1 data collection, measurement, & data quality in quantitative and qualitative research

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Data Collection, Measurement, & Data Quality in Quantitative and Qualitative Research

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Data Collection Methods

• Without appropriate data collection methods, the validity of research conclusions is easily

challenged

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• Using New Data

– Collect own data for the study

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• Using Existing Data

– Historical research• Use records and other

documents from the past

– Secondary analysis• Use of data gathered in a

previous study

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Key Dimensions of Data Collection Methods

• Structure– The data collection should be very structured and consistent

• Quantifiability– Able to be analyzed statistically

• Obtrusiveness– Degree to which people are aware that they are being studied

• Objectivity– Try to be as objective as possible

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Data Collection

Quantitative Research

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Types of Data Collection

• Self-Reports

• Observation

• Biophysiologic Measures

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• Self-Reports– Interviews– Questionnaires– Scales– Vignettes– Projective techniques– Q-sorts

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Types of Data Collection: Self-Reports

Interviews and Questionnaires (Structured)

• Participant's responses to questions by researcher

• Data is usually collected by means of a formal, written document (instrument)

• Uses an interview schedule for questions that are asked orally (face to face or via phone)

• Uses a questionnaire when participants complete the instrument themselves

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– Closed-ended questions (fixed alternative questions)

• Response alternatives are specified by the researcher• Ensures comparability of responses• Facilitates analysis• Easy to administer• More efficient time use• Difficult to develop• Could lead to overlooking something important

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– Open-ended questions• Allows participants to respond to questions in their own

words• Allows for richer, fuller information

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– Instrument Construction

• Develop outline of content of research

• Design questions• Pretest

– Trial run to determine if instrument is free of biases, errors, etc

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• Interviews Vs. Questionnaires

– Advantages of questionnaires• Less costly• Require less time and effort to administer• Can be completely anonymous• No biases relating to the researcher being present

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– Advantages of Interviews• Response rate is higher in face to face interviews• Effective for those that can not complete questionnaires

(children, blind, ESL, elderly)• Questions are less likely to be misinterpreted than

questionnaires• Interviews can produce additional information through

observation

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– Interviews are considered to be superior to questionnaires

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Types of Self-Reports (Structured)

• Composite Scales (social - psychological)

• Vignettes

• Projective techniques

• Q sorts

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Composite Scales (social - psychological)

– Scale: assigns a numeric score to people to place them on a continuum with respect to attributes being measured

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– Likert scale– Semantic Differential scale– Visual Analog scale

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– Likert scale (summated rating scales)• Consists of several declarative statements that express a

viewpoint• Participant indicates the degree to which they agree to

disagree• Able to summate the scores allowing for discrimination

among people with different viewpoints

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Example Likert Scale:

AU nursing students are very well prepared for working within the current healthcare system

Strongly agree Agree Neutral Disagree Strongly disagree

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– Semantic Differential• Participants rate a concept on a series of bipolar adjectives• Can measure any concept

– Visual Analog Scale• The scale is a straight line with anchors which are the

extreme limits of the experience or feeling• Measures subjective experiences

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– Semantic DifferentialExample

AU nursing graduates are:Competent IncompetentIntelligent Dim

– Visual Analog ScaleExample

On a scale of 0 to 10 how would you rate your pain if 10 was the worst pain you have even experienced and 0 was no pain

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Advantages of Scales

– Scales allow researchers to efficiently quantify the strength and intensities of individual characteristics

– Discriminates among people with different attitudes, fears, motives, perceptions, personality traits, needs

– Good for group and individual comparisons

– Can be implemented either verbally or in writing

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Disadvantages of Scales

Response set biases

– Social Desirability Response Set Bias• Participants give answers that are common social views

– Extreme Response Set Bias• Participants express attitudes or feelings in the extreme (always, never)

– Acquiescence Response Set Bias• Participants agree with all statements (yea-sayers or nay-sayers)

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Disadvantages of Scales

– Ways to Reduce Response Set Biases

• Counterbalancing: positively and negatively worded statements

• Developing sensitively worded questions

• Creating a permissive, nonjudgmental atmosphere

• Guaranteeing confidentiality

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Vignettes

– Brief description of events or situations to which participants are asked to react

– Information about perceptions, opinions, or knowledge– Questions post vignettes may be open-ended or close-

ended

– Economical to administer– May contain response biases

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Projective Techniques

– Verbal self reports to obtain psychological measurements

– Seek minimal participants’ conscious cooperation– Ambiguous or unstructured stimuli elicits participants

needs, motives, attitudes, personality traits

i.e. Inkblot test, word association, role playing, drawing

– Useful in children, hearing or speech impaired

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Q Sorts

– Uses a set of card with words, phrases or statements– Participant sorts cards along a bipolar dimension

