research concepts for HIM (health information management)
Health Informatics Research Methods: Principles and Practice, Second Edition
Chapter 11: Selecting the Research Design and Method and Collecting Data
© 2017 American Health Information Management Association
© 2017 American Health Information Management Association
Learning Objectives
Select a research design and method appropriate to the research question.
Articulate the processes of data collection.
Identify a data collection instrument appropriate to the research question.
Determine standard and suitable tools and techniques to collect data.
Select a sampling technique appropriate to the research question.
Explain how data collection procedures affect studies’ timelines and the quality of their collected data.
Use key terms associated with instruments, sampling, samples, and data collection appropriately.
© 2017 American Health Information Management Association
Selecting a Research Design and Method
Purpose of the research (most important)
Internal validity and external validity
Internal: Extent to which researchers’ design and processes are likely to have prevented bias and increased accuracy of results
External: Extent to which results can be applied to other settings, populations, or other phenomena
Other factors in selection
Skills
Time
Money and resources
Potential subjects
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Collecting Data
Planning
Selecting an instrument
Determining a collection method
Deciding upon a collection strategy and sample
Performing pre-collection procedures
Collecting data
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Plan for Data Collection
What, how, by whom, and when
Also includes timelines for obtaining approvals, training collectors, and performing pilot study
Detail necessary for other researchers to replicate and reproduce
Important to document plan and its execution to support validity of studies’ results
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Plan for Data Collection (cont.)
Quantitative
Detailed and step-by-step
Conjunction with statistical analysis plan
All necessary data collected
Sufficient numbers of cases
Qualitative
Less structured than quantitative, dependent upon
Time available
Knowledge of phenomenon
Available instruments
Planned analyses
Researcher’s experience
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Selection of an Instrument
Instrument: Standardized, uniform way to
collect data
Using a well-designed instrument minimizes bias and maximizes the certainty of the independent variable’s effect on dependent variable
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Types of Instruments
Checklists
Coding schemes and manuals
Clinical screenings and assessments
Educational tests
Index measures
Interview guides
Personality tests
Projective techniques
Psychological tests
Questionnaires
Rating scales
Scenarios
Vignettes
And many others
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Sources of Instruments
Electronic databases
Health IT Survey Compendium
Human Factors: Workbench Tools
HaPI (Health and Psychosocial Instruments)
Mental Measurements Yearbook with Tests in Print
Articles found during literature review
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Validity of Instruments
Validity (of instruments): Extent to which the instrument measures what it is intended to measure
Face validity
Subject matter experts
Content validity
CVR
Essential, useful but not essential, not necessary
CVI
Construct validity
Construct
Convergent, discriminant, concurrent
Criterion validity
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Reliability of Instruments
Reliability: Extent to which a procedure or an instrument yields similar results over repeated trials, over time, across similar groups, within individuals, and across raters
Dependable and consistent in measurement
Consistency, dependability, and reproducibility characterize reliable instruments
Types
Interrater reliability and intrarater reliability
Test-retest reliability
Internal consistency reliability
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Reliability of Instruments (cont.)
Interrater reliability and intrarater reliability
Intraclass correlation coefficient
Cohen’s kappa coefficient
Test-retest reliability
Pearson product-moment correlation coefficient
Intraclass correlation coefficient
Internal consistency reliability
Split-half reliability coefficient (Spearman-Brown correction)
Kuder-Richardson formula
Cronbach’s alpha
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Factors in Selecting an Instrument
Purpose: Match between researcher’s purpose and instrument’s purpose
Theoretical underpinnings
Operational definitions
Most important to assure that the data collected are relevant to the research question
Satisfactory ratings for validity and reliability in a developed instrument
Style and format of the instrument
Clear and direct
Formats
Delivery medium
Language
Age groups
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Attributes of Items
Structured questions
Closed-ended
Choice from list of possible responses
Advantage
Easier for subject to complete
Easier for researcher to tally and analyze
Example: What is your gender?
___Male
___Female
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Attributes of Items (cont.)
Unstructured questions
Open-ended
Free-form responses
Advantage:
Collect in-depth data
Discover potentially unknown aspects of issue
Example: What barriers prevent you from exercising?
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Attributes of Items (cont.)
Semi-structured questions
Begin with structured question and followed by unstructured to clarify
Advantages of structured and unstructured questions
Would you consider yourself physical fit?
___Yes
___No
Why or why not?
