Practice Quiz – 4c1ee5 – PassMRCPsych.com

Implement the plan
Collect feedback
Study the results
Develop a SMART plan
Adjust the plan

Plan
Do
Study
Act
Collect feedback

Plan
Do
Study
Act
Collect feedback

Ignore feedback
Collect feedback from patients and staff
Focus on external feedback only
Rely on intuition
Implement changes without explanation

To promote transparency, accountability, and continuous improvement
To increase profits
To reduce staff workload
To focus solely on patient satisfaction
To identify the most successful healthcare providers

By identifying areas where patient care can be improved
By focusing solely on cost reduction
By increasing the workload of healthcare providers
By ignoring patient feedback
By providing bonuses to the best-performing staff

To provide financial incentives
To hold healthcare providers accountable
To determine promotion opportunities
To focus on the physical appearance of healthcare facilities
To prioritize personal opinions over performance metrics

Promoting learning and professional development
Ignoring the need for continuous improvement
Focusing on individual performance over team performance
Prioritizing administrative tasks over patient care
Emphasizing theoretical knowledge over practical skills

Provide a single treatment option
Discourage questions
Provide clear and accurate information
Ignore patients' emotions
Focus solely on their own opinions

Decision aids
Financial calculators
Cooking recipes
Travel guides
Fashion magazines

The patient's favourite colour
The patient's values and preferences
The patient's favourite TV show
The patient's favourite food
The patient's zodiac sign

Ignore the patient's emotions
Tell the patient not to worry
Acknowledge and address the patient's emotions
Advise the patient to consult a psychic
Ask the patient to leave the clinic

Provide a list of medications
Assess the patient's understanding of hypertension
Recommend the most effective medication
Explain potential side effects
Discuss the cost of medications

Only provide information about the benefits
Only provide information about the risks
Provide information about both the benefits and risks
Make the decision for the patient
Tell the patient to research the treatment independently

Avoid discussing alternatives
Use medical jargon to explain options
Recommend a treatment option without discussing others
Encourage the patient to ask questions
Make the decision quickly to save time

Provide all information at once
Use a step-by-step approach
Present only the most expensive options
Withhold information about potential complications
Offer only one treatment option

Focus solely on the surgical option
Offer a second opinion
Pressure the patient to decide immediately
Explain the benefits of surgery only
Withhold information about potential risks

Utilize scare tactics
Use peer pressure
Provide evidence-based information
Share personal opinions
Suggest that the patient rely on intuition

Use simple language
Provide written materials
Use visual aids
Involve a family member or friend
All of the above

The patient's values and preferences
The patient's financial situation
The patient's social support system
The patient's cultural background
All of the above

Credibility
Transferability
Sample size
Dependability
Confirmability

Qualitative research
Quantitative research
Mixed methods research
Case study research
Action research

Appropriateness of the method
Clarity of the description
Reliability and validity
Researcher's biases and reflexivity
All of the above

Appropriateness of the research question
Clarity of the design
Justification of the sample size
Rigor and trustworthiness of the findings
All of the above

To perform a comprehensive literature search
To provide a high-level overview of a research question
To combine the results of multiple studies to obtain a summary effect size
To assess the quality of individual studies
To identify potential publication bias

Assessing the study selection process
Evaluating the search strategy
Assessing the quality of included studies
Evaluating the data extraction process
Conducting a power analysis

Systematic review
Meta-analysis
Quality assessment
Data extraction
Data synthesis

To provide a framework for reporting systematic reviews and meta-analyses
To assess the quality of individual studies
To provide a standardized approach for conducting meta-analyses
To evaluate the quality of reporting in meta-analyses of randomized controlled trials
To identify potential publication bias

Risk of bias
Study design
Outcome measures
Statistical methods
Data synthesis

A systematic review is a comprehensive literature search, while a meta-analysis is a statistical technique
A systematic review combines the results of multiple studies, while a meta-analysis provides a high-level overview of a research question
A systematic review evaluates the quality of individual studies, while a meta-analysis synthesizes all relevant research evidence
A systematic review identifies relevant studies, while a meta-analysis assesses the quality of included studies
A systematic review synthesizes research evidence, while a meta-analysis combines the results of multiple studies to obtain a summary effect size

The reporting of systematic reviews
The reporting of meta-analyses of randomized controlled trials
The quality assessment of individual studies
The data extraction process in systematic reviews
The data synthesis in meta-analyses

To ensure the validity and reliability of the results
To identify potential publication bias
To assess the reproducibility of the search strategy
To evaluate the study selection process
To improve the reporting of meta-analyses

The target population
The funding sources
The number of pages
The writing style
The authors' academic degrees

PRISMA
GRADE
AGREE II
CONSORT
STROBE

The colour of the cover page
The potential conflicts of interest
The use of a specific font
The authors' favourite books
The authors' zodiac signs

AGREE II
PRISMA
CONSORT
GRADE
STROBE

Case-control study
Cross-sectional study
Cohort study
Randomized controlled trial
Ecological study

Sample size
Temporality
Objective and valid measurement
Generalizability
Randomization

Sample size
Confounding factors
Generalizability
Randomization
Blinding

Can establish temporality
Can study multiple exposures
Randomization minimizes selection bias
Can calculate incidence rates
Efficient for studying rare outcomes

Sample size
Randomization
Follow-up period
Blinding
Generalizability

Selection bias
Recall bias
Confounding
Measurement bias
Information bias

Cannot establish temporality
Less efficient for studying rare outcomes
Limited to studying one exposure
Cannot calculate prevalence rates
Cannot control for confounding factors

Cost-effectiveness analysis
Cost-benefit analysis
Cost-utility analysis
Cost-consequence analysis
Cost-minimization analysis

Healthcare system perspective
Societal perspective
Patient perspective
Payer perspective
Provider perspective

Study design
Perspective
Study population, intervention, and setting
Uncertainty
Outcomes

Subgroup analysis
Sensitivity analysis
Meta-analysis
Regression analysis
Multivariate analysis

Direct costs
Indirect costs
Fixed costs
Variable costs
Opportunity costs

In natural units
In monetary terms
In quality-adjusted life years
In disability-adjusted life years
In life years gained

CONSORT statement
Drummond checklist
PRISMA statement
MOOSE guidelines
STROBE statement

Cost-effectiveness analysis
Cost-benefit analysis
Cost-utility analysis
Cost-consequence analysis
Cost-minimization analysis

Cost-effectiveness analysis
Cost-utility analysis
Cost-benefit analysis
Cost-consequence analysis
None of the above

Healthcare system
Society
Patient
Provider
Payer

Disability-Adjusted Life Years (DALYs)
Quality-Adjusted Life Years (QALYs)
Life Years Gained (LYG)
Incremental Cost-Effectiveness Ratio (ICER)
Willingness-to-pay (WTP)

