CH-4 Research: Its Role and Methods – Abnormal Child and Adolescent Psychology : Exam Guide

Chapter 4 Research: Its Role and Methods TRUE OR FALSE 1. Science comes from the Latin word for “seeker”. Answer: False 2. Random selection enhances the representativeness of a sample. Answer: True 3. An operational definition of a behavior refers to the procedures or operations employed to define the behavior. Answer: True 4. Interobserver reliability of a measured behavior refers to the degree to which observers believe that the measure is a true and accurate indicator of the behavior. Answer: False 5. The term external validity refers to the degree to which a research result can be generalized to populations and situations different from those with which the research was conducted. Answer: True 6. The general purpose of a descriptive study is to portray a phenomenon of interest. Answer: True 7. Randomized experiments come the closest to establishing cause and effect relationships. Answer: True 8. If a researcher obtained a Pearson r value of –.02, it is evident that some error has been made in measurement or calculation. Answer: False 9. A Pearson r correlation coefficient of +.44 is stronger than a coefficient of –.86. Answer: False 10. In the experiment, the purpose of random assignment of participants into groups is to ensure that the characteristics of the participants in one group are about the same as the characteristics of the participants in other groups. Answer: True 11. Efforts to increase internal validity may decrease external validity because more stringent control may result in research settings that are dissimilar to the "real world." Answer: True 12. A weakness of single-subject reversal designs is that ethical considerations may preclude the reversal phase in intervention studies in which the treatment was effective. Answer: True 13. In retrospective research designs, data are collected about past attributes or experiences of participants. Answer: True 14. The prevalence of a disorder in a population concerns the number of new cases diagnosed in a specific time period. Answer: False 15. An advantage of non-accelerated longitudinal research is that investigators do not need to be concerned about possible cohort effects in interpreting findings. Answer: False 16. Although quantitative and qualitative research strategies differ in many aims and methods, both place high value on objectivity. Answer: False 17. The sole function of Institutional Review Boards in the research process is to determine the scientific soundness of the proposed research. Answer: False 18. When conducting research on children, informed consent is obtained from the child. Answer: False 19. The ethical concept of beneficence requires that benefits to the research participant be maximized. Answer: True MULTIPLE CHOICE 20. When research findings fail to support the hypothesis being tested, A. the study was a waste of time and effort. B. the hypothesis is proven incorrect. C. the theory on which the hypothesis was based may be changed in some way. D. the study must have been poorly designed. Answer: C 21. Why is it valuable to randomly select persons from the population of interest to participate in a research study? A. Participants will feel they have been treated fairly, which can positively affect the study. B. It increases the chance that the participants will represent the population. C. It ensures that the participants will be of the same age. D. It ensures reliability of measurement. Answer: B 22. In a research study of anxiety in adolescents, anxiety was defined as a cut-off score on a questionnaire completed by each adolescent. This definition of anxiety A. is unacceptable because anxiety must be defined by a measure of heart rate or sweating. B. is referred to as the independent variable. C. is referred to as an operational definition of the anxiety. D. is unacceptable because adolescents are unable to provide accurate assessments of their feelings. Answer: C 23. Regarding research studies, validity is to reliability as _________ is to _________. A. cohort effects; correctness B. generalizability; cohort effects C. repeatability; generalizability D. accuracy; consistency Answer: D 24. _________ refers to examining individuals in their “real world” environment. A. Naturalistic observation B. Direct observation C. Observational learning D. Reality testing Answer: A 25. In the Dadds et al. study where researchers compared videotaped family interactions, efforts were made to decrease observer bias by A. ensuring the observers had a thorough understanding of the hypothesis. B. having each category of the videotapes coded by only one observer. C. the observers being “blind” to the clinical status of the children. D. inclusion of a nonclinic group of children. Answer: C 26. Dr. Smalley's research study showed that girls had less self-confidence at age 13 than at age 17. Dr. Smalley was not willing to conclude that the finding would be true for boys. Dr. Smalley thus appeared sensitive to the issue of A. internal validity. B. external validity. C. statistical significance. D. naturalistic observation Answer: B 27. _________ refers to whether the scores on a measure correlate with scores on another acceptable measure of the attribute of interest. A. Content validity B. Construct validity C. Face validity D. Concurrent validity Answer: D 28. One difference between experimental and quasi-experimental studies is A. only experimental studies include manipulation of an independent variable. B. only quasi-experimental studies have researcher control of procedures and extraneous factors. C. participants are not randomly assigned in quasi-experimental studies. D. quasi-experimental studies are not conducted on human participants. Answer: C 29. Which of the following is a strength of the case study method? A. Its ability to describe rare occurrences. B. Its reliance on retrospective data. C. Its high internal validity. D. Its high reliability. Answer: A 30. In the case study on Max reported in the textbook, Max was exhibiting early signs of A. autism. B. childhood schizophrenia. C. school phobia. D. depression. Answer: B 31. In the correlational study of infant attachment and later childhood adjustment noted in your text, the hypothetical data point to a positive correlation between the two variables. Based on the data reported in the text, it can be concluded that A. secure infant attachment causes later childhood adjustment. B. secure infant attachment is not significantly related to later childhood adjustment. C. secure infant attachment predicts later childhood adjustment. D. one cannot tell if attachment impacts later childhood adjustment or not. Answer: C 32. The research about the effects of institutionalization on children reported in the textbook is an example of A. an experiment of nature. B. an experiment of nurture. C. a quasi-experimental design. D. a case study. Answer: A 33. Which is true of the dependent variable in an experiment? A. It is the factor manipulated by the researcher. B. It is given to the experimental group but not to the control group. C. It is some kind of measure. D. It is responsible for changes in the independent variable. Answer: C 34. In an experiment, what is the purpose of the control group? A. to ensure that all participants are treated in the same way B. to ensure that participants represent the population of interest C. to increase internal validity D. to increase external validity Answer: C 35. In the Abecedarian Project (Ramey & Campbell), the authors examine an intervention on at-risk youth. The independent variable in that study was A. an educational program. B. food stamps and other instrumentals provided to the family. C. nutritional supplements given to the children. D. measures of intelligence. Answer: A 36. In the Abecedarian Project (Ramey & Campbell), statistically significant differences were found between children in the experimental group and children in the control group. Which of the following is true? A. These differences were likely due to chance. B. These differences will likely be found again if the study is repeated. C. The