psychology, stage 1 sace test revision:

1. The Biopsychosocial Model: Looking at the Whole Person

• What is it? This model says that to understand someone, we need to look at three big areas of their life: their body, their mind, and their world. It's like a three-piece puzzle!

  • Biological Factors (Body): This is all about your physical self. Think:

    • Your genes (what you inherit from your parents).

    • Your brain and nervous system.

    • Your hormones (chemical messengers in your body).

    • Any illnesses or injuries.

    • Example: Someone might feel sad (psychological) because they have a hormonal imbalance (biological).

  • Psychological Factors (Mind): This is all about your thoughts, feelings, and behaviors. Think:

    • How you think about things (optimistic or pessimistic).

    • Your emotions (happy, sad, angry).

    • Your personality (shy, outgoing).

    • How you cope with stress.

    • Example: Someone might avoid social situations (behavior) because they have anxiety (psychological).

  • Sociocultural Factors (World): This is all about your environment and how it affects you. Think:

    • Your family and friends.

    • Your culture and beliefs.

    • Your school or work.

    • Your social and economic status.

    • Example: Someone might feel pressure to succeed (psychological) because of their cultural background (sociocultural).

• Analyzing Behavior: When we look at someone's behavior, we don't just look at one thing. We try to see how all three factors work together. It's like a recipe – all the ingredients matter!

2. Ethical Practices in Psychological Research: Playing Fair

• What are they? These are rules that psychologists follow to make sure their research is safe and respectful.

• How to uphold them:

  • Informed Consent: People need to know what they're getting into before they agree to be in a study.

  • Confidentiality: Keeping people's information private.

  • Voluntary Participation: People should be able to say no.

  • Withdrawal Rights: People can leave a study at any time.

  • Debriefing: Telling people about the study after it's done.

  • No Harm: Not hurting people physically or emotionally.

3. Inquiry Questions and Hypotheses: Asking and Guessing

• Inquiry Question: This is a question you want to answer with your research. It's like asking "I wonder if...?"

  • Example: "Does eating breakfast improve school performance?"

• Hypothesis: This is an educated guess about the answer to your inquiry question. It's like saying "I think..."

  • Specific and Directional: It says exactly what you expect to happen.

    • Example: "Students who eat breakfast will have higher test scores than students who don't."

4. Variables: The Things We Measure

• Independent Variable (IV): This is the thing you change or control. It's like the ingredient you're adding to a recipe.

  • Example: Eating breakfast (yes or no).

• Dependent Variable (DV): This is the thing you measure to see if the IV had an effect. It's like the taste of the cake.

  • Example: Test scores.

• Constant Variable: Things that stay the same for everyone in the research.

• Confounding Variable: A variable that you did not plan for that changes the DV.

• Extraneous Variable: Any variable other than the IV that might affect the DV.

  • Difference: Extraneous variables can be controlled, but confounding variables are out of your control.

  • Types and Reduction: time of day, noise, and people's moods are examples. Reduce these by keeping the test location quiet, and keeping the test at the same time for all participants.

5. Quantitative and Qualitative Research: Numbers and Words

• Quantitative Research: Uses numbers and statistics to measure things. It's like counting how many apples you have.

  • Example: Surveys with multiple-choice questions.

• Qualitative Research: Uses words and descriptions to explore ideas. It's like describing the taste of an apple.

  • Example: Interviews or focus groups.

6. Experimental and Observational Designs: Testing and Watching

• Experimental Design:

  • You control the IV.

  • You can find cause-and-effect relationships (one thing causes another).

  • Random allocation of participants.

  • Advantages: You can prove cause and effect.

  • Disadvantages: It can be hard to do in real-world settings.

• Observational Design:

  • You watch what happens naturally.

  • Pre-existing groups.

  • You can find relationships between variables (correlation).

  • Advantages: It's more like real life.

  • Disadvantages: You can't prove cause and effect.

• Differences: Experimental designs manipulate the IV, observational designs watch pre-existing IV's. Experimental designs can show cause and effect, observational designs can only show relationships.

7. Focus Groups and the Delphi Technique: Group Discussions

• Focus Group: A small group of people discuss a topic.

  • Advantages: You get rich, detailed information.

  • Disadvantages: It can be hard to generalize the results.

• Delphi Technique: A group of experts answer questions anonymously over several rounds.

  • Advantages: It gathers expert opinions without group pressure.

  • Disadvantages: It can be time-consuming.

• Differences: Focus groups are face-to-face, the Delphi technique is anonymous and uses multiple rounds.

8. Data: What We Collect

• Quantitative Data: Numbers.

  • Advantages: Easy to analyze.

  • Disadvantages: Can miss important details.

• Qualitative Data: Words.

  • Advantages: Rich and detailed.

  • Disadvantages: Harder to analyze.

• Objective Data: Facts that can be measured.

  • Example: Heart rate.

• Subjective Data: Opinions and feelings.

  • Example: How happy someone feels.

• Measures of Psychological Response:

  • Objective Quantitative: Heart rate, brain waves.

  • Subjective Quantitative: Rating scales (1-10).

  • Qualitative: Interviews, observations.

• Mean and Median:

  • Mean: The average (add up all the numbers and divide).

  • Median: The middle number.

• Standard Deviation: How spread out the data is.

  • High standard deviation means the data is very spread out.

  • Low standard deviation means the data is close together.

• Content Analysis: A way to analyze qualitative data by looking for themes and patterns.

9. Samples and Populations: Who We Study

• Population: The whole group you're interested in.

• Sample: A smaller group from the population that you study.

• Sample Characteristics: Things like age, gender, and background.

• Unrepresentative Sample: A sample that doesn't reflect the population.

  • It can make your conclusions wrong.

10. Reliability and Validity: Trusting Our Results

• Reliability: Getting the same results over and over.

• Internal Validity: Making sure the IV is really what caused the DV.

• External Validity: Being able to apply your results to the real world.

  • These can be impacted by confounding variables, unrepresentative samples, and bad experimental design.