Field Methods in Psychology Notes

FIELD METHODS IN PSYCHOLOGY 𐙚˙⋆.˚

Ø  Study of behavior and mental processes in natural settings using observational

techniques, surveys, and other real-world data collection methods.

Research Methods in Psychology

1.      Correlational Methods

Purpose: Examine the relationship between two or more variables to identify associations without implying causation.

Strengths:

·         Identifies Relationships: Useful for discovering associations.

·         Natural Settings: Enhances ecological validity by conducting studies in real- world environments.

·         Ethical Flexibility: Suitable for studying variables that cannot be manipulated.

Limitations:

·         No Causation: Cannot establish cause- and-effect relationships.

·         Confounding Variables: Unseen variables may influence results.

·         Directionality Problem: Difficult to

determine which variable influences the other.

2.      Descriptive Methods

Purpose: Observe and detail behaviors or phenomena as they naturally occur without influencing the variables.

Strengths:

·         Detailed Observation: Provides rich, qualitative data.

·         Versatility: Applicable in various settings for exploratory research.

·         Non-Intrusive: Does not manipulate

variables, reducing alteration of behavior.

Limitations:

·         Lack of Control: Cannot isolate factors influencing behavior.

·         Subjectivity: Data interpretation may be biased.

·         Generalizability Issues: Findings may not apply to other contexts.

3.      Experimental Methods

Purpose: Manipulate variables to determine cause-and-effect relationships in controlled environments.

Strengths:

·         Causal Relationships: Establishes cause- and-effect through controlled manipulation.

·         Control: Reduces the influence of extraneous factors.

·         Replication: Enhances reliability through replicable methods.

Limitations:

·         Artificial Settings: May not reflect real- world conditions.

·         Ethical Constraints: Limits on variable manipulation for ethical reasons.

·         Limited Scope: Focuses on specific variables, potentially missing broader context.

Ethical Considerations in Field Research

1.      Informed Consent

Cultural Sensitivity: Use local dialects and

simple language, considering literacy levels and cultural norms.

Voluntary Participation: Emphasize that participation is entirely voluntary.

Examples: Explaining research in local dialects like Tagalog, Cebuano, or Ilocano.

2.      Respect for Local Customs

Cultural Norms: Avoid disrespectful inquiries; involve community leaders for approval.

Community Involvement: Engage with

stakeholders through community meetings. Examples: Acknowledging "utang na loob" (debt of gratitude) and organizing "pulong-pulong"

(community meetings).

3.      Confidentiality and Privacy Anonymity Concerns: Use pseudonyms or aggregate data in small communities.

Data Sensitivity: Handle sensitive topics carefully and ensure data is not misused. Examples: Respecting "amor propio" (self- respect) and avoiding "hiya" (shame).

4.      Power Dynamics

Avoiding Exploitation: Be mindful of power imbalances, ensuring participants are not

exploited.

Reciprocity: Ensure research benefits the community as well.

Examples: Avoiding social or economic pressure to participate; adhering to "bayanihan"

(community spirit).

5.      Cultural Adaptation of Research Methods Methodological Flexibility: Adapt tools and methods to fit cultural contexts.

Culturally Informed Interpretation: Avoid ethnocentric biases and misinterpretations.

Examples: Using "pakikipagkwentuhan" (storytelling) for culturally familiar data collection.

Quantitative and Qualitative Methods Quantitative Methods

·         Data Collection: Uses structured tools like

surveys, questionnaires, and tests.

·         Data Type: Numerical data for statistical analysis.

·         Objective: Determine relationships, causality, and trends by controlling variables.

·         Analysis: Statistical techniques like correlation, regression, t-tests, ANOVA.

·         Strengths:

o    Precise, quantifiable evidence.

o    Easier to replicate and validate.

o    Facilitates comparison and statistical analysis.

·         Weaknesses:

o    May oversimplify complex phenomena.

o    Lacks contextual depth.

o    Potential for bias if the sample is not representative.

Qualitative Methods

·         Data Collection: Uses unstructured

techniques like interviews, focus groups, and observations.

·         Data Type: Non-numerical data analyzed for themes and patterns.

·         Objective: Gain a deep understanding of experiences, processes, and cultural contexts.

·         Analysis: Thematic analysis, content analysis, narrative analysis.

·         Strengths:

o    Captures complexity and richness of experiences.

o    Provides deep understanding of context and meaning.

o    Flexible and adaptable.

·         Weaknesses:

o    More difficult to replicate due to subjectivity.

o    Time-consuming and resource- intensive.

o    Harder to generalize findings.

Comparison of Quantitative and Qualitative Methods

·         Nature of Data: Quantitative is numerical; qualitative is descriptive.

·         Purpose: Quantitative focuses on

measurement; qualitative on understanding meanings.

·         Sample Size: Quantitative typically involves larger samples; qualitative involves smaller, focused samples.

·         Outcome: Quantitative research provides generalizable results; qualitative research offers in-depth insights.

Statistical Methods in Psychological Research Descriptive Statistics

·         Measures:

o    Mean, Median, Mode: Indicate central tendency.

o    Standard Deviation, Variance: Measure data dispersion.

o    Frequency Distribution: Shows how often each value occurs.

