scientific inquiry psych

Ethical guidelines and practices for psychological research

• The role of ethics/ethical guidelines in psychological research

  • This involves understanding why ethical guidelines are important in conducting psychological research. Ethics ensure the well-being, rights, and dignity of participants are protected throughout the research process.

• The role of ethics committee approval and monitoring of conduct for all psychological research

  • This refers to the necessity of having research proposals reviewed and approved by an ethics committee. These committees monitor research conduct to ensure ethical standards are maintained.

• Understand and apply ethical guidelines and practices related to human participants

  • This involves knowing and implementing specific ethical guidelines when dealing with human participants, ensuring their safety and rights.

  • Protection from harm – physical and psychological

    • Ensuring participants are not exposed to physical or psychological distress during the research.

  • Informed consent

    • Obtaining voluntary agreement from participants after fully informing them about the research's purpose, procedures, potential risks, and benefits.

  • Withdrawal rights

    • Participants have the right to leave the study at any time without penalty.

  • Deception

    • If deception is necessary, it must be justified, and participants must be debriefed afterward.

  • Confidentiality

    • Keeping participants' personal information private and secure.

  • Privacy

    • Respecting participants' personal space and boundaries.

  • Voluntary participation

    • Ensuring participation is freely chosen without coercion.

  • Debriefing

    • Informing participants about the study's true purpose after their involvement, addressing any misconceptions, and providing support if needed.

Formulating research

• Identify variables

  • This involves recognizing and defining different types of variables in a study.

  • Independent

    • The variable that is manipulated or changed by the researcher.

  • Dependent

    • The variable that is measured to see if it is affected by the independent variable.

  • Control

    • Variables that are kept constant to prevent them from influencing the dependent variable.

  • Extraneous – participant, environment, researcher

    • Variables other than the independent variable that could affect the dependent variable (e.g., participant characteristics, environmental conditions, or researcher bias).

  • Confounding

    • Variables that are not controlled and systematically vary with the independent variable, making it difficult to determine the true effect of the independent variable on the dependent variable.

Methodology

• Types of research designs – application, method, strengths, and limitations

  • Understanding different research designs and their appropriate use, including their benefits and drawbacks.

  • Experimental (control and experimental group)

    • A design that involves manipulating an independent variable to determine its effect on a dependent variable, using control and experimental groups for comparison.

  • Non-experimental

    • Research designs that do not involve manipulation of variables.

    • Observational

      • Collecting data by observing participants in their natural setting.

    • Case study

      • An in-depth investigation of a single individual, group, or event.

    • Correlational

      • Examining the relationship between two or more variables without manipulating them.

    • Longitudinal

      • Studying the same participants over an extended period.

    • Cross-sectional

      • Studying different groups of participants at a single point in time.

• Selection of participants

  • The process of choosing participants for a study.

  • Identification of sample and population

    • Defining the group of individuals who will participate in the study (sample) and the larger group they are meant to represent (population).

  • Methods to sample participants – application, method, strengths, and limitations

    Here’s a breakdown of the application, method, strengths, and limitations for each sampling method:

    Convenience Sampling

    • Application: Commonly used in preliminary research or when time and resources are limited.

    • Method: Select participants who are readily available and easily accessible.

    • Strengths:

      • Quick and inexpensive.

      • Easy to implement.

    • Limitations:

      • High risk of bias.

      • May not be representative of the population.

    Snowball Sampling

    • Application: Useful when studying populations that are difficult to reach or identify.

    • Method: Participants recruit other participants from their networks.

    • Strengths:

      • Effective for reaching hidden populations.

      • Can provide in-depth information.

    • Limitations:

      • Potential for bias from similar networks.

      • Limited generalizability.

    Random Sampling

    • Application: Used when it’s important to have a representative sample of the population.

    • Method: Every member of the population has an equal chance of being selected.

    • Strengths:

      • Minimizes bias.

      • Increases generalizability.

    • Limitations:

      • Can be time-consuming and expensive.

      • Requires a complete list of the population.

    Stratified Sampling

    • Application: Used when specific subgroups within a population need to be accurately represented.

    • Method: Divide the population into subgroups (strata) and randomly sample from each subgroup.

    • Strengths:

      • Ensures representation of all subgroups.

      • Increases accuracy and generalizability.

    • Limitations:

      • Requires detailed knowledge of the population.

      • Can be more complex and time-consuming.

    • Convenience sampling

      • Selecting participants who are easily accessible.

    • Snowballing

      • Participants recruit other participants.

    • Random sampling

      • Every member of the population has an equal chance of being selected.

    • Stratified sampling

      • Dividing the population into subgroups and randomly sampling from each subgroup.

• Sources and effects of extraneous variables and confounding variables

  • Understanding where these variables come from and how they can impact research outcomes.

  • Placebo effect

    • A change in a participant's behavior or health due to the belief that they are receiving treatment.

  • Experimenter effect

    • The influence of the researcher's expectations or behavior on the results of the study.

