mixed methods: myths, traditions & strategies methods myths traditions...1. convergent parallel...

Mixed Methods:

Myths, Traditions &

Strategies

Canada Research Chair Seminar Series, Aging and Community Health Research Unit, School of Nursing, McMaster University

May 5 2015

By: Kathryn Fisher, PhD

Topics

1. Defining features of mixed methods research

2. Current techniques to integrate qualitative and

quantitative research

3. Value of using qualitative approaches in intervention

studies

4. Key challenges in using qualitative research alongside

RCTs

1. Defining Features of Mixed

Methods Research

Defining Feature #1: Controversy

Creswell’s 11 Key Controversies1

1. How should mixed methods be defined?

2. Does the use of “quantitative” and “qualitative” in mixed methods create an artificial and unnecessary binary distinction?

3. Should there be a bilingual nomenclature for mixed methods?

4. Have we arrived at an understanding of the types of research designs in mixed methods?

5. Can we “mix” paradigms in mixed methods?

6. What is the value added by mixed methods beyond conducting a quantitative or a qualitative study?

7. What is driving the interest in mixed methods?

8. Is mixed methods a “new” approach?

9. Does mixed methods privilege post-positivism?

10. Is there a dominant, meta-narrative discourse emerging in mixed methods?

11. Is mixed methods claiming other designs as “their own” ?

Controversy - Continued

fundamental questions continue to be debated:

• What is mixed methods?

• Can we do it?

• How do we do it?

• Why do it?

• Does it really exist?

Despite these debates, we observe…

Controversy - Continued

long tradition of mixed methods in sociological research (since1800’s)2,3

qualitative methods now common in4,5 :

clinical trials

surveys of attitudes/beliefs

epidemiological studies

Guidelines and operating procedures now exist – examples:

Best Practice Guidelines for Mixed Methods Research in the Health Sciences (U.S., 2011)6

Standard Operating Procedures for Qualitative Methods in Clinical Trials (U.K., 2013)7

Defining Feature #2: Qualitative + Quantitative

Most researchers use the term mixed methods to refer to

the use of qualitative and quantitative research methods

to investigate a topic8-11

Some researchers consider multiple methods, even within

the same tradition, as mixed methods, particularly if they

have a core & supplementary component12,13

Defining Feature #3: Integration

Most researchers claim that mixed methods requires9:

1. Deliberate integration.

2. Sum greater than the parts.

Some researchers claim that mixed methods can be10:

1. Mere use of qualitative and quantitative methods in same study.

2. Comparing qualitative and quantitative results.

3. Actual integration/merging of the two data types.

Defining Feature #4: Pragmatism

“Paradigm Wars” of 80’s & 90’s have ended and methodological

focus is now on integration2

Pragmatism now the dominant epistemology8,10

At philosophical level: accept that scientific truths are both

constructed and grounded in the world

At practical level: choose design assemblages (methods) that

best address research aim(s)

Defining Feature #5: Complementarity

main goal of mixed methods:

to gain a more complete picture (complementarity)

not “triangulating” in traditional sense (one method validatingthe other, ˃1 method addressing same research question)

Why validation not the goal:

Defy direct comparison: qualitative and quantitative methods

address different questions & differ in what they look at, how

they see it, & how they describe it42-44

Similar findings: comforting/reassuring but not validating

Defining Feature #6: Prototypical Designs

15+ mixed methods design typologies published14

Current view:

the research question(s) determine the method(s)15

use existing typologies as guide to tailor-make design that

answers your research question(s)16

Design typologies differ on 2 dimensions:

Timing

Emphasis

Prototypical Designs - Continued

most typologies recognize 2 major designs originally proposed

by Cresswell & Plano Clark9,16 :

1. Concurrent Designs:

Timing: qualitative and quantitative components

undertaken simultaneously

Emphasis: varies (equal if done in parallel, if embedded

less emphasis on nested method)

2. Sequential Designs:

Timing: qualitative completed before quantitative

component or vice versa

Emphasis: on method that comes first

2. Integrating Qualitative and

Quantitative Findings

Integration

Options for integration span 2 dimensions:

How to integrate

Where to integrate

Sampling

Data collection

Data analysis

Interpretation

Mixed Methods Matrix , Triangulation Protocols:

Qualitative & quantitative findings displayed on same page

Identify patterns, cross-cutting (“meta”) themes, paradoxes

Following a thread:

Theme from one component followed up with the other

Example: hypothesis from qualitative findings tested by survey

Data transformation:

“Quantitizing” qualitative data

“Qualitizing” quantitative data

Example: cross-tab qualitative themes against quantitative data

How to Integrate- Specific Approaches10,42

Where to Integrate

often conceptualized by linking methods of data collection

and analysis (methods level integration)14

Methods level integration relates to the study design14,32

We will discuss:

