Data Collection Methods NURS 306, Nursing Research Lisa Broughton, MSN, RN, CCRN

Types of Collection Methods 0 Existing data versus original data 0 Secondary analysis 0 Three major types of collection methods to gather original data 0 Self-reports 0 Direct observation 0 Biophysical measures (temperature, blood pressure, etc.)

Collection Decisions 0 Quantitative researchers determine up front which data collection methods will be used 0 Qualitative researchers have a general idea, but do not rule out other possible sources of information while in the field 0 Key dimensions: 0 Information should be obtained in a comparable, pre-specified way 0 Data that will be analyzed statistically must be quantifiable 0 Data collection methods differ in their degree of obtrusiveness 0 Quantitative methods strive for objectivity; qualitative methods do not 0 Research questions typically determine which collection methods should be used

Self-Reports 0 Qualitative self-reporting techniques 0 Use flexible methods 0 Limits a set of questions to be asked but start with general questions and allow participants to tell their stories 0 Unstructured interviews 0 Semi-structured interviews 0 Focus group interviews 0 Life histories 0 Diaries or blogs 0 Critical incident technique 0 Think-aloud method

Self-Reports 0 Quantitative self-reporting techniques 0 Usually collected by a formal, written document- instrument 0 Closed-ended questions 0 Can be yes/no or rated in a Likert-type format 0 Open-ended questions 0 Vignettes 0 Instrument construction 0 Pilot-testing 0 Interviews versus questionnaires 0 Questionnaires are more cost effective, less time consuming, and more private but exclude some participants such as blind or illiterate 0 Interviews have a better response rate, are less likely to be misinterpreted, and can produce more thorough information

Advantages and Disadvantages of Self-Reports 0 Advantages 0 The most direct approach 0 Disadvantages 0 Validity and accuracy of self-reports 0 Qualitative self-reports are time consuming and demanding

Measurement 0 Assigning numbers to qualities of objects to designate the quantity of an attribute 0 Removes guesswork and ambiguity 0 Can obtain reasonably precise information

Levels of Measurement 0 Nominal 0 Involves using numbers to categorize attributes; numbers do not have quantitative meaning 0 Male=1, Female=2 0 Ordinal 0 Ranks objects based on their relative standing on an attribute 0 Ranking individuals heaviest to lightest or class rank 0 Interval 0 Can specify rankings of objects on an attribute and the distance between those attributes 0 IQ tests 0 Ratio 0 Have a rational, meaningful zero and provide information about the magnitude of an attribute 0 Weight, temperature, blood pressure

Observation 0 Direct observation of an individual’s behavior 0 Qualitative observation methods 0 Skillful, unstructured observation allows researchers to see the world as study participants see it and to develop a rich understanding of the concept of interest 0 Participant observation 0 Positioning 0 Recording

Observation 0 Quantitative observation methods 0 Structured observation uses formal instruments and/or protocols on what to observe, how long, and how to record the data 0 Documents specific behaviors, actions, and/or events 0 Category system 0 Rating scale 0 Time sampling 0 Event sampling

Advantages and Disadvantages of Observation 0 Advantages 0 Certain research questions are better suited to observation than self-reports 0 Disadvantages 0 Reactivity to being watched 0 Ethical considerations 0 Observation bias

Biophysical Measures 0 Used mainly to describe physiologic responses to nursing actions and/or interventions 0 Can be in vivo or in vitro 0 Accurate and precise 0 Objective

Important Considerations 0 Who will collect the data? What kind of training must be provided? Can the people collecting the data produce valid and accurate assessments? 0 How will data be collected? Privacy must be ensured

Errors of Measurement 0 Error of measurement 0 Difference between the true score and the obtained score 0 Response-set biases 0 Personal factors 0 Variations in collection 0 Item sampling

Reliability 0 Consistency with which an instrument measures the attribute 0 Three aspects of reliability: 0 Stability 0 Test-retest reliability 0 Reliability coefficient (r) 0 Ranges from ; the higher the value, the more stable the instrument 0 Internal consistency 0 Items all measure the same trait 0 Most common measure used to test reliability 0 Cronbach’s alpha or coefficient alpha 0 Ranges from ; the higher the value, the more internally consistent the instrument 0 Equivalence 0 Two or more observers agree about the scoring on the instrument 0 Inter-rater reliability

Validity 0 The degree to which an instrument measures what it is supposed to measure 0 Instruments cannot be valid if unreliable but can be reliable but not valid

Validity 0 Four aspects of validity: 0 Face validity 0 The instrument looks like it will measure the appropriate construct, especially to those completing it 0 Content validity 0 The instrument has an appropriate sample of items to test the construct and adequately covers the construct 0 Determined by experts in the field; based on judgment

Validity 0 Four aspects of validity: 0 Criterion-related validity 0 Establishes a relationship between scores on an instrument and an external criterion 0 Predictive validity 0 Concurrent validity 0 Validity coefficient 0 Ranges from ; the higher the value, the more valid the instrument 0 Construct validity 0 Does it validly measure the concept of interest 0 Logical analysis based upon theory related to the concept being studied