11 Chapter 11: Student Workbook & Assignments

Assignment Questions

Your Response

1) Broad Research Topic: Explore the scope of the ABCD study and identify a broad research topic that interests you (there are thousands of possible topics).

• State the broad research topic you are considering and how it relates to the ABCD study.
• Discuss potential sources of inspiration for your topic, such as current research trends, societal issues, or personal interests.

2) Choosing Variables: Identify and list the variables that interest you and are relevant to your research topic. You should list at least two demographic variables, at least one independent variable, and at least one dependent variable. Note: in some cases, it may help to complete question 3 before question 2.

3) Research Question: Based on your chosen variables, write a confirmatory research question.

4) Confounding Factors: What are some potential confounding factors that could influence the outcomes of your study? In other words, consider if there are confounding variables impacting the relationships between your independent and dependent variables.

5) Introducing Control Variables: Focus on what you consider to be the most important or impactful confounders. Write additional research questions or modify your initial question to use control variables to address these confounders. In other words, you do not need to write new questions for every possible confounder that you may have identified in question 4. Recommended: limit your total variables to 3-5.

6) Justification: What justified your decisions in question 5? Why did you pick these confounders over the others?

7) Falsifiable Research Hypothesis: Write a clear, testable, and falsifiable hypothesis that aligns with your research question, including your control variables.

8) Explaining Falsifiability: Briefly explain how your hypothesis is falsifiable.

9) Alignment with ABCD Study Design: Explain how the ABCD study design, such as its sample characteristics, longitudinal nature, and the types of data collected, supports your ability to investigate your research question and test your hypothesis. Highlight specific aspects of the ABCD study that make it particularly suited to answering your question.

(20 points)

Assignment Questions

Your Response

1) Broad Research Topic: Explore the scope of the ABCD study and identify a broad research topic that interests you (there are thousands of possible topics).

• State the broad research topic you are considering and how it relates to the ABCD study.
• Discuss potential sources of inspiration for your topic, such as current research trends, societal issues, or personal interests.

Topic: The Impact of Socioeconomic Status on Academic Achievement and Behavioral Problems in Adolescents.

Justification: This topic is important to me because it examines how different socioeconomic environments influence educational outcomes and behavioral issues, which have long been debated in adolescent development studies, and it is an area covered by the ABCD study.

2) Choosing Variables: Identify and list the variables that interest you and are relevant to your research topic. You should list at least two demographic variables, at least one independent variable, and at least one dependent variable.

Demographic Variables: Age (9-12), Gender

Independent Variable: Socioeconomic Status (SES)

(note to students: this is an example of demographic variable serving as an independent variable)

Dependent Variables: Academic achievement and Behavioral Problems

3) Research Question: Based on your chosen variables, write a confirmatory research question. Write the research question in simple terms.

How does socioeconomic status (SES) effect academic achievement and behavioral problems in adolescents maturing between ages 9-12?

4) Confounding Factors: What are some potential confounding factors that could influence the outcomes of your study? In other words, consider if there are confounding variables impacting the relationships between your independent and dependent variables.

Potential confounding factors could include parental involvement, which might affect both the educational outcomes and the behavior of the children. Another could be the school environment, which might vary significantly between different socioeconomic contexts.

5) Introducing Control Variables: Focus on what you consider to be the most important or impactful confounders. Write additional research questions or modify your initial question to use control variables to address these confounders. In other words, you do not need to write new questions for every possible confounder that you may have identified in question 4.

To control for the effects of parental involvement and school environment on the relationship between socioeconomic status and the outcomes, the research question can be modified to:

How does socioeconomic status affect academic achievement and behavioral problems in adolescents, controlling for parental involvement and school type?

6) Justification: What justified your decisions in question 5? Why did you pick these confounders over the others?

Parental involvement is known to have a significant positive impact on both academic and behavioral outcomes, independent of socioeconomic status. Controlling for this variable ensures that the effects measured are primarily due to socioeconomic differences rather than differences in parental engagement. The type of school can also influence both academic and behavioral outcomes, with private or charter schools potentially offering different resources and environments compared to public schools.

7) Falsifiable Research Hypothesis: Write a clear, testable, and falsifiable hypothesis that aligns with your research question, including your control variables.

Adolescents from lower SES backgrounds will exhibit lower academic achievement and more behavioral problems compared to their higher SES counterparts, even when accounting for levels of parental involvement and the type of school attended.

8) Explaining Falsifiability: Briefly explain how your hypothesis is falsifiable.

This hypothesis seeks a direct relationship between lower SES and more troubling adolescent outcomes. This relationship will be tested while controlling for parental involvement, which is often higher in higher SES families and positively impacts academic success, and school type, which influences the quality of educational resources and environments available to the adolescent. The hypothesis is structured to be falsifiable: if data analysis shows no significant difference in outcomes based on SES, after controlling for the specified variables, the hypothesis would be considered disproven.

9) Alignment with ABCD Study Design: Explain how the ABCD study design, such as its sample characteristics, longitudinal nature, and the types of data collected, supports your ability to investigate your research question and test your hypothesis. Highlight specific aspects of the ABCD study that make it particularly suited to answering your question.

(20 points)

The longitudinal design of the ABCD study allows for the tracking of academic and behavioral changes over time, which is crucial for analyzing the impact of socioeconomic status as the children grow. The comprehensive data collection on demographic factors, parental background, and educational and behavioral assessments make the ABCD study particularly suited to address this research question.

Assignment Questions

Your Response

1) Broad Research Topic: Explore the scope of the ABCD study and identify a broad research topic that interests you (there are thousands of possible topics).

• State the broad research topic you are considering and how it relates to the ABCD study.
• Discuss potential sources of inspiration for your topic, such as current research trends, societal issues, or personal interests.

My broad topic is the impact of anxiety on impulsive behavior among urban youth. Impulsive behavior is linked to many behavioral health problems, notably addiction. Simultaneously, today’s urban youth are more and more anxious, perhaps due to social media, social pressures, and academic success pressures. I see this in among my friends and peers on campus.

2) Choosing Variables: Identify and list the variables that interest you and are relevant to your research topic. You should list at least two demographic variables, at least one independent variable, and at least one dependent variable. Note: in some cases, it may help to complete question 3 before question 2.

Demographic Variables: Age, Urban/Rural residence

Independent Variable: Levels of anxiety

Dependent Variable: Impulsivity as measured by delay discounting scores

3) Research Question: Based on your chosen variables, write a confirmatory research question.

What are effects of anxiety and impulsivity, as measured by delay discounting scores, among urban adolescents compared to their rural counterparts?

4) Confounding Factors: What are some potential confounding factors that could influence the outcomes of your study? In other words, consider if there are confounding variables impacting the relationships between your independent and dependent variables.

Potential confounding factors in this study could include socioeconomic status (SES), parental education levels, and exposure to environmental stressors. Each of these could influence both the living environment (urban vs. rural) and levels of impulsivity independently.

5) Introducing Control Variables: Focus on what you consider to be the most important or impactful confounders. Write additional research questions or modify your initial question to use control variables to address these confounders. In other words, you do not need to write new questions for every possible confounder that you may have identified in question 4. Recommended: limit your total variables to 3-5.