  • Demand characteristics

    • Cues in the experiment that lead participants to guess the purpose of the study and change their behavior accordingly.

• Minimise the effects of extraneous and confounding variables

  • Techniques to reduce the impact of these variables on research results.

  • Random allocation of participants

    • Assigning participants to different groups randomly to ensure equal distribution of participant characteristics.

  • Use of a placebo

    • Providing a fake treatment to control for the placebo effect.

  • Single-blind and double-blind procedures

    • Single-blind: participants are unaware of which group they are in; double-blind: neither participants nor researchers know the group assignments.

  • Standardisation of procedures and instructions

    • Ensuring all participants receive the same instructions and procedures to reduce variability.

Data collection

• Types of data

  • Understanding the different types of data that can be collected in research.

  • Qualitative data

    • Non-numerical data that describes qualities or characteristics.

  • Quantitative data

    • Numerical data that can be measured and analyzed statistically.

• Methods of data collection – application, strengths, and limitations

  • Different techniques for gathering data, each with its advantages and disadvantages.

  Methods of data collection – application, strengths, and limitations

  Qualitative

  Interviews – focus group and individual; structured, semi-structured

  Gathers data through asking questions; can be with groups or individuals, and can be highly structured or more flexible.

  • Advantages:

  Rich, detailed data Flexibility in questioning

  • Limitations:

  Time-consuming
  Potential for interviewer bias

  Open-ended survey

  Collecting data through questionnaires that allow participants to provide detailed, free-form answers.

  • Advantages:

  Collects detailed, free-form answers.
  Can gather a large amount of information.

  • Limitations:

  Data can be difficult to analyze.
  Lower response rates compared to closed-ended surveys.

  Quantitative

  Objective physiological measures – heart rate, breathing rate, galvanic skin response (GSR)

  Using physiological measurements to gather numerical data about participants' physical responses.

  • Advantages:

  Objective and reliable
  Provides precise measurements

  • Limitations:

  Can be expensive
  May not reflect real-world behavior

  Subjective measures – rating scales, such as Likert scales

  Collecting data through participants' self-reported ratings or evaluations.

  • Advantages:

  Easy to administer and analyze
  Gathers insights into opinions and attitudes

  • Limitations:

  Prone to response bias
  May not capture the complexity of attitudes

  Mixed methods – data collection may be a combination of qualitative and quantitative data

  Using both qualitative and quantitative data collection methods in a single study.

  • Advantages:

  Provides a more comprehensive understanding
  Can strengthen findings

  • Limitations:

  Can be complex and time-consuming
  Requires expertise in both qualitative and quantitative methods

  • Quantitative

    • Objective physiological measures – heart rate, breathing rate, galvanic skin response (GSR)

      • Using physiological measurements to gather numerical data about participants' physical responses.

    • Subjective measures – rating scales, such as Likert scales

      • Collecting data through participants' self-reported ratings or evaluations.

  • Mixed methods – data collection may be a combination of qualitative and quantitative data

    • Using both qualitative and quantitative data collection methods in a single study.

• Differences between subjective and objective data

  • Understanding the distinction between data based on personal opinions or feelings (subjective) and data based on measurable facts (objective).

Processing and analysing data

• Construct and interpret data displays

  • Creating and understanding visual representations of data.

  • Graphs – scatterplot, column, line, histogram

    • Different types of graphs used to display relationships and distributions in data.

  • Tables – summary, frequency

    • Organized arrangements of data in rows and columns used to present key information.

• Calculate and interpret the mean and median as measures of central tendency

  • Finding and understanding the average (mean) and middle value (median) of a dataset to describe typical values.

• Interpret Pearson’s correlation coefficient as a measure of strength and direction of linear relationships

  • Understanding how to use Pearson’s correlation coefficient to assess the strength and direction of linear relationships between two variables.

Drawing conclusions

• Evidence-based conclusions consistent with psychological evidence and relevant to the hypothesis or inquiry question

  • Forming conclusions based on the data collected and relevant to the research question.

Evaluation of research

• Application and use of the concept of validity as a measure of evaluating research

  • Assessing whether the research measures what it intends to measure.

  • Internal validity

    • The degree to which the results of a study are due to the independent variable and not other factors.

  • External validity

    • The extent to which the results of a study can be generalized to other situations and people.

• Application and use of the concept of reliability as a measure of evaluating research

  • Assessing the consistency and stability of research results.

  • Test-retest reliability

    • The consistency of results when a test is repeated over time.

  • Inter-rater reliability

    • The degree of agreement among different researchers or observers.

• Generalisability of sample to the population

  • The extent to which the findings from the sample can be applied to the larger population.

• Suggest relevant improvements to address limitations of research

  • Identifying and proposing ways to fix weaknesses in the research design or methods.

• Ethical implications

  • Considering the ethical issues and consequences of the research.

• Critical evaluation of information from a range of scientific sources

  • Assessing the quality and credibility of information from various sources.

ask about hypothesis

• directional: shows the type of change

• non directional: doesn’t show the type of change