Meta-analysis
Sensitivity analysis
Subgroup analysis
Regression analysis
Multivariate analysis

To assess the cost of the interventions
To ensure the results are reliable, valid, and relevant to clinical practice
To determine the effectiveness of the interventions
To calculate the budget impact of the interventions
To analyse the cost-saving potential of the interventions

Cost-effectiveness analysis
Cost-utility analysis
Cost-benefit analysis
Cost-consequence analysis
None of the above

PRISMA
Drummond checklist
STROBE
JADAD
Cochrane risk of bias tool

Clinical effectiveness
Safety
Patient preferences
Equity considerations
All of the above

To standardize clinical practice
To improve the quality of reporting diagnostic accuracy studies
To critique cross-sectional studies
To estimate disease prevalence
To provide guidelines for treatment

Sample size
Data collection methods
Non-random selection of study participants
Outcome measures
Generalizability

Selection bias
Misclassification bias
Observer bias
Reporting bias
Generalizability bias

Study population
Sample size
Data collection methods
Outcome measure(s)
Statistical analysis

Study population
Sample size
Data collection methods
Statistical analysis
Study limitations

Sample size
Data collection methods
Outcome measure(s)
Statistical analysis
All of the above

Randomization
Blinding
Cohort design
Case-control design
Cross-sectional design

Generalizability
Follow-up period
Objective and valid assessment
Confounding factors
Study population

Follow-up period should be short and follow-up rate should be low
Follow-up period should be long and follow-up rate should be low
Follow-up period should be short and follow-up rate should be high
Follow-up period should be long and follow-up rate should be high
Generalizability of the results

Study design
Statistical analysis
Generalizability
Confounding factors
Sample size

To provide guidance on conducting systematic reviews
To improve the quality of reporting RCTs
To standardize the reporting of observational studies
To evaluate the quality of diagnostic accuracy studies
To assess the validity of cohort studies

To provide evidence-based recommendations
To standardize medical education
To ensure patient compliance
To increase healthcare costs
To replace clinical judgment

SIGN
NICE
WHO
CDC
FDA

To determine the focus and boundaries of the guideline
To gather feedback from stakeholders
To approve the final guideline
To identify potential conflicts of interest
To monitor the implementation of recommendations

Scoping
Evidence review
Draft guideline
Consultation
Final guideline

A Guideline Development Group (GDG)
Stakeholders
The general public
Regulatory authorities
Medical publishers

To gather feedback from stakeholders
To determine the focus and boundaries of the guideline
To approve the final guideline
To conduct systematic reviews
To identify potential conflicts of interest

NICE
SIGN Council
WHO
CDC
FDA

Development of implementation tools and resources
Approval by regulatory authorities
Gathering feedback from the general public
Monitoring healthcare costs
Ensuring stakeholder compliance

To standardize clinical practice
To reduce healthcare costs
To limit clinical judgment
To dictate patient preferences
To increase complexity in healthcare

Limited applicability
Complexity
Resistance to change
Improved patient outcomes
Potential for harm

Standardization
Evidence-based recommendations
Reduced healthcare costs
Limited applicability
Improved outcomes

By promoting the use of cost-effective treatments
By increasing complexity in healthcare
By limiting clinical judgment
By encouraging unnecessary tests and procedures
By disregarding patient preferences

Standardization
Resistance to change
Improved outcomes
Cost-effectiveness
Evidence-based recommendations

Complexity
Limited applicability
Evidence-based recommendations
Potential for harm
Resistance to change

Standardization
Cost-effectiveness
Resistance to change
Potential for harm
Improved outcomes

Clinical judgment autonomy
Complexity in healthcare
Resource allocation and cost reduction
Healthcare professional resistance
Limited applicability

Ensuring consistency
Ensuring accuracy
Confirming findings
Enhancing generalizability
Increasing sample size

Triangulation
Member checking
Random sampling
Snowball sampling
Stratified sampling

Triangulation
Member checking
Purposive sampling
Convenience sampling
Data saturation

To increase sample size
To enhance generalizability
To ensure data saturation
To confirm the accuracy of the researcher's interpretation of data
To confirm the accuracy of data collection tools

Reflexivity
Bracketing
Triangulation
Member checking
Data saturation

Reflexivity
Bracketing
Triangulation
Member checking
Purposive sampling

Encourages approaching data without preconceived ideas
Reduces the risk of researcher bias
Enhances transparency and credibility of the findings
Ensures data saturation
Increases sample size

Requires significant time and effort to implement
Can be difficult to achieve complete objectivity
May not eliminate all potential biases
Can be difficult to implement in practice
Enhances transparency and credibility of the findings

Content analysis
Constant comparison
Reflexivity
Bracketing
Triangulation

Content analysis
Constant comparison
Reflexivity
Bracketing
Member checking

Emphasizes the importance of context and complexity
Provides rich and detailed data
Facilitates the development of grounded theory
Systematic and objective approach
Enables comparison and integration of data across different cases

Limited to surface-level data
Overly descriptive and lacks depth
Time-consuming
May overlook important contextual factors
Can be subjective

Data saturation
Data triangulation
Data extraction
Data validation
Data analysis

To ensure the research is rigorous and results are reliable
To increase the sample size
To minimize researcher bias
To identify irrelevant data
To avoid the use of triangulation

By indicating when enough data has been collected to identify consistent patterns and themes
By requiring a predetermined sample size
By setting a minimum sample size for all qualitative studies
By focusing on the quantity of data rather than the quality
By avoiding the need for data analysis

To collect as much data as possible
To determine when the data collection process can be stopped
To identify the most appropriate data analysis method
To compare the experiences of different healthcare providers
To explore the impact of the researcher's own biases

Grounded theory
Phenomenological research
Ethnographic research
Observational study
Systematic review

Grounded theory
Phenomenological research
Ethnographic research
Observational study
Systematic review

Grounded theory
Phenomenological research
Ethnographic research
Observational study
Systematic review

Grounded theory
Phenomenological research
Ethnographic research
Observational study
Systematic review

Grounded theory
Phenomenological research
Ethnographic research
Observational study
Systematic review

Grounded theory
Phenomenological research
Ethnographic research
Observational study
Systematic review

Purposive sampling
Convenience sampling
Snowball sampling
Random sampling
Quota sampling

Purposive sampling
Convenience sampling
Snowball sampling
Random sampling
Quota sampling

Purposive sampling
Convenience sampling
Snowball sampling
Random sampling
Quota sampling

Purposive sampling
Convenience sampling
Snowball sampling
Random sampling
Quota sampling

Purposive sampling
Convenience sampling
Snowball sampling
Random sampling
Quota sampling

Purposive sampling
Convenience sampling
Snowball sampling
Random sampling
Quota sampling

Focus groups
Structured interviews
Semi-structured interviews
Unstructured interviews
Convenience sampling