Is there a stronger association between anxiety and impulsivity, as measured by delay discounting scores, among urban adolescents compared to their rural counterparts, after controlling for family income?

6) Justification: What justified your decisions in question 5? Why did you pick these confounders over the others?

Family income was selected as a control variable primarily because the delay discounting task involves participant’s subjective perception on the value of money. As money is valued differently for people of different income brackets, income and social class are common control variables in studies using delay discounting scores. Additionally, As family income affects access to resources, stress levels, and overall mental well-being, it is important to control for this variable to discern the true effects of other predictors on anxiety levels.

7) Falsifiable Research Hypothesis: Write a clear, testable, and falsifiable hypothesis that aligns with your research question, including your control variables.

Higher levels of anxiety in urban youth are associated with greater impulsivity as measured by delay discounting scores, controlling for family income.

8) Explaining Falsifiability: Briefly explain how your hypothesis is falsifiable.

This hypothesis is falsifiable because it can be empirically tested through the collection of data on anxiety levels, impulsivity scores, and family income. It can be proven false if no significant relationship is found between anxiety levels and impulsivity after controlling for family income.

9) Alignment with ABCD Study Design: Explain how the ABCD study design, such as its sample characteristics, longitudinal nature, and the types of data collected, supports your ability to investigate your research question and test your hypothesis. Highlight specific aspects of the ABCD study that make it particularly suited to answering your question.

(20 points)

The ABCD study is uniquely positioned to support the investigation of how anxiety levels impact impulsivity among adolescents due to its extensive and diverse data collection methods, longitudinal design, and comprehensive sample characteristics. The ABCD study collects a wide array of data types, including detailed psychological assessments that cover surveys on anxiety and impulsivity through measures such as delay discounting tasks.

Question 1: Introduction to the Literature Review

Below, restate your research question(s) and hypothesis(es) from Assignment 1, you are welcome to have revised your research question or hypothesis.

Your response to question 1:

Research question: How does state-level macroeconomic factors, such as cost of living and anti-poverty programs, influence the association between low income and brain structure and mental health in children? (Weissman, Hatzenbuehler et al. 2023)

The hypothesis is that lower family income would be associated with smaller hippocampal volume and higher internalizing and externalizing problems, and that these associations would be moderated by state-level macrostructural characteristics.

Question 2: Setting Objectives for the Literature Review

Below, define specific objectives for your literature review. This should focus on justifying your choice of variables and demonstrating the relevance and timeliness of your research question. Additionally, your focus should be on uncovering gaps in the literature and extending the current understanding of your topic, which will justify your research proposal.

Example Objectives:

• To evaluate how previous research has investigated the relationship between your chosen variables.
• To identify methodological approaches used and their limitations.
• To uncover gaps that your study will address, particularly focusing on what has not been answered yet.

Your response to question 2:

To explore the relationship between state-level macroeconomic factors and children’s brain development: This involves examining how varying economic conditions and anti-poverty programs across states influence brain structure and mental health outcomes in children.

To analyze the moderating effects of these macroeconomic factors on the correlation between family income and brain development: Assessing whether state policies can buffer the negative impacts of low income on children’s neurological and mental health.

To identify research gaps in the current understanding of economic disparities and their neurological outcomes in children: Focusing on the understudied aspects of how broader socioeconomic policies influence childhood development at the neurobiological level.

Question 3: Developing a Search Strategy

Below, describe the strategy you used to gather sources (publications) for your literature review. Specifically, describe the search keywords and your inclusion/exclusion criteria for selecting articles to use.

Details to Include:

• List of keywords and combinations used in your search.
• Your inclusion/exclusion criteria for selecting studies.
• List at least five publications that you will include in your literature review. Recommended: indicate which of your objectives (from question 2) the publication corresponds to.

Your response to question 3:

Keywords: “state-level economic factors,” “child brain development,” “impact of poverty on brain,” “family income and child mental health,” “effects of anti-poverty programs.”

Inclusion Criteria: Studies published in the last 10 years, articles from peer-reviewed journals, studies that specifically address the intersections of socioeconomic factors with child neurodevelopment and mental health.

Exclusion Criteria: Non-English articles, studies focusing on adult populations, non-peer-reviewed articles.

Key Publications:

Weissman et al., 2023 – Directly ties into all objectives by discussing state-level factors.

Hanson et al., 2013 – Examines the impact of poverty on brain structures in children, relevant for understanding baseline effects.

Noble et al., 2015 – Looks at socio-economic factors and brain structure, helping to address objective 2.

Costello et al., 2003 – This study evaluates the effects of poverty reduction through a natural experiment, providing direct evidence of how changes in economic status impact children’s psychological outcomes and brain development (objective 2).

Luby et al., 2013 – Focuses on how poverty influences brain development, particularly the stress systems and associated cognitive development (objective 1).

Question 4: Organization of Literature

Below, organize the research into thematic categories relevant to your variables and hypothesis.

Guidance:

• Choose themes that directly relate to and illuminate aspects of your research question and hypothesis.
• Use themes to help pinpoint neglected areas or where the literature conflicts or lacks depth, this will help to justify your research question.

Your response to question 4:

Theme 1: Impact of Family Income on Childhood Development

Discusses the correlation between lower family income and developmental challenges such as educational attainment and dependency on public assistance.

Relevant studies, such as Duncan, Ziol-Guest, & Kalil, 2010; McLaughlin et al., 2011, support the hypothesis by illustrating the direct impacts of socioeconomic status (SES) on mental and physical health outcomes, aligning with the research question about the influence of macroeconomic factors on brain structure and mental health.

Theme 2: Socioeconomic Influences on Brain Development

Reviews how economic hardship influences brain structures critical to cognitive development, like the hippocampus.

Key studies by Hair et al., 2015; Hanson et al., 2013 show smaller hippocampal volumes in children from lower-income families, directly supporting the hypothesis that SES affects brain development, and affirming the necessity to examine state-level influences.

Theme 3: Neurological Impacts of Stress

Focuses on the relationship between chronic stress, common in low-income environments, and its harmful effects on brain structures such as the hippocampus.

Cited works by McEwen & Magarinos, 1997; Ivy et al., 2010 illustrate the biological mechanisms through which poverty-induced stress impacts brain development, validating the research question’s focus on the broader socio-economic context.

Theme 4: Role of Environmental and Macrostructural Factors

Examines how variations in state-level economic policies and the cost of living can influence the developmental outcomes of low-income families.

Studies such as Duncan et al., 2010 investigate state-specific variations and their impacts, essential for understanding how different macrostructural environments moderate SES effects on brain development and mental health.

Theme 5: Influence of Public Policies

Investigates the role of governmental interventions, like Medicaid and TANF, in mitigating the adverse effects of low SES on neurodevelopment.

Research by Costello et al., 2003; Noble et al., 2015 discusses the variability in policy effectiveness across states, which is crucial for assessing the hypothesis about macrostructural moderation of income effects.

Theme 6: Comparison with European Contexts

Compares findings from the U.S. to those in European countries to understand the potential impact of differing social policies on the association between income and brain volume.

