Research Problems, Questions and Conceptual Frameworks

Introduction

Health-care management research begins with a practical concern: delayed treatment, unsafe transitions of care, inequitable access, staff turnover, poor patient experience, weak implementation of policy, or ineffective use of digital systems. A practical concern, however, is not automatically a research problem. It becomes a research problem when there is a significant issue that requires systematic inquiry because current knowledge, explanations, or practices are inadequate.

Qualitative research is particularly valuable when the researcher must understand meaning, experience, social processes, relationships, organizational culture, professional judgement, and the context in which health-care activity occurs. It can explain not only what happens, but how and why it happens, how different actors interpret it, and how institutional arrangements shape those interpretations and actions.

This chapter explains how to move from a broad health-care concern to a feasible qualitative study. It examines literature review, knowledge gaps, qualitative research questions, sensitizing concepts, logic models, and theoretical and conceptual frameworks. It also considers scope, reflexivity, ethics, feasibility, and the implications of frameworks for health-care managers and researchers.

Learning objectives

By the end of this chapter, the reader should be able to:

1. Distinguish a health-care topic, practical problem, research problem, purpose statement, and research question.
2. Formulate qualitative questions that are open, focused, answerable, and methodologically appropriate.
3. Conduct a critical literature review and identify different forms of knowledge gap.
4. Explain the role of sensitizing concepts in qualitative inquiry.
5. Construct and use logic models without treating them as deterministic causal theories.
6. Compare theoretical frameworks, conceptual frameworks, and sensitizing concepts.
7. Establish appropriate study boundaries, sampling implications, and ethical safeguards.
8. Critically evaluate a proposed framework in a health-care management study.

From a health-care concern to a researchable problem

A topic is a broad area of interest, such as patient safety, telemedicine, workforce retention, or hospital discharge. A practical problem is an undesirable condition or unresolved challenge in practice. A research problem is a gap in understanding, explanation, interpretation, or evidence that can be investigated systematically.

For example:

• Topic: hospital discharge.
• Practical problem: some older patients return to hospital soon after discharge.
• Initial research problem: health-care organizations do not adequately understand how patients and family caregivers experience discharge planning, or how coordination failures arise across professional and organizational boundaries.
• Possible qualitative purpose: to explore how older patients, caregivers, and health professionals experience and negotiate discharge preparation and follow-up.

The distinction matters because a qualitative study does not ordinarily attempt to prove that one intervention causes a numerical change in readmission rates. It may instead investigate how an intervention is understood, implemented, adapted, resisted, or incorporated into everyday work.

A strong research problem normally demonstrates five qualities:

1. Significance: it matters for patients, populations, professionals, organizations, policy, or theory.
2. Specificity: its population, setting, process, or phenomenon can be identified.
3. Knowledge relevance: existing evidence does not adequately answer the question.
4. Qualitative suitability: experiences, meanings, interaction, context, or process are central.
5. Feasibility: participants, data, time, skills, ethics approval, and analytic resources are available.

A useful problem statement identifies the situation, the consequence, what is not understood, and why understanding it matters. It should avoid presuming the answer. “Nurses resist electronic prescribing because they lack digital competence” is an explanation presented as a fact. “How do nurses experience and interpret the introduction of electronic prescribing?” is more open and suitable for inquiry.

The role of the literature review

A literature review is not a list of summaries. It is a reasoned account of what is known, how it has been studied, where findings converge or conflict, and what remains uncertain. In qualitative health research, the review should include empirical studies, theoretical literature, policy documents, professional guidance, implementation research, and, where relevant, patient or public involvement literature.

Searching strategically

A search strategy should begin with the concepts in the provisional problem statement. Synonyms and related terms are important because different disciplines use different language. For instance, “care transitions” may be indexed alongside “hospital discharge,” “continuity of care,” “care coordination,” and “transitional care.” Searches may use Boolean operators, truncation, subject headings, citation chaining, and database-specific filters.