differences indicate a cause and effect relationship between the independent and dependent variables. D. The differences must have been due to the intervention. Answer: B 37. The goal of translational research is A. to translate research finding into multiple languages. B. to move evidence-based care into the community. C. to examine the dynamic effect of relationships in a child’s environment. D. to improve the internal validity of studies that examine interventions. Answer: B 38. In the single case ABA design, B refers to the A. baseline period. B. intervention period. C. reversal period. D. reinstatement of the intervention. Answer: B 39. In the single-case ABAB design, what is the main purpose of the first A period? A. to test the effectiveness of the manipulation with another subject B. to test the effectiveness of the manipulation for a second time C. to measure behavior before any manipulation is introduced D. to reintroduce the successful intervention Answer: C 40. Assume that the ABA design has been used to evaluate the effectiveness of a treatment for social skills. Which of the following would be the clearest indicator of the effectiveness of the treatment? A. Social skills are higher in the B period than in the first A period. B. Social skills are lowest in the first A period and equally high in the B and second A period. C. Social skills are higher in the B period than in either of the A periods. D. Social skills are higher in the first A period than in any other period. Answer: C 41. _________ provides information on frequency of disorders in the population and helps the pubic understand the need for treatment and who is at risk for a disorder. A. Experimental design research B. Correlational analyses C. Multiple baseline research D. Epidemiology Answer: D 42. The proportion of persons in a population diagnosed with a disorder during a specific time period is referred to as the _________ of the disorder. A. lifetime prevalence B. prevalence C. incidence D. none of the above Answer: B 43. Which of the following statements about cross-sectional studies is true? A. They trace developmental change with certainty. B. They are especially costly. C. They can reveal differences associated with persons of different ages. D. The same participants are examined at multiple points in time. Answer: C 44. A researcher is investigating motor ability by simultaneously studying three groups of youngsters: ages 6, 10, and 14 years. Which research strategy is the researcher using? A. qualitative B. retrospective C. sequential D. cross-sectional Answer: D 45. A psychologist is investigating the growth of language by studying a group of children from the time they are two years of age to their sixteenth birthdays. Which statement is true about his approach? A. He is using a prospective approach. B. His data may be unreliable due to old records and poor memories. C. He will be unable to chart developmental change. D. He will not need to be concerned about the impact of societal changes while these children mature. Answer: A 46. Assume that on average, 60-year-olds, 40-year-olds, and 20-year-olds perform differently on a psychological test. Assume also that the group differences are due to the different social and educational life experiences available to each generation. The group differences are thus due to A. an experimental effect. B. a developmental effect. C. a triangulation effect. D. a cohort effect. Answer: D 47. Research designs that combine longitudinal and cross-sectional strategies are called A. prospective designs. B. retrospective designs. C. accelerated longitudinal. D. high risk designs. Answer: C 48. Dr. Foster plans to collect data on the prevalence of learning disabilities in all children in New York City during the current school year. She will also collect data on many characteristics of the children, their families, and their environments in order to determine which variables are associated with the occurrence of learning disabilities. This kind of research is referred to as A. a longitudinal research strategy. B. a sequential research strategy. C. epidemiological research. D. mixed design research. Answer: C 49. Which of the following is true for the qualitative research approach? A. Participant observation is often valued. B. More than one variable is usually manipulated during the course of a research study. C. The sample sizes are typically quite large. D. There is a commitment to conducting research in the laboratory rather than in the field because the laboratory more readily lends itself to control. Answer: A 50. In the evaluation of the Parent-to-Parent support program, the qualitative analysis A. served as the only method to assess the program. B. involved thematic categories constructed from telephone interviews. C. ultimately was judged inferior to the quantitative analysis. D. showed that parents of adolescent drug users are extremely stressed. Answer: B 51. The qualitative approach to research, in contrast to the quantitative approach, is more likely to A. employ the experiment as its basic method. B. assume that the personal view of the research participants is of critical importance. C. transform data into numbers and involve statistical analyses. D. depend on well-established procedures to evaluate validity of the findings. Answer: B 52. _________ assumes that participants have the right to control the degree to which personal information can be disclosed. A. Informed consent B. Beneficence C. Non maleficence D. Confidentiality Answer: D BRIEF ESSAY QUESTIONS 53. The book noted 8 major research questions in the field of developmental psychopathology. List and describe 4 of these questions. Answer: Developmental psychopathology explores how biological, psychological, and social factors interact across the lifespan to shape mental health and well-being. Eight major research questions in this field, as noted in various textbooks and research literature, include: 1. Nature vs. Nurture: • This classic question examines the relative contributions of genetic predispositions (nature) and environmental influences (nurture) to the development of psychopathology. • Researchers investigate how genetic vulnerabilities interact with environmental stressors (such as family dynamics, peer relationships, socioeconomic status) to influence the onset, course, and severity of mental health disorders. 2. Risk and Protective Factors: • Researchers seek to identify specific factors that increase (risk factors) or decrease (protective factors) the likelihood of developing psychopathology. • Examples of risk factors include genetic predispositions, adverse childhood experiences (e.g., trauma, abuse), chronic stress, and lack of social support. Protective factors may include strong social connections, positive coping skills, and access to supportive resources. 3. Developmental Trajectories: • This question explores how mental health disorders unfold over time, considering variations in onset, progression, and outcomes across different stages of development. • Researchers examine how early signs of psychopathology manifest in childhood, adolescence, and adulthood, as well as factors that influence the stability or change in symptoms over time. 4. Resilience and Vulnerability: • Researchers investigate why some individuals exhibit resilience—adaptation and successful functioning despite exposure to risk factors—while others show vulnerability to mental health disorders. • Factors contributing to resilience may include genetic factors, positive early relationships, cognitive flexibility, and effective coping strategies. Understanding resilience informs interventions aimed at promoting mental health and reducing risk. These research questions provide a framework for understanding the complex interplay of factors that contribute to mental health outcomes across the lifespan. Addressing these questions helps inform prevention, intervention, and treatment strategies to support individuals' well-being and mental health resilience. 