Walhovd et al., 2022 suggests that social policy differences may lead to weaker associations in Europe, supporting the hypothesis by implying that macrostructural characteristics significantly influence health outcomes.

Question 5: Writing an Outline of the Literature Review

Below, write a detailed outline that arranges your literature review into sections based on the themes identified. Each section of the outline should build towards identifying the gaps in the literature, clearly outlining where further investigation is needed. Be sure to use in-text citations and then paste your full citations at the end of this table – use any citation format that you wish.

Structure:

• Introduction: Overview of the themes and structure of the review.
• Body: Detailed sections for each theme, with bullet points for key studies, findings, and how they relate to your research.
• Conclusion: Summarize how the reviewed literature supports your research question and hypothesis.

Your response to question 5:

Impact of Family Income on Childhood Development

Lower family income correlates with lower educational attainment, reliance on public assistance, and health issues in adulthood (Duncan, Ziol-Guest, & Kalil, 2010).

Socioeconomic status (SES) influences brain structure and mental health, affecting later-life outcomes (McLaughlin et al., 2011; Peverill et al., 2021).

Socioeconomic Influences on Brain Development

Consistent findings show smaller hippocampal volumes in children from lower-income families (Hair et al., 2015; Hanson et al., 2013).

Economic hardship limits resources available for child development, increasing exposure to stress (Evans, 2004; Evans et al., 2005).

Neurological Impacts of Stress

Chronic stress and adversity, common in low-income settings, detrimentally affect hippocampal structure (McEwen & Magarinos, 1997; Ivy et al., 2010).

Role of Environmental and Macrostructural Factors

Differences in state-level economic policies and cost of living can exacerbate or mitigate the impacts of low income on brain development and health (Duncan et al., 2010).

Influence of Public Policies

Anti-poverty programs like Medicaid and Temporary Assistance for Needy Families (TANF) may buffer negative effects of low SES on neurodevelopment (Costello et al., 2003; Noble et al., 2015).

Variability in policy implementation across states impacts the effectiveness of these interventions (Duncan et al., 2010).

Comparison with European Contexts

Studies suggest weaker associations between income and brain volume in European countries, potentially due to different social policies (Walhovd et al., 2022).

Hypotheses

Presents the study’s hypotheses that lower family income will be associated with smaller hippocampal volume and higher internalizing and externalizing problems, and that these associations will be moderated by state-level macrostructural characteristics.

Question 6: Drafting the Literature Review

Below, write the literature review based on your outline. Focus on synthesizing the information in a way that highlights gaps and argues for the need for your study. Be sure to use in-text citations and then paste your full citations at the end of this table – use any citation format that you wish.

Guidance:

• Use the PIER system to structure each paragraph, emphasizing the explanation of how the cited studies lead to the need for your research.
• Critically evaluate the methodologies, findings, and conclusions of the studies you include.

Your response to question 6:

For an example see the Introduction of:

Weissman, D.G., Hatzenbuehler, M.L., Cikara, M. et al. State-level macro-economic factors moderate the association of low income with brain structure and mental health in U.S. children. Nat Commun 14, 2085 (2023). https://doi.org/10.1038/s41467-023-37778-1

Your Citations:

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5. Noble KG, et al. Family income, parental education and brain structure in children and adolescents. Nat. Neurosci. 2015;18:773–778. doi: 10.1038/nn.3983. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

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Question 1: State Your Variables and Research Question

Below, restate your variables, research question(s), and hypothesis(es) from Assignment 1, you are welcome to have revised your research question or hypothesis.

Your response to Q1:

Question 2: Simple vs Complex Operationalization

Below, categorize your variables as simple or complex concepts. Explain why each variable is considered simple or complex based on the concepts they represent.

Your response to Q2:

Question 3: Operationalizing Simple Variables

Use the ABCD data dictionary to identify one to three specific questions/measures that correspond to your simple variables. Do this by filling in the table below. Erase the example before you begin. Add additional rows if necessary.

Question 4: Understanding Simple Measures

Below, for each simple variable, describe the instrument used to measure the variable. Explain how the instrument operationalizes the variable.

Details to Include:

• Instrument Type: Specify the type of instrument (e.g., survey, neurocognitive task, brain scan).
• Description of Instrument: Briefly describe the instrument, including any relevant details about its structure or components.
• How It Measures the Variable: Explain how the design and components of the instrument are used to measure the concept of your simple variable.

Your response to Q4:

Delete the EXAMPLE below and provide your own responses

Gender Identity (kbi_gender)

Instrument Type: Survey

Description of Instrument: The instrument used to measure the variable of gender identity in the ABCD study is a simple survey question that asks participants to identify their current gender identity. This survey item is part of a broader questionnaire (Youth Gender Survey: gish_y_gi), that includes various demographic and psychological measures. The question is designed to be inclusive by offering multiple response options beyond the traditional binary choices.

How It Measures the Variable:

The survey question operationalizes the concept of gender identity by allowing participants to self-identify their gender from a set of predefined categories. This method acknowledges the diversity of gender identities beyond the male/female binary by including options for “another gender” and providing an option for participants who may not understand the question or feel that none of the categories apply (“I don’t understand”). This approach ensures that participants can express their gender identity in a way that feels most accurate to them. The nominal level of measurement is appropriate here, as the data collected from this question categorizes individuals without implying any ordinal relationship or quantifiable difference between the categories. Each response is treated as a distinct category, which is crucial for respecting individual identity and for subsequent analyses that may explore correlations between gender identity and other variables in the study.

Question 5: Operationalizing Complex Variables

Use the ABCD data dictionary to identify multiple ABCD questions/measures that will compose your new, complex. Do this by filling in the table below. Erase the example before you begin. Add additional rows if necessary.

Question 6: Understanding Complex Measures

Below, for each complex variable identified in Question 5, provide a detailed explanation of the instrument used to measure the variable. Describe how the design of the instrument (e.g., questionnaire, neurocognitive task, brain scan) specifically measures the concept represented by your variable. Note: You should consult the ABCD wiki documentation (and/or scientific literature) to accurately describe and evaluate the measurement methods used for your complex variables. Use in-text citations and references.

Details to Include:

• Instrument Type: Specify the type of instrument (e.g., survey, neurocognitive task, brain scan).
• Description of Instrument: Briefly describe the instrument, including any relevant details about its structure or components.
• How It Measures the Variable: Explain how the design and components of the instrument are used to measure the concept of your complex variable. Discuss how the instrument’s methodology aligns with the operational definition of the variable.

Additional Guidance:

• If the complex variable is a survey (questionnaire), explain how the questions in the survey collectively measure the variable.
• If the complex variable is a neurocognitive task, describe the task’s setup and how it assesses the cognitive functions related to the variable.
• If the complex variable utilizes novel technology, then describe the specific technology used and how it contributes to the measurement of the variable. Refer to the ABCD study’s Novel Technologies documentation for detailed information on how these technologies are integrated and their roles in data collection.
• If the complex variable is a brain scan, detail the type of scan used (e.g., MRI, fMRI) and how the scan’s results relate to the variable being studied.