A transparent search record should document:

• databases and information sources;
• search terms and combinations;
• date ranges and language restrictions;
• inclusion and exclusion criteria;
• screening and appraisal decisions; and
• reasons for treating sources as relevant.

The purpose is not always to produce a systematic review. A focused qualitative project may use an iterative or exploratory review, particularly when the research design is interpretive and the researcher wishes to avoid imposing a fixed framework too early. Nevertheless, the process should be sufficiently systematic to support credible claims about the literature.

Reading critically

Each source should be examined in relation to its question, assumptions, design, setting, participants, analysis, and limitations. Important questions include:

• Whose perspective is represented, and whose is absent?
• Is the setting comparable to the proposed setting?
• Are experiences treated as individual attitudes, or as shaped by institutions and power?
• Are conclusions supported by the data?
• Are concepts defined consistently?
• Does the study examine implementation, outcomes, or lived experience?
• What methodological choices may explain disagreement between studies?

Quality appraisal should not be reduced to a checklist score. A study with a small sample may provide rich, credible insight into meaning and process, while a large survey may offer limited understanding of how people interpret a situation. Appraisal should therefore consider fitness for purpose.

Types of knowledge gap

A knowledge gap is more precise than the statement “little research exists.” Common forms include:

A defensible gap statement specifies the evidence base and the exact uncertainty. “The literature is limited” is weak. “Existing studies describe patient satisfaction with virtual consultations, but provide limited insight into how clinicians negotiate clinical uncertainty and safeguarding when consultations are remote” is stronger.

Constructing qualitative research questions

A research question gives direction to the study while preserving openness to discovery. It should identify the phenomenon, participants or social actors, and context without embedding an unsupported conclusion.

Common qualitative question forms include:

• Experience: How do patients experience receiving care in a virtual clinic?
• Meaning: What meanings do nurses attach to professional autonomy during service redesign?
• Process: How is a new referral pathway implemented across organizational boundaries?
• Interaction: How do clinicians and patients negotiate treatment decisions?
• Context: How does organizational culture shape speaking up about safety?
• Variation: How do experiences differ across rural and urban services?
• Power and equity: How do eligibility rules affect access for people with limited digital access?

A broad central question can be supported by subquestions. For example:

Central question: How do older adults and family caregivers experience hospital discharge planning after an acute admission?

Subquestions:

1. How do participants understand their roles and responsibilities during discharge preparation?
2. How do communication and coordination occur among patients, caregivers, and professionals?
3. What organizational conditions enable or constrain continuity after discharge?
4. How do experiences differ for participants with limited health literacy or digital access?

The central question should not be a disguised evaluation question such as “Why does the discharge programme fail?” It may be reframed as “How is the discharge programme experienced and enacted, and what conditions shape its implementation?” This retains the possibility that the programme works differently for different groups or in different circumstances.

Characteristics of strong questions

Strong qualitative questions are:

• open-ended rather than answerable with yes or no;
• focused enough to guide sampling and data collection;
• aligned with the chosen methodology;
• sensitive to context and multiple perspectives;
• neutral enough not to predetermine findings;
• feasible within the available time and access; and
• ethically appropriate.

The question “What is the effect of nurse understaffing on patient mortality?” is primarily quantitative and causal. A qualitative alternative might be: “How do nurses and ward managers experience and respond to staffing shortages in everyday patient care?” A mixed-methods programme could legitimately include both questions, but they require different designs and forms of evidence.

Alignment with qualitative methodologies

The question should fit the methodology. Phenomenology commonly addresses the meaning and lived experience of a phenomenon. Ethnography examines culture, practice, and social organization in context. Grounded theory investigates processes and seeks to develop an explanatory account grounded in data. Case study examines a bounded case using multiple sources. Narrative inquiry focuses on stories, temporality, and identity. Qualitative description seeks a low-inference account of events and experiences.

These are not rigid categories. However, a study claiming to use grounded theory but asking only “How satisfied are patients?” shows weak alignment. The design, sampling, data collection, and analysis should all follow from the question and purpose.

