Science Inquiry: Ethical Guidelines

Science Inquiry

Ethical Guidelines

• Codes of practice act as a guide for those involved in psychological research.
• These codes help people understand what is considered right or wrong in research.

Protection from Harm

• Researchers must protect participants' physical and psychological well-being.
• Example: Providing a debrief after a study to reduce the risk of continued psychological harm.

Informed Consent

• Researchers must obtain written consent from participants.
• A consent form is required.
• For participants under 18 or lacking intellectual ability, legal guardians must provide consent.
• Consent forms should include the study's purpose, participant requirements, potential risks, length, and withdrawal rights.

Withdrawal Rights

• Participants can leave the study or have their results removed without pressure or penalty.

Confidentiality

• Information collected must be stored securely and disposed of when no longer required.
• Names should not be used; use numbers instead.
• Written consent must be obtained for publishing participant information.

Privacy

• Only information relevant to the study should be collected.

Voluntary Participation

• Participants should partake without bribery; it should be their choice.

Deception

• Lying about the study's true nature or the participant's role.
• It is often used when knowing the true purpose might affect results.
• If deception causes risks outweighing benefits, it should not be used.

Debriefing

• An explanation given to participants at the study's end.
• If deception occurs, participants need to be informed.
• Opportunity for counseling should be provided.
• Mistaken beliefs that may have been formed must be dispelled.
• Participants' right to remove results from the study needs to be upheld.

Animals in Research

• Priority is respecting animals, demonstrated by applying the 3 R's.
• Refinement: Use methods minimizing potential distress/pain.
• Reduction: Use methods to reduce the number of animals used.
• Replacement: Use alternative methods eliminating the need for animals.

Steps to Formulating Research

• Identify the Aim: A general statement explaining the research's purpose.
• Example: To investigate whether hemp seed oil affects sleepiness in students.
• Develop a Research Question: Based on the aim, it should be a well-defined question based on background information.
• It intends to be answered by collecting and analyzing data.
• Example: What is the relationship between hemp seed oil consumption and sleepiness in students?

Identifying Variables

• Develop operational definitions of both independent (IV) and dependent (DV) variables when developing a testable hypothesis.
• Activities of researcher in measuring/manipulating variable are specified.
• IV = ingesting hemp seed oil vs. not.
• DV = time taken to fall asleep over two weeks.
• CV = capsule is taken at the same time of day by participants.
• EV = amount of screen time participants have before bed.

Constructing a Hypothesis (Quantitative)

• It informs the methodology that follows and is used in research producing quantitative data.
• Should include the population and how IV/DV will be measured.

Directional Hypothesis

• Compares the predicted outcome of each condition; used when past research provides a clue.
• Example: It is hypothesized that students who take hemp seed oil before bed for two weeks will take LESS time to fall asleep, compared to students who do not take hemp seed oil.

Non-Directional Hypothesis

• A statement that there is a difference, but does not specify the type of difference.
• Used when there is no previous research, or previous research provides contradictory results.
• Example: It is hypothesized that students who take hemp seed oil before bed for two weeks will DIFFER in the time taken to fall asleep, compared to students who do not take hemp seed oil.

Constructing an Inquiry Question (Qualitative)

• Inquiry questions can be used instead of formulating a hypothesis.
• Does not make research outcome predictions, instead prompts broad exploration of the research topic.
• Used in research that produces qualitative data.
• Open-ended question that the research is aiming to explore; starts with a question word.
• Example: What effect does hemp seed oil have on sleep?

Types of Research Designs: Experimental

• Where the independent variable (IV) is manipulated.
• A cause-and-effect relationship can be found.
• Participants can be randomly allocated.
• Includes a control group and an experimental group.
• Control: Exposed to all conditions except the IV to provide a basis for comparison.
• Experimental: Group of participants exposed to the IV.

Strengths (Experimental)

• Researchers have control over variables.
• Cause-and-effect relationships can be found.

Limitations (Experimental)

• Controlled experiments reduce realism and can impact behavior.
• Trying to control variables can further risk human error.

Non-Experimental

• The independent variable (IV) cannot be manipulated.
• Cause-and-effect relationships cannot be found.
• Participants cannot be randomly allocated.
• Includes case studies, observational studies, correlational studies (e.g., Watson + Rayner's 'Little Albert').

Strengths (Non-Experimental)

• Observing what occurs naturally in the environment; a controlled setting does not have to be created.
• Allows for research where manipulating variables would be unethical.

Limitations (Non-Experimental)

• Reliable casual conclusions cannot be made.
• Larger sample sizes are required for more participants to be observed.

Observational

• Researchers monitor participants and record notes, used to study behaviors (e.g., Bandura, Ross + Ross' Bobo doll experiment).

