Sampling Technique

To assess the prevalence of noise-induced hearing loss among factory workers, researchers could select every 10th employee on the company payroll list.

• simple random sampling

• stratified sampling

• systematic sampling

• cluster sampling

A researcher studying the health effects of air pollution on a city's residents could use a random number generator to select participants from a list of all city residents.

• simple random sampling

• stratified sampling

• cluster sampling

• quota sampling

An investigation into the impact of a new waste management facility on nearby communities could randomly select neighbourhoods from the surrounding area and then survey all residents within those neighbourhoods.

• simple random sampling

• purposive sampling

• systematic sampling

• cluster sampling

A study investigating the link between pesticide exposure and health outcomes in agricultural workers might stratify the sample by age, gender, and years of experience, then randomly select participants from each stratum.

• purposive sampling

• stratified sampling

• systematic sampling

• quota sampling

Experts in occupational health and safety could be purposefully selected for interviews to gain insights into best practices for preventing workplace injuries in a specific industry.

• consecutive sampling

• snowball sampling

• purposive sampling

• quota sampling

A study exploring the experiences of construction workers exposed to asbestos might recruit initial participants and then ask them to refer colleagues who have also been exposed (useful for reaching a hard-to-reach population but risks bias towards similar work experiences).

• snowball sampling

• stratified sampling

• quota sampling

• convenient sampling

Researchers studying the psychological effects of shift work on nurses could recruit participants from nurses working at a single hospital (convenient but potentially not representative of all nurses).

• quota sampling

• convenient sampling

• purposive sampling

• consecutive sampling

An investigation into the prevalence of work-related musculoskeletal disorders (MSDs) in different job sectors could set quotas to ensure the sample reflects the proportions of workers in various industries (useful for descriptive comparisons but not generalizable).

• simple random sampling

• convenient sampling

• snowball sampling

• quota sampling

A researcher studying heat stress among construction workers might recruit participants at a construction site throughout the day until they reach their target sample size. This method is convenient but may overrepresent workers who are present on that specific day and time, potentially missing night shift workers or those with different work schedules.

• consecutive sampling

• purposive sampling

• convenient sampling

• cluster sampling

A study investigating the prevalence of work-related musculoskeletal disorders (MSDs) among construction workers could stratify the sample by job type (carpenters, electricians, laborers) and then randomly select workers from each category. This allows for comparisons of MSD prevalence across different construction trades.

• simple random sampling

• convenient sampling

• stratified sampling

• systematic sampling