Purpose statements and scope

A purpose statement connects the problem to the study’s intended contribution. A useful structure is:

The purpose of this qualitative [design] is to explore or understand [phenomenon/process] among [participants] in [setting], in order to [intended contribution].

For example:

The purpose of this qualitative case study is to understand how multidisciplinary teams coordinate care for frail older adults across hospital and community services, in order to identify organizational conditions that support continuity.

Scope is established through boundaries rather than through an attempt to include everything. Boundaries may include:

• population and eligibility;
• geographical and organizational setting;
• time period;
• service or care pathway;
• phenomenon of interest;
• perspectives included and excluded;
• data sources; and
• level of analysis.

Scope decisions are substantive, not merely logistical. Excluding family caregivers may remove a central perspective. Including every professional group may make analysis superficial. The researcher should explain why boundaries are appropriate and what they leave unexamined.

Sensitizing concepts

The sociologist Herbert Blumer distinguished between definitive concepts, which specify attributes and boundaries, and sensitizing concepts, which provide a general sense of direction and alert the researcher to potentially relevant features. In qualitative research, sensitizing concepts are provisional lenses rather than variables to be measured.

Examples include trust, stigma, uncertainty, professional identity, moral distress, legitimacy, relational continuity, discretion, vulnerability, and organizational resilience. A study of telemedicine may use “trust” as a sensitizing concept, while remaining open to how patients and clinicians define trust in practice. Participants may describe reliability, privacy, competence, responsiveness, or personal familiarity without using the word trust.

Sensitizing concepts are useful because they:

• guide initial literature review and interview topics;
• direct attention to potentially important interactions;
• support comparison across cases;
• help connect empirical material with theory; and
• remain adaptable as understanding develops.

They become problematic when treated as predetermined codes that force all data into an existing model. The researcher should record where the concept illuminates data, where it fails, and what alternative concepts emerge. Reflexive memos can document these changes.

Theoretical and conceptual frameworks

A theoretical framework is an established body of concepts and propositions that explains relationships, processes, or social phenomena. Examples relevant to health-care research include Normalization Process Theory, the Consolidated Framework for Implementation Research, the Theoretical Domains Framework, street-level bureaucracy, Bourdieu’s theory of practice, symbolic interactionism, and theories of organizational sensemaking.

A conceptual framework is a researcher-developed map of the main concepts and presumed relationships relevant to a particular study. It may draw from several theories, prior evidence, policy documents, and professional knowledge. It is usually more specific to the research problem than a general theory.

A logic model is a structured representation of how resources and activities are expected to produce outputs and outcomes. It often includes inputs, activities, outputs, short-term outcomes, and longer-term outcomes. It is especially useful in programme evaluation and implementation research.

These forms overlap, but they are not interchangeable. A logic model generally represents an intervention pathway; a theoretical framework explains or sensitizes the researcher to social and organizational processes; a conceptual framework integrates relevant ideas for one study.

Using a logic model critically

Consider a proposed integrated discharge programme. A simplified logic model might be:

Figure: A logic model for an integrated discharge programme, with qualitative questions added to examine how the pathway operates in context.

The model helps identify where inquiry is needed. Staff may have adequate resources but disagree about roles. Patients may receive a written plan but not understand it. A referral may be completed technically but fail because the receiving service lacks capacity. Qualitative research can examine these mechanisms and unintended consequences. The arrows in a logic model are expectations, not proof of inevitable causation.

Choosing a framework

Framework selection should be driven by the research problem, not by the popularity of a model. The researcher should ask:

1. What phenomenon does the framework explain?
2. Is it compatible with the study’s epistemological position?
3. Does it illuminate individual, interpersonal, organizational, or policy-level processes?
4. Can the concepts be recognized in the proposed data?
5. Does it allow unexpected findings?
6. What assumptions about power, agency, rationality, or change does it contain?
7. Will it improve sampling, data collection, analysis, or interpretation?