Focus groups
Structured interviews
Semi-structured interviews
Unstructured interviews
Convenience sampling

Focus groups
Structured interviews
Semi-structured interviews
Unstructured interviews
Convenience sampling

Focus groups
Structured interviews
Semi-structured interviews
Unstructured interviews
Convenience sampling

Purposive sampling
Convenience sampling
Snowball sampling
Random sampling
Quota sampling

Purposive sampling
Convenience sampling
Snowball sampling
Random sampling
Quota sampling

Purposive sampling
Convenience sampling
Snowball sampling
Random sampling
Quota sampling

Purposive sampling
Convenience sampling
Snowball sampling
Random sampling
Quota sampling

Purposive sampling
Convenience sampling
Snowball sampling
Random sampling
Quota sampling

Purposive sampling
Convenience sampling
Snowball sampling
Random sampling
Quota sampling

Conceptualization
Item generation
Item evaluation and selection
Psychometric evaluation
Finalization and implementation

Understanding the complexity of the construct
Generating a diverse pool of items
Ensuring cultural and contextual relevance
Informing item evaluation and selection
None of the above

Conceptualization
Item generation
Item evaluation and selection
Psychometric evaluation
Finalization and implementation

Cost-effectiveness analysis
Cost-utility analysis
Cost-benefit analysis
Cost-minimization analysis
None of the above

QALY
DALY
Life expectancy
Disability weight
None of the above

1.4
2.1
3
3.5
4.2

5.6
7.6
9.6
10
12

To estimate costs
To measure patient satisfaction
To compare the benefits of interventions on a common scale
To measure the effectiveness of interventions in isolation
None of the above

QALY
DALY
Life expectancy
Utility score
None of the above

QALY
DALY
Life expectancy
Disability weight
None of the above

Cost-effectiveness
Cost-benefit analysis
Opportunity cost
Budget constraint
Marginal utility

The total cost of each option
The expected benefits of each option
The opportunity cost of each option
The number of people affected by each option
The financial return on investment for each option

Direct cost
Indirect cost
Fixed cost
Opportunity cost
Variable cost

Discounting
Sensitivity analysis
Regression analysis
Marginal analysis
Time series analysis

Constant rate approach
Declining rate approach
Incremental cost-effectiveness ratio
Time series approach
Sensitivity analysis approach

World Health Organization (WHO)
United Nations (UN)
Centres for Disease Control and Prevention (CDC)
International Monetary Fund (IMF)
World Bank

To adjust future costs and benefits to present value
To calculate the incremental cost-effectiveness ratio
To explore the robustness of the results to changes in assumptions or inputs
To determine the most cost-effective intervention
To estimate quality-adjusted life years

One-way sensitivity analysis
Multi-way sensitivity analysis
Probabilistic sensitivity analysis
Constant rate discounting
Declining rate discounting

One-way sensitivity analysis
Multi-way sensitivity analysis
Probabilistic sensitivity analysis
Constant rate discounting
Declining rate discounting

Cost of insulin
Lost wages due to missed work
Travel expenses to the clinic
Caregiver time
None of the above

Physician fees
Hospital charges
Medical supplies
Time spent by family members providing care
None of the above

To determine which treatment has the lowest direct costs
To determine which treatment has the lowest indirect costs
To determine the most efficient use of resources in terms of health outcomes
To determine the overall cost of treating the disease
None of the above

The cost of medical supplies
The cost of hospital charges
The cost of physician fees
Assumptions and extrapolations used in the estimation process
None of the above

Cost-effectiveness analysis
Cost-utility analysis
Cost-benefit analysis
Cost-minimization analysis
None of the above

Cost-effectiveness analysis
Cost-utility analysis
Cost-benefit analysis
Cost-minimization analysis
None of the above

Cost-effectiveness analysis
Cost-utility analysis
Cost-benefit analysis
Cost-minimization analysis
None of the above

Cost per additional year of life gained
Cost per QALY gained
Net present value of costs and benefits
Benefit-cost ratio
None of the above

Cost-effectiveness analysis
Cost-utility analysis
Cost-benefit analysis
Cost-minimization analysis
None of the above

Ignore the study
Investigate potential sources of heterogeneity
Include the study in the analysis
Remove the study from the analysis
None of the above

Disregard the results
Interpret the results without caution
Further explore potential sources of heterogeneity
Assume all studies share the same underlying effect size
None of the above

To combine results from multiple studies
To estimate the overall effect of the intervention
To identify potential sources of bias and heterogeneity
To calculate the sample size
None of the above

To test the influence of each study on the overall effect estimate
To assess the impact of the intervention on the individual studies
To examine the study quality of each individual study
To calculate the sample size for each study
None of the above

Publication bias
Inclusion/exclusion criteria
Study quality
Statistical methods used
All of the above

Estimating effect size
Enhancing statistical power
Addressing inconsistencies
Identifying gaps
Assessing heterogeneity

Reducing publication bias
Assessing heterogeneity
Accurate and consistent data extraction and synthesis
Enhancing statistical power
Identifying gaps in the literature

Fixed-effect model
Random-effects model
Linear regression model
Logistic regression model
Multiple regression model

Fixed-effect model
Random-effects model
Linear regression model
Logistic regression model
Multiple regression model

Studies are heterogeneous
Studies have different effect sizes
Studies are measuring the same underlying phenomenon
Studies have the same design and population
Studies have varying interventions

Fixed-effect model
Random-effects model
Linear regression model
Logistic regression model
Multiple regression model

Publication bias
Heterogeneity between studies
Quality of included studies
Data extraction and synthesis challenges
Sample size

Requires a larger sample size
Cannot account for unobserved heterogeneity
Incorporates the variability between studies
Allows for more generalizable conclusions
More prone to model misspecification errors

High statistical heterogeneity
Low statistical heterogeneity
All studies have the same effect size
Small sample size
None of the above

No statistical heterogeneity
Presence of statistical heterogeneity
All studies have the same effect size
All studies have the same population
None of the above

No statistical heterogeneity
Presence of statistical heterogeneity
Small sample size
All studies have the same population
None of the above

High effect size
Low effect size
High precision of the estimate
Low precision of the estimate
None of the above

Simple linear regression
Multiple regression analysis
Logistic regression
None of the above
Cannot be determined

To determine the strength of the relationship between the dependent and independent variables
To determine the proportion of variation in the dependent variable explained by the independent variables
To assess the precision of the regression coefficients
To determine whether the regression coefficients are statistically significant
Cannot be determined

Intention to treat (ITT)
Last observation carried forward (LOCF)
Multiple imputation (MI)
Best case analysis
Worst case analysis

Intention to treat (ITT)
Last observation carried forward (LOCF)
Multiple imputation (MI)
Best case analysis
Worst case analysis

Intention to treat (ITT)
Last observation carried forward (LOCF)
Multiple imputation (MI)
Best case analysis
Worst case analysis

