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Related Concept Videos

Sampling Plans01:23

Sampling Plans

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Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
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Community Based Intervention01:30

Community Based Intervention

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Community-based interventions in mental health represent a paradigm shift from institution-centered care to treatments embedded within the fabric of local communities. By prioritizing inclusion and leveraging existing societal structures, this approach fosters a supportive environment conducive to addressing mental health challenges while promoting individual dignity and agency.
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Convenience Sampling Method00:55

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
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Systematic Sampling Method01:17

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Cluster Sampling Method01:20

Cluster Sampling Method

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Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
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Stratified Sampling Method01:16

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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Related Experiment Video

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Sampling and Recruiting Community-Based Programs Using Community-Partnered Participation Research.

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Community partners in research design enhance scientific integrity. This study shows community-partnered, participatory research (CPPR) improves rigorous randomized trials, ensuring both community relevance and validity.

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Area of Science:

  • Public Health
  • Health Services Research
  • Community-Based Participatory Research

Background:

  • Concerns exist regarding scientific integrity when community partners influence statistical design in research.
  • Community-partnered, participatory research (CPPR) integrates community input into study processes.

Purpose of the Study:

  • To examine the implications of CPPR on study validity and community relevance within a cluster-randomized trial.
  • To present a case study of CPPR in designing and implementing a comparative effectiveness trial for depression interventions.

Main Methods:

  • A community-partnered, participatory research (CPPR) cluster-randomized, comparative effectiveness trial was conducted.
  • Administrative data were used to describe the CPPR design and implementation for sampling, recruitment, and randomization.
  • Participation rates were calculated, and cross-tabulation assessed balance on key program characteristics.

Main Results:

  • Achieved 51.5% agency and 89.6% program participation rates.
  • No significant differences were found in service sector, location, or program size between intervention arms.
  • Participating programs did not differ significantly from eligible non-participating programs on community characteristics.

Conclusions:

  • Claims that community involvement compromises scientific integrity are refuted.
  • CPPR processes can enhance the implementation of rigorous, community-grounded randomized trials.