Your response to Q6:

Citations for Question 6:

Question 7: Reliability & Validity of Complex Measures

Discuss how the reliability and validity of the instruments used for your complex variables were tested. In some cases, you will need to check the ABCD wiki for this information, in other cases, you may need to search the internet for the specific measure (e.g., KSADS instruments) and how it has been tested for reliability and validity. Use in-text citations and references.

Your response to Q7:

Citations for Question 7:

Question 1: State Your Variables and Research Question

Below, restate your variables, research question(s), and hypothesis(es) from Assignment 1, you are welcome to have revised your research question or hypothesis.

Your response to Q1:

Is there a stronger association between anxiety and impulsivity, as measured by delay discounting scores, among urban adolescents compared to their rural counterparts, after controlling for family income?

Question 2: Simple vs Complex Operationalization

Below, categorize your variables as simple or complex concepts. Explain why each variable is considered simple or complex based on the concepts they represent.

Your response to Q2:

Family income is a simple variable because is it measured in one dimension – a family’s annual income.

Urban vs suburban vs rural residency is also a simple variable as it is measured in only one question at the nominal level.

Anxiety is a complex variable because …

Impulsivity as measured by delay discounting scores is also a complex variable because …

Question 3: Operationalizing Simple Variables

Use the ABCD data dictionary to identify one to three specific questions/measures that correspond to your simple variables. Do this by filling in the table below. Erase the example before you begin. Add additional rows if necessary.

Question 4: Understanding Simple Measures

Below, for each simple variable, describe the instrument used to measure the variable. Explain how the instrument operationalizes the variable.

Details to Include:

• Instrument Type: Specify the type of instrument (e.g., survey, neurocognitive task, brain scan).
• Description of Instrument: Briefly describe the instrument, including any relevant details about its structure or components.
• How It Measures the Variable: Explain how the design and components of the instrument are used to measure the concept of your simple variable.

Your response to Q4:

Family income

• Instrument Type: Demographic Questionnaire.
• Description of Instrument: The demographic questionnaire in the ABCD study collects basic information, including the participant’s date of birth.
• How It Measures the Variable: Participant’s parents are asked their total family income.

Urban/Rural Residence

• Instrument Type: Linked External Data.
• Description of Instrument: These measures were derived from publicly available census data from 2010 (https://www.census.gov/programs-surveys/geography/about/faq/2010-urban-area-faq.html).
• How It Measures the Variable: Urban area is a categorical variable indicating if participants’ addresses were in census tracts considered to be urban (50,000 or more people), urban clusters (at least 2,500 and less than 50,000 people) or rural (less than 2,500 people per tract, and/or not included in urban areas or clusters).

Question 5: Operationalizing Complex Variables

Use the ABCD data dictionary to identify multiple ABCD questions/measures that will compose your new, complex. Do this by filling in the table below. Erase the example before you begin. Add additional rows if necessary. Note: You should consult the ABCD wiki documentation to find the exact number of questions included in the table/assessment and information on the levels of measurement.

Question 6: Understanding Complex Measures

Below, for each complex variable identified in Question 5, provide a detailed explanation of the instrument used to measure the variable. Describe how the design of the instrument (e.g., questionnaire, neurocognitive task, brain scan) specifically measures the concept represented by your variable. Note: You should consult the ABCD wiki documentation (and/or scientific literature) to accurately describe and evaluate the measurement methods used for your complex variables. Use in-text citations and references.

Details to Include:

• Instrument Type: Specify the type of instrument (e.g., survey, neurocognitive task, brain scan).
• Description of Instrument: Briefly describe the instrument, including any relevant details about its structure or components.
• How It Measures the Variable: Explain how the design and components of the instrument are used to measure the concept of your complex variable. Discuss how the instrument’s methodology aligns with the operational definition of the variable.

Additional Guidance:

• If the complex variable is a survey (questionnaire), explain how the questions in the survey collectively measure the variable.
• If the complex variable is a neurocognitive task, describe the task’s setup and how it assesses the cognitive functions related to the variable.
• If the complex variable utilizes novel technology, then describe the specific technology used and how it contributes to the measurement of the variable. Refer to the ABCD study’s Novel Technologies documentation for detailed information on how these technologies are integrated and their roles in data collection.
• If the complex variable is a brain scan, detail the type of scan used (e.g., MRI, fMRI) and how the scan’s results relate to the variable being studied.

Your response to Q6:

Anxiety

• Instrument Type: The instrumentation to measure anxiety is the questionnaire KSADS – Generalized Anxiety Disorder.
• Description of Instrument: The KSADS is a semi-structured interview designed to assess current and past episodes of psychiatric illness in children and adolescents according to DSM criteria. It includes specific items focused on symptoms related to generalized anxiety disorder, such as excessive worry, restlessness, and fear.

How It Measures the Variable: The KSADS utilizes a scoring system where responses to various anxiety-related questions are quantified. Each response is scored based on severity and frequency, which are then summed to create a summary score representing the overall level of anxiety. This method allows for a detailed assessment of anxiety levels, providing a nuanced view of the severity and specific characteristics of anxiety in the individual.

Impulsivity measured by delay discounting

• Instrument Type: The instrumentation to measure impulsivity is the delay discounting task administered in ABCD.
• Description of Instrument: The delay discounting task in the ABCD study measures impulsivity by offering participants choices between smaller immediate rewards and larger delayed rewards at various time intervals. Participants are presented with various scenarios where they must choose between a smaller amount of money available immediately and a larger amount available after a delay, thereby revealing their preference for immediate versus delayed gratification.
• How It Measures the Variable: The task calculates the ‘indifference point’ at different delays to quantify impulsivity. This point is the amount at which the participant is equally likely to choose the immediate or delayed reward, reflecting their impulse control. Lower indifference points at shorter delays indicate higher impulsivity, as the participant favors smaller immediate rewards over larger delayed ones.

Citations for Question 6:

ABCD Wiki. KSADS – Social Anxiety Disorder (Indiv. Questions). https://wiki.abcdstudy.org/release-notes/non-imaging/mental-health.html#ksads—generalized-anxiety-disorder-indiv.-questions

Barch DM, Albaugh MD, Avenevoli S, Chang L, Clark DB, Glantz MD, Hudziak JJ, Jernigan TL, Tapert SF, Yurgelun-Todd D, Alia-Klein N, Potter AS, Paulus MP, Prouty D, Zucker RA, Sher KJ. Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: Rationale and description. Dev Cogn Neurosci. 2018 Aug;32:55-66. doi: 10.1016/j.dcn.2017.10.010. Epub 2017 Nov 3. PMID: 29113758; PMCID: PMC5934320

Johnson, M. W., & Bickel, W. K. (2008). An algorithm for identifying nonsystematic delay-discounting data. Experimental and clinical psychopharmacology, 16(3), 264–274

Question 7: Reliability & Validity of Complex Measures

Discuss how the reliability and validity of the instruments used for your complex variables were tested. In some cases, you will need to check the ABCD wiki for this information, in other cases, you may need to search the internet or literature for the specific measure (e.g., KSADS instruments) and how it has been tested for reliability and validity. Use in-text citations and references.

