Psychology Chapter 1-3 PDF
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This document introduces different perspectives in psychology, including psychoanalytic, behaviorist, and humanistic approaches. It explores key figures, theories, and methods related to these perspectives. It also provides an overview of the scientific method in psychology.
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1.1.01 The Psychoanalytic Perspective A number of psychological theories have been developed to explain phenomena related to the mind and behavior. One of the most influential figures in the history of psychology, [Sigmund Freud](javascript:void(0)), was an Austrian physician. Around the turn of...
1.1.01 The Psychoanalytic Perspective A number of psychological theories have been developed to explain phenomena related to the mind and behavior. One of the most influential figures in the history of psychology, [Sigmund Freud](javascript:void(0)), was an Austrian physician. Around the turn of the twentieth century, Freud developed the **psychoanalytic approach** (or perspective) in an attempt to treat his patients who sought help for their psychological problems. Through his work with these patients, he advanced the notion of the **unconscious mind**, lying just beyond conscious awareness. Freud\'s theories focused on how unconscious factors (eg, drives, conflicts stemming from childhood) impact human development and behavior. Although controversial at times (eg, for its focus on sex and aggression), Freud\'s psychoanalytic approach continues to influence psychology to this day; many of his followers (ie, \"Neo-Freudians\" such as Carl Jung and Alfred Adler) developed influential theories of their own. The application of the psychoanalytic (or psychodynamic) perspective to personality is covered in Lesson 26.1 **The Behaviorist Perspective** 1.2.01 The Behaviorist Perspective In contrast to psychoanalytic psychology\'s focus on the conscious and unconscious aspects of the mind (Lesson 1.1), the **behaviorist perspective** emerged in the early 1900s to emphasize the scientific study of observable actions. In the 1920s, [John Watson](javascript:void(0)), considered by many to be the founder of behaviorism, built off the work of [Ivan Pavlov](javascript:void(0)) (Lesson 17.1) and studied classically conditioned fear. In the 1930s, [B.F.](javascript:void(0)) [Skinner](javascript:void(0)) studied the impact of reinforcement and punishment on behavior in his studies on operant conditioning (Lesson 17.2). These early behaviorists dismissed the study of mental processes to focus solely on overt, observable behavior. Although few psychologists would advocate for this extreme stance today, the behaviorist perspective continues to play a critical role in understanding learning (eg, Chapter 17), personality, and the development and treatment of psychological disorders (Lesson 31.1) **The Humanistic Perspective** 1.3.01 The Humanistic Perspective In the 1960s, the **humanistic perspective** arose in response to the psychoanalytic (Lesson 1.1) and behaviorist (Lesson 1.2) approaches, which were thought to be too pessimistic and mechanistic, respectively. Instead, humanistic psychology takes a more holistic approach to the individual, emphasizing the higher aspects of human nature. For example, **Abraham Maslow** proposed that humans are motivated to achieve needs in a hierarchy of importance, and at the highest level, self-actualization (ie, fulfilling one\'s greatest potential) is possible. Another humanistic psychologist, **Carl Rogers**, emphasized the concept of unconditional positive regard (ie, acceptance and support, regardless of someone\'s behavior). The humanistic perspective continues to serve an important role in psychology, from understanding personality (Lesson 26.2) to understanding and treating psychological disorders (Lesson 31.1 Enter word / phrase to search UBook text Automatic ZoomActual SizePage Width100%50%75%100%125%150%200%300%400% Chapter 2: Research in Psychology Lesson 2.1 **The Scientific Method** 2.1.01 Hypotheses Psychology is the scientific study of mind and behavior. (Note: this chapter covers research in psychology, although many of the terms are also relevant to sociology. See Chapter 33 for more information on research in sociology.) A scientific **hypothesis** is a testable explanation for a phenomenon. The **alternative hypothesis** is based on prior evidence and assumes that a significant relationship or difference exists between variables (and often predicts the nature of that relationship or difference). For example, if a researcher developed a novel intervention for social anxiety (see Concept 29.1.01) and wanted to test if it was more effective in lowering social anxiety than an educational program (see placebo in Concept 2.3.01), the alternative hypothesis could be that the group that received the novel intervention will have significantly lower levels of social anxiety than the group that received the education. The inverse of the alternative hypothesis, the **null hypothesis**, states that there is no significant difference or relationship between the variables. In this example, the null hypothesis would be that there is no significant difference in levels of social anxiety between the group that received the novel intervention and the group that received the education. 