Intention to treat (ITT)
Last observation carried forward (LOCF)
Multiple imputation (MI)
Sensitivity analysis
Best case analysis

It is computationally intensive
It requires assumptions about the data
It ignores the potential positive outcomes of missing data
It ignores the potential negative outcomes of missing data
It assumes that the participant's response remains constant over time

Intention to treat (ITT)
Last observation carried forward (LOCF)
Multiple imputation (MI)
Best case analysis
Worst case analysis

Increased generalizability
Reduced heterogeneity
Enhanced statistical power
Decreased publication bias
Improved study quality

Identifying gaps
Addressing inconsistencies
Estimating effect size
Enhancing statistical power
Assessing heterogeneity

Publication bias
Heterogeneity
Poor quality of included studies
Data extraction challenges
Inadequate statistical power

Publication bias
Heterogeneity
Data extraction challenges
Estimating effect size
Enhanced statistical power

Type I error
Type II error
Both Type I and Type II errors
Neither Type I nor Type II errors
Cannot be determined

Lower power
Higher power
No change in power
No relationship to power
Cannot be determined

There is a statistically significant difference between the two therapies
There is no statistically significant difference between the two therapies
The true difference in treatment outcomes is between -3 and 7
Both A and C
Both B and C

P values
Confidence intervals
Both p values and confidence intervals
Neither p values nor confidence intervals
Cannot be determined

They do not provide information about the size or direction of the effect
They can be influenced by sample size
They can lead to over-reliance on statistical significance rather than clinical significance
All of the above
None of the above

The treatments are statistically significantly different
The treatments are not statistically significantly different
The true difference in treatment outcomes is between -0.5 and 1.5
Both A and C
Both B and C

Spearman's rank correlation coefficient
Pearson's correlation coefficient
Both Spearman's and Pearson's correlation coefficients
Neither Spearman's nor Pearson's correlation coefficients
Cannot be determined

Spearman's rank correlation coefficient
Pearson's correlation coefficient
Both Spearman's and Pearson's correlation coefficients
Neither Spearman's nor Pearson's correlation coefficients
Cannot be determined

There is a strong positive relationship between the variables
There is a strong negative relationship between the variables
There is no relationship between the variables
The relationship between the variables is random
Cannot be determined

The correlation is statistically significant
The correlation is not statistically significant
There is a strong linear relationship between the variables
There is a strong monotonic relationship between the variables
Cannot be determined

Simple linear regression
Multiple regression analysis
Logistic regression
None of the above
Cannot be determined

Simple linear regression
Multiple regression analysis
Logistic regression
None of the above
Cannot be determined

There is no relationship between the independent and dependent variables
The independent variables explain 65% of the variation in the dependent variable
The independent variables explain 35% of the variation in the dependent variable
The dependent variable predicts the independent variables
Cannot be determined

A strong positive relationship
A strong negative relationship
A weak positive relationship
A weak negative relationship
No relationship

ANCOVA
Wilcoxon matched-pairs signed rank test
Mann-Whitney U test
Kruskal-Wallis test
T-test

ANCOVA
Wilcoxon matched-pairs signed rank test
Mann-Whitney U test
Kruskal-Wallis test
T-test

ANCOVA
Wilcoxon matched-pairs signed rank test
Mann-Whitney U test
Kruskal-Wallis test
T-test

ANCOVA
Wilcoxon matched-pairs signed rank test
Mann-Whitney U test
Kruskal-Wallis test
T-test

ANCOVA
Wilcoxon matched-pairs signed rank test
Mann-Whitney U test
Kruskal-Wallis test
T-test

ANCOVA
Wilcoxon matched-pairs signed rank test
Mann-Whitney U test
Kruskal-Wallis test
T-test

The null hypothesis can be rejected
The null hypothesis cannot be rejected
The first diet is better
The second diet is better
The diets are equal

The side effect occurs in exactly 25% of patients
The side effect occurs in exactly 35% of patients
We are 95% confident that the true population proportion falls within this interval
We are 95% confident that the side effect occurs in exactly 30% of patients
The side effect occurs in 95% of patients

The null hypothesis can be rejected
The null hypothesis cannot be rejected
Therapy A is superior
Therapy B is superior
There is no difference between the therapies

The treatment is effective for 55% of patients
The treatment is effective for 75% of patients
The treatment is effective for 95% of patients
We are 95% confident that the true population proportion falls within this interval
None of the above

The null hypothesis can be rejected
The null hypothesis cannot be rejected
Technique A is superior
Technique B is superior
The success rates are equal

Type I error
Type II error
True positive
True negative
False negative

Type I error
Type II error
True positive
True negative
False negative

The probability of making a Type I error is 0.90
The probability of making a Type II error is 0.90
The probability of correctly rejecting a false null hypothesis is 0.90
The probability of incorrectly rejecting a true null hypothesis is 0.90
None of the above

Increase the sample size
Decrease the sample size
Increase the significance level
Decrease the significance level
None of the above

To prove the null hypothesis
To prove the alternative hypothesis
To make decisions about population parameters based on sample statistics
To eliminate all possible sources of error in a study
To determine the causality between two variables

To prove the null hypothesis
To prove the alternative hypothesis
To quantify sampling variability
To determine the causality between two variables
To eliminate all possible sources of error in a study

T-test
Wilcoxon rank-sum test
Mann-Whitney U test
Kruskal-Wallis test
Spearman's correlation

Parametric data
Non-parametric data
Nominal data
Ordinal data
Ratio data

T-test
ANOVA
Pearson's correlation
Mann-Whitney U test
Linear Regression

Assumes a normal distribution
Assumes nominal or ordinal data
Assumes no outliers
Assumes a non-normal distribution
Assumes a linear relationship between variables

The null hypothesis cannot be rejected
The null hypothesis can be rejected
The alternative hypothesis cannot be rejected
The test statistic is not significant
There is insufficient evidence to make a decision

High statistical power
More efficient
Robust to outliers and non-normal data
Assumes interval or ratio data
Sensitive to outliers and non-normal data

Chi-square test
Fisher's exact test
McNemar's test
T-test
ANOVA

Chi-square test
Fisher's exact test
McNemar's test
T-test
ANOVA

Chi-square test
Fisher's exact test
McNemar's test
T-test
ANOVA

Chi-square test
Fisher's exact test
McNemar's test
T-test
ANOVA

Chi-square test
Fisher's exact test
McNemar's test
Paired t-test
Unpaired t-test

Chi-square test
Fisher's exact test
McNemar's test
Paired t-test
Unpaired t-test

The treatment increases the benefit by 8% in the treatment group.
The treatment increases the benefit by 8% in the control group.
The treatment has no effect on the benefit.
The treatment increases the benefit by 8% compared to the control group.
The treatment increases the benefit by 8% in both groups.