Your response to Q7:

Anxiety (measured by KSADS – Generalized Anxiety Disorder)

• Reliability: The KSADS has been extensively tested for reliability, including test-retest and inter-rater reliability. It consistently shows high reliability scores, indicating that the instrument measures anxiety consistently over time and across different raters (de la Peña 2018).
• Validity: The validity of the KSADS has been confirmed through various studies comparing its results with other established measures of anxiety and psychiatric diagnoses. Its ability to accurately assess generalized anxiety disorder in accordance with DSM criteria demonstrates its strong criterion validity (de la Peña 2018).

Impulsivity (Measured by delay discounting task)

• Reliability: The delay discounting task shows good internal consistency and test-retest reliability. This indicates that the task consistently measures the trait of impulsivity across time and similar testing conditions (Johnson et al 2020).
• Validity: The construct validity of the delay discounting task is supported by research linking performance on the task to impulsive behavior in real-world settings. The task’s results correlate with measures of impulsivity from other neuropsychological assessments, demonstrating its validity in measuring the intended psychological construct (Johnson et al 2020).

Citations for Question 7:

de la Peña, F.R., Villavicencio, L.R., Palacio, J.D. et al. Validity and reliability of the kiddie schedule for affective disorders and schizophrenia present and lifetime version DSM-5 (K-SADS-PL-5) Spanish version. BMC Psychiatry 18, 193 (2018). https://doi.org/10.1186/s12888-018-1773-0

Johnson, Kelli L., Michael T. Bixter, and Christian C. Luhmann. “Delay discounting and risky choice: Meta-analytic evidence regarding single-process theories.” Judgment and Decision Making 15.3 (2020): 381-400.

Assignment Questions

Your Responses

1) Restate your variables, research question(s), and hypothesis(es) from Assignment 1, you are welcome to have revised your research question or hypothesis.

Data Collection Procedures

2) Review the ABCD wiki and instrumentation literature. Based on this literature, describe how the data was collected for the instruments that you used in Assignment 3. Complete this for three different instruments, prioritizing the “complex” variables that you outlined in the Assignment 3. Note any data collection errors and corrections to these errors. Describe the first instrument:

Citations for Question 2:

3) Describe the second instrument:

Citations for Question 3:

4) Describe the third instrument:

Citations for Question 4:

Sample & Population

5) Describe how the demographics, any clinical characteristics, and geographical distribution in the ABCD sample align with variables of interest in your research question.

6) What will be your inclusion/exclusion criteria to build your sample from the ABCD data? Have you excluded participants based on recommendations found in the ABCD Wiki? These are recommendations by the ABCD Working Groups & ABCD Data Analytics and Informatics Core.

Any citations used for Question 6:

7) Search the ABCD publications for studies with similar or related inclusion/exclusion criteria as yours. What was the sample size and sample characteristics (demographics) in the study(s)? Use this data as an estimate of your sample size and demographics.

Citations for Question 7:

8) Describe your estimated sample’s representativeness of your research population. Consider key demographics of interest and their quantities in your estimated sample. Additionally, how will this affect the generalizability of your findings?

Any citations used for Question 8:

Assignment Questions

Your Responses

1) Restate your variables, research question(s), and hypothesis(es) from Assignment 1, you are welcome to have revised your research question or hypothesis.

Is there a stronger association between anxiety and impulsivity, as measured by delay discounting scores, among urban adolescents compared to their rural counterparts, after controlling for family income?

Data Collection Procedures

2) Review the ABCD wiki and instrumentation literature. Based on this literature, describe how the data was collected for the instruments that you used in Assignment 3. Complete this for three different instruments, prioritizing the “complex” variables that you outlined in Assignment 3. Note any data collection errors and corrections to these errors. Describe the first instrument:

Delay Discounting Task (DDT):

The ABCD study uses the Delay Discounting Task to assess decision-making and impulse control across different age groups. This task involves participants making choices between receiving smaller immediate rewards versus larger delayed rewards at various time intervals (6 hours, 1 day, 1 week, 1 month, 3 months, 1 year, and 5 years). The task is administered using standardized software on iPads, ensuring consistent delivery across study sites. The task has been part of the study since the 1-year follow-up and continued in subsequent waves without modifications.

Participants are presented with 42 choices, grouped into seven blocks based on the delay to the larger reward. Each block contains six choices where participants decide between a small immediate monetary reward or a hypothetical $100 reward delayed to a specified time in the future. As participants make choices, the amount of the immediate reward is adjusted to determine the point at which the participant is indifferent between the immediate smaller reward and the $100 delayed reward. This is known as the indifference point, where the participant values both options equally. The process continues until the subjective values of the immediate and delayed rewards converge.

The indifference points from each delay block are used to calculate the discounting curve, typically represented as a hyperbolic function. This curve reflects the decline in the subjective value of the reward as the delay increases, indicative of how much a person discounts the value of future rewards.

Quality Control: The task includes quality control measures to ensure that the discounting behavior follows a logical pattern (e.g., the subjective value should decrease as the delay increases). Data that do not follow this pattern are flagged for further review to determine if they should be excluded from analysis due to potential random or inconsistent responding by participants. This is measured by the JBPass criteria 1 and 2.

Citations for Question 2:

ABCD Study Consortium. (2024). Neurocognition: Delay discounting scores. Retrieved from https://wiki.abcdstudy.org/release-notes/non-imaging/neurocognition.html#delay-discounting-scores

Luciana, Monica, et al. “Adolescent neurocognitive development and impacts of substance use: Overview of the adolescent brain cognitive development (ABCD) baseline neurocognition battery.” Developmental cognitive neuroscience 32 (2018): 67-79.

3) Describe the second instrument:

KSADS – Generalized Anxiety Disorder, Youth Instrument (Indiv. Questions)

The ABCD study employs the Kiddie Schedule for Affective Disorders and Schizophrenia for School-Aged Children (KSADS-COMP) to assess Generalized Anxiety Disorder (GAD) among participants. This is a semi-structured interview designed to evaluate current and past symptoms of mood, anxiety, psychotic, and disruptive behavior disorders in children from ages 6 to 18. The KSADS-COMP, a computerized version, ensures detailed and standardized data collection across various diagnostic categories.

Data for the GAD individual questions (Release 5.0 Data Table: mh_y_ksads_gad) is collected across multiple waves, including baseline, 2-year follow-up, and 4-year follow-up. The KSADS 2.0, introduced in the 3-year follow-up, includes a range of questions designed to comprehensively assess GAD symptoms.

This data collection method also considers the developmental appropriateness of the assessments, adjusting the age range for self-reports based on research and expert advice. The ABCD study ensures that all research assistants are well-trained to support young participants during the completion of the KSADS, with ongoing training provided to maintain high standards of data collection integrity and accuracy.

In addition to standard assessments, special protocols are in place at each study site to address any concerning reports from parents or youths, such as self-harm or suicidal ideation, ensuring immediate and appropriate responses. The study also periodically updates the assessment tools and procedures to align with developmental needs as participants age, ensuring that the data remains relevant and valid throughout the longitudinal study.