For example, Normalization Process Theory may be appropriate when the question concerns how a new practice becomes embedded in routine work. A framework emphasizing individual beliefs may be insufficient if the problem is shaped by workload, hierarchy, funding, and interorganizational rules. Conversely, an excessively broad framework may produce an unmanageable study.

Frameworks can be used deductively, inductively, or abductively. A deductive use begins with concepts that guide data collection and coding. An inductive use allows concepts to emerge from data with minimal prior structure. An abductive use moves iteratively between empirical observations and plausible theoretical explanations. Many applied health studies use a flexible combination: an initial framework guides attention, while data can revise or challenge it.

A worked formulation example

Suppose a health system introduces video consultations for people with diabetes. Managers report inconsistent uptake and complaints about quality.

Topic: virtual diabetes care.

Practical problem: use and experiences vary across clinics and patient groups.

Literature review: existing research reports clinical feasibility and satisfaction, but gives limited attention to how clinicians judge uncertainty, how patients manage privacy and technology, and how organizational workflow shapes use.

Knowledge gap: an interpretive and contextual gap concerning how virtual care is enacted in routine practice, especially among patients with limited digital resources.

Sensitizing concepts: trust, clinical uncertainty, digital exclusion, professional discretion, and continuity.

Purpose: to explore how patients and clinicians experience and enact video consultations for diabetes management across two outpatient clinics.

Central question: How are video consultations for diabetes management experienced, interpreted, and incorporated into routine care?

Subquestions:

• How do patients and clinicians define a good or inadequate video consultation?
• How is clinical uncertainty managed when physical examination is limited?
• How do access to devices, connectivity, language, and privacy shape participation?
• How do clinic procedures and professional roles enable or constrain virtual care?

Possible design: comparative qualitative case study using interviews, observation of workflow, and relevant documents.

This formulation is more coherent than asking whether video consultations are “successful.” Success requires a defined outcome and comparison, whereas the qualitative formulation investigates meanings, mechanisms, and variation that could inform later evaluation.

Sampling and data implications

A question determines who can contribute relevant knowledge. Purposive sampling selects participants because they have experience or insight relevant to the phenomenon. Maximum-variation sampling may include contrasting settings or participant characteristics. Criterion sampling includes all participants meeting defined conditions. Theoretical sampling, associated particularly with grounded theory, follows concepts that emerge during analysis and seeks data that refine or challenge developing categories.

Sampling should reflect the conceptual framework without becoming captive to it. If the study concerns cross-boundary coordination, patients, ward nurses, discharge coordinators, community providers, and managers may each occupy different positions in the process. A single stakeholder group cannot represent the whole system.

Data sources may include interviews, focus groups, observations, field notes, patient diaries, documents, digital traces, and service artefacts. Triangulation is not simply the accumulation of sources. It involves comparing perspectives or forms of evidence to develop a more nuanced interpretation. Contradictory accounts may reveal differences in role, power, timing, or institutional position rather than indicating that one participant is unreliable.

Reflexivity, ethics, and governance

The researcher is part of the knowledge-production process. Professional status, clinical experience, managerial authority, institutional affiliation, age, gender, language, and assumptions may influence access, interaction, interpretation, and reporting. Reflexivity requires more than a brief positionality statement. It involves keeping analytic memos, discussing interpretations with colleagues or participants where appropriate, and examining how power shaped the research encounter.

Health-care qualitative research raises specific ethical issues:

• Voluntariness: patients or employees may feel obliged to participate when recruitment occurs through a care or employment relationship.
• Confidentiality: small teams and distinctive experiences may make individuals identifiable even after names are removed.
• Sensitive disclosure: participants may report unsafe practice, discrimination, trauma, or illegal conduct.
• Dual roles: a manager who researches their own staff must separate research from performance management.
• Data governance: recordings, transcripts, electronic messages, and health information require secure handling and defined retention periods.
• Group confidentiality: confidentiality cannot be fully guaranteed in focus groups.
• Fair representation: quotations should not be selected merely because they are dramatic or convenient.

