Mental Health Research Methods Quiz

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Questions and Answers

What was the primary outcome measured in the study investigating the effectiveness of mirtazapine?

Beck Depression Inventory scores (correct)

Blood pressure

Body Mass Index (BMI)

Height

What statistical method was used to analyze the continuous outcome data in the study?

ANOVA

T-test

Linear regression (correct)

Chi-square test

What was the mean BDI-II score for the active treatment group at 12 weeks of follow-up?

19.7

18.0 (correct)

20.5

17.3

What was the mean difference in BDI-II scores between the active treatment group and the placebo group?

-1.7 Signup and view all the answers

How many adults were recruited for the study on mirtazapine?

480 Signup and view all the answers

What are the three most common types of outcome measurement seen in mental health research papers?

Continuous outcomes, binary outcomes, time-to-event outcomes Signup and view all the answers

Which statistical concept is important for understanding the reliability of study conclusions?

Confidence intervals Signup and view all the answers

In the PICO framework, which component refers to what researchers measure?

Outcome Signup and view all the answers

Why is statistics particularly important in mental health research?

To answer questions about mental health in the population Signup and view all the answers

Which of the following is NOT one of the steps in the four-step approach to research?

Sample size Signup and view all the answers

What are binary outcomes in the context of mental health research?

Outcomes that produce two distinct categories Signup and view all the answers

What is the goal of hypothesis testing in statistical analyses?

To evaluate evidence against a null hypothesis Signup and view all the answers

What does a p-value indicate in statistical analysis?

The likelihood of observing the data if the null hypothesis is true Signup and view all the answers

What is the risk of depression for children with adverse childhood experiences (ACEs)?

10% Signup and view all the answers

Which of the following statements is true regarding the odds of depression in children without ACEs?

Odds are calculated as 160/3,200. Signup and view all the answers

What does an odds ratio greater than 1 indicate?

There is an increased risk in the exposed. Signup and view all the answers

Which variable serves as the exposure in the longitudinal study?

Presence of adverse childhood experiences (ACEs). Signup and view all the answers

What does a risk ratio of 1 indicate about the comparison between two groups?

No difference in risk between the groups. Signup and view all the answers

Why is odds more commonly used than risk in health research?

Odds provide a clearer understanding of exposure effects. Signup and view all the answers

What outcome variable is measured at age 16 in the longitudinal study?

Diagnosis of depression. Signup and view all the answers

What is the interpretation of an incidence rate ratio (IRR) greater than 1?

The incidence rate is higher in the exposed group compared to the unexposed group. Signup and view all the answers

How can Poisson regression models be adjusted in analyzing incidence rates?

By adjusting for multiple confounders or covariates. Signup and view all the answers

Which is the correct null hypothesis statement for comparing outcomes between groups?

There is no difference in the outcome between the groups. Signup and view all the answers

In the context of depression rates among males and females, what were the rates for females aged 16-20?

20.92 Signup and view all the answers

What does a confidence interval (CI) generated around the IRR represent?

The range in which the true IRR is likely to fall. Signup and view all the answers

How can one disprove the hypothesis that depression always begins during adolescence?

By finding just one individual who had their first episode as an adult. Signup and view all the answers

What determines the outcome variable when using Poisson regression in mental health research?

It must be a count variable. Signup and view all the answers

Which rate indicates a higher level of depression between females and males in the provided data?

Females with a rate of 20.92. Signup and view all the answers

What is the null value that would represent the null hypothesis when interpreting risk or odds ratios?

1 Signup and view all the answers

Which statement best describes a p-value in the context of hypothesis testing?

It reflects the strength of evidence against the null hypothesis. Signup and view all the answers

How should p-values be interpreted regarding their thresholds?

Thresholds like 0.05 are arbitrary and can be misleading. Signup and view all the answers

What does a smaller p-value indicate about the null hypothesis?

Stronger evidence against the null hypothesis. Signup and view all the answers

Why is it considered bad practice to interpret p-values based solely on a threshold?

It can overlook the actual evidence provided by the p-value. Signup and view all the answers

What does a p-value of 0.035 suggest in comparison to a p-value of 0.051?

0.035 implies a greater significance than 0.051. Signup and view all the answers

What does it mean when the p-value approaches 1?

There is little evidence against the null hypothesis. Signup and view all the answers

What aspect of p-values is emphasized regarding their reporting?

Precise values should be reported for clarity. Signup and view all the answers

What is the primary effect estimate produced by logistic regression?

Odds Ratio Signup and view all the answers

Which statistical method is primarily used to compare two rates?

Poisson Regression Signup and view all the answers

How does risk differ from rate in a study context?

Risk measures outcomes relative to the initial population at risk. Signup and view all the answers

What is a crucial component to include in the denominator to reduce bias?

Person years at risk Signup and view all the answers

Which of the following can logistic regression accommodate in its analysis?

Multiple binary, categorical, or continuous exposures Signup and view all the answers

In a cohort study, what is a primary characteristic of how participants are followed?

They are grouped by a common exposure characteristic. Signup and view all the answers

What occurs when participants are in a study for longer observation periods?

