Field Methods in Psychology

Meta-analysis

A statistical technique used to combine and analyze results from multiple studies on a particular topic.

Key Features of Meta-analysis

• Pooling Data

• Consistency and Variability

• Subgroup Analysis and Sensitivity Analysis

• Publication Bias

• Forest plots and Funnel Plots

Pooling Data

Increases statistical power and improve estiates of the effect size.

Consistency and Variability

They help in identify consistent patterns and sources of variability. They also assess the robustness of outcomes across various study designs, populations, or contexts.

Subgroup Analysis and Sensitivity Analysis

Meta-analyses often explore different subgroups to determine if effects differ among them. Sensitivity analyses test the stability of results by considering different assumptions or excluding certain studies.

Publication Bias

Where studies with positive results are more likely to be published than those with negative or inconclusive results.

Forest Plots and Funnel Plots

Graphical tools used in meta-analyses

Forest plots

Show the individual effect sizes and confidence intervals of studies.

Funnel plot

Help assesspublication bias by illustrating the distribution of studies' effect sizes and sample sizes

Steps in Conducting a Meta-Analysis

1. Research Question and Inclusion Criteria

2. Literarture Search

3. Data Extraction

4. Statistical Analysis

5. Assessment of Bias and Heterogeneity

6. Interpretation of Results

Importance of Meta-Analysis

• Synthesizing research evidence

• Guiding clinical practices

• Informing policy decisions

• Suggesting future research direction

Sensitivity analyses

Test the stability of results by considering different assumptions or excluding certain studies.

Neuroimaging and other Psychophysiological Methods

Encompass a broad range of techniques used to study the brain and nervous system's structure, function, and activity. These methods allow researchers to visualize brain regions, track neural activity, and understand brain-behavior relationships.

Neuroimaging Methods

Involves various techniques that create images of the brain. These methods can be categorized into structural and functional neuroimaging.

Types of Structural Neuroimaging

• Magnetic Resonance Imaging (MRI)

• Computed Tomography (CT)

Magnetic Resonance Imaging (MRI)

This method uses magnetic fields and radio waves to create detailed images of brain structures. It's commonly used to detect abnormalities, measure brain volume, and examine brain development over time.

Computed Tomography (CT)

CT scans use X-rays to create cross-sectional images of the brain, providing less detailed images than MRI but often used in emergency settings to quickly detect injuries or abnormalities like tumors.

Functional Neuroimaging

• Functional Magnetic Resonance Imaging (fMRI)

• Positron Emission Tomography (PET)

• Single Photon Emission Computed Tomography (SPECT)

Functional Magnetic Resonance Imaging (fMRI)

Measures changes in blood flow to different brain regions, indicating neural activity, it’s widely used to study brain function, identify active regions during specific tasks, and map brain connectivity.

Positron Emission Tomography (PET)

PET scans use radioactive tracers to visualize metabolic activity in the brain, allowing researchers to track neurotransmitter function and brain metabolism.

Single Photon Emission Computed Tomography (SPECT)

Similar to PET, SPECT uses radioactive tracers but has lower resolution. It's used to study brain perfusion and diagnose brain disorders.

Other Psychophysiological Methods

• Electroenecephalography (EEG)

• Magnetoencephalography (MEG)

• Electromyography (EMG)

• Galvanic Skin Response (GSR)

Electroencephalography (EEG)

EEG records electrical activity in the brain using electrodes placed on the scalp. It offers high temporal resolution, making it ideal for studying brain responses to stimuli and diagnosing conditions like epilepsy.

Magnetoencephalography (MEG)

MEG measures magnetic fields produced by neural activity. It has high spatial and temporal resolution, allowing detailed studies of brain function.

Electromyography (EMG)

EMG records electrical activity in muscles, useful for studying muscle activation and nervous system control of muscle function.

Galvanic Skin Response (GSR)

GSR measures skin conductance changes due to sweat gland activity, often used to study emotional responses and stress.

Application and Importance

• Research, helps researchers understand brain structure, function, and connectivity.