(agree/disagree)

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Advantages of Self-Reporting Methods

• Most common method of data collection used by nurses

• Reveal information that is difficult to obtain by other means

• Can gather retrospective and prospective data

• Can measure psychological characteristics

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Disadvantages of Self-Reporting Methods

• Questionable validity and accuracy

• Biases

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Types of Data Collection: Observation

• Observational Methods– An alternative to self-reports– Can be used to gather information such as characteristics,

condition of individuals, verbal communication, nonverbal communication, activities, environmental conditions

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Observational Methods

• Researcher has flexibility in the following areas:– The focus of observation

• What events are to be observed

– Concealment– Duration of observation– Method of recording observations

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Observational Methods (structured)– Categories and checklists– Rating Scales

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Categories and Checklists

• Category system: – attempts to designate information in a systematic, quantitative

manner– Clear definition of behaviors and characteristics to be observed is

necessary– Lists all behaviors or activities the observer wants to observe and

records occurrences

• Checklist: – instrument to record observations

• Rating Scales:– Are tools that require the observer to rate some phenomena along a

descriptive continuum

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– Observational Sampling

• Time sampling– Selection of time periods for observations

• Event sampling– Selects behaviors or events for observation

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Evaluation of Observational Methods

• Advantages– Provides depth and variety of information– Some problems are better suited to observation

• Disadvantages– Potential ethical issues– Lack of consent to be observed– Participants reaction to be observed– Biases

• Faulty inferences

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Biophysiologic

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Types of Data Collection: Biophysiologic

Types of Biophysiologic Measures

– In vivo• Measures performed directly within or on living organisms

– i.e. blood pressure, temperature

– In vitro• Data gathered from participants by extracting some

biophysiologic material from them for lab analysis– i.e. blood work, microbiologic measures, cytology and histological

measures

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Advantages of Biophysiologic Measures

– Are relatively accurate and precise– Are objective– Provide valid measures of targeted variables– Equipment is readily available

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Disadvantages of Biophysiologic Measures

– Measuring tool may affect variables it is attempting to measure

– Interferences may create artifact– Energy must often be applied to the organism when

taking measurements

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• Measurement and Assessment of Data

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Measurement

• Involves rules for assigning numeric values to qualities

• Determines how much of an attribute is present

• Quantification– Communicates the amount in numbers

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Advantages of Measurement

– Removes guesswork in gathering information– Tends to be objective– Obtains precise information– Can differentiate among people who possess different

degrees of an attribute– Common language

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Errors of Measurement

– Always the potential for error in all tools– Extraneous factors affect measurement and distort

results• Obtained score – is observed score• True score – true score if no errors• Error of measurement – the different between the true and

obtained scores

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Factors Contributing to Errors of Measurement

– Situational contaminants» People’s awareness of observer, environmental factors

– Response set biases

– Transitory personal factors» Fatigue, mood, hunger (temporary)

– Administration variations» Alterations in data collection methods

– Item sampling» Errors introduced as a result of sampling

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Reliability of Measuring Instruments

Reliability

– Refers to the consistency with which an instrument measures the attribute

– The less variation in repeat measures the higher its reliability

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Reliability

– Aspects of reliability • Stability• Internal consistency• Equivalence

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• Stability

• The extent to which the same scores are obtained when the instrument is used with the same people on separate occasions

• To assess stability: Test-retest reliability– researcher administers the same measure to a sample of

people on two occasions and then compares the scores

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• Internal Consistency

• Reliable to the extent that all its subparts measure the same characteristic

• To assess internal consistency: Split-half technique – the items comprising the test or scale are split into two

groups and scored, compute reliability coefficient

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• Equivalence

• Determines the consistency or equivalence of the instrument by different observers or raters

• To assess equivalence – interrater (interobserver) reliability– Has two or more trained observers make simultaneous,

independent observations, compete reliability coefficient

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• Reliability Coefficients– A quantitative statistic that estimates how reliable an

instrument is

• Determine an instrument’s quality• Low reliability makes it difficult to adequately test research

hypothesis• If sample too homogeneous, the lower reliability coefficient

will be (instruments are designed to measure differences)

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Validity of Measuring Instruments

Validity

– Is the concern whether the measurement tools actually measure what they are supposed to measure

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Aspects of Validity• Face validity• Content validity• Criterion-related validity• Construct validity

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– Face validity• Whether the instrument

looks as though it is measuring the appropriate construct

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– Content Validity• Concerned with

adequacy of coverage of the content area being measured

– Tests of knowledge– Psychosocial traits– Based on judgment

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– Criterion-Related Validity

• Wants to establish the relationship between scores on an instrument and some external criterion

– Compute a validity coefficient – correlates scores on the instrument with scores in the criterion variable

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– Construct Validity• Concerned with what

construct is the instrument actually measuring

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• To assess construct validity–– known-groups technique

» Groups that are expected to differ on certain attributes are administered the instrument then scores are compared

– Factor analysis» Statistical procedure

– Examination of relationships based on theoretical predictions

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• If a measuring device is not reliable, it can not be valid– High reliability of an instrument provides no evidence of its

validity– Low reliability is evidence of low validity

• An instrument can be reliable without being valid

Reliability consistently measures accurately

Validity measures what it is supposed to

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Data Collection

Qualitative Research

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Questions for Thought

• What are the systematic rules for analyzing qualitative data?