2.1.02 Variables In an experiment (see Concept 2.2.02), the **independent variable** is manipulated by the experimenter to determine if changes to the independent variable impact the **dependent variable**, which is the outcome that is measured. Using the example in Concept 2.1.01, if a researcher wanted to test whether participation in a novel intervention for social anxiety lowers levels of social anxiety, the independent variable would be participation in the novel intervention, and the dependent variable would be the level of social anxiety (ie, the measured outcome). **Types of Studies** 2.2.01 Correlational Studies **Correlational studies** describe relationships between variables but cannot demonstrate cause and effect because no variables are being manipulated. In these research designs, the association between predictor variables and outcome variables may be assessed, although specific causal relationships cannot be determined. For example, in a study that examines the relationship between the number of close friendships (ie, predictor variable) and the number of serious health problems (ie, outcome variable), researchers would not change the participants\' number of close friendships to examine the impact on health. Therefore, this is a correlational research design because it does not involve the manipulation of a variable and cannot demonstrate cause and effect. 2.2.02 Experimental Studies In contrast to correlational research designs (Concept 2.2.01), in an **experimental study** (also called an experiment), the researcher manipulates the independent variable (Concept 2.1.02) (eg, participation in a novel intervention for social anxiety) to determine its impact on the dependent variable, or outcome (eg, level of social anxiety). Because changes to the dependent variable are assumed to be caused by the independent variable, experiments can demonstrate a cause-and-effect relationship between variable **Results and Conclusions** 2.3.01 Placebos A variety of criteria are used to judge the extent to which scientific results can be trusted or believed (ie, are credible). The overall study design is one such criterion that must be examined. One component used in some experimental designs is a **placebo**, an inactive substance or sham procedure that serves as a comparison to the intervention of interest. Although placebo groups are often helpful in assessing the true benefit of a treatment, a placebo group may be unethical if a sham procedure could result in harm (eg, sham surgery). The **placebo effect** occurs when the use or application of an inactive substance or sham procedure (ie, a placebo) corresponds with a change in the recipient, often due to their expectations concerning the intervention. For example, a research participant who is given a sugar pill (placebo) instead of a new medicine being tested experiences an improvement of symptoms due to their expectation that the treatment will work. 2.3.02 Reliability and Validity As Concept 2.3.01 states, scientific findings must be evaluated for their credibility (ie, the extent to which they can be trusted or believed). Both the overall study design and particular measures (eg, surveys) used in a study must be examined for [reliability and validity](javascript:void(0)). **Reliability** refers to the extent to which an experiment or measure can consistently produce similar results (eg, a test produces a similar score for someone who takes it twice). In contrast, **validity** refers to the accuracy of a study or measure. **Internal validity** refers to the extent to which a measure or experiment produces a true result (eg, measures what it was intended to). **External validity**, also known as **generalizability**, is the extent to which study results can be applied outside the laboratory to real-life situations **Ethical Considerations** 2.4.01 Informed Consent Ethics are concerned with moral principles that guide behavior. **Ethical** **research** protects vulnerable populations, minimizes risks while maximizing benefits, maintains confidentiality, and respects the rights and dignity of participants. In the United States, ethics committees must approve research on human and animal subjects. One ethical research practice involves seeking informed consent from human research participants. **Informed consent** (Figure 2.1) is the process of instructing potential research participants about the study, its risks, and their rights (eg, to withdraw, to have their information protected) so they can voluntarily decide to participate **Descriptive Statistics** 3.1.01 Descriptive Statistics To analyze scientific data, researchers can use descriptive and/or inferential statistics (Lesson 3.2 covers inferential statistics). (Note: both psychologists and sociologists use descriptive and inferential statistics.) **Descriptive statistics,** which describe a dataset, include **measures of central tendency** (ie, mean, median, mode) and variation (eg, range): **Mean** refers to the average data point. The mean represents the sum of the data points divided by the number of data points. **Median** refers to the middle value when data points are arranged in numerical order. The median is the midpoint at which half the data points are above and half are below. If there is an even number of data points, the two middle data points are averaged. **Mode** refers to the most frequently occurring data points. **Range** refers to the difference between the lowest and highest data points **Inferential Statistics** 3.2.01 Correlations **Inferential statistics** are used to draw conclusions that reach beyond the sample\'s dataset. The Pearson correlation coefficient *r* can be used as an inferential statistic; the **correlation coefficient *r*** describes the linear relationship between two variables (Figure 3.1). The value of *r* ranges from −1 to 1 and describes the direction (sign) and strength of an association. The sign of the *r*-value indicates a positive or negative association, and the closer *r* is to its margins (−1 or 1), the stronger the relationship. A positive correlation (*r* \> 0) means both variables increase or decrease together. A negative correlation (*r* \< 0) means that as one variable increases, the other decreases. Lastly, a lack of linear relationship between variables is called a zero correlation. **Figure 3.1** Correlation coefficient. Because a correlation describes relationships, it does not imply causation; an *r*-value does not give information about the causal nature of changes in either variable.