Strengths (Observational)

• Can be replicated by other researchers.
• Participants are more likely to behave naturally.

Limitations (Observational)

• Observer bias may occur: the researcher sees or records what they want to see.
• Participants may change behavior if they know they are being observed.
• Voluntary participation and informed consent may be breached as participants are unknowingly involved in research.

Case Study

• In-depth investigation of a single person, group, or event.
• Useful for examining unusual events that can't be replicated in a lab.
• Includes lots of data that is largely qualitative.

Strengths (Case Study)

• Has lots of detailed information.
• Information can be gathered from a range of perspectives.

Limitations (Case Study)

• Results cannot be generalized to the population.
• Conclusions are limited due to the lack of formal control groups.

Correlational

• Measures linear relationships between 2 variables. E.g. a positive correlation was found between birth weight + childhood intelligence in a 2020 study of 1719 children.

Strengths (Correlational)

• Potential hypothesis based on correlation can be tested using experimental design.
• Can be used when manipulating variables in experimental research is unethical.

Limitations (Correlational)

• Correlations do not show how variables are related because there's no cause-and-effect.
• Extraneous variables are not controlled and could intervene.

Longitudinal

• Data is collected more than once using the same participants, could be days, weeks, or decades. Often used to study developmental trends across a lifespan.

Strengths (Longitudinal)

• Developmental trends can be studied over a lifetime.
• Frequency, timing, and duration of events can be studied (e.g., depressive episode).

Limitations (Longitudinal)

• Takes a long time to get results.
• Participants may drop out over time.

Cross-Sectional

• Data from participants is collected at one point in time.
• The Australian census gets information from a survey from every Australian household at one point in time.

Strengths (Cross-Sectional)

• Quicker to conduct than longitudinal studies.
• Costs less than longitudinal studies.

Limitations (Cross-Sectional)

• Only a snapshot in time is chosen.
• Sample size may not be large enough.

Selection and Allocation of Participants

• Population: The entire group of people of interest to the researcher.
• Sample: A subsection of the population; should be representative.
• Sampling: The process of selecting participants from the population of research interest in a study.

Convenience Sampling

• Method: Participants who are easily accessible are selected.

Strengths (Convenience Sampling)

• Low time, effort, and costs.

Limitations (Convenience Sampling)

• May have a high level of researcher bias: they are subjectively selecting participants.
• The sample is unlikely to be representative.

Snowball Sampling

• Method: Initial participants are chosen, then encouraged to refer other people to contact the researcher.

Strengths (Snowball Sampling)

• Allows the researcher to find a sample that may be difficult to recruit (e.g., drug users or sex workers).
• Less time is needed for the researcher to gather initial participants.

Limitations (Snowball Sampling)

• Unlikely to be representative of the population.
• Researchers are minimally involved.
• The sample may be biased.

Random Sampling

• Method: Names of all members in a population are collected, then randomly selected, for example, by drawing out of a hat or using a computer-generated list.

Strengths (Random Sampling)

• Researcher bias is minimized.
• Each participant has a chance of being selected.

Limitations (Random Sampling)

• Time and effort are high.
• The sample is unlikely to be representative of the population if the sample size is not adequate.

Stratified Sampling

• Method: The population is broken into subgroups based on characteristics relevant to the study.
• Participants from each subgroup are then randomly selected in the same proportions as they appear in the population.

Strengths (Stratified Sampling)

• Researcher bias is minimized.
• The sample is likely to be representative.

Limitations (Stratified Sampling)

• High time and effort involved.
• It can be hard to classify each participant of population into subgroups.

Random Allocation

• Method: Random distribution of participants into experimental and control groups to reduce researcher bias and increase generalizability.
• Names of participants in the sample are collated and names are randomly selected.
• Allows for good generalizability (equivalent groups of participants are created); prevents selection bias.

Limitations (Random Allocation)

• Cannot be used when the independent variable cannot be manipulated by the researcher.
• Equality of groups regarding characteristics is not guaranteed.

Types of Variables

• IV (Independent Variable): What is being manipulated by the experimenter to observe the effect on the DV.
• DV (Dependent Variable): Variable being measured.
• CV (Controlled Variables): Variables that stay consistent throughout an experiment, controlled to see if the independent variable has an effect.
• EV (Extraneous Variables): Unwanted variables that may impact the dependent variable (not always known to the researcher until after the study is complete).

Types of Extraneous Variables: Participant Variables

• Relating to the individual characteristics of participants.
• Can be controlled by making sure participants have similar personal characteristics suitable for the study or by using random allocation to ensure equivalent groups are made.

Participant Variables to Consider

• Motivation, educational background, age, gender, self-esteem, intelligence, memory, prior experience, personality characteristics, health, physical ability, and mood.

Environment Variables

• Relating to the environment and how it may affect participants.
• Consider: Testing venue, background noise, air temperature, time of day.