Methods level integration paths for main study designs

Examples from intervention studies (or study protocols)

17

QUAN

Data &

Results Interpretation

QUAL

Data &

Results

1. Convergent Parallel Design

Concurrent Mixed Methods Designs

• Most common design used in healthcare research29

• Timing:

• concurrent data collection

• data may or may not be collected from same study sample

• Emphasis: equal for qualitative and quantitative components

• Integration (“Merging”, “Triangulating”):• two databases merged for analysis &/or interpretation• identify convergence, divergence or complementarity

Example 1: Group Cohesion in Patients Participating in Physical Exercise Intervention41

Purpose: explore cohesion and quality of life (QoL) in cancer patients participating in

a 6 week physical exercise intervention.

Methods:

• QUAN: validated survey administered at baseline and 6 weeks used to determine

changes in QoL and health status

• QUAL: focus groups conducted post intervention to explore group cohesion.

Results:

• QUAN: showed significant improvements in emotional functioning, social functioning and mental health

• QUAL: showed that group setting motivated patients by developing a sense of

obligation to train and do their best, thereby improving their social and emotional

functioning and mental healthDiscussion: the results converge to support the theory that group cohesion and sense

of belonging facilitates achievement of social and emotional functioning.


1. Convergent Parallel Design (Example – Convergent Results)

Example 1: Caregiver Outcomes & Experiences of a Respite Care Intervention40

Purpose: explore caregivers’ stress and perceptions of respite services provided by an

independent hospice.

Methods:

• QUAN: validated Relative Stress Scale Inventory (RSSI) was used to measure stress & was completed (pre & post) by 12 caregivers

• QUAL: 12 caregivers also completed interviews about views of respite care

Results:

• QUAN: showed no significance difference between pre & post stress levels

• QUAL: findings supportive of the intervention, showing that most caregivers saw

respite care as important as it gave them a break/rest from caregiving

Discussion: researchers concluded that divergent results indicated an inadequate

questionnaire (RSSI), others29 suggest that theory underpinning the research should be changed to suggest that respite care may relieve instrumental caregiving

responsibilities, but that other support is needed to relieve caregiving distress.


1. Convergent Parallel Design (Example – Divergent Results)

Example 2: Palliative Care Practices & Meanings in End of Life Nursing Home Residents31

Purpose: explore palliative care practices in nursing home residents with dementia at

end of life (EOL) and perceptions (of residents, family, nursing home staff) of EOL care.

Methods:

• QUAN: independent strand (n=30) with its own questions, samples, data collection,

and analysis techniques. Used a retrospective chart review to assess (a) symptoms

(b) interventions, (c) decisions to limit curative care, and (d) death cause/location.

• QUAL: independent strand (n=30) that used an ethnographic field study to examine

views about what was good/not good and what could be done differently.

Results:

• QUAN: life-prolonging measures rare, symptom management less conservative and

symptoms increased dramatically in the last month of life

• QUAL: challenges in gauging decline, determining when to intervene & how, & how

to maintain normalcy & dignity.

Discussion: QUAL and QUAN results were complementary, indicating that palliative care

can be appropriate in nursing homes, but should begin earlier to help residents/families understand the condition & treatment options, and adjust to changes over time.


1. Convergent Parallel Design (Example – Complementary Results)

21

QUAN

Pre-test

Data &

Results

QUAN

Post-test

Data &

Results

Intervention

qual

Process

(before, during or after)

Interpretation

2. Embedded Design (AKA “Basic Intervention Mixed Methods Design”9,32)


• Qualitative data collected mainly to support development of intervention,

understand contextual factors, and/or explain results5,9

• Timing: two data collection methods, one embedded in the other, embedded

one can occur before, during or after intervention

• Emphasis: priority given to method addressing primary question (QUAN)9

• Integration (“Embedding”): results often embedded at multiple points, data integrated for analysis and interpretation

22

2. Embedded Design (Example)


Example: Study Protocol for Pilot RCT of Stepped Care Treatment of Depression

(STEPS)33

Purpose: determine feasibility and acceptability of STEPS intervention; results to inform

design of a fully-powered RCT on the effectiveness & efficiency of stepped care.Methods:

• QUAN: obtain pilot data on recruitment, retention and the pathway of patients

through treatment to assess feasibility. Outcome data (depressive symptoms, worry,

anxiety, QoL) collected at baseline and 6 months on the effects of stepped care

compared with high-intensity therapy. A minimum of 60 patients with Major

Depressive Disorder will be recruited from an Improving Access to Psychological

Therapies service and randomly allocated to each group.