The treatment reduces the risk of the outcome by 30% in the treatment group.
The treatment reduces the risk of the outcome by 30% in the control group.
The treatment has no effect on the risk of the outcome.
The treatment reduces the risk of the outcome by 30% compared to the control group.
The treatment reduces the risk of the outcome by 30% in both groups.

The treatment increases the benefit by 15% in the treatment group.
The treatment increases the benefit by 15% in the control group.
The treatment has no effect on the benefit.
The treatment increases the benefit by 15% compared to the control group.
The treatment increases the benefit by 15% in both groups.

1
5
10
15
20

For every 25 patients treated with the medication, one will experience an adverse outcome.
For every 25 patients treated with the medication, one will experience a benefit.
The medication has no effect on the risk of adverse outcomes.
The medication reduces the risk of adverse outcomes.
The medication increases the risk of adverse outcomes.

1
2
5
10
15

5
10
15
20
25

The therapy reduces the risk of the outcome by 50% in the treatment group.
The therapy reduces the risk of the outcome by 50% in the control group.
The therapy reduces the risk of the outcome by 50% compared to the control group.
The therapy reduces the risk of the outcome by 0.15 in the treatment group.
The therapy reduces the risk of the outcome by 0.15 compared to the control group.

The drug is more likely to cause harm than to provide benefits.
The drug is equally likely to cause harm as it is to provide benefits.
The drug is less likely to cause harm than to provide benefits.
The drug has no effect on the risk of adverse outcomes.
The drug increases the risk of adverse outcomes.

Measuring the average of a population
Estimating the range of a population
Quantifying sampling variability
Determining the median of a population
Calculating the mode of a population

Population mean
Sample standard deviation
Population standard deviation
Sample size
Population size

Increases precision
Decreases precision
No effect on precision
Increases precision if sample size is small
Increases precision if sample size is large

Correlation analysis
Hypothesis testing
Analysis of variance
Factor analysis
Cluster analysis

The sample estimate is more precise and less variable
The sample estimate is less precise and more variable
The sample size is too small
The population mean is smaller than the sample mean
The population mean is larger than the sample mean

The new antidepressant improves depression symptoms
The new antidepressant worsens depression symptoms
The new antidepressant has no effect on depression symptoms
The new antidepressant reduces depression symptoms in men only
The new antidepressant reduces depression symptoms in women only

Reject the null hypothesis
Fail to reject the null hypothesis
Increase the sample size
Lower the level of significance
Raise the level of significance

Crude death rate
Death rate
Mortality rate
Age-adjusted death rate
Standardized mortality ratio

Crude death rate
Death rate
Mortality rate
Age-adjusted death rate
Standardized mortality ratio

Crude death rate
Death rate
Mortality rate
Age-adjusted death rate
Standardized mortality ratio

Crude death rate
Death rate
Mortality rate
Age-adjusted death rate
Standardized mortality ratio

Crude death rate
Death rate
Mortality rate
Age-adjusted death rate
Standardized mortality ratio

The treatment has no effect on the risk of cardiovascular events.
The treatment reduces the risk of cardiovascular events.
The treatment increases the risk of cardiovascular events.
The treatment has an equal effect on both groups.
Cannot be determined.

The treatment reduces the risk of heart attacks by 5% in the treatment group.
The treatment increases the risk of heart attacks by 5% in the control group.
The treatment has no effect on the risk of heart attacks.
The treatment reduces the risk of heart attacks by 5% compared to the control group.
The treatment reduces the risk of heart attacks by 5% in both groups.

Odds ratio
Absolute risk reduction
Relative risk reduction
Number needed to treat
Number needed to harm

Treatment A reduces the risk of the outcome by 20% compared to Treatment B.
Treatment A increases the risk of the outcome by 20% compared to Treatment B.
Treatment A has no effect on the risk of the outcome compared to Treatment B.
Treatment A reduces the risk of the outcome by 20% in both groups.
Cannot be determined.

The predictor has a strong positive association with the outcome.
The predictor has a strong negative association with the outcome.
The predictor has no association with the outcome.
The predictor has a weak positive association with the outcome.
The predictor has a weak negative association with the outcome.

Odds ratio
Absolute risk reduction
Relative risk reduction
Number needed to treat
Number needed to harm

For every 50 patients treated with the medication, one will experience an adverse outcome.
For every 50 patients treated with the medication, one will experience a benefit.
The medication has no effect on the risk of adverse outcomes.
The medication reduces the risk of adverse
The medication reduces the risk of adverse outcomes.

Prevalence
Cumulative incidence
Incidence rate
Mortality rate
Attack rate

Prevalence
Cumulative incidence
Incidence rate
Mortality rate
Attack rate

Prevalence
Cumulative incidence
Incidence rate
Mortality rate
Attack rate

Kaplan-Meier
Relative survival
Median survival
Log-rank test
Cox proportional hazards model

Kaplan-Meier
Relative survival
Median survival
Log-rank test
Cox proportional hazards model

Kaplan-Meier
Relative survival
Median survival
Log-rank test
Cox proportional hazards model

Kaplan-Meier
Relative survival
Median survival
Log-rank test
Cox proportional hazards model

Kaplan-Meier
Relative survival
Median survival
Log-rank test
Cox proportional hazards model

Censoring
Missing data
Confounding variables
Treatment side effects
None of the above

Crude death rate
Death rate
Mortality rate
Age-adjusted death rate
Standardized mortality ratio

Crude death rate
Death rate
Mortality rate
Age-adjusted death rate
Standardized mortality ratio

Crude death rate
Death rate
Mortality rate
Age-adjusted death rate
Standardized mortality ratio

PPV increases, NPV decreases
PPV decreases, NPV increases
Both PPV and NPV increase
Both PPV and NPV decrease
No change in PPV and NPV

0.02
0.33
0.5
0.75
0.9

0.1
0.2
0.3
0.4
0.5

0.89
1.11
2
4
8

0.22
0.33
0.67
1
2

0.05
0.1
0.15
0.2
0.25

0.4
0.6
0.75
0.8
0.9

0.05
0.1
0.2
0.3
0.4

Perfect discrimination
Moderate discrimination
No better discrimination than chance
Poor discrimination
Unable to determine discrimination based on AUC

High sensitivity and specificity
Poor discrimination
Perfect discrimination
No better discrimination than chance
The test is not applicable in this setting

It balances sensitivity and specificity
It indicates poor discrimination
It represents the highest false positive rate
It represents the lowest sensitivity
It is unrelated to test performance

Prevalence of the disease
Potential harm of false positives and negatives
Cost and availability of confirmatory tests
Test's overall diagnostic accuracy
All of the above