Citations for Question 3:

ABCD Study Consortium. (2024). Youth Instruments: Kiddie Schedule for Affective Disorders and Schizophrenia for School-Aged Children. Retrieved from Mental Health (abcdstudy.org)

Barch, Deanna M., et al. “Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: Rationale and description.” Developmental cognitive neuroscience 32 (2018): 55-66.

4) Describe the third instrument:

Urban vs suburban vs rural residency

The ABCD data collection process for the variable reshist_addr1_urban_area from the led_l_urban table is structured to capture the urban or rural classification of participants’ addresses based on U.S. Census definitions. The urban or rural classification is based on census tracts’ population counts from the 2010 U.S. Census data. These classifications are:

• Urbanized Areas (UAs): Areas with 50,000 or more people.
• Urban Clusters (UCs): Areas with at least 2,500 but less than 50,000 people.
• Rural: Areas encompassing all population, housing, and territory not included within an urban area or cluster.

This variable categorizes participants’ residential addresses into one of the three categories above, helping researchers analyze the impact of urban versus rural living environments on various developmental outcomes.

Collection Process: Initially, the data collection involved capturing participants’ residential addresses at a single point in time, generally assumed to be their baseline addresses. This method did not account for possible changes in addresses over time. There have been efforts by the ABCD Policy Working Group to improve the accuracy and comprehensiveness of residential history data. This includes better capturing of both retrospective and prospective address changes to reflect the participant’s actual residential locations throughout the study’s timeline. Earlier versions of the data dictionary had errors in labeling urbanicity, which were corrected in subsequent releases. The corrected categorizations are now included in the latest release notes and data dictionary. Ongoing updates are planned to further refine the data collection of residential histories. Until the updates are fully implemented, researchers are advised to consider the limitations and assumptions of the currently available data, particularly that earlier data might only reflect baseline addresses without accounting for possible moves or changes in urbanicity status over time.

Citations for Question 4:

ABCD Study Consortium. (2024). Linked External Data: Urban/Rural Area (Census). Retrieved from Linked External Data (abcdstudy.org)

Sample & Population

5) Describe how the demographics, any clinical characteristics, and geographical distribution in the ABCD sample align with variables of interest in your research question.

The ABCD study encompasses a diverse geographical distribution, which aligns with the variables of interest in our research question regarding anxiety and impulsivity among adolescents. The nationwide scope of the study ensures that urban and rural populations are well-represented, allowing us to investigate the effects of different environments on psychological outcomes. The clinical characteristics, such as anxiety levels measured through KSADS and impulsivity through the Delay Discounting Task, are assessed across a wide demographic range, including various socioeconomic statuses, ethnic backgrounds, and ages. This diversity enables a comprehensive analysis of how these factors might interact with our variables of interest, potentially affecting the generalizability of our findings to broader populations.

6) What will be your inclusion/exclusion criteria to build your sample from the ABCD data? Have you excluded participants based on recommendations found in the ABCD Wiki? These are recommendations by the ABCD Working Groups & ABCD Data Analytics and Informatics Core.

Considering the delay discounting data, the ABCD Wiki states: “The ABCD consortium Neurocognition Workgroup recommends caution in using data from cases wherein ‘values.JBPass1_NumberViolations’ is greater than 1 or 2.” Similarly, the same workgroup cautions inclusion of participants with data from cases wherein “values.Consistent_per_JBcriterion2” is not “yes” (ABCD Study Consortium 2024). Generally, this means that ABCD Neurocognition Workgroups favors excluding participants with illogical responses to the delay discounting task, as these cases would not meet data quality standards. This criterion helps ensure that the data analyzed reflects genuine discounting behavior rather than random or non-systematic responses.

For this reason, in previous studies utilizing ABCD data on delay discounting, large sections of the dataset showed issues with data quality, particularly in responses that did not display systematic discounting behavior. Following the methodologies of Kohler et al. (2022) and Sloan et al. (2023), my study will apply strict inclusion/exclusion criteria focusing on systematic responding. Specifically, only participants who display monotonically decreasing indifference scores, without exceeding a 20% increase from one delay to the next sooner delay, will be included.

Any citations used for Question 6:

ABCD Study Consortium. (2024). Neurocognition: Delay discounting scores. Retrieved from https://wiki.abcdstudy.org/release-notes/non-imaging/neurocognition.html#delay-discounting-scores

Sloan, Matthew E., et al. “Delay discounting and family history of psychopathology in children ages 9–11.” Scientific Reports 13.1 (2023): 21977.

Kohler, R. J., Lichenstein, S. D., & Yip, S. W. (2022). Hyperbolic discounting rates and risk for problematic alcohol use in youth enrolled in the Adolescent Brain and Cognitive Development study. Addiction biology, 27(2), e13160. https://doi.org/10.1111/adb.13160

7) Search the ABCD publications for studies with similar or related inclusion/exclusion criteria as yours. What was the sample size and sample characteristics (demographics) in the study(s)? Use this data as an estimate of your sample size and demographics.

From Kohler et al 2022:

N = 4,357

Sex

 F1,975

 M2,382

Household Income

 [<50K]837

 [>=100K]2,050

 [>=50K & <100K]1,166

 N/A304

From Sloan et al 2023:

White: 3138 (71.9%)

Black: 386 (8.8%)

Asian: 115 (2.6%)

Other/mixed: 686 (15.7%)

Citations for Question 7:

Sloan, Matthew E., et al. “Delay discounting and family history of psychopathology in children ages 9–11.” Scientific Reports 13.1 (2023): 21977.

Kohler, R. J., Lichenstein, S. D., & Yip, S. W. (2022). Hyperbolic discounting rates and risk for problematic alcohol use in youth enrolled in the Adolescent Brain and Cognitive Development study. Addiction biology, 27(2), e13160. https://doi.org/10.1111/adb.13160

8) Describe your estimated sample’s representativeness of your research population. Consider key demographics of interest and their quantities in your estimated sample. Additionally, how will this affect the generalizability of your findings?

According to Sloan et al (2023): “There were significant demographic differences between the full sample and the subsample that met data quality criteria, where those that met the criteria were more likely to be White, non-Hispanic, have higher household income, greater parental education, and live in houses where their parents were married.”

Therefore, my anticipated sample will be skewed towards White, non-Hispanic participants, with higher household incomes and higher parental education levels. Race is not explicitly one of the variables in my research question, but urban residency is, and race tends to correlate with urban residency. Such a demographic skew could limit the generalizability of my study’s findings, as the sample may not adequately represent the broader, more diverse population.

Any citations used for Question 8:

Sloan, Matthew E., et al. “Delay discounting and family history of psychopathology in children ages 9–11.” Scientific Reports 13.1 (2023): 21977.

Question

Response

1) Restate your variables, research question(s), and hypothesis(es) from Assignment 1, you are welcome to have revised your research question or hypothesis.

Data Ethics

2) Describe how you will adhere to Clause 3 of the DUC, which prohibits the distribution of data. Outline steps you will take to ensure data is only shared with authorized collaborators. What mechanisms will you put in place to verify that collaborators are authorized under the DUC and to prevent unauthorized data sharing?