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Attributes of Items
Numerical
Respondent enters number
Metric data
Specify unit of measure
Categorical
Respondent selects category or grouping
Nominal or ordinal data
All-inclusive
Mutually exclusive
Form meaningful clusters
Sufficiently narrow or broad
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Attributes of Items (cont.)
Scales: Form of categorical item that uses progressive categories, such as size, amount, importance, rank, or agreement
Scale
Points (2, 3, 4, 5-verbal frequency, 7-expanded Likert)
Likert scale (5-point)
Reliability improves from 2 to 7, but then improvement trivial
Semantic differential scale
Perspectives and images
Words that are polar opposites on ends of continua
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Attributes of Items (cont.)
Standardized categories found during literature review or obtained from authoritative sources
Races, age groups, and other subpopulations
Allow comparisons to other researchers’ results
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Attributes of Items (cont.)
Feasible logistics
Public domain items can be copied and used freely
Proprietary items must be purchased and cannot be copied
Hidden costs
Scoring
Users manual or scoring guide
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Examples of Instruments Used in Health Informatics and HIM
System Usability Score (SUS)
Software Usability Measurement Inventory (SUMI)
Questionnaire for User Interaction Satisfaction (QUIS)
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Techniques and Tools of Data Collection
Survey: Systematic collection of self-report data through interviews or questionnaires
Census survey: All members of the population
Sample survey: Representative members of the population
Observation: Collection of data by noting and recording
Tools developed prior to use
Transcription prior to coding and analysis
Rich data
Saturation
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Techniques and Tools of Data Collection (cont.)
Elicitation: Collecting data by evoking, bringing out, or drawing out through interview or review of documents
Purpose of obtaining unarticulated or tacit knowledge is what classifies a technique as elicitation
Uncover informants’ unarticulated knowledge
Used to obtain users’ and experts’ views
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Techniques and Tools of Data Collection (cont.)
Data sources
Primary
Secondary
Data access
Approval or permission
Individual or aggregate data
Public or proprietary data
Location of data
Data mining: use of various analytical tools to discover new facts, valid patterns, and relevant relationships in large databases
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Target Population, Sample, and Sampling
Target population: Set of individuals (or objects) of interest to the researchers
Sample: Set of units, such as portion of a target population
Sampling: Process of selecting the units to represent the target population
Sampling frame
Coverage error
Sampling error
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Methods of Sampling
Random sampling
Quantitative
Unbiased selection of subjects from target population in which all members have equal and independent chance of being selected
Underpins many statistical tests
Nonrandom sampling
Qualitative
No use of statistical methods of probability to select samples
No equal or independent chance of selection
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Types of Samples
| RANDOM | NONRANDOM |
| Simple | Convenience* |
| Stratified | Purposive |
| Systematic | Snowball |
| Cluster | Quota |
| Theoretical |
*Also sometimes used in quantitative research studies
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Sample Size and Sample Size Calculation
Sample size
Number of subjects determined by researcher to be included in order to represent the population
Should be large enough to support statistical tests
Sample size calculation
Quantitative and qualitative procedures to estimate the appropriate sample size
Best guess
Considerations
Purpose
Relationships among level of significance, power, effect size, statistical test, and sample size
Information about target population
Others
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Response Rate
Response rate: Number of people who completed or interviewed divided by total number of people in the sample
Adequacy of response rate
Review literature for typical response rates and factors affecting response rates
Mixed mode approach
Response bias: Systematic difference between responders and nonresponders
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Data Collection Procedures
Data collection procedures common to both quantitative studies and qualitative studies
Approvals of oversight committees
Training and testing
Pilot study
Assembling and storing data
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Review
Selecting the appropriate research design and method increase the likelihood that the data collected are relevant, high quality, and directly related to the research question
Factors in selecting a research design and method include purpose, internal and external validity, and others
Supporting the quality of the data and the study’s results are the processes of data collection, planning, selecting an instrument, determining techniques and tools, deciding upon a sampling strategy and sample, performing pre-collection procedures, and collecting data
An instrument is a standardized, uniform way to collect data
Factors in selecting an instrument are its validity and reliability of which there are multiple, the researcher’s purpose, and others
Techniques and tools of data collection vary by the method
Random sampling and nonrandom sampling are methods of sampling and several types of samples exist
Procedures associated with collecting data should be taken into account
© 2017 American Health Information Management Association