Research Mod 6, Chapter 10

Process of selecting portion of population to represent the *population*
an entire aggregate of cases/group of interest
Eligibility criteria
*Inclusion criteria* and *exclusion criteria* are used to define population characteristics
Accessible population
portion of the target population that is accessible to the researcher
Target population
entire population in which a researcher is interested
subset of population elements (elements = humans)
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Representative sample
Characteristics closely approximate those of the population.
Sampling bias
Systematic overrepresentation or underrepresentation of some segment of the population in terms of key characteristics
sub-populations; mutually exclusive. ex: population of all RNs, then a strata of that is seeing how many males vs. females
Nonprobability sampling
researchers select elements by nonrandom methods in which every element usually does not have a chance to be included (less likely to produce representative sampling, more bias, but practical/economical)
Convenience sampling
-Selecting the most conveniently available people as participants.
-WEAKEST quantitative sampling
ex: At a health fair, by convenience give health info to participants “conveniently” available.
Quota sampling
Divides the population into homogeneous strata to ensure representation of subgroups in sample; w/in each stratum, people are sampled by convenience
-Same percentage/proportion of strata as entire population
Consecutive sampling
Nonprobability sampling to recruit *all* people from accessible population over specific time interval.
-likely to yield a representative sample
-Better than convenience sampling
-Good with “rolling enrollment”
Purposive sampling
participants are hand-picked to be included based on the researcher’s knowledge about the population.
-biased but useful if want experts:
Ex: assess views of 22 expert nurse about development of taxonomy for domain of clinical nursing research.
Probability Sampling
Random selection of elements form a population (NOT random assignment)
-only viable method of obtaining representative samples
random sampling
each element in the population has an equal, independent change of being selected
Simple random sampling
most basic probability sampling
-establish *sampling frame*: where to get the sample (student list roster, ex.)
Stratified random sampling
divided into >=2 strata, from which elements are randomly selected
-similar to quota to enhance representativeness
Systematic sampling
Selection of every kth case from a list, such as every 10th person on a patient list
Sampling interval
standard distance between selected cases (used in systematic sampling)
Sample size
the number of study participants
power analysis
• Process for determining the sample size for a study
• Used to increase the probability of detecting an effect if
one truly exists
Critiquing Sampling Plans
• Is the population under study clearly identified?
• Were the sampling procedures clearly described?
• Were the eligibility criteria clearly described and appropriate?
• Is the sample size sufficiently large? Was a power
analysis reported?
• Does the sample support inferences about external
validity? To whom can the study results generalize?
-Type of sampling approach used (convenience, consecutive, random)
-Population under study and eligibility criteria for sample selection
-Sample size, with rationale
-Description of sample’s main characteristics (ex. gender, age, clinical status)
-Number and characteristics of potential subject who declined to participate
Data Collection in Quantitative Research
• Basic decision is the use of:
– New data, collected specifically for research purposes, or
– Existing data
• Records (e.g., patient charts)
• Historical data
• Existing data set (secondary analysis)
Examples of Existing Data using Records,
Documents, and Available Data
• Hospital records (e.g., nurses’ shift reports)
• School records (e.g., student absenteeism)
• Corporate records (e.g., health insurance choices)
• Letters, diaries, minutes of meetings, etc.
• Photographs
Major Types of Data Collection
• Self‐reports
– Participant’s responses to questions posed by researcher
• Observation
– Techniques for gathering data through the direct observation of phenomena
• Biophysiologic measures
Structured Self‐Reports
• Data are collected with a formal instrument
• Closed‐ended (fixed alternative) questions
Ex: Within the past 2 weeks, I have been able to laugh and see the funny side of things”
A. Every day
B. Some days
C. Hardly ever
• Open‐ended questions
Ex: “How has your mood been over the past 2 weeks?”
Advantages of Questionnaires
(Compared With Interviews)
• Lower cost
• Possibility of anonymity, greater privacy
• Easier to analyze for a quantitative study
• Able to reach a large number of people
Advantages of Interviews
(Compared With Questionnaires)
• Higher response rates
• Appropriate for more diverse audiences (e.g., children, elderly)
• Opportunities to clarify questions or determine comprehension
• Gain greater depth or insight on variables
• Opportunity to collect supplementary data through observation
Composite Psychosocial Scales (2)
• *Scales*—used to quantitatively measure attitudes, perceptions, traits
• *Likert scales*—summated rating scales
– Consist of several declarative statements (items)
expressing viewpoints
– Responses are on an strongly agree/agree/neutral/disagree/strongly disagree continuum (usually five or seven response options).
– Responses to items are summed to compute a total scale score
Visual Analog Scale (VAS)
• Used to measure subjective experiences (e.g., pain, nausea)
• Measurements are on a straight line measuring 100 mm.
• End points labeled as extreme limits of sensation
Response Set Biases
• Biases reflecting the tendency of some people to respond to items in characteristic ways, independently of item content
• Examples:
– Social desirability response set bias
– Extreme response set
– Acquiescence response set (yea‐sayers)
• Structured observation of pre‐specified behaviors
• Need to clearly define the focus of the observation (ex: patient interactions, response to medication)
• Potential for reactivity
• Concealment (unobtrusive observation)
• Multiple ways to record observations
• Video
• Sleep‐wake cycle recordings
• checklists
Structured Observations
• Category systems ->->checklists
– Formal systems for systematically recording the incidence or frequency of prespecified behaviors or events
– Systems vary in their exhaustiveness.
• *Exhaustive system*: All behaviors of a specific type recorded, and each behavior is assigned to one mutually
exclusive category.
• *Nonexhaustive system*: specific behaviors, but not all
behaviors, recorded
Rating Scales
• Ratings are on a *descriptive continuum*
• Ratings can occur:
– At specific intervals
– Upon the occurrence of certain events
– After an observational session (global ratings)
Structured observational sampling: time sampling
technique in which a designated amount of time is set and one observes what behavior occurs during that time
Ex: observation of patient interactions during a 24 hour
period on a psychiatric unit
Structured observational sampling: Event sampling:
Technique in which the frequency of
specified events are observed
Ex: observation of frequency of agitated behavior among patients on a psychiatric unit
Evaluation of Observational Methods
• Excellent method for capturing many clinical phenomena and behaviors
• Potential problem of reactivity when people are aware that they are being observed
• Risk of observational biases—factors that can interfere with objective observation
• Strategies for ensuring that observational data is collected accurately and appropriately are essential
Biophysiologic Measures
• *In vivo measurements*
– Performed directly within or on living organisms
(e.g., blood pressure measures)
• *In vitro measurements*
– Performed outside the organism’s body (e.g., urinalysis)
Evaluation of Biophysiologic Measures
• Can be strong on accuracy, objectivity, validity, and precision, though still need to be calibrated to ensure accuracy
• Advanced skills may be needed for
Critiquing the Data Collection Plan
• Are the data collection procedures clearly described?
• Did the researchers use the best or most appropriate methods of capturing study phenomena (i.e., self‐reports, observation, biophysiologic methods)?
• Were efforts made to evaluate and minimize response bias or reactivity?
Which of the following is the most widely used data collection method by nurse researchers?
Strata are incorporated into the design of which of the following sampling approaches?
The sampling design that would be especially likely to yield a representative sample is which of the following?
Which sampling method would be most practical and provide the most reliable data to study the medication errors by registered nurses who work in city, county, and federal prisons?
Stratified Random
When is a small sample size appropriate for a research study?
Large differences are expected in members of the population on the variable of interest.

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