54. What is selection bias? What issues exist when study participants are chosen from clinics and other facilities serving youth with problems? Answer: Selection bias occurs when the participants included in a study are not representative of the broader population from which they are drawn. This bias can arise due to various factors related to how participants are selected or recruited, leading to a distortion in the study's findings and limiting the generalizability of results to the broader population. When study participants are chosen from clinics and other facilities serving youth with problems, several issues can arise: 1. Limited Generalizability: Participants recruited from clinics or specialized facilities may not represent the full spectrum of youth experiencing similar problems in the general population. These individuals may differ in severity of symptoms, access to resources, and other characteristics that affect outcomes. 2. Sampling Bias: The process of recruiting participants from clinics or facilities may systematically exclude certain subgroups of youth who do not access or are not referred to these settings. For example, youth from marginalized communities, those without access to healthcare, or those with less severe symptoms might be underrepresented. 3. Exaggerated Associations: Studies conducted in clinic-based samples may overestimate the strength of associations between risk factors and outcomes because the sample is enriched with individuals already experiencing the outcome or seeking treatment. This can distort the perceived magnitude of effects in the broader population. 4. Treatment Effects: Participants in clinics or specialized facilities may be receiving treatments or interventions that influence their outcomes. This can confound the relationship between variables of interest and outcomes, making it challenging to attribute observed effects solely to the variables being studied. 5. Ethical Considerations: There are ethical concerns about the generalizability of findings and the potential stigmatization of individuals seeking help in specialized settings. It's essential to ensure that research findings accurately reflect the diverse experiences and needs of all youth, not just those receiving specialized services. To mitigate these issues, researchers can employ strategies such as recruiting from multiple settings (including community-based samples), using random sampling techniques where feasible, and carefully describing the characteristics of the sample to facilitate interpretation and generalization of findings. Awareness of selection bias and its implications is crucial for designing studies that provide valid and applicable insights into youth development and mental health. 55. What are the different types of measurement validity? Answer: Measurement validity refers to the extent to which a measure accurately captures the construct it is intended to measure. There are several types of validity that researchers consider when evaluating the quality and appropriateness of a measurement tool. Here are the main types of measurement validity: 1. Content Validity: • Definition: Content validity refers to the extent to which a measurement instrument adequately covers all aspects of the construct of interest. • Example: For a test of reading comprehension, content validity would be demonstrated if the test includes a representative sample of the types of reading passages and questions that assess different aspects of comprehension skills. 2. Criterion-Related Validity: • Definition: Criterion-related validity assesses how well a measurement correlates with a criterion that is theoretically related to the construct being measured. • Types: • Concurrent Validity: This is demonstrated when a measure correlates well with a criterion measure that is administered at the same time. • Predictive Validity: This type is demonstrated when a measure predicts future performance or behavior on a criterion measure. 3. Construct Validity: • Definition: Construct validity refers to the extent to which a measurement accurately measures the theoretical construct or trait it claims to measure. • Types: • Convergent Validity: This is demonstrated when scores on the measure correlate strongly with scores on other measures of the same or similar constructs. • Discriminant Validity: This is demonstrated when scores on the measure do not correlate strongly with scores on measures of unrelated constructs, indicating that the measure is distinct from others. 4. Face Validity: • Definition: Face validity refers to the extent to which a measurement instrument appears to measure what it is intended to measure, based on its face value. • Example: A questionnaire designed to measure job satisfaction should include items that clearly appear to assess aspects of job satisfaction to respondents and observers. 5. Internal Validity: • Definition: Internal validity refers to the extent to which a study's design and methods accurately answer the research question or test the hypothesis being investigated. • Example: In an experiment, internal validity ensures that the changes in the dependent variable are directly attributable to the manipulation of the independent variable and not due to other extraneous factors. Each type of validity serves a specific purpose in ensuring that the measurements used in research are accurate, reliable, and applicable to the constructs under investigation. Researchers often use a combination of these validity types to establish the credibility and robustness of their measurement instruments. 56. Contrast the concepts of internal and external validity with regard to research findings. Answer: Internal validity and external validity are both important concepts in research methodology, but they address different aspects of the validity of research findings: 1. Internal Validity: • Definition: Internal validity refers to the extent to which a study accurately demonstrates a causal relationship between the variables being studied. It assesses whether the changes in the dependent variable (outcome) can be attributed to the manipulation of the independent variable (cause), rather than to other factors. Key Considerations: • Controlled Conditions: Internal validity is maximized when researchers can control extraneous variables and isolate the effects of the independent variable. • Experimental Design: It is typically associated with experimental research designs where variables are manipulated and random assignment is used to minimize confounding variables. • Threats: Common threats to internal validity include history (external events), maturation (natural changes over time), testing effects (repeated measures influencing responses), and selection bias (non-random assignment). • Example: In a drug efficacy study, internal validity would ensure that any observed improvements in health outcomes are indeed due to the drug treatment and not to other factors like placebo effects or changes in diet. 2. External Validity: • Definition: External validity refers to the extent to which the findings of a study can be generalized or applied to populations, settings, and conditions beyond the specific ones studied in the research. Key Considerations: • Population Generalizability: External validity considers whether the study findings can be extended to different populations that were not included in the study. • Ecological Validity: It also considers whether the study findings hold true in real-world settings and everyday situations, beyond the controlled environment of the study. • Contextual Factors: External validity assesses whether the findings are applicable across different times, locations, and conditions. • Example: If a psychological intervention is found effective in improving mental health outcomes in a specific clinical setting, external validity would question whether similar outcomes can be expected in other clinical settings or with different demographic groups. Contrast: • Focus: Internal validity focuses on the accuracy of causal inferences within the study context, ensuring that observed changes in the dependent variable are directly attributable to the independent variable manipulation. External validity, on the other hand, focuses on the generalizability of study findings to broader populations, settings, and conditions. • Methodological Considerations: Achieving high internal validity often requires tightly controlled experimental designs and rigorous methods to isolate causal relationships. In contrast, establishing external validity requires consideration of the diversity and representativeness of the sample and the relevance of the study conditions to real-world situations. In summary, while internal validity ensures the accuracy of causal conclusions within a study, external validity ensures the applicability and generalizability of those conclusions to broader contexts and populations. Both types of validity are crucial in evaluating the robustness and relevance of research findings in advancing knowledge and informing practical applications. 