• QUAL: interviews will obtain data on acceptability. Pilot trial and interviews will be undertaken concurrently. Quantitative and qualitative data will be analysed

separately and then integrated.

23

Sequential Designs Mixed Methods Designs

QUAN

Data &

ResultsInterpretation

qual

Data &

ResultsConnecting to (following up)

1. Explanatory Design

• Usually used when quantitative results are unexpected, or measures

known to be insufficient to address research question,

• Timing: collection and analysis of quantitative data followed by the

collection and analysis of qualitative data.

• Emphasis: priority may be with quantitative method, or can be equal

• Integration (“Connecting”): qualitative database links to the

quantitative database through sampling (e.g., subset of survey respondents selected based on survey scores)

24


1. Explanatory Design (Example)

Example: Prevalence and predictors of premature discontinuation of antiplatelet

drug therapy after stent placement36,37

Purpose: determine the prevalence and predictors of discontinuing antiplatelet

drugs before the recommended duration.Methods:

• QUAN: patients with acute myocardial infarction (AMI) (n=500) followed to see if

they took the recommended antiplatelet drug for the recommended duration.

• Qual: AMI patients who discontinued either clopidogrel (n=11) or cholesterol-

lowering therapy (n=29) interviewed to determine reasons for discontinuation.

Results:

• QUAN: 14% of patients with AFI discontinued drugs despite potentially fatal

consequences for early termination

• Qual: patients cited a number of reasons for discontinuing the drugs, many

related to poor communication between physician and patient.

Discussion: the reasons for discontinuing the drugs informed the development of a

guide to support patient-clinician communication about heart medications.38

25


QUAL

Data &

Results

quan

Data &

ResultsInterpretation

Building to

2. Exploratory Design

• Often used in instrument development

• Timing: collection and analysis of qualitative data followed by the

collection and analysis of quantitative data

• Emphasis: priority may be with qualitative method or equal

• Integration (“Building”): qualitative results inform data collection approach used in quantitative component (e.g., items in survey built from previously collected qualitative data)

26


2. Exploratory Design (Example)

Example: Use and Perceptions of Electronic Dietary Assessment (e-DA) Tools by Health

Care Professionals39

Purpose: explore provider use & perspectives on e-DA tools in mobile apps & websites.

Methods:

• QUAL: 11 interdisciplinary focus groups with 50 providers to obtain perspectives on

use of e-DA. Focus group transcripts used to develop web-survey, interpretive themes added depth/context.

• Quan: web-based survey sent to Family Health Teams throughout Ontario,

descriptive and bivariate analyses completed.

Results:

• QUAL: suggested barriers to using e-DA include: patients’ lack of comfort with using

technology, patient misinterpretation of e-DA results, time and education for

providers to interpret results & train/educate patients.• QUAN: indicated e-DA used to improve: 1) patients’ eating habits; 2) quality of

dietary assessment; and, 3) care process. Dietitians used e-DA more than other

providers. Strong interest across disciplines in using e-DA tools for managing

obesity, diabetes and heart disease, especially for patient self-monitoring.

3. Value of Using Qualitative

Approaches in Intervention

Studies

Value of Qualitative Approaches in Intervention Studies

we focus on:

1. how qualitative research is used in RCTs

2. the value, or potential value, of qualitative results in generating evidence for the effectiveness of interventions.

Key reviews: O’Cathain et al. (2013)45, Lewin et al. (2011)5

Q1: How is Qualitative Research Actually Used?

Before a trial:

Explore research question, health condition & context

Identify ethical issues

Explore issues relating to recruitment, retention, diversity

Identify models, mechanisms, theory & hypotheses for RCT

Develop or refine intervention content & delivery

Explore feasibility & acceptability of intervention & trial

Develop or select outcome measures

During a trial:

Determine Intervention actually delivered & fidelity

“Unpack” processes of implementation and change

Explore feasibility & acceptability of intervention & trialAfter a trial:

Explain findings

Explain variation in effectiveness of intervention

Assess appropriateness of theory, modify accordinglyGenerate further questions, hypotheses, future studies

Q2: What is the Value of Qualitative Research in RCTs?