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Qualitative Data CollectionTypes of Self-Reports - Unstructured

Self-Reports Methods (Unstructured)

• Interviews• Diaries• Observation

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Interviews• Flexible• Not directed by set questions• Interviews are conversational in nature• Usually interviews are long• Can be tape recorded or researcher may take notes

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• Completely unstructured interviews• Start with broad (grand tour) questions• Further questions are guided by initial responses – one

question's answer leads to the next question

• Focused or semi-structured interviews• Researcher lists topics that must be covered in an interview• Uses a topic guide to ensure all question areas are covered

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• Focus group interviews• Interviews with groups of 5 to 15 people whose opinions and

experiences are solicited simultaneously• Uses topic guide to guide questions

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• Life Histories• Narrative self-disclosures about life experiences• Has informants describe experiences in chronological order• Orally or written

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Diaries• Have informants

maintain daily logs of some aspect of their lives

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Qualitative Data Collection: Observational Methods - Unstructured

Observational Methods• Unstructured observation

– Attempt to see the world as the participants see it– Participant observation – data collector actually participates in the

group» Participation can be from the role as an observer or totally

immersed in the social setting as a participant» Researcher needs to gain entrée into the social group under

investigation» Researcher needs to establish rapport and develop trust within

the group

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• Observational Data Collection– Physical setting

» In what context is the human behaviour occurring– Participants

» Information about the participants, what are their roles, characteristics

– Activities» What are the participants doing

– Frequency and duration» Specific information about the activity

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– Process» How is event occurring

– Outcomes» Why is the activity occurring and what are the results

– Single positioning» Staying in a single location

– Multiple positioning» Involves moving around to observe behaviour from different

perspectives– Mobile positioning

» Involves following a person throughout a given activity

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• Observational Data Recording• Uses logs and field notes

» Log – records daily events» Field notes – observer’s efforts to record information and

understand data» Observational notes – descriptions of events and conversations» Theoretical notes – interpretive attempts to attach meaning to

observations» Methodologic notes – instructions about what observations that

need to be made» Personal notes – comments about researcher’s own feelings

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Assessment of Qualitative Data

– Do the measures used by the researcher yield data reflecting the truth

– Qualitative research attempts to do this through establishing the data’s trustworthiness

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Assessment of Qualitative Data

Establish Trustworthiness by assessing:– 1. Credibility– 2. Dependability– 3. Confirmability– 4. Transferability

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Assessment of Qualitative Data:Trustworthiness

1. Credibility– Confidence in the truth of the data

• Prolonged engagement and persistent observation– Sufficient time to collect data, focus on the phenomena being studied

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Triangulation– Use of multiple referents to draw conclusions, attempts to distinguish true

information from errors

– Data Source Triangulation» Multiple data sources (interviewing diverse informants on same topic)

– Investigator Triangulation» Using more than one person to collect data

– Theory Triangulation» Using multiple perspectives to interpret data

– Method Triangulation» Using multiple methods (observation and interviews)

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• External checks: Peer debriefing and member checks– Peer debriefing – review and explore various aspects of inquiry with

objective peers– Member checks – providing feedback to study participants and

assessing their reactions

• Searching for Disconfirming evidence– Search for data that challenges the emerging conceptualization or

theory

• Researcher credibility

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2. Dependability– Data stability over time and over conditions

– Stepwise replication• Having several researchers break into teams and evaluate

the data separately and then compare conclusions

– Inquiry audit• Scrutiny of the data and supporting documents by an

external reviewer

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3. Confirmability– The objectivity or neutrality of the data, can other

independent people agree about data’s relevance

– Audit trail – documentation that allows an independent auditor to come to the same conclusions about the data

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4. Transferability– The extent to which the findings from the data can be

transferred to other settings or groups

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Reference

• Loiselle, C. G., Profetto-McGrath, J., Polit, D. F., & Beck, C. T. (2011). Canadian essentials of nursing research. (Third Edition). Philadelphia: Lippincott, Williams & Wilkins.

1 data collection, measurement, & data quality in quantitative and qualitative research

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