3) According to Clause 5, data re-identification is strictly prohibited. Discuss the measures you will implement to ensure that no identification of study participants occurs through your handling or analysis of the data. How will you handle and report findings in publications to avoid any potential re-identification of the data subjects?

4) Detail your compliance plan for Clauses 8 and 9 of the DUC concerning data security and the deletion of data. Describe the security measures you will implement to protect the data and outline the process for securely deleting the data once your research is completed or if the DUC is terminated.

Data Analysis

5) Discuss any planned methods for handling missing data or potential outliers.

Citations for question 5:

6) What statistical tests will you use to analyze the data and address your research questions? For each (test) analysis, why did you choose these statistical tests? Explain your rationale. Preferably, your explanation should be based on ABCD literature.

Citations for Question 6:

7) What do you expect to find? Describe what results you expect to find and why, based on your hypotheses and prior research. How will you interpret these findings?

Citations for Question 7 (if applicable):

8) Describe the steps you will take to ensure that your analysis is reproducible. What documentation will you provide to support the reproducibility of your results?

9) Below, describe the main limitations of your study. Areas to consider:

• Sources of Bias: Reflect on any biases that may arise from the study design, research questions, selection of instruments, and the sampling method. How might these biases influence the outcomes of your study?
• Data Collection and Reliability: Evaluate how the methods of data collection could affect the reliability and validity of your study results. Consider aspects such as the consistency of data collection procedures and any factors that may lead to data degradation over time.
• Statistical Limitations: Discuss any limitations related to the statistical methods chosen for data analysis. How might these limitations affect the interpretation and generalizability of your results?
• External Validity: Consider how generalizable your findings are to other settings or populations based on the sample and data analysis methods used.

Any citations used for Question 9:

Question

Response

1) Restate your variables, research question(s), and hypothesis(es) from Assignment 1, you are welcome to have revised your research question or hypothesis.

Is there a stronger association between anxiety and impulsivity, as measured by delay discounting scores, among urban adolescents compared to their rural counterparts, after controlling for family income?

Data Ethics

2) Describe how you will adhere to Clause 3 of the DUC, which prohibits the distribution of data. Outline steps you will take to ensure data is only shared with authorized collaborators. What mechanisms will you put in place to verify that collaborators are authorized under the DUC and to prevent unauthorized data sharing?

Example not provided 😊

3) According to Clause 5, data re-identification is strictly prohibited. Discuss the measures you will implement to ensure that no identification of study participants occurs through your handling or analysis of the data. How will you handle and report findings in publications to avoid any potential re-identification of the data subjects?

Example not provided 😊

4) Detail your compliance plan for Clauses 8 and 9 of the DUC concerning data security and the deletion of data. Describe the security measures you will implement to protect the data and outline the process for securely deleting the data once your research is completed or if the DUC is terminated.

Example not provided 😊

Data Analysis

5) Discuss any planned methods for handling missing data or potential outliers.

My study is less concerned with generalizability and representativeness as my sample will be constrained due to data quality control problems with the delay discounting data (Sloan et al., 2023; Kohler et al., 2022). Therefore, I will delete missing values. Moreover, the ABCD Consortium recommends this approach for delay discounting data: “Many investigators simply exclude data from participants who do not discount at all” (ABCD Wiki, 2024). Sloan et al. (2023) found about 8 percent of data was missing for family income (which is also my control variable). Similarly, any missing data for generalized anxiety disorder will also be handled with deletion. This will ensure that my data is clean and that the analyses are not distorted by non-responsive or non-participating segments of the sample. Lastly, the data quality control protocols in delay discounting and KSAD Generalized Anxiety Disorder naturally address outliers.

Citations for question 5:

Sloan, Matthew E., et al. “Delay discounting and family history of psychopathology in children ages 9–11.” Scientific Reports 13.1 (2023): 21977.

Kohler, R. J., Lichenstein, S. D., & Yip, S. W. (2022). Hyperbolic discounting rates and risk for problematic alcohol use in youth enrolled in the Adolescent Brain and Cognitive Development study. Addiction biology, 27(2), e13160. https://doi.org/10.1111/adb.13160

ABCD Study Consortium. (2024). Neurocognition: Delay discounting scores. Retrieved from https://wiki.abcdstudy.org/release-notes/non-imaging/neurocognition.html#delay-discounting-scores

6) What statistical tests will you use to analyze the data and address your research questions? For each (test) analysis, why did you choose these statistical tests? Explain your rationale. Preferably, your explanation should be based on ABCD literature.

To analyze the Delay Discounting Task data, I will do use statistical tests:

• Area Under the Curve (AUC) and Discounting Constant (k):
• Purpose: To measure delay discounting quantitatively.
• Explanation: These metrics summarize how individuals value future versus immediate rewards. The AUC provides a single value that represents an individual’s tendency to prefer smaller immediate rewards over larger delayed ones, and ‘k’ represents the rate at which the value of a delayed reward decreases over time (ABCD 2024).
• Data Quality Criteria
• Purpose: To ensure that the data used in the study meets a minimum standard of reliability.
• Explanation: This involves rules to exclude data that do not show consistent decision-making patterns, which might indicate random or nonsensical responses rather than true behavioral tendencies. This is measured using the JBPass1 and JBPass 2 criteria (ABCD 2024).

To analyze the relationship between generalized anxiety disorder and delay discounting for urban are rural residents, controlling for family income, I will use two statistical tests:

• Correlational Analysis
• Purpose: To determine if there is a relationship between generalized anxiety disorder and delay discounting and delay discounting behavior in youth.
• Method Used: Spearman’s correlation coefficients, based on Sloan et al (2023).
• Explanation: Sloan et al (2023) used this method assesses how strongly the delay discounting behavior is associated with the presence of psychopathology in family members. The values of correlation range from -1 to 1, where values closer to 0 suggest no correlation, and values closer to -1 or 1 suggest a strong negative or positive correlation, respectively.

• Multivariate Regression
• Purpose: To analyze the effects of generalized anxiety disorder and impulsivity on urban versus rural adolescents, while controlling for socioeconomic factors such as family income.
• Method Used: Multiple regression analysis, which is ideal for examining the relationship between multiple independent variables and a single dependent variable. This method is appropriate for your research as it allows for the control of various confounding variables, ensuring that the observed effects on delay discounting scores are more directly attributable to anxiety levels rather than other factors.
• Explanation: This statistical test is used to determine the unique contribution of each predictor (anxiety and impulsivity) to the outcome variable (delay discounting scores) while accounting for other variables. For instance, it can help identify whether the impact of anxiety on decision-making is consistent across different socio-economic backgrounds and residential settings. Multiple regression is particularly useful in behavioral research for exploring the interrelationships between complex psychological traits and their behavioral outcomes.

Citations for Question 6:

ABCD Study Consortium. (2024). Neurocognition: Delay discounting scores. Retrieved from https://wiki.abcdstudy.org/release-notes/non-imaging/neurocognition.html#delay-discounting-scores

Sloan, Matthew E., et al. “Delay discounting and family history of psychopathology in children ages 9–11.” Scientific Reports 13.1 (2023): 21977.

