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research in health informatics is stimulating, dynamic, and varied. Provide reasons why you agree or why you disagree with the statement.

2. Identify the difference between a positive (direct) relationship and a negative (inverse relationship.

3. Why is evaluation research the “workhorse” of health informatics research?

i attached a powerpoint to help.

minimum of 100 words

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

© 2017 American Health Information Management Association

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

© 2017 American Health Information Management Association

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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

© 2017 American Health Information Management Association

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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

© 2017 American Health Information Management Association

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

© 2017 American Health Information Management Association

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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

© 2017 American Health Information Management Association

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

© 2017 American Health Information Management Association

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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

© 2017 American Health Information Management Association

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

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