Exam Flashcards
What is the difference between health promotion and disease prevention?
- Health promotion: maintain people’s current health status and ideally a shift towards better health
- Disease prevention: to prevent people from getting a disease and prevent a shift towards the seriousness of a disease
True or false: tackling upstream determinants is a form of primary prevention
True
At what environmental level lie community-based interventions?
Meso
Explain the structuring in environmental determinants
- Physical: air pollution, designing cities for walkability and ensuring access to clean water
- Socio-cultural: social relationship/ behaviors within a society, considering community dynamics to effectively promote health
- Economic: employment, access to education, address low SEP, create equal opportunities
- Political: policies, regulations, the promotion of vaccination programs
Explain prevention concerning hearing impairment
- Primary prevention: prenatal care, protection, reduction of noise
- Secondary prevention: neonatal screening, screening at primary school, self-screening of adults
- Tertiary prevention: ENT consultation
What is the Behavior Change Wheel?
Helps identifying key factors influencing behaviors related to hearing protection and guides the development of effective strategies to promote healthy hearing practices
What is the COM-B model?
Aimed at changing behavior and is used among people with hearing impairment to improve the use of hearing aid.
Capability, Opportunity, Motivation, and Behavior
What are fundamental aspects of quality of life?
- Subjective (reflects an individual’s perception of how an illness an its treatment affect health
- Multidimensional
- Patient reported outcome/ reported by the individual
What is important when measuring quality of life?
To define QoL by operationalizing and clearly determining your instrument(s)
A good questionnaire to measure quality of life consists of good:
- Validity: the variables being measured align with the intended aspects of quality of life
- Reliability: consistency in results of the measurement
- Responsiveness: ability to detect changes when a patient improves or deteriorates
What types of questionnaires to measure quality of life are there?
- Generic: assesses overall quality of life of individuals irrespective of their specific health status or medical condition
- Disease-specific: assesses quality of life in individuals with a specific medical condition or disease
What is the difference between QoL and HRQoL?
Quality of life encompasses a broader range of factors beyond health, while health-related quality of life concentrates on the health-related aspects of well-being
What are reasons for evaluation?
- To determine the effect(s) of a program
- Accountability
- Development
- Ethical aspects
What are reasons to not evaluate?
- Money
- Threat
- Time constraints
- Already proven effective
- Intervention is still developing
What is an effect evaluation?
Assesses the impact or outcomes of an intervention. Whether the intended effects have been achieved and to what extend
What is a process evaluation?
Focuses on understanding how an intervention is implemented. Provides insights into the implementation process and helps identify factors that may influence the outcomes
What is a costs/ economic evaluation?
Assesses the financial costs associated with an intervention and compares them to the outcomes achieved
What does the RE-AIM framework stand for?
- Reach: explores characteristics of study participants
- Effectiveness: refers to the positive and negative outcomes of the intervention at the individual level
- Adoption: explores the facilitators and barriers for adoption
- Implementation: refers to the extent to which the intervention was delivered as intended
- Maintenance: refers to the long-term sustainability of the intervention and its effects over time
What is GRADE?
Grading of Recommendations, Assessment, Development, and Evaluations
It provides a transparent and structured method for assessing the quality of evidence and strength of recommendations, enhancing the rigor and reliability of healthcare guidelines and recommendations.
Why do researchers need a sample size calculation?
A sample size calculation is about figuring out how many participants or observations you need to make sure your study is meaningful, trustworthy, and has the best chance of finding real effects.
What are the steps of a sample size calculation?
- Effect size: the ‘size’ of the difference or effect you expect to find in your study
- Significance level (a): setting the bar for how sure you want to be that your results are real and not just by chance
- Power (1 - B): the ability of your study to catch a real effect if it’s there
- Variability (Standard Deviation): how much your data points are likely to spread out from the average
- Type of test: choosing the right tool for your study
- Desired precision: how much “wiggle room” you’re willing to tolerate in your results
- Expected dropout or loss to follow-up: accounting for the fact that not everyone might finish your study
- Practical considerations: thinking about what’s doable in the real world
Situation A: you perform a sample size calculation and it seems that you need 80 patients in each group. However, you can only include a maximum of 60 patients. What do you do?
You do the study and you may end up with a non-significant result. In reality, you almost never have enough power. The study can still be relevant and give important information. A meta-analysis would increase this power.
Situation B: you perform a sample size calculation and it seems that you need 80 patients in each group. However, you can easily include 200 patients for each group. What do you do?
You go for a study that is as big as possible, because the standardized mean will be smaller.
Is it best to calculate the relative risk or the analysis of covariance in an RCT and why?
Relative change, often calculated as a percentage change or ratio of post-treatment to baseline measurements, can be influenced by regression to the mean and might not be the most appropriate measure for assessing treatment effects in certain situations, especially when extreme baseline values are present. Using an analysis of covariance (ANCOVA) is recommended as an alternative approach, since it adjusts for baseline differences, offers a more rigorous and controlled analysis, contributing to a more accurate assessment of true treatment effects in RCTs.