7) What do you expect to find? Describe what results you expect to find and why, based on your hypotheses and prior research. How will you interpret these findings?

Based on the existing literature, I anticipate finding that anxiety will be associated with increased delay discounting scores among urban adolescents, but not for rural residents, particularly after controlling for family income. This expectation aligns with previous studies that have demonstrated stronger associations between anxiety and impulsivity in urban settings (Xia et al., 2017; Van der Wal et al., 2013).

Several key points underpin this hypothesis:

Influence of Anxiety: In general, the literature on the relationship between anxiety and delay discounting is mixed, with some studies showing stronger associations (Xia et al., 2017; Rounds et al., 2007), other studies finding none (Jenks & Lawyer, 2015), and other studies finding a negative association (anxiety leads to less impulsivity) (Steinglass et al., 2017). My study seeks to clarify this relationship in the context of urban vs. rural environments.

Urban vs. Rural Differences: Van der Wal et al. (2013) found that calming, natural landscapes are associated with less delay discounting (less impulsivity), while other studies found disadvantaged urban environments are associated with more delay discounting (Cheong et al., 2014).

Family History and Psychopathology: Sloan et al. (2023) highlight that only family history of depression was associated with increased delay discounting (anxiety was not considered). While my study focuses on anxiety, the patterns observed in Sloan et al. suggest that different forms of family histories of psychopathology could differentially affect impulsivity.

Interpretation of Findings:

If the anticipated pattern is observed — stronger associations of anxiety with impulsivity among urban adolescents — this would suggest that environmental factors moderate the relationship between anxiety and decision-making behaviors.

A lack of significant association among rural adolescents would further underscore the role of environmental context in shaping the psychological impacts of anxiety.

Citations for Question 7 (if applicable):

Xia, L., Gu, R., Zhang, D. and Luo, Y., 2017. Anxious individuals are impulsive decision-makers in the delay discounting task: An ERP study. Frontiers in behavioral neuroscience, 11, p.5.

Rounds, J.S., Beck, J.G. and Grant, D.M., 2007. Is the delay discounting paradigm useful in understanding social anxiety?. Behaviour research and therapy, 45(4), pp.729-735.

Steinglass, J.E., Lempert, K.M., Choo, T.H., Kimeldorf, M.B., Wall, M., Walsh, B.T., Fyer, A.J., Schneier, F.R. and Simpson, H.B., 2017. Temporal discounting across three psychiatric disorders: anorexia nervosa, obsessive compulsive disorder, and social anxiety disorder. Depression and Anxiety, 34(5), pp.463-470.

Armstrong, C.H. and Hoge, E.A., 2024. Associations of Delay Discounting Rate with Anxiety Disorder Symptomatology and Diagnoses. The Psychological Record, pp.1-16.

Jenks, C.W. and Lawyer, S.R., 2015. Using delay discounting to understand impulsive choice in socially anxious individuals: Failure to replicate. Journal of Behavior Therapy and Experimental Psychiatry, 46, pp.198-201.

Van der Wal, A.J., Schade, H.M., Krabbendam, L. and Van Vugt, M., 2013. Do natural landscapes reduce future discounting in humans?. Proceedings of the Royal Society B: Biological Sciences, 280(1773), p.20132295.

Cheong, J., Tucker, J.A., Simpson, C.A. and Chandler, S.D., 2014. Time horizons and substance use among African American youths living in disadvantaged urban areas. Addictive behaviors, 39(4), pp.818-823.

8) Describe the steps you will take to ensure that your analysis is reproducible. What documentation will you provide to support the reproducibility of your results?

All analyses will be conducted using R statistical software. I will provide the complete R scripts used for all statistical tests, including data cleaning, transformation, analysis, and visualization steps. I will provide any accompanying document explaining the rationale for the choice of statistical tests, the model assumptions checked, and the parameter settings for each test. I will share the scripts and the accompanying document on Github for other researchers to reproduce my analysis.

9) Below, describe the main limitations of your study. Areas to consider:

• Sources of Bias: Reflect on any biases that may arise from the study design, research questions, selection of instruments, and the sampling method. How might these biases influence the outcomes of your study?
• Data Collection and Reliability: Evaluate how the methods of data collection could affect the reliability and validity of your study results. Consider aspects such as the consistency of data collection procedures and any factors that may lead to data degradation over time.
• Statistical Limitations: Discuss any limitations related to the statistical methods chosen for data analysis. How might these limitations affect the interpretation and generalizability of your results?
• External Validity: Consider how generalizable your findings are to other settings or populations based on the sample and data analysis methods used.

Sources of Bias:

Based on Sloan et al (2023), my anticipated sample will disproportionately include participants who are White, non-Hispanic, from higher-income households, and with greater parental education levels. This introduces selection bias. This demographic skew is likely to influence the study outcomes as it may not accurately represent the broader population, particularly in urban areas where racial and economic diversity is higher. This limitation is crucial because urban residency, a key variable in my study, is correlated with race and socioeconomic status, potentially confounding the study results.

Statistical Limitations:

The chosen statistical methods, while robust, have inherent limitations that could affect the interpretation of the data. For example, the use of complex multivariable models requires assumptions about the distribution and independence of variables that may not hold in all cases.

External Validity:

The generalizability of the findings is limited by the nature of the sample and the study design. As mentioned, the sample is skewed towards a particular demographic, which may not represent the broader population effectively, especially in different geographic or cultural settings. This limitation impacts the external validity of the study, as the findings may not be applicable to other populations with different demographic characteristics.

Any citations used for Question 9:

Sloan, Matthew E., et al. “Delay discounting and family history of psychopathology in children ages 9–11.” Scientific Reports 13.1 (2023): 21977.

Item to Include in Your Preregistration

✔

Title: Enter the Title of Your Project

Research Questions

• Begin with your literature review From Assignment 2
• Conclude your literature review with your research questions and hypotheses from Assignment 1

Variables & Measures

• Detail the measures and instruments used to collect data, as outlined in Assignment 3.
• Describe the operational definitions of all variables.

Sampling

• Describe the population and sampling methods.
• Explain your inclusion and exclusion criteria from Assignment 4.
• Mention the estimated sample size and how it was determined using prior studies from Assignment 4.

Data Collection

• Outline the procedures for data collection including any steps to ensure consistency and reliability from Assignments 3 & 4.
• Note any specific settings or conditions under which data will be collected.

Ethics

• Explain how ethical considerations, especially those related to data privacy and participant consent, are addressed from Assignment 5.
• Refer to specific clauses from the ABCD Data Use Certificate that apply to your study.

Data Analysis Plan

• Describe the statistical tests you will use to analyze the data from Assignment 5.
• Explain the rationale for choosing these tests based on literature from Assignment 5.
• Discuss any planned methods for handling missing data or potential outliers from Assignment 5.

Limitations

• Identify potential sources of bias and other limitations in your study design from Assignment 5.
• Discuss the implications of these limitations for the interpretation of your results.

Expected Outcomes

• Describe what results you expect to find and why, based on your hypotheses and prior research, from Assignment 5.

References

• Include all references to all citations from Assignments 1-5.