• Clinical, aids in diagnosing and treating neurological and psychiatric conditions.

• Therapeutic Developement, for therapy development.

Challenges and Limitations

• Resolution and Accuracy, techniques may lack spatial accuracy.

• Cost and Accessibility, not all facilities are accessible to advanced technologies like fMRI or MEG.

• Ethical Concerns, may raise ethical questions about privacy and consent.

Quasi-Experiment

A research design used in various fields, including social sciences, education, psychology, and medicine, to evaluate the impact of an intervention or treatment without the full control associated with a true experiment.

Key Characteristics

• Lack of Random Assignment, it don't employ randomization, meaning participants are assigned to groups based on other criteria, such as pre-existing conditions, natural groups, or other characteristics.

• Control and Experimental Groups, while quasi-experiments may have distinct control and experimental groups, their formation isn't randomized. This can lead to group differences, impacting the experiment's internal validity.

• Flexibility, allowing researchers to study interventions in real-world settings where randomization is impractical or impossible.

Type of Quasi-Experiments

1. Non-equivalent Groups Design: In this setup, there are distinct groups, but they're not randomly assigned. Researchers may try to control for group differences through statistical methods like matching or covariate analysis.

2. Interrupted Time Series Design: This design tracks a specific outcome over time, introducing an intervention, then monitoring changes post-intervention. This design is useful for assessing trends before and after the intervention.

3. Regression Discontinuity Design: Here, participants are assigned to groups based on a cutoff score on a pre-assessment. Those above a certain threshold might receive the treatment, and those below do not.

4. Pre-test/Post-test Design: This involves measuring outcomes before and after an intervention. It's used when there's a single group, allowing researchers to assess changes over time.

Strengths

• Practicality

• Ethical Considerations

• External Validity

Limitations

• Internal Validity

• Confounding Variables

• Less Control

Application

• Education

• Public Health

• Psychology

• Social Sciences

Twin Study

A type of research design used primarily in genetics, psychology, and medical studies to examine the influence of genetic and environmental factors on various traits, behaviors, or conditions.

Key Characteristics

• Monozygotic (MZ) Twins

• Dizygotic (DZ) Twins

• Control for Genetic Variability

• Environment and Shared Experiences

Design of Twin Studies

• Classical Twin Study

• Twin Registries

• Longitudinal and Cross-Sectional Approaches

Types of Research Questions Addressed by Twin Studies

• Heritability: Twin studies can estimate the heritability of traits, providing insights into the proportion of trait variance due to genetic factors.

• Gene-Environment Interaction: Researchers can investigate how genetics and environment interact to influence outcomes, considering both shared and non-shared experiences.

• Behavioral Genetics: Twin studies help researchers understand the genetic and environmental factors that contribute to behaviors and mental health conditions.

Applications

• Psychology

• Psychiatry

• Behavioral Genetics

• Medical Research

Retrospective and Prospective Cohorot Study

A cohort study is a type of observational research design where a group of individuals (the "cohort") is followed over time to examine the relationship between a specific exposure and the development of a particular outcome, such as a disease or a condition.

Retrospective Cohort Study

Researchers look back in time to identify a cohort based on historical data and follow their outcomes up to the present or another specified time point in the past.

Characteristics

• Data Source: Uses existing data sources, such as medical records, insurance claims, or employment histories.

• Exposure: Identified based on past events.

• Outcome Measurement: Researchers follow outcomes from the point of exposure to a given endpoint, usually in the past.

• Study Design: Observational; participants are not assigned to groups, and exposure status is not manipulated.

Advantage

• Efficiency: Retrospective studies can be quicker and less expensive because they use pre-existing data.

• Study of Rare Conditions:Can be useful for studying rare conditions due to the large amount of data available.

• Long Follow-up Periods: The use of historical data allows for longer follow-up times without waiting for future events.

Disadvantage

• Bias and Confounding: Retrospective studies are more susceptible to bias (e.g., selection bias, recall bias) and confounding due to reliance on existing data.