Prevalence
Cumulative incidence
Incidence rate
Mortality rate
Attack rate

Prevalence
Cumulative incidence
Incidence rate
Mortality rate
Attack rate

Prevalence
Cumulative incidence
Incidence rate
Mortality rate
Attack rate

Prevalence
Cumulative incidence
Incidence rate
Mortality rate
Attack rate

Sensitivity
Specificity
Positive likelihood ratio
Negative likelihood ratio
None of the above

Sensitivity
Specificity
Positive likelihood ratio
Negative likelihood ratio
Both positive and negative likelihood ratios

It is likely to produce many false positives.
It is likely to produce many false negatives.
It is most appropriate for ruling in a disease.
It is most appropriate for ruling out a disease.
None of the above

Sensitivity
Specificity
Positive likelihood ratio
Negative likelihood ratio
None of the above

A positive test result increases the likelihood of having the disease.
A positive test result decreases the likelihood of having the disease.
A positive test result has no effect on the likelihood of having the disease.
None of the above
A positive test result has an inverse effect

1.25
4
16
0.84
None of the above

Specificity
Sensitivity
Positive likelihood ratio
Negative likelihood ratio
None of the above

Specificity
Sensitivity
Positive likelihood ratio
Negative likelihood ratio
None of the above

Positive likelihood ratio
Negative likelihood ratio
Sensitivity
Specificity
None of the above

A negative test result increases the likelihood of having the disease.
A negative test result decreases the likelihood of having the disease.
A negative test result increases the likelihood of not having the disease.
A negative test result decreases the likelihood of not having the disease.
None of the above

Sensitivity
Specificity
Positive likelihood ratio
Negative likelihood ratio
Both positive and negative likelihood ratios

True Positive
False Positive
True Negative
False Negative
None of the above

Sensitivity/(1-specificity)
(1-specificity)/sensitivity
(1-sensitivity)/specificity
Specificity/(1-sensitivity)
None of the above

True Positive
False Positive
True Negative
False Negative
None of the above

Sensitivity
Specificity
Positive Predictive Value
Negative Predictive Value
Prevalence

High PPV, low NPV
Low PPV, high NPV
High PPV, high NPV
Low PPV, low NPV
None of the above

Positive Predictive Value
Negative Predictive Value
Both PPV and NPV will be high
Both PPV and NPV will be low
None of the above

Sensitivity alone
Specificity alone
Sensitivity and specificity
Sensitivity, specificity, and disease prevalence
None of the above

Bar chart
Histogram
Pie chart
Scatter plot
Box plot

Bar chart
Histogram
Pie chart
Scatter plot
Box plot

Bar chart
Histogram
Pie chart
Scatter plot
Box plot

Bar chart
Histogram
Pie chart
Scatter plot
Box plot

Bar chart
Histogram
Pie chart
Scatter plot
Box plot

Bar chart
Histogram
Pie chart
Scatter plot
Box plot

Bar chart
Histogram
Pie chart
Scatter plot
Box plot

Bar chart
Histogram
Pie chart
Scatter plot
Box plot

Bar chart
Histogram
Pie chart
Scatter plot
Box plot

Bar chart
Histogram
Pie chart
Scatter plot
Box plot

Bar chart
Histogram
Pie chart
Scatter plot
Box plot

Sensitivity 80%, Specificity 90%
Sensitivity 90%, Specificity 80%
Sensitivity 90%, Specificity 90%
Sensitivity 80%, Specificity 80%
None of the above

The test will have a high rate of false positives
The test will have a high rate of false negatives
The test will accurately identify most infected individuals and exclude most uninfected individuals
The test will accurately identify most uninfected individuals and exclude most infected individuals
None of the above

High sensitivity
High specificity
A balance of sensitivity and specificity
High positive predictive value
None of the above

Specificity
Sensitivity
Positive likelihood ratio
Negative likelihood ratio
None of the above

Specificity
Sensitivity
Positive likelihood ratio
Negative likelihood ratio
None of the above

Positive likelihood ratio
Negative likelihood ratio
Sensitivity
Specificity
None of the above

A negative test result increases the likelihood of having the disease.
A negative test result decreases the likelihood of having the disease.
A negative test result increases the likelihood of not having the disease.
A negative test result decreases the likelihood of not having the disease.
None of the above

Sensitivity
Specificity
Positive likelihood ratio
Negative likelihood ratio
Both positive and negative likelihood ratios

True Positive
False Positive
True Negative
False Negative
None of the above

Sensitivity/(1-specificity)
(1-specificity)/sensitivity
(1-sensitivity)/specificity
Specificity/(1-sensitivity)
None of the above

True Positive
False Positive
True Negative
False Negative
None of the above

Mean
Median
Mode
Range
Standard Deviation

Mean
Median
Mode
Range
Interquartile Range

Mean
Median
Mode
Range
Interquartile Range

Mean
Median
Mode
Range
Standard deviation

Mean
Median
Mode
Range
Standard deviation

Proportion
Mean
Median
Mode
Standard deviation

Mean
Median
Mode
Range
Standard deviation

Proportion
Mean
Median
Mode
Standard deviation

Mean
Median
Mode
Range
Standard deviation

Mean
Median
Mode
Range
Interquartile range

Mean
Median
Mode
Range
Standard deviation

2×2 table
Frequency table
Frequency distribution
None of the above
All of the above

2×2 table
Frequency table
Frequency distribution
None of the above
All of the above

2×2 table
Frequency table
Frequency distribution
None of the above
All of the above

Proportion of true positive results
Proportion of true negative results
Proportion of false positive results
Proportion of false negative results
None of the above

Proportion of true positive results
Proportion of true negative results
Proportion of false positive results
Proportion of false negative results
None of the above

2×2 table
Frequency table
Frequency distribution
None of the above
All of the above

2×2 table
Frequency table
Frequency distribution
None of the above
All of the above

2×2 table
Frequency table
Frequency distribution
None of the above
All of the above

Bar chart
Histogram
Pie chart
Scatter plot
Box plot

Bar chart
Histogram
Pie chart
Scatter plot
Box plot

Bar chart
Histogram
Pie chart
Scatter plot
Box plot

Ordinal
Nominal
Dichotomous
Interval
Ratio

Ordinal
Nominal
Dichotomous
Interval
Ratio

Ordinal
Nominal
Dichotomous
Interval
Ratio

Ordinal
Nominal
Dichotomous
Interval
Ratio

Ordinal
Nominal
Dichotomous
Interval
Ratio

Mean
Median
Mode
Range
Interquartile Range

Mean
Median
Mode
Range
Standard Deviation

Mean
Median
Mode
Standard Deviation
Interquartile Range

Mean
Median
Mode
Proportion
Standard Deviation

Range
Mean
Median
Mode
Standard Deviation

Evaluating the long-term effects of an intervention in a large population
Comparing the effectiveness of two treatments in a group of patients
Determining the optimal treatment for a specific patient with a chronic condition
Investigating the association between an exposure and an outcome at a population level
None of the above