Consent should be an ongoing process, especially in observation and longitudinal studies. Researchers should explain what participation involves, how data will be used, whether withdrawal is possible, and the limits of confidentiality. Governance requirements may include research ethics approval, institutional permissions, information-governance review, data-protection compliance, and procedures for responding to disclosures of serious risk.

Common problems and how to avoid them

The “everything” question

A study asking about experiences, outcomes, implementation, culture, equity, cost, and policy across an entire health system is unlikely to produce depth. Prioritize one phenomenon and define secondary questions.

The leading question

Questions such as “Why do staff fail to follow the policy?” assume failure and blame. Ask how the policy is understood, enacted, and experienced, and examine the conditions shaping variation.

Framework imposition

A framework should support interpretation, not determine findings in advance. Include disconfirming evidence and concepts that do not fit.

Conceptual ambiguity

Terms such as engagement, empowerment, access, quality, resilience, and integration may have multiple meanings. Define how each term is used and remain attentive to participants’ own language.

Mismatch between question and method

A question about prevalence, effect size, or statistical association requires quantitative or mixed methods. A question about meaning, process, or context requires qualitative methods, although qualitative and quantitative designs may be combined in a broader programme.

Treating participant accounts as transparent facts

Accounts are situated interpretations. They are valuable evidence of experience and meaning, but should be analysed in relation to context, interaction, institutional position, and other sources.

Technology and AI in problem formulation

Digital search tools, citation managers, qualitative data software, and artificial-intelligence systems can support literature discovery, organization, transcription, translation, and preliminary text management. They do not replace scholarly judgement. AI-generated summaries may omit methodological limitations, reproduce bias, fabricate references, or obscure whose perspectives are missing.

Best practice includes verifying every source, retaining search records, protecting confidential data, disclosing substantial AI assistance where required, and avoiding the upload of identifiable patient or staff information to unapproved systems. Automated coding should be treated as an aid to organization rather than as an independent interpretation. Meaning, context, irony, silence, and power relations require human and reflexive analysis.

Illustrative case: understanding failed care coordination

This is a fictional illustrative case.

Background

A regional health network introduces a digital referral platform intended to connect hospital specialists with primary-care teams. After six months, referral completion appears inconsistent. Managers initially assume that staff need more technical training.

Problem

The initial problem statement—“staff do not use the platform correctly”—is narrow and potentially blame-oriented. A preliminary review finds that completion rates vary by specialty, primary-care practice, and referral type. Interviews in prior studies focus mainly on usability, not on accountability, professional boundaries, or workarounds.

Analysis and reframing

The research team identifies an explanatory and contextual gap. The platform is not merely a technical tool; it redistributes information, responsibility, and visibility. Sensitizing concepts include discretion, trust, accountability, and boundary work. A conceptual framework links platform rules, professional interpretations, local workflow, and coordination practices.

The revised purpose is:

To explore how hospital and primary-care professionals interpret and enact digital referrals, and how organizational conditions shape coordination across the network.

The central question is:

How do professionals negotiate responsibility and continuity when using the digital referral platform?

The team proposes a comparative case study of two specialties and three primary-care practices, using interviews, observations of referral work, and document analysis.

Approach and anticipated contribution

Analysis begins with sensitizing concepts but permits new categories such as “silent handover,” “visibility without ownership,” and “workaround as safety practice.” Comparison shows that the platform functions well where teams have established relationships and clear escalation routes. In other settings, staff use telephone calls and informal messaging because the digital system records transmission but does not clarify who must act.

Outcome

The study does not conclude simply that training is inadequate. It shows that the problem involves role ambiguity, uneven trust, specialty-specific workflows, and a system design that treats referral completion as a technical event rather than a shared process. Managers consequently revise escalation rules, clarify responsibility, and redesign audit measures to include acknowledgement and follow-up.

Learning points

1. A practical complaint may conceal a more complex organizational problem.
2. Qualitative questions can reveal mechanisms and meanings hidden by performance indicators.
3. Frameworks should examine relationships between technology, work, power, and context.
4. Workarounds are not automatically non-compliance; they may represent adaptation or risk management.
5. Findings become more useful when linked to feasible organizational decisions without overstating causality.