57. For each of the following research designs, discuss major benefits and weaknesses: case study, correlational, experimental. Answer: Let's discuss the major benefits and weaknesses of each of the following research designs: 1. Case Study Benefits: • Rich, Detailed Data: Case studies provide in-depth, detailed information about the individual or phenomenon being studied. This depth can uncover unique insights and nuances that might not be captured in larger-scale studies. • Exploratory Research: They are particularly useful for generating hypotheses and exploring rare or unusual phenomena that are difficult to replicate in experimental settings. • Contextual Understanding: Case studies allow researchers to understand complex interactions within real-life contexts, including environmental, social, and psychological factors. Weaknesses: • Limited Generalizability: Findings from case studies are often difficult to generalize to larger populations due to the uniqueness of each case and potential idiosyncrasies. • Subjectivity and Bias: Interpretation of case study data can be influenced by researcher biases or preconceptions, which may affect the objectivity of findings. • Lack of Control: Case studies lack experimental control over variables, making it challenging to establish causal relationships between variables. 2. Correlational Study Benefits: • Establishing Relationships: Correlational studies examine the relationships between variables in their natural settings, providing insights into how variables co-vary. • Predictive Power: They can help predict outcomes based on patterns of association between variables, aiding in understanding potential causal mechanisms. • Ethical Considerations: Correlational studies can be conducted when experimental manipulation is not feasible or ethical, particularly in studying naturally occurring behaviors or phenomena. Weaknesses: • Directionality Problem: Correlation does not imply causation. Establishing causation is difficult because correlational studies cannot manipulate variables or control for all potential confounding variables. • Third Variables: There may be unidentified third variables influencing both the variables under study, leading to spurious correlations. • Measurement Issues: The reliability and validity of measures used in correlational studies can impact the accuracy of results. 3. Experimental Study Benefits: • Causal Inference: Experimental studies allow researchers to establish cause-and-effect relationships by manipulating the independent variable and measuring its effect on the dependent variable. • Control Over Variables: Researchers can control extraneous variables through random assignment and experimental design, increasing the internal validity of the study. • Replication: Experiments can be replicated to test the reliability and generalizability of findings across different samples and settings. Weaknesses: • Artificiality: Laboratory settings and experimental manipulations may not fully capture real-world complexity and behaviors, limiting ecological validity. • Ethical Concerns: Some experimental manipulations may raise ethical concerns, especially when participants are exposed to potentially harmful conditions. • Practical Constraints: Conducting experiments can be resource-intensive, requiring time, funding, and specialized equipment, which may limit sample size or study duration. In summary, each research design—case study, correlational study, and experimental study—has distinct strengths and weaknesses that researchers must consider based on their research questions, ethical considerations, and practical constraints. Choosing the appropriate design depends on the specific aims of the study and the nature of the phenomenon being investigated. 58. Why is it problematic to assume causality from correlational studies? Answer: It is problematic to assume causality from correlational studies primarily because correlation does not imply causation. Here are several key reasons why making causal claims based solely on correlational evidence can be misleading: 1. Directionality Problem: • In correlational studies, variables are measured as they naturally occur, without manipulation. Therefore, it is unclear which variable is causing changes in the other, or if there is a bidirectional relationship where both variables influence each other. • Example: A study might find a positive correlation between the amount of exercise individuals engage in and their mental health. However, it's unclear if exercise improves mental health (causation from exercise to mental health), if better mental health leads to more exercise (reverse causation), or if other factors (like overall health or personality traits) influence both variables simultaneously. 2. Third Variable Problem: • Correlation between two variables may be due to the influence of a third variable that is not measured or controlled for in the study. This third variable, also known as a confounding variable, can create a spurious relationship between the variables of interest. • Example: Studies often find a positive correlation between ice cream sales and drowning deaths. However, the underlying factor causing both is hot weather (a third variable). Ice cream sales and drowning deaths are not causally related; they are both influenced by hot weather. 3. Confounding Factors: • Correlational studies may not adequately account for all factors that could influence the relationship between variables. Factors such as participant characteristics, environmental influences, or measurement errors can impact the strength and direction of correlations. • Example: A study finds a negative correlation between screen time and academic performance in children. However, without controlling for factors like parental involvement in education or socioeconomic status, the observed correlation might not accurately reflect the true relationship. 4. Ecological Validity: • Correlational studies often measure variables in controlled settings or through surveys, which may not fully capture the complexities and dynamics of real-life behaviors and interactions. • Example: A study might find a correlation between smartphone use and social skills. However, the conditions under which smartphones are used (e.g., social media interaction vs. gaming) and individual differences in usage patterns can significantly influence the observed correlation. Due to these limitations, researchers must exercise caution when interpreting correlational findings and avoid making causal claims without additional evidence from experimental studies or other research designs. While correlational studies are valuable for identifying associations and generating hypotheses, establishing causality requires rigorous experimental manipulation and control over variables to demonstrate causal relationships definitively. 59. Construct a hypothetical randomized experiment, making clear the hypothesis, independent and dependent variables, procedures, and conclusions that could be drawn from the data. Answer: Hypothesis: Increased physical exercise improves mood among college students. Independent Variable: Amount of physical exercise (manipulated variable with two levels: low exercise and high exercise). Dependent Variable: Mood (measured using a standardized mood questionnaire). Procedure: 1. Participant Selection: Randomly select 100 college students from a university population who are willing to participate in the study. 