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

Data Collection Methods Without appropriate data collection methods, the validity of research conclusions is easily challenged

Data Collection Methods Using New Data Collect own data for the study

Data Collection Methods Using Existing Data Historical research Use records and other documents from the past Secondary analysis Use of data gathered in a previous study

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

Quantitative Research Data Collection Quantitative Research

Types of Data Collection Self-Reports Observation Biophysiologic Measures

Types of Data Collection Self-Reports Interviews Questionnaires Scales Vignettes Projective techniques Q-sorts

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

Types of Data Collection: Self-Reports Interviews and Questionnaires (Structured) 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

Types of Data Collection: Self-Reports Interviews and Questionnaires (Structured) Open-ended questions Allows participants to respond to questions in their own words Allows for richer, fuller information

Types of Data Collection: Self-Reports Interviews and Questionnaires (Structured) Instrument Construction Develop outline of content of research Design questions Pretest Trial run to determine if instrument is free of biases, errors, etc

Types of Data Collection: Self-Reports 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

Types of Data Collection: Self-Reports Interviews Vs. Questionnaires 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

Types of Data Collection: Self-Reports Interviews Vs. Questionnaires Interviews are considered to be superior to questionnaires

Types of Data Collection: Self-Reports Types of Self-Reports (Structured) Composite Scales (social - psychological) Vignettes Projective techniques Q sorts

Types of Data Collection: Self-Reports Composite Scales (social - psychological) Scale: assigns a numeric score to people to place them on a continuum with respect to attributes being measured

Types of Data Collection: Self-Reports Composite Scales (social - psychological) Likert scale Semantic Differential scale Visual Analog scale

Types of Data Collection: Self-Reports Composite Scales (social - psychological) 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

Types of Data Collection: Self-Reports Composite Scales (social - psychological) Example Likert Scale: AU nursing students are very well prepared for working within the current healthcare system Strongly agree Agree Neutral Disagree Strongly disagree

Types of Data Collection: Self-Reports Composite Scales (social - psychological) 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

Types of Data Collection: Self-Reports Semantic Differential Example AU nursing graduates are: Competent Incompetent Intelligent Dim Visual Analog Scale 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

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

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)

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

Types of Data Collection: Self-Reports 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

Types of Data Collection: Self-Reports 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

Types of Data Collection: Self-Reports Q Sorts Uses a set of card with words, phrases or statements Participant sorts cards along a bipolar dimension (agree/disagree)

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

Disadvantages of Self-Reporting Methods Questionable validity and accuracy Biases

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

Types of Data Collection: Observation 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

Types of Data Collection: Observation Observational Methods (structured) Categories and checklists Rating Scales

Types of Data Collection: Observation 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

Types of Data Collection: Observation Observational Sampling Time sampling Selection of time periods for observations Event sampling Selects behaviors or events for observation

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

Types of Data Collection Biophysiologic

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

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

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

Measurement and Assessment of Data

Measurement Involves rules for assigning numeric values to qualities Determines how much of an attribute is present Quantification Communicates the amount in numbers

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

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

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

Reliability of Measuring Instruments Refers to the consistency with which an instrument measures the attribute The less variation in repeat measures the higher its reliability

Reliability of Measuring Instruments Aspects of reliability Stability Internal consistency Equivalence

Reliability of Measuring Instruments 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

Reliability of Measuring Instruments 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

Reliability of Measuring Instruments 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

Reliability of Measuring Instruments 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)

Validity of Measuring Instruments Is the concern whether the measurement tools actually measure what they are supposed to measure

Validity of Measuring Instruments Aspects of Validity Face validity Content validity Criterion-related validity Construct validity

Validity of Measuring Instruments Face validity Whether the instrument looks as though it is measuring the appropriate construct

Validity of Measuring Instruments Content Validity Concerned with adequacy of coverage of the content area being measured Tests of knowledge Psychosocial traits Based on judgment

Validity of Measuring Instruments 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

Validity of Measuring Instruments Construct Validity Concerned with what construct is the instrument actually measuring

Validity of Measuring Instruments 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

Reliability of Measuring Instruments 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

Data Collection Qualitative Research

Questions for Thought What are the systematic rules for analyzing qualitative data?

Qualitative Data Collection Types of Self-Reports - Unstructured Self-Reports Methods (Unstructured) Interviews Diaries Observation

Qualitative Data Collection Types of Self-Reports - Unstructured 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

Qualitative Data Collection Types of Self-Reports - Unstructured 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

Qualitative Data Collection Types of Self-Reports - Unstructured Focus group interviews Interviews with groups of 5 to 15 people whose opinions and experiences are solicited simultaneously Uses topic guide to guide questions

Qualitative Data Collection Types of Self-Reports - Unstructured Life Histories Narrative self-disclosures about life experiences Has informants describe experiences in chronological order Orally or written

Qualitative Data Collection Types of Self-Reports - Unstructured Diaries Have informants maintain daily logs of some aspect of their lives

Qualitative Data Collection: Observational Methods - Unstructured 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

Qualitative Data Collection: Observational Methods - Unstructured 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

Qualitative Data Collection: Observational Methods - Unstructured 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

Qualitative Data Collection: Observational Methods - Unstructured 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

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

Assessment of Qualitative Data Establish Trustworthiness by assessing: 1. Credibility 2. Dependability 3. Confirmability 4. Transferability

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

Assessment of Qualitative Data: Trustworthiness 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)

Assessment of Qualitative Data: Trustworthiness 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

Assessment of Qualitative Data: Trustworthiness 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

Assessment of Qualitative Data: Trustworthiness 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

Assessment of Qualitative Data: Trustworthiness 4. Transferability The extent to which the findings from the data can be transferred to other settings or groups

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.