Lack of randomization
Inability to assess safety and efficacy
Limited external validity (generalizability)
Inability to compare multiple interventions
None of the above

Necessary cause
Sufficient cause
Component causes
Coherence
Consistency

Strength of association
Consistency
Specificity
Temporality
Biological gradient

Case-control study
Cohort study
Cross-sectional study
Randomized controlled trial
Systematic review

Case-control study
Cohort study
Cross-sectional study
Randomized controlled trial
Systematic review

Case-control study
Cohort study
Cross-sectional study
Randomized controlled trial
Systematic review

Case-control study
Cohort study
Cross-sectional study
Randomized controlled trial
Systematic review

Case-control study
Cohort study
Cross-sectional study
Randomized controlled trial
Systematic review

Case-control study
Cohort study
Cross-sectional study
Randomized controlled trial
Systematic review

Case-control study
Cohort study
Cross-sectional study
Randomized controlled trial
Systematic review

Case-control study
Cohort study
Cross-sectional study
Randomized controlled trial
Systematic review

Systematic review
Randomized controlled trial
Ecological survey
Cohort study
Cross-sectional study

Systematic review
Randomized controlled trial
Ecological survey
Cohort study
Cross-sectional study

Systematic review
Randomized controlled trial
Ecological survey
Cohort study
Cross-sectional study

Parallel-group trial
Equivalence trial
Cluster trial
None of these
All of these

Systematic review
Randomized controlled trial
Ecological survey
Cohort study
Cross-sectional study

Systematic review
Randomized controlled trial
Ecological survey
Cohort study
Cross-sectional study

Systematic review
Randomized controlled trial
Ecological survey
Cohort study
Cross-sectional study

Parallel-group trial
Equivalence trial
Cluster trial
None of these
All of these

Systematic review
Randomized controlled trial
Ecological survey
Cohort study
N-of-1 clinical trial

Simple randomization
Stratified randomization
Minimization
Cluster randomization
Block randomization

Simple randomization
Stratified randomization
Minimization
Cluster randomization
Block randomization

Simple randomization
Stratified randomization
Minimization
Cluster randomization
Block randomization

Simple randomization
Stratified randomization
Allocation concealment
Cluster randomization
Block randomization

Simple randomization
Stratified randomization
Allocation concealment
Cluster randomization
Block randomization

Simple randomization
Stratified randomization
Minimization
Cluster randomization
Block randomization

Simple randomization
Stratified randomization
Minimization
Cluster randomization
Block randomization

Single-blind
Double-blind
Triple-blind
Unblinded
Partially blinded

Single-blind
Double-blind
Triple-blind
Unblinded
Partially blinded

Single-blind
Double-blind
Triple-blind
Unblinded
Partially blinded

Placebo pills
Sham surgery
Central randomization
Coded group allocation
Data analyst blinding

Sham surgery
Placebo
Central randomization
Stratification
Data analyst blinding

Single-blind
Double-blind
Triple-blind
Unblinded
Partially blinded

Blinding of participants
Blinding of researchers
Blinding of data analysts
Blinding of reviewers
Blinding of outcome assessors

To improve participant adherence
To increase the sample size
To ensure allocation concealment
To reduce measurement bias
To simplify data analysis

Strength of association
Consistency
Specificity
Temporality
Biological gradient

Association
Time order
Directionality
Strength of association
Coherence

Necessary cause
Sufficient cause
Component causes
Coherence
Consistency

Koch's postulates
Hill's criteria
Rothman's causal pie model
Susser's causal web
Susser's triad of essential causal properties

Strength of association
Consistency
Specificity
Temporality
Biological gradient

Temporality
Strength and consistency of association
Dose-response relationship
Alternative explanations
Complex interactions between risk factors

Construct validity
Content validity
Face validity
Concurrent validity
Predictive validity

Construct validity
Content validity
Face validity
Concurrent validity
Predictive validity

Construct validity
Content validity
Face validity
Concurrent validity
Predictive validity

Construct validity
Content validity
Face validity
Criterion validity
Predictive validity

Simple random sampling
Stratified random sampling
Systematic sampling
Cluster sampling
None of the above

Simple random sampling
Stratified random sampling
Systematic sampling
Cluster sampling
None of the above

Simple random sampling
Stratified random sampling
Systematic sampling
Cluster sampling
None of the above

Simple random sampling
Stratified random sampling
Systematic sampling
Cluster sampling
None of the above

Simple random sampling
Stratified random sampling
Systematic sampling
Cluster sampling
None of the above

Simple random sampling
Stratified random sampling
Systematic sampling
Cluster sampling
None of the above

Simple random sampling
Stratified random sampling
Systematic sampling
Cluster sampling
None of the above

Simple random sampling
Stratified random sampling
Systematic sampling
Cluster sampling
None of the above

Restriction
Matching
Adjustment
Randomization
Cluster sampling

Randomization
Restriction
Matching
Stratification
Multivariable regression models

Restriction
Randomization
Matching
Stratification
Cluster sampling

Stratification
Restriction
Matching
Randomization
None of the above

Interaction
Randomization
Confounding
Restriction
Matching

Randomization
Restriction
Adjustment
Stratification
Matching

Maximize the potential for confounding
Eliminate all confounding factors
Control for confounding factors
Focus solely on the risk factor
Ignore confounding factors

Randomization
Restriction
Matching
Cluster sampling
Adjustment

Simple randomization
Stratified randomization
Minimization
Cluster randomization
Block randomization

Selection bias
Detection bias
Attrition bias
Reporting bias
Publication bias

Selection bias
Detection bias
Attrition bias
Reporting bias
Measurement bias

Selection bias
Detection bias
Attrition bias
Reporting bias
Publication bias

Selection bias
Detection bias
Attrition bias
Reporting bias
Confounding bias

Measurement bias
Confounding bias
Reporting bias
Publication bias
Detection bias

Measurement bias
Detection bias
Attrition bias
Reporting bias
Confounding bias

Selection bias
Detection bias
Attrition bias
Reporting bias
Publication bias

Blinding
Stratification
Pre-registering study protocol
Funnel plots
Intention-to-treat analysis

Using validated measures
Conducting systematic reviews
Blinding outcome assessors
Employing retention strategies
Using stratification

Intention-to-treat analysis
Blinding
Stratification
Pre-registering study protocol
Funnel plots

CONSORT
Funnel plots
Blinding
Pre-registering study protocol
Intention-to-treat analysis

Funnel plots
Stratification
Blinding
Intention-to-treat analysis
Pre-registering study protocol

Using validated measures
Conducting systematic reviews
Blinding
Pre-registering study protocol
Funnel plots

Blinding
Pre-registering study protocol
Funnel plots
Stratification
Intention-to-treat analysis

Inter-rater reliability
Test-retest reliability
Intraclass correlation coefficient
Kappa coefficient
None of the above