2. Baseline Assessment: Administer a baseline mood questionnaire to all participants to establish their initial mood scores. 3. Random Assignment: Randomly assign participants to either the low exercise group or the high exercise group. • Low Exercise Group (Control Group): Participants in this group are instructed to maintain their current level of physical activity throughout the study period. • High Exercise Group (Experimental Group): Participants in this group are instructed to engage in 30 minutes of moderate-intensity aerobic exercise (e.g., brisk walking, jogging) five days a week for four weeks. 4. Monitoring and Compliance: Participants in the high exercise group are provided with activity trackers to monitor their exercise adherence. Both groups are contacted weekly to assess compliance and address any questions. 5. Post-Intervention Assessment: At the end of the four-week intervention period, administer the mood questionnaire again to both groups to measure changes in mood. 6. Data Analysis: Compare the post-intervention mood scores between the low exercise and high exercise groups using appropriate statistical tests (e.g., t-test or ANOVA). Control for any baseline differences in mood scores using analysis of covariance (ANCOVA) if necessary. Expected Conclusions: • If the high exercise group shows a significant improvement in mood compared to the low exercise group, it would provide evidence supporting the hypothesis that increased physical exercise improves mood among college students. • If there is no significant difference in mood between the two groups, it would suggest that the amount of exercise (30 minutes of moderate-intensity aerobic exercise five days a week) used in this study may not be sufficient to produce measurable changes in mood within a four-week period, or that factors other than exercise might play a significant role in influencing mood. Ethical Considerations: • Ensure informed consent from all participants. • Protect participants' confidentiality and privacy. • Monitor participants' well-being throughout the study. By conducting this randomized experiment, researchers can better understand the potential impact of physical exercise on mood among college students, contributing to evidence-based recommendations for promoting mental health through physical activity interventions. 60. In what situations might the ABA design be inappropriate and what other kinds of single-subject experiments might be more appropriately employed? Answer: The ABA design (also known as a reversal or withdrawal design) is a single-subject experimental design commonly used in applied behavior analysis to evaluate the effects of interventions on behavior. In an ABA design, the researcher observes baseline behavior (A), introduces an intervention or treatment (B), and then returns to baseline conditions (A) to observe if the behavior returns to its original state. Here are situations where the ABA design might be inappropriate and alternative single-subject experimental designs that could be more appropriate: Inappropriate Situations for ABA Design: 1. Irreversible Interventions: • If the intervention being studied is expected to have lasting effects that cannot be withdrawn (reversed) once implemented, the ABA design may not be suitable. • Example: Teaching a child a new language or skill that, once learned, cannot be unlearned or returned to baseline. 2. Ethical Concerns: • When withdrawing an effective intervention could harm the participant or compromise their well-being, it is unethical to use an ABA design. • Example: Withdrawing essential medical treatment from a patient for research purposes. 3. Long-Term Effects: • If the study aims to assess long-term effects of an intervention and a short-term withdrawal period is insufficient to observe these effects, an ABA design may not provide adequate data. • Example: Studying the effects of a parenting intervention on child behavior over several years. Alternative Single-Subject Experimental Designs: 1. Multiple Baseline Design: • Description: In this design, multiple behaviors, individuals, or settings are measured over time, with interventions implemented at different times across baselines. • Appropriate Use: Useful when the behavior or intervention effects cannot be reversed or when it's unethical to withdraw the intervention. It allows for demonstrating experimental control and observing generalization of effects. 2. Changing Criterion Design: • Description: In this design, the intervention's effectiveness is evaluated by gradually changing the criterion for successful performance over time. • Appropriate Use: Suitable when the goal is to measure gradual improvement or shaping of behavior rather than a complete reversal of effects. 3. Alternating Treatment Design (Multi-element Design): • Description: This design involves rapidly alternating between different interventions or conditions within the same phase to compare their effects on behavior. • Appropriate Use: Useful when comparing the immediate effects of different interventions or when assessing variable treatment effects across different contexts or stimuli. 4. Multiple Probe Design: • Description: Used primarily in educational research, this design involves probing the participant's ability to perform a behavior at different points during intervention implementation, rather than withdrawing interventions. • Appropriate Use: Suitable for assessing the acquisition and maintenance of skills over time, without requiring full reversals of interventions. Choosing the appropriate single-subject experimental design depends on the research question, ethical considerations, and the nature of the intervention and behavior being studied. Researchers should carefully consider these factors to ensure the design chosen provides valid and meaningful results while respecting participant welfare and ethical guidelines. 61. Suppose that you wanted to use a multiple baseline research study to test the idea that positive reinforcement can increase children’s interaction with other children on the playground. Describe your design to test this hypothesis. How would you know if the intervention was effective? Answer: To test the hypothesis that positive reinforcement can increase children’s interaction with other children on the playground using a multiple baseline design, here is how the study could be structured: Design: Participants: Select a small group of children who currently show low levels of interaction with peers on the playground. The number of participants should be based on practical considerations and the specific dynamics of the playground environment. Baselines: Establish baselines for each participant individually. A multiple baseline design could include: 1. Baseline Phase (Baseline A): • Measure each child's baseline level of interaction with peers on the playground over a specified period. This phase serves as the control where no intervention is applied. 2. Intervention Phase (Baseline B): • After the baseline data collection, implement the positive reinforcement intervention for one child at a time, starting with the first participant. • The intervention involves systematically reinforcing (e.g., praising, rewarding) instances of positive social interactions with peers on the playground. The reinforcement should be contingent upon the desired behavior (interaction with peers). 