each time. - Only one person was the actual participant – all others were actually working with the experimenter as ‘confederates’. - The confederates would purposely pick the wrong line, to see if the real participant would conform. - About three quarters of the real participants conformed to the wrong answer at least once. Milgram’s shock study: - Conducted at Yale in the 1960’s. - A participant was greeted by a researcher conducting the study; they were told that the study is about the effects of ‘punishment on learning’. - The ‘learner’ in the study was another participant, who was actually a confederate. - The learner would memorise combinations of words, and with each wrong answer, the participant (teacher) would deliver an electric shock – ranging from slight shock to danger severe shock to XXX. - Many participants were visibly anxious and uncomfortable, yet did not stop. The Stanford prison experiment: - Conducted by Phillip Zimbardo in 1971 to study the psychological effects of perceived power dynamics. - Volunteers were randomly assigned to roles of prisoners or guards in a mock prison. - Guards quickly assumed authoritarian roles, enforcing strict rules and engaging in abusive behaviours towards prisoners; prisoners showed signs of psychological distress and rebellion. - Terminated very early due to extreme conditions, including mental and physical harm to participants, raising ethical concerns about the treatment of human participants in psychological research. - Demonstrates how situational factors can influence behaviour and the power of social roles. Social norms: - Social norms are shared expectations about how people should think, feel and behave; they are the glue that binds social systems behaviour. - Social norms are different across cultures, for instance: o What is trauma? What is attractive? How to show respect? Social control: - Mechanisms used by society to regulate individual behaviour and maintain social order. - Includes formal institutions like laws and informal norms and expectations. - Aimed at preventing deviant behaviour and promoting conformity to societal standards. - Can be exerted through various means, such as rewards, punishments and social sanctions. - Plays a crucial role in shaping individual actions and maintaining cohesion within communities. Peer surveillance: - Monitoring or observation of individuals’ behaviour by their peers. - Occurs within social groups, communities or online networks. - Can be explicit or implicit, intentional or unintentional. - Often influences behaviour by promoting conformity to group norms. - Can lead to social pressure and conformity as individuals modify their actions to align with perceived group expectations. Behaviours and beliefs within groups Deindividuation and diffusion of responsibility: - Deindividuation: o Occurs when individuals lose their sense of individual identity and responsibility in group settings. o Often leads to decreased self-awareness and inhibition, resulting in impulsive or deviant behaviour. o Factors such as anonymity, group size and arousal contribute to deindividuation effects. o Examples include riots and mob violence. - Diffusion of responsibility: o Phenomenon where individuals feel less accountable for their actions in group contexts. o Assumes others will take responsibility or intervene, leading to decreased personal accountability. o Can result in bystander apathy, where individuals fail to help others in emergency situations due to diffusion of responsibility. Mob mentality and groupthink: - Mob mentality: o Phenomenon where individuals in a group lose their sense of individuality and engage in impulsive or irrational behaviour. o Often occurs in emotionally charged situations, leading to actions individuals wouldn’t typically undertake alone. - Groupthink: o Occurs when group cohesion and the desire for unanimity override critical thinking and decision-making. o Leads to faulty decision-making, ignoring alternative viewpoints and suppression dissent. In-group versus out-group: - In-group: o Social group to which an individual belongs and identifies with. o Provides a sense of belonging, identity and social support. - Out-group: o Social group with which an individual does not identify or belong. o Often subject to stereotypes, prejudice and discrimination from the in-group. Group polarisation: - Phenomenon where group discussions lead to the strengthening of pre-existing attitudes or opinions. - Group members’ initial inclinations become more extreme after discussion, amplifying the group’s collective stance. - Occurs due to informational influence and social comparison processes occurring within the group. Echo chambers: - Environments where individuals encounter only information or opinions that reinforce their existing beliefs. - Often formed via self-selection and algorithmic filtering. - Amplifies polarised viewpoints and fosters confirmation bias. - Limits exposure to diverse perspectives, hindering constructive dialogue. Social loafing and social facilitation: - Social loafing: o Tendency for individuals to exert less effort in group tasks compared to when working alone. o Occurs when individuals perceive their contribution as less critical or when effort is not individually evaluated. - Social facilitation: o Phenomenon where individuals perform better on simple or well-rehearsed tasks in the presence of others. o Presence of others increases arousal and motivation, enhancing performance on tasks one is already proficient in. More social influences: - Outgroup homogeneity effect: o Perceiving outgroup members as more similar to each other than ingroup members. o Simplifies perceptions, fostering stereotypes and prejudice. - False consensus effect: o Overestimating the extent to which others share one’s beliefs or behaviours. o Leads to misjudgements and projection of one’s own opinions onto others. - Bandwagon effect: o Likelihood of individuals adopting beliefs increases with perceived majority opinion. o Driven by conformity and desire to avoid social exclusion. Robber’s cave experiment: - The Robber’s cave experiment was conducted by Muzafer Sherif in the 1950’s to study intergroup conflict and cooperation

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