Best-practice checklist

Before finalizing a qualitative proposal, ask:

• Is the practical and research problem clearly distinguished?
• Does the literature review demonstrate a specific gap?
• Are the purpose and questions aligned with one another?
• Is the qualitative approach justified?
• Are the central concepts defined but open to refinement?
• Does the framework illuminate rather than predetermine findings?
• Are perspectives, setting, time, and boundaries explicit?
• Do sampling and data sources fit the questions?
• Have power, reflexivity, confidentiality, and data governance been addressed?
• Is the intended contribution realistic and relevant to health-care practice?

Chapter Summary

A health-care concern becomes a research problem when an important uncertainty in understanding, explanation, interpretation, or practice can be investigated systematically. Qualitative research is well suited to questions about experience, meaning, interaction, implementation, organizational process, power, and context.

A critical literature review establishes what is known, how it is known, whose perspectives are represented, and what remains uncertain. Knowledge gaps may be descriptive, interpretive, explanatory, contextual, representational, methodological, theoretical, or implementation-related. Strong qualitative questions are open, focused, feasible, ethically appropriate, and aligned with the selected methodology.

Sensitizing concepts provide provisional direction without functioning as fixed variables. Theoretical frameworks offer established explanatory ideas, conceptual frameworks organize concepts for a particular study, and logic models represent expected programme pathways. Each should be selected critically and used flexibly. Frameworks must not suppress unexpected findings or impose unsupported assumptions.

Purpose, scope, sampling, data sources, reflexivity, and ethics are interconnected. A well-designed study makes its boundaries explicit, includes relevant perspectives, protects participants, and links findings to realistic health-care decisions. The central discipline is alignment: problem, literature, question, framework, design, data, analysis, and intended contribution should form a coherent whole.

Key Terms

Conceptual framework: A study-specific map of concepts and their presumed relationships.

Definitive concept: A concept with specified attributes and boundaries.

Epistemology: Assumptions about knowledge and how it can be developed or justified.

Ethnography: Qualitative inquiry into culture, practice, and social organization in context.

Explanatory gap: Uncertainty about processes or conditions that produce a phenomenon.

Framework: An organized set of concepts used to guide inquiry or interpretation.

Grounded theory: An approach that develops an explanatory account through systematic analysis grounded in data.

Knowledge gap: A significant area in which existing evidence is incomplete, contested, or insufficient.

Logic model: A representation linking programme inputs, activities, outputs, and outcomes.

Methodological alignment: Consistency among the research question, design, data, and analysis.

Phenomenology: Inquiry concerned with the meaning and structure of lived experience.

Positionality: The researcher’s social and professional location and its influence on inquiry.

Purposive sampling: Selecting participants because they possess relevant experience or knowledge.

Qualitative research question: An open and focused question about meaning, experience, interaction, process, or context.

Research problem: A significant and investigable uncertainty in knowledge or practice.

Sensitizing concept: A provisional concept that directs attention while remaining open to refinement.

Scope: The population, setting, period, phenomenon, and boundaries of a study.

Theoretical framework: An established theory or body of concepts used to explain or interpret a phenomenon.

Triangulation: Comparison of perspectives, sources, methods, or investigators to deepen interpretation.

Review Questions

Short Answer Questions

1. Distinguish a practical problem from a research problem in health-care management.
2. What is a sensitizing concept, and how does it differ from a definitive concept?
3. Identify four characteristics of a strong qualitative research question.
4. Explain one difference between a theoretical framework and a logic model.
5. Why is reflexivity important in qualitative health research?

Long Answer Questions

1. Explain how a researcher can move from a broad health-care concern to a focused qualitative purpose statement and central research question.
2. Discuss the major types of knowledge gap and illustrate at least three with health-care examples.
3. Compare phenomenology, ethnography, grounded theory, and case study in relation to the kinds of questions they address.
4. Explain how a conceptual framework should guide, but not predetermine, qualitative data collection and analysis.
5. Discuss the ethical and governance challenges of interviewing health-care employees about unsafe practice.