Item Potential Value Examples

1. Bias Avoids measurement

bias

-Helps test face and content validity of

instruments with patients/providers

2. Efficiency Increases recruitment

rate

-Use of observation and interviews to

identify problems with recruitment

Saves money -stops attempts to undertake full trials of

poor/unacceptable interventions or

weak trial designs

-ensures full trials are only undertaken on

promising/optimized interventions

3. Ethics Determine sensitivities

of providers & patients

-design recruitment and communication

strategies to ensure positive experience

Improves informed

consent

-communication valued as much as

information (“gold standard” of informed

consent)



4. Implementation Replication in real

world

-describes components and essential

elements of intervention to enable

replication

Transferability -identifies mechanisms or action or

contextual issues needed for success

5. Interpretation Explain findings -explains null findings

-contextualizes successful interventions to

disseminate & transfer to real world

-explains variation in outcomes

6. Relevance Ensures intervention

meets needs of

providers and patients

-identifies benefits/values as seen by

providers & patients

-ensures appropriate (culture, context)

7. Success Makes trial viable,

feasible, successful

-engenders stakeholder support

-ensures trial appropriate (culture, context)



8. Validity Internal Validity - Ensures right outcomes & measures used

External Validity - Identifies and addresses recruitment issues

to obtain hard to reach groups


O’Cathain et al. (2013) & Lewin et al. (2011) both found little evidence of integration

and few discussions of how qualitative methods were used to explain trial findings

this may be why the previous list of values understates a significant contribution that

qualitative methods can bring to RCTs:

AN ENRICHED UNDERSTANDING OF THE RESEARCH PROBLEM RESULTING FROM

COMPARING QUALITATIVE AND QUANTITATIVE FINDINGS

this contribution may be significant particularly where findings conflict:

Next step: reciprocal interrogation of both sets of findings, which may

reveal deficiencies in quantitative instruments/measures29,47

highlight methodological or design weaknesses47

uncover a deviant or “off-quandrant” dimension of problem3, 46

modify existing theories or create new ones3,29

4. Key Challenges in Using

Qualitative Research Alongside

RCTs

Key Challenges - Continued

Challenges arise related to:

Different mixed methods designs

Broader Issues that impact all designs

Challenges (or Strengths) Relating to Design Types16

Issue Sequential Designs Concurrent Designs

Personnel Can be done by a single or small group of researchers

- requires team of researchers (multiple activities occur in parallel)- team dynamics, power issues (can

threaten quality of each component)

Skills Difficult for single or small group to

acquire different skills to do both qualitative and quantitative research

-team members can be skilled in

qualitative and quantitative research-may need mixed methods specialist

Duration Longer than concurrent designs Quicker but intensive in short term

Funding,Ethics

-Challenging to secure upfront if cannot specify subsequent component(s) before completing 1st one-Amendments required if cannot specify upfront

Easier to specify all components upfront in sufficient detail to secure funding & ethics approval

Publication Lends itself to separate publications Lends itself to joint publication (one component may make little sense without the other)

Challenges (or Strengths) Relating to Design Types - Continued17

Issue Sequential Designs Concurrent Designs

Feedback of Interim or Final Qualitative Findings

-feedback not problematic as one component is intended to inform the other

-knowledge of dissatisfaction with, or acceptability of, the intervention or research process may result in changes

to intervention or recruitment/follow-up/outcome procedures, which can threaten scientific integrity-knowledge that adherence to, or acceptability of, the intervention differs by sub-group may bias recruitment in favour or particular groups-feedback of participant views of the intervention can result in unblinding

.

need guidelines & measures for evaluating complex interventions18,19

Pragmatic RCTs:

CONSORT extension focuses on effects, not process or mixed

methods20

Complex interventions:

CONSORT extension for complex interventions is being developed21

UK’s MRC 2008 update22: called for evaluation of both effects and

process but few details on how to evaluate process

Process evaluation – useful frameworks:

Normalization Process Theory (NPT)23

Implementation Fidelity24

Program Theory25

UK’s Standard Operating Procedures for Qualitative Research in Trials7

Challenges Relating to all Designs

Integrating qualitative and quantitative findings remains a

challenge in RCTs despite the many textbooks, journal

articles and best practice guidelines now available

Lewin et al.’s (2011) systematic review of RCTs of complex

interventions5 found only 30% used qualitative approaches,

and in these:

little discussion of integration

few discussed contributions of both methods to

overall study interpretations

Other studies support Lewin et al.’s (2011) findings34,35,45


integration challenges in RCTs may persist because the

legacy of the epistemological divide lingers in16,28 :

training researchers

biases favouring one approach over the other

imbalances in status and power between groups of

researchers


the role of theory should be considered from the beginning

theory emphasized in UK’s MRC 2008 guidelines for complex

interventions and design of standard operating procedures

for qualitative methods used in UK clinical trials7

theory may be important for integration of qualitative results:

Lewin et al.(2011) found that twice as many RCTs that

included qualitative work had a clearly stated theoretical

basis compared with RCTs without any qualitative work

Theory increases likelihood that the role of qualitative work

is planned ahead of time and funded appropriately


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