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Review and Preview

Review and Preview

In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...

Review and Preview

Review and Preview

Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...

Random and Systematic Errors

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...

Systematic Sampling Method

Systematic Sampling Method

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. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
Systematic sampling is one of the simplest methods...

Propagation of Uncertainty from Systematic Error

Propagation of Uncertainty from Systematic Error

The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...

Systematic Error: Methodological and Sampling Errors

Systematic Error: Methodological and Sampling Errors

In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...

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Client Preferences for Contraceptive Counseling: A Systematic Review.

Edith Fox¹, Arlene Reyna¹, Nikita M Malcolm²

¹Department of Family and Community Medicine, University of California, San Francisco, San Francisco, California.

American Journal of Preventive Medicine

|October 22, 2018

Summary

This summary is machine-generated.

Understanding client preferences in contraceptive counseling is key to achieving reproductive goals. This review highlights how provider attention to these preferences can improve family planning care quality.

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Area of Science:

Reproductive Health
Family Planning
Evidence Synthesis

Background:

Client-centered contraceptive counseling is essential for achieving reproductive goals.
Individualized contraceptive decision-making necessitates understanding client preferences.
Previous reviews did not comprehensively cover client preferences in contraceptive counseling.

Purpose of the Study:

To systematically review and summarize evidence on client preferences for contraceptive counseling.
To identify specific client preferences regarding information, decision-making, provider relationships, and counseling context.

Main Methods:

Systematic review of 26 articles published between October 1992 and November 2016.
Searches conducted across 16 electronic bibliographic databases.
Inclusion criteria focused on studies detailing client preferences for contraceptive counseling.

Main Results:

Nineteen articles reported on preferences for information received during counseling.
Thirteen articles detailed preferences for the decision-making process.
Thirteen articles addressed preferences for provider-client relationships, and 11 for counseling context.

Conclusions:

Client preferences significantly shape the contraceptive counseling experience.
Incorporating client preferences can enhance the quality of family planning services.
Further research is recommended to develop interventions that meet these identified preferences.