3. Delayed Baseline (Baseline C, if applicable): • Once the intervention has been implemented for the first participant and stable improvements in interaction are observed, introduce the intervention for the second participant, and so on. • This staggered introduction across participants creates multiple baselines across time or participants. Measurement and Data Collection: • Dependent Variable: Interaction with peers on the playground, measured through direct observation or structured play observations by trained observers. • Data Collection: Collect frequency or duration data of interactions during baseline phases (A), intervention phases (B), and any delayed baseline phases (C). Evaluation of Effectiveness: To determine if the positive reinforcement intervention was effective, researchers would analyze the data collected during the intervention phases compared to baseline phases: • Visual Analysis: Examine the graphs of interaction data for each participant across phases. Look for consistent increases in interaction levels during intervention phases compared to baseline phases. • Statistical Analysis (if applicable): Conduct statistical tests (e.g., visual analysis with Tau-U or non-overlap of all pairs (NAP) analysis) to determine the magnitude and significance of changes observed during the intervention phase compared to baseline phases. Criteria for Effectiveness: • Criterion for Improvement: Define a priori criteria for what constitutes meaningful improvement in interaction with peers (e.g., doubling the frequency of interactions, maintaining interactions for a certain duration). • Social Validity: Assess the social validity of the intervention by collecting feedback from teachers, parents, and participants themselves about perceived improvements in social interactions and the acceptability of the intervention. Conclusion: If the positive reinforcement intervention demonstrates consistent and significant increases in children’s interaction with peers during the intervention phase compared to baseline phases, it provides support for the hypothesis that positive reinforcement can effectively increase social interactions on the playground. The strength of this conclusion depends on the robustness of the data analysis and the replication of results across participants in the study. 62. What are the goals of epidemiological research and how is such research conducted? Answer: Epidemiological research aims to investigate the distribution and determinants of health-related states or events in populations, and to apply this knowledge to control health problems. The primary goals of epidemiological research include: 1. Describing Disease Patterns: Epidemiological studies aim to describe the occurrence and distribution of diseases, health outcomes, and risk factors within populations. This involves identifying who is affected, where they are located, and when the health events occur. 2. Identifying Risk Factors: Epidemiological research seeks to identify and understand the determinants or risk factors associated with disease occurrence or health outcomes. This includes exploring factors such as behaviors, genetic predispositions, environmental exposures, and social determinants of health. 3. Exploring Causal Relationships: Epidemiological studies aim to establish causal relationships between exposures (risk factors) and health outcomes. This involves assessing the strength, consistency, and temporality of associations through observational studies or randomized controlled trials. 4. Evaluating Interventions: Epidemiological research evaluates the effectiveness of public health interventions, preventive measures, and healthcare policies in reducing disease burden and improving population health outcomes. Conducting Epidemiological Research: Epidemiological research is conducted through systematic and rigorous methods to ensure the validity and reliability of findings. Key steps and methods involved include: 1. Study Design Selection: • Observational Studies: These include cohort studies, case-control studies, and cross-sectional studies. They observe individuals without intervening or manipulating exposures. • Experimental Studies: These include randomized controlled trials (RCTs), where interventions or treatments are randomly assigned to participants to evaluate their effects on health outcomes. 2. Sampling: Epidemiological studies use various sampling techniques to select representative samples from target populations. Samples must reflect the diversity and characteristics of the population under study to ensure generalizability of findings. 3. Data Collection: Researchers collect data through various methods, including: • Surveillance: Monitoring and collecting data on disease occurrence and health events. • Surveys: Administering questionnaires or interviews to gather information on risk factors, health behaviors, and health outcomes. • Biological Samples: Collecting biological specimens (e.g., blood, urine) for laboratory analysis to assess biomarkers or disease markers. 4. Data Analysis: Epidemiologists analyze collected data using statistical methods to: • Describe disease patterns and distributions (e.g., prevalence, incidence rates). • Assess associations between exposures and outcomes (e.g., odds ratios, relative risks). • Control for confounding variables and biases that may affect the accuracy of study findings. 5. Interpretation and Dissemination: Researchers interpret study results in the context of study objectives, discuss implications for public health practice and policy, and disseminate findings through scientific publications, reports, and presentations to stakeholders and the public health community. Challenges and Considerations: • Bias and Confounding: Ensuring that study designs minimize biases and account for confounding variables that could distort associations between exposures and outcomes. • Ethical Considerations: Respecting ethical principles in research, including participant consent, confidentiality, and protection from harm. • Generalizability: Ensuring that findings are applicable beyond the study sample to broader populations or settings. Epidemiological research plays a crucial role in informing public health policies, preventive strategies, and interventions aimed at improving population health and reducing the burden of disease worldwide. 63. What are the advantages and disadvantages of the cross-sectional and longitudinal research strategies, especially with regard to tracing development? Answer: Cross-sectional and longitudinal research strategies are both valuable approaches in developmental psychology and other fields, each offering unique advantages and disadvantages, particularly when tracing development over time. Cross-Sectional Research: Advantages: 1. Efficiency: Cross-sectional studies can collect data from participants of different ages simultaneously, providing a snapshot of development across different age groups in a relatively short period. 2. Cost-Effectiveness: They are often less time-consuming and less costly compared to longitudinal studies, as data collection occurs at a single point in time. 3. Useful for Initial Exploration: Cross-sectional studies can quickly generate hypotheses about developmental trends and potential relationships between variables. 4. Reduced Attrition: Unlike longitudinal studies, there is no issue of attrition over time, where participants may drop out or become unavailable. Disadvantages: 1. No Assessment of Change: They do not allow for the assessment of individual change over time, as each participant is assessed only once. This limits the ability to draw conclusions about developmental trajectories or causality. 2. Cohort Effects: Differences observed between age groups could be due to generational or cohort effects rather than true developmental differences. This can complicate interpretation of findings. 3. Age-Related Differences: Cross-sectional designs cannot distinguish between age-related changes and cohort effects, which may confound interpretations of developmental trends. Longitudinal Research: Advantages: 1. Assessment of Change: Longitudinal studies track the same individuals over an extended period, allowing researchers to observe developmental changes within individuals over time. This provides insights into developmental trajectories and individual differences. 2. Causal Inference: They can establish temporal precedence and help determine causality between variables, as changes in the independent variable can be directly linked to changes in the dependent variable. 3. Developmental Patterns: They reveal patterns of stability and change within individuals across different stages of development, offering a comprehensive understanding of developmental processes. 