·         Purpose: Offers a snapshot of the data to understand distribution, central tendencies, and variability.

Inferential Statistics

·         Techniques:

o    T-tests: Compare the means of two groups.

o    ANOVA: Compares means across three or more groups.

o    Chi-square Test: Examines

relationships between categorical variables.

o    Correlation: Measures the strength and direction of the relationship

between variables.

o    Regression Analysis: Explores

relationships between variables for prediction.

·         Interpretation: Determines whether observed effects are genuine or due to chance using p-values and confidence intervals.

Reliability and Validity

·         Reliability:

o    Cronbach’s Alpha: Measures internal consistency.

o    Test-Retest Reliability: Assesses stability over time.

o    Inter-Rater Reliability: Evaluates consistency between raters.

·         Validity:

o    Content Validity: Ensures

comprehensive coverage of the construct.

o    Construct Validity: Assesses if the survey measures the intended

construct.

o    Criterion-Related Validity: Correlates survey results with other established measures.

Survey Design and Psychometric Properties

·         Survey Design Evaluation:

o    Clarity: Questions should be clear and easy to understand.

o    Length: Must be concise to avoid fatigue but comprehensive enough to cover relevant aspects.

o    Sampling Method: Random sampling for generalizability, stratified for representation.

o    Pre-testing: Pilot studies to identify potential issues.

·         Psychometric Properties:

o    Internal Consistency: Measures if survey items assess the same

construct (Cronbach’s Alpha).

o    Dimensionality: Explores the factor structure using EFA and CFA.

o    Item Response Theory (IRT):

Models the probability of

responses based on item properties and participant traits.

Qualitative Interview Approaches Structured Interviews

·         Characteristics: Predetermined questions; limited flexibility.

·         Effectiveness: Suitable for large studies requiring comparability.

·         Limitations: Lacks depth and limits exploration of participant responses.

Semi-Structured Interviews

·         Characteristics: Guided flexibility; allows follow-up questions.

·         Effectiveness: Balances structure with depth for a range of studies.

·         Limitations: Variability in how interviews are conducted; time-consuming.

Unstructured Interviews

·         Characteristics: Conversational, open- ended; participant-led.

·         Effectiveness: Suitable for exploratory research to understand complex

experiences.

·         Limitations: Hard to compare responses; potential for bias.

Focus Group Interviews

·         Characteristics: Group setting with

interaction; generates collective insights.

·         Effectiveness: Efficient for exploring social dynamics and group norms.

·         Limitations: Risk of groupthink, logistical challenges, and dominant personalities.

Field Research Project Design

  Phase 1: Descriptive Method:

·         Objective: Collect baseline data using surveys, interviews, and observations.

·         Outcome: Develop a descriptive profile of key variables and trends.

  Phase 2: Correlational Method:

·         Objective: Analyze relationships using statistical methods.

·         Outcome: Identify significant correlations for further research.

  Phase 3: Experimental Method:

·         Objective: Implement an intervention to test causal relationships.

·         Outcome: Assess the impact of interventions.

Mixed Methods in Research Approaches:

·         Explanatory Sequential Design: Start with quantitative data, followed by

qualitative exploration.

·         Exploratory Sequential Design: Begin with qualitative data to develop a

quantitative instrument.

·         Convergent Parallel Design:

Simultaneous collection of both data types for comparison.

·         Embedded Design: One method as

primary with another providing additional insights.

Benefits:

·         Comprehensive Understanding:

Explores breadth (quantitative) and depth (qualitative).

·         Triangulation: Validates findings with multiple data sources.

·         Contextualization: Provides context and meaning to numerical data.

Analyzing Focus Group Discussions (FGDs)

1.      Thematic Analysis: Identifying,

analyzing, and reporting themes within the data.

2.      Content Analysis: Quantifying the

presence of certain words, themes, or concepts.

Creating a Comprehensive Qualitative Research Plan

1.      Research Topic Selection: Choose a topic within social psychology for mixed methods exploration.

2.      Research Questions and Hypotheses:

Develop qualitative and quantitative research questions.

3.      Study Design: Select a mixed methods design like explanatory sequential or convergent parallel.

4.      Participant Recruitment: Use a

combination of purposive and random sampling for diversity.

5.      Data Collection: Use quantitative

instruments like surveys, then qualitative methods like interviews or focus groups.

6.      Data Analysis:

·         Quantitative: Use statistical methods to test hypotheses.

·         Qualitative: Apply thematic, content, or discourse analysis.

7.      Integration and Interpretation: Combine findings to gain a comprehensive

understanding.

8.      Reporting: Write a research report

covering introduction, methods, results, and discussion.

9.      Presentation: Present findings to peers and consider optional publication.

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3.      Discourse Analysis: Examining language

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use and underlying power dynamics in conversations.

4.      Grounded Theory: Generating a theory directly from the data through open, axial, and selective coding.

5.      Narrative Analysis: Focusing on the stories participants tell to understand their identities and experiences.

/    づ♡ good luck!!