• Inconsistencies in Data: Data may be incomplete or inaccurate.

• Limited Control: Researchers have limited control over how data was collected and recorded.

Prospective Cohort Study

A prospective cohort study, in contrast, starts by identifying a cohort in the present and follows them forward over time to assess the relationship between an exposure and an outcome.

Characteristics

• Data Source

• Study Description

• Exposure

• Outcome Measurements

Advantages

• Control over data collection

• Reduced Bias

• Time-Related Events

Disadvantages

• Cost and time

• Droupout race

• Sanple Sizes

Applications

• Epidemiological researcg and public help.

Research Involving Human Participants and Animal Subjects

The guidelines, ethics, and regulations surrounding scientific studies involving living beings.

Ethical Consideration

1. Informed Consent: : Participants must be informed about the research's purpose, procedures, risks, and benefits. They should provide voluntary consent to participate.

2. Confidentiality and Privacy: Researchers must ensure that participants' personal information is protected and that their privacy is maintained throughout the study.

3. Beneficence: Researchers must ensure that the research has potential benefits and that risks to participants are minimized.

4. Justice: The selection of participants must be fair, avoiding exploitation or discrimination.

Regulatory Bodies and Guidelines

• Institutional Review Boards (IRBs)

• Institutional Animal Care and Use Committees (IACUCs)

• The Declaration of Helsinki

• The Belmont Report

• The Animal Welfare Act

Research Practices

1. Ethical Review and Approval s (IRBs for human research, IACUCs for animal research).

2. Risk Assessment, identify potential risks to participants or animals and develop plans to mitigate these risks.

3. Training and Education, researchers must undergo training in ethical research practices and understand the ethical considerations involved in their studies

4. Monitory and ovbersight, ongoing monitoring of research projects ensures compliance with ethical guidelines and addresses any emerging risks or issues

Implications of Responsibilities

• Accountability: Researchers are accountable for the ethical treatment of participants and animals, as well as for compliance with regulations.

• Transparency: Researchers must be transparent about their methods, procedures, and outcomes, allowing for peer review and public scrutiny.

• Public Trust: Upholding ethical standards in research builds public trust, which is essential for the success of scientific research and its acceptance by the broader community

Institutional Review Boards (IRBs)

IRBs review and approve research proposals involving human participants to ensure ethical compliance. They evaluate the risks and benefits of the study and oversee informed consent.

Institutional Animal Care and Use Committees (IACUCs)

IACUCs oversee research involving animal subjects, ensuring humane treatment and adherence to animal welfare laws.

The Declaration of Helsinki

This set of ethical principles, adopted by the World Medical Association, guides research involving human subjects in the medical field.

The Belmont Report

This document outlines ethical principles and guidelines for human subjects' protection, focusing on respect for persons, beneficence, and justice.

The Animal Welfare Act

A U.S. law that regulates the treatment of animals in research and mandates standards for their care.

Ethical Considerations

The core of research involving human participants and animal subjects

Classical Twin Study

This design compares the similarity of MZ twins to DZ twins for a given trait. If MZ twins are more similar than DZ twins, it suggests a genetic influence on the trait.

Twin Registries

Researchers often use twin registries to identify twins for large-scale studies. These registries contain detailed information on twins' demographics, health, and other characteristics.

Longitudinal and Cross-Sectional Approaches

Twin studies can be longitudinal, following twins over time to study changes, or cross-sectional, examining twins at a specific point.

Monozygotic (MZ) Twins

These are identical twins that originate from a single fertilized egg, sharing 100% of their genetic material.

Dizygotic (DZ) Twins

These are fraternal twins that come from two separate eggs fertilized by two different sperm cells, sharing about 50% of their genetic material, similar to regular siblings.

Control for Genetic Variability

By comparing MZ twins with DZ twins, researchers can determine the extent to which a trait or behavior is influenced by genetics versus environmental factors.

Environment and Shared Experiences

Twin studies consider shared environmental factors, such as family upbringing and education, and non-shared factors, like different peer groups or life experiences.