4. Addressing Attrition: Longitudinal studies can employ strategies to mitigate attrition, such as follow-up incentives, maintaining participant engagement, and using advanced statistical techniques to handle missing data. Disadvantages: 1. Time and Resources: They are resource-intensive and require significant time commitments from researchers and participants. Longitudinal studies may span years or even decades, making them costly and logistically challenging. 2. Sample Attrition: Participants may drop out or become lost to follow-up over time, potentially biasing results if attrition is related to the variables under study. 3. Practice Effects: Repeated assessments may lead to practice effects where participants improve or change their responses due to familiarity with testing procedures, rather than true developmental changes. 4. External Validity: Longitudinal findings may not generalize to other populations or cohorts due to cohort effects or changes in societal factors over time. Tracing Development: • Cross-sectional Approach: Useful for identifying age-related trends or differences across different age groups at a single point in time. However, it cannot capture intra-individual changes or developmental trajectories. • Longitudinal Approach: Ideal for studying individual developmental trajectories and understanding how factors interact and influence development over time. It allows for examining stability, change, and factors contributing to developmental outcomes. In summary, both cross-sectional and longitudinal research strategies offer distinct advantages and disadvantages when tracing development. The choice between them depends on research goals, feasibility, resources, and the specific developmental questions being addressed. Integrating findings from both types of studies can provide a more comprehensive understanding of developmental processes and outcomes. 64. Define and compare retrospective and prospective research designs. Answer: Retrospective and prospective research designs are two fundamental approaches used in various fields of study, including epidemiology, psychology, sociology, and medicine. They differ primarily in the directionality of data collection in relation to the occurrence of events or conditions being studied. Retrospective Research Design: Definition: • Retrospective research involves collecting data from the past. Researchers begin by identifying individuals who have experienced the outcome or condition of interest (cases) and those who have not (controls), and then look backward to collect data on their exposures or experiences. • It is often used when it is not feasible or practical to conduct a prospective study due to time constraints, cost, or the nature of the research question. Key Features: • Data Collection: Researchers collect historical data from records, documents, interviews, or surveys to reconstruct past events, exposures, or behaviors. • Time Sequence: The sequence of events is known from the start (outcome → exposure). • Example: A retrospective study might investigate the association between smoking (exposure) and lung cancer (outcome) by comparing the smoking history of individuals diagnosed with lung cancer to a control group of individuals without lung cancer. Advantages: • Efficiency: Retrospective studies are typically quicker and less costly to conduct compared to prospective studies. • Useful for Rare Outcomes: They are particularly useful for studying rare diseases or outcomes that occur infrequently. Disadvantages: • Recall Bias: Relies on participants' ability to accurately recall past events or exposures, which may introduce recall bias. • Data Quality: Dependent on the availability and quality of historical data or records, which may be incomplete or inaccurate. Prospective Research Design: Definition: • Prospective research involves collecting data over time, starting from the present or baseline and following participants into the future to observe outcomes as they occur. • It is considered the gold standard for studying causality and understanding the natural course of events or conditions. Key Features: • Data Collection: Researchers collect data prospectively through observations, interviews, measurements, or interventions at regular intervals over a defined period. • Time Sequence: The sequence of events unfolds during the study period (exposure → outcome). • Example: A prospective study might track a cohort of individuals without diabetes (baseline) and assess their risk factors (e.g., diet, exercise) over several years to identify factors associated with the development of diabetes. Advantages: • Causality: Allows for the establishment of temporal relationships between exposures and outcomes, supporting causal inference. • Reduced Bias: Minimizes recall bias and other biases associated with retrospective data collection. • Detailed Data: Provides detailed data on the timing and progression of events or conditions. Disadvantages: • Time and Resources: Prospective studies require substantial time, resources, and long-term commitment from participants and researchers. • Attrition: Participants may drop out or be lost to follow-up over time, potentially biasing results if attrition is related to the variables under study. Comparison: • Temporal Sequence: Retrospective studies establish the sequence of events retrospectively (outcome → exposure), while prospective studies establish it prospectively (exposure → outcome). • Bias: Retrospective studies may be more prone to recall bias, while prospective studies minimize this bias by collecting data as events unfold. • Time and Cost: Retrospective studies are typically quicker and cheaper, making them suitable for certain research questions. Prospective studies require more time and resources but provide stronger evidence for causal relationships. In summary, the choice between retrospective and prospective research designs depends on the research question, feasibility, availability of data, and the ability to control for biases. Both designs have their strengths and limitations, and researchers often consider these factors when designing studies to ensure the validity and reliability of their findings. 65. Use an example to explain why one would combine quantitative and qualitative research strategies. Answer: Combining quantitative and qualitative research strategies can provide a more comprehensive understanding of complex phenomena that quantitative or qualitative methods alone may not fully capture. Here’s an example illustrating the benefits of integrating both approaches: Example: Studying Patient Satisfaction in Healthcare Quantitative Approach: • Objective: Measure overall patient satisfaction scores and identify factors associated with high or low satisfaction ratings. • Method: Conduct a survey using standardized questionnaires with Likert scale responses to assess patient satisfaction. Variables could include waiting times, communication with healthcare providers, cleanliness of facilities, etc. • Analysis: Use statistical techniques (e.g., regression analysis, correlation) to quantify relationships between satisfaction scores and factors such as wait times, communication quality, and demographics. Qualitative Approach: • Objective: Explore in-depth experiences and perceptions of patients regarding healthcare services and satisfaction. • Method: Conduct semi-structured interviews or focus groups with a subset of patients who provided varying satisfaction ratings in the quantitative survey. Probe deeper into their reasons for satisfaction or dissatisfaction, their emotional responses, and their suggestions for improvement. • Analysis: Employ thematic analysis to identify recurring themes, patterns, and nuances in patients' narratives. Capture qualitative data on aspects like trust in healthcare providers, emotional support received, and the impact of facilities' ambiance on their experience. Integration of Both Approaches: 1. Triangulation of Data: By integrating findings from both quantitative surveys and qualitative interviews, researchers can compare and contrast different perspectives and corroborate findings. For instance, quantitative data may show a correlation between shorter wait times and higher satisfaction scores, while qualitative data can explain why patients value shorter wait times (e.g., feeling respected and valued). 