To measure agreement between raters
To ensure consistency of a measure over time
To control for confounding factors
To minimize selection bias
To improve measurement accuracy

Inter-rater reliability
Test-retest reliability
Intraclass correlation coefficient
Kappa coefficient
None of the above

Intraclass correlation coefficient
Test-retest reliability coefficient
Kappa coefficient
Pearson correlation coefficient
Spearman rank correlation coefficient

Inter-rater reliability
Test-retest reliability
Intraclass correlation coefficient
Kappa coefficient
None of the above

Intraclass correlation coefficient
Test-retest reliability coefficient
Kappa coefficient
Pearson correlation coefficient
Spearman rank correlation coefficient

To ensure validity and guide clinical decision-making
To control for confounding factors
To minimize selection bias
To reduce publication bias
To improve measurement accuracy

It refers to the consistency and stability of a measure or test
It is not important for the accuracy of research results
It only applies to psychiatric research
It is unrelated to validity
It is not relevant to clinical decision-making

Construct validity
Content validity
Face validity
Concurrent validity
Predictive validity

Construct validity
Content validity
Face validity
Concurrent validity
Predictive validity

Construct validity
Content validity
Face validity
Concurrent validity
Predictive validity

Construct validity
Content validity
Face validity
Concurrent validity
Predictive validity

Systematic error
Random error
Internal validity
External validity
None of the above

Increase the sample size
Decrease the sample size
Minimize selection bias
Minimize measurement bias
None of the above

Measurement bias
Selection bias
Random error
Internal validity
External validity

Internal validity
External validity
Random error
Selection bias
Measurement bias

Selection bias
Measurement bias
Confounding bias
Observer bias
None of the above

Use random sampling techniques
Use validated measurement tools
Control for potential confounders
Stratify the sample
None of the above

Selection bias
Measurement bias
Confounding bias
Observer bias
None of the above

Use random sampling techniques
Use validated measurement tools
Control for potential confounders
Stratify the sample
None of the above

An underestimation of the effect of a treatment or intervention
An increase in access to research for diverse audiences
A waste of resources and potentially harmful decisions based on incomplete evidence
An increase in the number of studies conducted
A decrease in the quality of studies conducted

Cinahl
Cochrane Library
EMBASE
PsycINFO
Sigle

Cinahl
Cochrane Library
EMBASE
PsycINFO
Sigle

Cinahl
Cochrane Library
EMBASE
PsycINFO
Sigle

Cinahl
Cochrane Library
EMBASE
PsycINFO
Sigle

Cinahl
Cochrane Library
EMBASE
PsycINFO
Sigle

Cinahl
Cochrane Library
EMBASE
PsycINFO
Sigle

Cinahl
Cochrane Library
EMBASE
PsycINFO
Sigle

Cinahl
Cochrane Library
EMBASE
PsycINFO
Sigle

Medical Subject Headings (MeSH)
Cochrane Library classification system
Boolean operators
Truncation
Wildcards

Truncation
Wildcards
Boolean operators
Medical Subject Headings (MeSH)
Cochrane Library classification system

Truncation
Wildcards
Boolean operators
Medical Subject Headings (MeSH)
Filters and limiters

PubMed (Medline)
The Cochrane Library
EMBASE
PsycINFO
Cinahl

Use MeSH terms
Use the search box
Browse by topic
Use natural language processing
Use the Cochrane Library classification system

Use MeSH terms
Use Boolean operators
Use filters
Use the search box
Browse by topic

Systematic review
Randomized controlled trial
Cohort study
Cross-sectional study
Case report

Cohort study
Case-control study
Randomized controlled trial
Cross-sectional study
Case series

Case report
Randomized controlled trial
Cohort study
Systematic review
Economic evaluation

Randomized controlled trial
Cohort study
Case-control study
Cross-sectional study
Expert opinion

Randomized controlled trial
Cohort study
Case-control study
Systematic review and meta-analysis
Case report

Cohort study
Case-control study
Randomized controlled trial
Cross-sectional study
Case report

Systematic review
Randomized controlled trial
Expert opinion
Cohort study
Cross-sectional study

Cohort study
Case-control study
Randomized controlled trial
Diagnostic accuracy study
Case report

Systematic review or meta-analysis of RCTs
Cohort study
Case-control study
Cross-sectional study
Qualitative study

Systematic review or meta-analysis of RCTs
Systematic review or meta-analysis of cohort studies
Systematic review or meta-analysis of cross-sectional studies
Economic evaluation
Qualitative study

Randomized controlled trial
Cohort study
Cross-sectional study
Systematic review or meta-analysis of economic evaluations
Qualitative study

Systematic review or meta-analysis of RCTs
Systematic review or meta-analysis of cohort studies
Case-control study
Cross-sectional study
Qualitative study

Systematic review or meta-analysis of RCTs or cohort studies
Randomized controlled trial
Case-control study
Cross-sectional study
Qualitative study

Systematic review or meta-analysis of RCTs
Systematic review or meta-analysis of cohort studies
Case-control study
Cross-sectional study
Qualitative study

Randomized controlled trial
Cohort study
Cross-sectional study
Economic evaluation
Systematic review or meta-synthesis of qualitative studies

Expert opinion
Case reports
Cross-sectional studies
Randomized controlled trials
Systematic reviews and meta-analyses

When studies are published only in certain languages
When studies with positive or significant results are more likely to be published
When studies are published without peer-review
When studies are funded by industry
When studies are published after the results are known

When studies are published only in certain languages
When studies with positive or significant results are more likely to be published
When studies are published without peer-review
When studies are funded by industry
When studies are published after the results are known

Conduct more observational studies
Increase the sample size of studies
Promote open access and multilingual publishing
Only include studies with positive results in systematic reviews
Increase the funding for industry-sponsored studies

P
E
C
O
T

P
E
C
O
T

Therapy
Harm
Aetiology
Prognosis
Diagnosis

Therapy
Harm
Aetiology
Economic
Diagnosis

Therapy
Harm
Aetiology
Prognosis
Qualitative

Therapy
Harm
Aetiology
Prognosis
Diagnosis

Randomized controlled trials (RCTs)
Cohort studies
Case-control studies
Economic evaluations
Qualitative research methods

Therapy
Harm
Aetiology
Prognosis
Diagnosis

Randomized controlled trials (RCTs)
Cohort studies
Case-control studies
Both B and C
None of the above

Therapy
Harm
Aetiology
Prognosis
Diagnosis

P
E
C
O
T

Compare
Constant
Comparison
Conversion
Conditions

P
E
C
O
T

P
E
C
O
T

Order
Outbound
Organ
Outcome
Oranges

Google Scholar
PubMed
Cochrane Library
Both B and C
None of the above

Practice Quiz – 4c1ee5

Practice Quiz – 4c1ee5

Quiz Summary

Information

Results

Results

Categories

1. Question

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