The risk of outcome events generally increases. Signup and view all the answers

What does the term 'immortal time bias' refer to in pharmacoepidemiology?

Time during which participants cannot develop outcomes due to study rules. Signup and view all the answers

Study Notes

Session 4: 4th Oct - pt2

Introduction to Applied Statistics:
- Covered three common outcome variables in mental health research: continuous, binary, and rates.
- Used practical examples to determine appropriate statistical methods.
- Provided how to interpret results from research papers.
- Reading material available from PSBS0002: Core Principles of Mental Health Research | University College London (talis.com)
- Class preparation included webpages on calculating the mean value, standard deviation, and variance.
Objectives:
- Describe the aims of statistical analyses and investigations.
- Comment on three primary outcome measurements in mental health research papers:
  - Continuous outcomes
  - Binary outcomes
  - Count outcomes
  - Time-to-event outcomes
Why use statistics in mental health?:
- Answer questions about mental health within the population.
- Example questions include:
  - How common are mental health problems?
  - Who is more likely to develop mental health problems?
  - Causes of mental health problems?
  - Outcomes of mental health problems?
  - Which treatments are effective?
PICO Framework:
- Four-step approach to research:
  - Patient/problem
  - Intervention
  - Comparison
  - Outcome
- Simple framework for understanding research.
- Example research question: Are adverse childhood experiences (ACEs) associated with psychotic symptoms in adolescence?
Step 2: Define the Comparison:
- Comparing two or more groups using examples like: Those exposed to risk factors versus those not exposed.
- Example: Comparing treatment effectiveness (e.g., mirtazapine + sertraline vs. sertraline alone).
Step 3: Collect & Summarise Data:
- Gathering mental health data on psychotic, depressive symptoms, and other relevant variables.
- Collection often takes place at multiple time points.
Step 4: Test for Differences Between Groups:
- Determining the magnitude of differences using effect size or association measures (e.g., mean difference, odds ratio, risk ratio).
- Estimating the results' precision using 95% confidence intervals (CI).
- Testing statistical significance using p-values.

Continuous Outcomes

Comparing Two Means:
- Linear Regression
- What does continuous outcome mean? (quantitative trait, e.g., depression, psychotic, eating disorder symptom score, BMI, height, age, blood pressure)
- Example: Research into the efficacy of combining mirtazapine with another antidepressant for resistant depression. Randomizing participants to active treatment (mirtazapine + usual antidepressant) or placebo (placebo + usual antidepressant), and monitoring depressive symptoms over 12, 24, and 52 weeks using the Beck Depression Inventory(BDI-II).

Binary Outcomes

Comparing Two Proportions:
- Probability, risks, and odds. Logistic regression.
Frequentist Definition: Probability = proportion of times that event would occur across numerous trials.
Example: Exploring the link between adverse childhood experiences (ACEs) and depression in adolescence.
- Longitudinal study (4000 children aged 8-16) tracking ACEs exposure against depression diagnosis at age 16 using binary variables (exposed/unexposed, depression/no depression).
- Calculate risks, odds, and odds ratios for these groups.
- Calculation of risk and odds ratios, relating the probability to the observed values.
Risks:
- Risk of outcome in the exposed = a / (a + b)
- Risk of outcome in the unexposed = c / (c + d)
Odds:
- Odds of outcome in exposed = a/b
- Odds of outcome in unexposed = c/d
- Odds ratios = (odds in exposed)/(odds in unexposed)
Key summary of risk and odds: Ratios close to 1 (or 0) would indicate no difference, ratios greater than 1 could indicate high risk.

Count Outcomes/Rates

Comparing Two Rates:
- Incidence rate ratios, Poisson regression.
- Mostly used in cohort studies.
- People with and without known exposures followed over time
Information Collection: Exposure and outcomes tracked over the observation period. Calculating incidence rates and ratios.
Example: Investigating the link between family socioeconomic position in childhood and the development of depressive symptoms.
- Observing a population (e.g., specific birth cohort) to measure socioeconomic status and tracking how many develop depressive symptoms over a period of time. Calculated incidence rates for those with certain exposures against those with no exposures.

Hypothesis Testing and P-values

Null-hypothesis:
- There's no difference between groups.
P-Values:
- Probability of obtaining results at least as extreme as the observed ones if the null hypothesis were true.
- Low p-value indicates strong evidence against the null hypothesis.
Interpretation: Smaller p-values indicate stronger evidence against the null hypothesis. Larger p-values indicate weaker evidence against the null hypothesis and may need further investigation.
Confidence Intervals:
- Range of likely values for an unknown population parameter (e.g., mean).
- 95% CI range means there's a 95% confidence that the range will include the true value.

Cox Regression Model

This model explores the relationship between a time-to-event outcome.
Example: How long until an event occurs (e.g. first episode of depression)?
Examining how well an external factor predicts how long a person might take to experience that outcome.

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Description

Test your knowledge on the study methodologies used in mental health research, particularly focusing on mirtazapine. This quiz covers various aspects such as outcome measurement, statistical methods, and the PICO framework. Enhance your understanding of key concepts that influence study conclusions in mental health studies.