2. Comprehensive Understanding: Quantitative data provide breadth by quantifying satisfaction levels across a large sample, while qualitative data provide depth by revealing the underlying reasons and contexts influencing those satisfaction levels. 3. Enhanced Validity and Contextualization: Qualitative insights can contextualize quantitative findings, helping researchers interpret statistical relationships within the broader social, cultural, and personal contexts of patients' lives. 4. Iterative Exploration: Integrating qualitative and quantitative methods allows for an iterative approach where initial quantitative findings may guide further qualitative inquiry to explore unexpected or contradictory results. Conclusion: In the example of studying patient satisfaction in healthcare, combining quantitative surveys with qualitative interviews or focus groups enhances the richness and validity of the research findings. This combined approach not only provides a holistic view of patient experiences and satisfaction but also offers insights that can inform healthcare policies, service improvements, and patient-centered care initiatives effectively. Therefore, the integration of quantitative and qualitative research strategies is essential for gaining a deeper understanding of complex phenomena and addressing research questions comprehensively in various fields of study. 66. What common elements of a study are communicated or shared with children and their parents before they participate? Answer: Before children and their parents participate in a study, researchers typically communicate or share several key elements to ensure informed consent and ethical conduct throughout the research process. These elements include: 1. Purpose of the Study: • Researchers explain the overall goal or objective of the study in language appropriate for both children and parents. This includes why the study is being conducted and what researchers hope to learn or achieve. 2. Procedures Involved: • Describe the specific activities or tasks that participants will engage in during the study. This may include interviews, questionnaires, observations, experimental tasks, or interventions. • Provide an overview of the duration of each session or visit, as well as the total time commitment required from participants. 3. Risks and Benefits: • Outline any potential risks or discomforts associated with participation. For children, these risks are often minimal and may include temporary discomfort, fatigue, or boredom. • Explain the potential benefits of the study, both direct (e.g., learning something new) and indirect (e.g., contributing to scientific knowledge). 4. Confidentiality and Privacy: • Assure participants and their parents that their personal information and data will be kept confidential. Explain how data will be stored securely and who will have access to it. • Describe any circumstances under which confidentiality may be breached (e.g., concerns about safety). 5. Voluntary Participation and Withdrawal: • Emphasize that participation in the study is voluntary and that participants can withdraw at any time without penalty or consequence. • Explain the procedure for withdrawing from the study and ensure that participants understand their right to withdraw without needing to provide a reason. 6. Incentives or Compensation: • If applicable, clarify any incentives or compensation provided to participants or their families for their time and participation. • Provide details on how incentives will be distributed and any conditions associated with receiving them. 7. Contact Information: • Provide contact information for the researchers, including names, affiliations, and ways to reach them (e.g., phone number, email address). • Encourage participants and their parents to ask questions at any time before, during, or after the study. 8. Child-Friendly Language and Approaches: • Tailor the information to be age-appropriate and use language that children can understand. Use visuals or simplified explanations to enhance comprehension. • Encourage parents to discuss the study with their child and address any concerns or questions they may have. By clearly communicating these elements, researchers ensure that children and their parents can make informed decisions about participation in research studies. This process not only upholds ethical standards but also fosters trust and cooperation between researchers and participants, ultimately contributing to the validity and reliability of the research findings. 67. Give examples of 3 common ethical issues raised when conducting research on children. Answer: Conducting research involving children requires careful consideration of ethical principles to ensure their well-being, protection, and rights are upheld. Several common ethical issues that arise in research on children include: 1. Informed Consent and Assent: • Issue: Children may not fully understand the purpose, procedures, risks, and benefits of research participation. This raises challenges in obtaining informed consent and assent. • Example: Researchers must ensure that both parents or legal guardians provide informed consent for their child's participation. Additionally, children who are capable of understanding the research (depending on their age and maturity) should provide assent, indicating their willingness to participate. 2. Privacy and Confidentiality: • Issue: Protecting the privacy and confidentiality of child participants is crucial, especially when sensitive information is collected. • Example: Researchers must ensure that data collected from children are anonymized or kept confidential. This includes securing data storage and transmission methods to prevent unauthorized access or disclosure of personal information. 3. Risk of Harm and Benefits: • Issue: Balancing the potential risks and benefits of research participation for children is essential. Researchers must minimize harm and maximize benefits while ensuring that risks are proportionate to the potential benefits. • Example: Studies involving experimental interventions or sensitive topics must carefully assess and mitigate potential physical or psychological risks to children. Researchers should also consider whether benefits, such as contributing to scientific knowledge or receiving therapeutic benefits, outweigh potential harms. 4. Coercion and Inducements: • Issue: Avoiding coercion or undue influence when recruiting children for research is critical. Offering inducements that could potentially coerce children or their parents into participating raises ethical concerns. • Example: Researchers should provide incentives or compensation that are reasonable and do not unduly influence children or their parents' decision to participate. Incentives should not be so substantial that they induce children to take risks they would not otherwise take. 5. Parental Permission and Proxy Consent: • Issue: Determining who can provide consent for a child's participation in research can be complex, especially in cases involving divorced parents, legal guardianship disputes, or situations where one parent is unavailable. • Example: Researchers must follow legal and ethical guidelines for obtaining parental permission or proxy consent. This includes understanding local regulations and ensuring that consent procedures are clear and equitable for all parties involved. Addressing these ethical issues requires adherence to established guidelines and ethical principles, ongoing dialogue with stakeholders (including children and their parents), and careful consideration of the unique vulnerabilities and capacities of child participants. Ethical oversight through Institutional Review Boards (IRBs) or Ethics Committees is also essential to ensure that research on children meets rigorous ethical standards. Test Bank for Abnormal Child and Adolescent Psychology Rita Wicks-Nelson, Allen C. Israel 9781317351344, 9780205036066, 9780205901128