Analytical / Application Questions

1. A hospital reports poor uptake of a new electronic medication system and proposes a study asking, “Why do nurses resist technology?” Critically revise the problem statement, purpose, central question, and two subquestions.
2. Construct a brief logic model for a community-based chronic-disease programme. Then identify two qualitative questions that would investigate how the expected pathway is enabled or disrupted in practice.
3. A literature review finds abundant studies of patient satisfaction with telehealth but few studies of clinician decision-making and digital exclusion. Formulate a defensible knowledge-gap statement, identify three sensitizing concepts, and propose an appropriate qualitative design.

Multiple Choice Questions with Answers

Question 1

Which statement best defines a qualitative research problem?

A. A numerical estimate of a population characteristic

B. A significant uncertainty about meaning, process, experience, or context that can be investigated systematically

C. A predetermined explanation that the study must confirm

D. A list of all possible variables in a health-care system

Correct Answer: B. A significant uncertainty about meaning, process, experience, or context that can be investigated systematically

Question 2

Which question is most clearly qualitative?

A. What proportion of patients miss appointments?

B. Does the intervention reduce readmissions by 20 percent?

C. How do patients experience and interpret appointment reminders?

D. What is the average waiting time before and after implementation?

Correct Answer: C. How do patients experience and interpret appointment reminders?

Question 3

What is the principal purpose of a sensitizing concept?

A. To function as a fixed variable measured identically for every participant

B. To provide provisional direction while remaining open to refinement

C. To replace the need for data collection

D. To guarantee that the researcher’s initial theory is confirmed

Correct Answer: B. To provide provisional direction while remaining open to refinement

Question 4

Which item is normally part of a logic model?

A. Inputs, activities, outputs, and outcomes

B. Only statistical significance tests

C. Only participant demographic characteristics

D. A list of interview quotations without interpretation

Correct Answer: A. Inputs, activities, outputs, and outcomes

Question 5

A study asks how a new clinical practice becomes embedded in routine work. Which framework is especially relevant?

A. Normalization Process Theory

B. A sampling quota alone

C. A laboratory reference range

D. A patient satisfaction questionnaire

Correct Answer: A. Normalization Process Theory

Question 6

Which is an example of a contextual knowledge gap?

A. No definition of the research topic exists anywhere

B. Evidence comes from urban hospitals but the proposed study concerns rural services

C. The researcher has not yet chosen a font for the proposal

D. A study contains more than one interview

Correct Answer: B. Evidence comes from urban hospitals but the proposed study concerns rural services

Question 7

Why should a qualitative framework not be imposed rigidly on all data?

A. Frameworks are never useful in qualitative research

B. Rigid imposition can obscure unexpected meanings and alternative explanations

C. Participants are not allowed to discuss concepts in a framework

D. Frameworks can only be used in quantitative studies

Correct Answer: B. Rigid imposition can obscure unexpected meanings and alternative explanations

Question 8

Which sampling approach selects participants because they have relevant experience of the phenomenon?

A. Purposive sampling

B. Random digit sampling only

C. Convenience sampling without eligibility criteria

D. Systematic sampling of laboratory specimens

Correct Answer: A. Purposive sampling

Question 9

Which revision best avoids a blame-oriented question about policy compliance?

A. Why are staff careless about the policy?

B. Why do staff fail despite knowing better?

C. How is the policy understood and enacted in everyday practice?

D. Which staff member is responsible for non-compliance?

Correct Answer: C. How is the policy understood and enacted in everyday practice?

Question 10

Which practice best supports responsible use of AI in qualitative research?

A. Uploading identifiable patient interviews to any free online tool

B. Accepting generated references without verification

C. Using AI as an aid while verifying sources and protecting confidential data

D. Allowing automated coding to replace researcher interpretation

Correct Answer: C. Using AI as an aid while verifying sources and protecting confidential data