Researcher Variables

• Relating to the personality characteristics, appearance, and conduct of the researcher that may unintentionally impact the participants' responses.
• Consider: Accent.

Confounding Variables

• Impact the dependent variable (DV) and also have a casual or correlational relationship with the independent variable (IV).
• Alters the relationship between the IV and DV.
• Can complicate results, making them difficult to interpret.
• Possible for some extraneous variables to become confounding if not carefully controlled.

Experimenter Effect

• Expectations and behaviors of the researcher that may bias results.
• They unconsciously influence participants, may inaccurately record or interpret data.
• Can be reduced by a double-blind procedure, where the researcher and participants are unaware of the experimental conditions.
• This can allow for demand characteristics at times.

Demand Characteristics

• Cues that participants perceive during a study leading them to believe they've discovered the aim of the study.
• Can cause them to try to please or to disapprove of the researcher

Minimizing Effects of Extraneous and Confounding Variables

• Random allocation of participants: ensures each participant has an equal chance of being chosen for the control/experimental group to help minimize participant variables and researcher effects.
• Single-blind procedure: the experimenter is aware of experimental conditions, but the participants are unaware. Participants aren't told which experimental condition they're in and might not even know the aim.
• Deception would occur: this is explained during debriefing.
• Standardizing procedures and instructions: minimize environment variables by providing the same location and conditions for all participants (example: using a lab setting).

Data Collection: Qualitative vs. Quantitative

Qualitative

• Descriptive data in the form of words.
• Data Format: Written words.
• How is Data Displayed: Flow charts, taxonomy, Venn diagrams, summary tables.
• Question format: Open-ended questions, providing free-form answers.
• Method of Collection: Interviews (structured/semi-structured), focus groups, open-ended surveys, observation (naturalistic).
• How to Analyze: Large amounts of descriptive data is assessed for patterns.

Quantitative

• Information in the form of numbers.
• Data Format: Numerical.
• How is Data Displayed: Graphs, summary tables (i.e., frequency tables).
• Question Format: Closed-ended questions, limiting answers to set responses.
• Method of Collection: Checklists, rating scales, observation (controlled), using equipment in physiological measures such as thermometers.

Methods of Collecting Quantitative Data

• Subjective Data & Objective Data

Objective Data

• Data based on facts that can be supported through observation and measurements.
• Physiological measures: Heart/breathing rate, changes in emotional stress/physical effort/consciousness, Galvanic Skin Response (GSR) which changes in electrical conductivity of the skin and can detect anxiety, guilt, fear, and excitement etc.

Strengths (Objective Data)

• Participant bias is limited as these measures are difficult to change.
• It can be recorded in real time.

Limitations (Objective Data)

• Exercise/heat can cause changes to the measurements.
• Participants could feel anxious during the measurement which could then alter the results.

Subjective Data

• Data based on personal opinions and judgements.
• Checklist: Collecting yes/no information.
• Rating Scales: Participants indicate their strength of agreement to possible statements.

Strengths (Subjective Data)

• Data can be statistically analyzed.
• Large sample sizes can be used and give data in a short amount of time.

Limitations (Subjective Data)

• Can be completed remotely.
• Responses are limited; does not allow for elaboration.
• Participants must rely on reading ability. + Phrasing and the order of statements can affect responses.
• Likert scales and mixed methods etc

Likert Scales

• Each question uses a 5- or 7-point scale. Each point is allocated a numerical score used to determine whether the overall attitude is positive or negative. It usually includes a neutral option and the can provide a score on a diagnostic test.

Mixed Methods

• Both qualitative and quantitative data are collected from participants in the same study.
• Using both interviews + rating scales.

Strengths (Mixed Methods)

• Allows for a greater understanding of the research problem.
• The two can complement each other. + The interview can lead to the development of a checklist.

Limitations (Mixed Methods)

• Greater expertise is required to collect and analyze data.
• Time required is greater.

Sensation + Perception

• Stimulus energy is transferred → sensory receptors → electrochemical signals → brain
• Sensation: The conversion of physical energy in order to relay info to the brain by using our sense organs. It turns this signal into an electrical, neuronal signal. Physiological process.
  • Reception: The detection of sensory information in order to stimulate sense organs by sensory receptors.
  • Transduction: The conversion of sensory info into electrochemical energy from the assistance of sensory receptors.
  • Transmission: the movement of electrochemical energy from sensory receptors to the brain for interpreting.

Attention + Memory

• Attention: The mental capacity to concentrate on specific stimuli while ignoring other stimuli. It can also be voluntary and involuntary at times.
• Memory: The cognitive function used where information and past experiences are actively processed, stored and received.
  • Process of Memory: Storage is defined as the retention of information within the stores of memory