Research Question Refinement Prompt

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Research Question Refinement Prompt

Research Question Refinement Prompt

Refine a broad topic into answerable research questions with scope, variables, methods, and constraints.

Transform a broad research topic into a defensible primary question and supporting subquestions with explicit scope, constructs, evidence, method fit, feasibility, and validation criteria.

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Use this prompt to develop precise, answerable research questions and compare alternative formulations before committing to a study design, proposal, thesis, or evaluation plan.

Research Question Refinement
Research Planning
Evidence Review
Source Comparison
Findings Synthesis

Narrowing a thesis or dissertation topic into a primary question and coherent subquestions
Translating a policy, program, or organizational decision into an answerable evaluation question
Comparing qualitative, quantitative, mixed-methods, and evidence-synthesis question formulations
Diagnosing ambiguous constructs, excessive scope, leading wording, and unsupported causal claims
Preparing a research question set for supervisor, methodologist, statistician, or ethics review

Goal or task
Current context
Constraints
Files, data, or examples
Definition of done

Broad topic
Research purpose and intended decision
Population or unit of analysis
Setting and scope
Available evidence and source materials
Constraints and feasibility limits
Methodological preferences
Ethical or sensitivity considerations
Success criteria

Replace every bracketed placeholder before running. Give the model enough context to inspect assumptions, ask only blocking questions, and produce a concrete deliverable. For code prompts, include relevant files, errors, logs, and test commands.

In ChatGPT, replace every bracketed variable with your research context. Provide the broad topic, intended decision, relevant literature or source excerpts, existing questions, population details, methodological constraints, data-access limits, timelines, and ethics requirements. Upload or paste only materials ChatGPT is permitted to inspect, then run the prompt and route the resulting draft to the appropriate subject-matter, methods, and ethics reviewers.

Use this when you need a production-ready research design result in Research, not a generic brainstorm. The expected output should include findings, implementation steps, risks, and verification checks.

A public-health researcher can provide a broad topic about remote-work stress, the target employee population, available survey instruments, a six-month timeline, and several literature summaries. The prompt will compare exploratory, associational, and evaluative formulations; identify unsupported causal wording; define key constructs and proxies; and produce a primary question and subquestions for methodologist review.

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Research Question Refinement Prompt | AMO.ng

Research Question Refinement Prompt | AMO.ng

Refine a broad topic into answerable research questions with scope, variables, methods, and constraints.

Refine broad topics into answerable research questions with explicit scope, evidence, constructs, method fit, feasibility, and validation checks.

Prompt-body line comparison

Removed Added Unchanged context

−Act as a senior Research specialist using ChatGPT. Your task is: [Goal or task].
+Refine the supplied topic into a defensible research question set. Use ChatGPT to analyze only the information and sources available in the conversation or through explicitly enabled tools. Do not imply access to omitted files, subscription databases, participants, institutional systems, or unpublished evidence.
 
−Context:
−- Current situation: [Current context]
−- Constraints: [Constraints]
−- Available materials: [Files, data, examples, URLs, logs, notes]
−- Success criteria: [Definition of done]
+Inputs
+- Broad topic: [Broad topic]
+- Research purpose and intended decision: [Research purpose and intended decision]
+- Population or unit of analysis: [Population or unit of analysis]
+- Setting and scope: [Setting and scope]
+- Available evidence and source materials: [Available evidence and source materials]
+- Constraints and feasibility limits: [Constraints and feasibility limits]
+- Methodological preferences: [Methodological preferences]
+- Ethical or sensitivity considerations: [Ethical or sensitivity considerations]
+- Success criteria: [Success criteria]
 
−Workflow:
−1. Restate the objective in operational terms and identify any missing information that would block a reliable answer.
−2. Make reasonable assumptions only when they are low risk, and label them clearly.
−3. Produce the main deliverable for "Research Question Refinement Prompt" with enough detail that a skilled operator can execute it immediately.
−4. Include edge cases, failure modes, dependencies, and tradeoffs that a junior prompt would usually miss.
−5. Add a verification checklist with concrete tests, review questions, metrics, or acceptance criteria.
−6. End with the smallest safe next action.
+Input handling
+Treat the broad topic and research purpose as blocking prerequisites. If either is missing or materially ambiguous, ask up to five focused clarification questions before refining the questions. Ask about other missing information only when it could change the study population, constructs, question type, feasibility, ethics, or method fit. Otherwise proceed with a bounded draft, label unknowns, and present alternatives rather than inventing details. Preserve conflicts among supplied sources or stakeholder goals instead of silently reconciling them.
 
−Output format:
−- Executive summary
−- Detailed plan or implementation
−- Risks and mitigations
−- Verification checklist
−- Next action
+Evidence rules
+1. Maintain a clear distinction among supplied facts, source claims, assumptions, hypotheses, inferred implications, conflicts, and unknowns.
+2. Cite or identify the supplied source supporting each material factual premise. If browsing is explicitly enabled and used, provide source links and access dates; otherwise state that no independent literature search was performed.
+3. Do not claim novelty, consensus, prevalence, causality, validated measurement, or an evidence gap unless the available material supports that conclusion. Phrase an apparent gap as provisional when the literature search is incomplete.
+4. Do not fabricate citations, study findings, variables, datasets, participant characteristics, effect sizes, or institutional requirements.
 
−Do not give generic advice. Optimize for a production-quality research design outcome.
+Refinement process
+1. Diagnose the starting topic. Identify its central phenomenon, intended contribution or decision, population or unit of analysis, context, timeframe, and current overbreadth or ambiguity.
+2. Classify the likely question type as exploratory, descriptive, comparative, associational, causal, predictive, interpretive, or evaluative. Explain why the classification fits the purpose.
+3. Select a suitable framing structure only when useful. Examples include PICO or PECO for intervention and exposure questions, SPIDER for qualitative evidence, and population–concept–context for scoping questions. Do not force intervention-style variables onto qualitative, interpretive, historical, or conceptual research.
+4. Generate three to five materially distinct candidate questions. Avoid merely rewording one formulation. Include narrower or broader alternatives when scope is uncertain.
+5. Test each candidate for:
+   - one interpretable central inquiry rather than an accidental double-barrelled question;
+   - explicit population or unit of analysis where relevant;
+   - defined constructs, exposure or intervention, comparator, outcome, context, and timeframe where the question type requires them;
+   - neutral wording that does not presume a preferred result;
+   - alignment with the stated research purpose and intended decision;
+   - answerability using evidence that could realistically be obtained;
+   - compatibility with a plausible qualitative, quantitative, mixed-methods, evidence-synthesis, or conceptual design;
+   - manageable scope under the supplied time, access, sample, data, skill, and budget constraints;
+   - risks from confounding, selection bias, measurement error, construct underrepresentation, reverse causality, or inappropriate causal language;
+   - ethical and privacy implications, especially for sensitive topics, vulnerable populations, protected characteristics, or identifiable data.
+6. For causal wording, determine whether a credible identification strategy could plausibly support it. If not, recommend associational or exploratory wording and explain the trade-off.
+7. Recommend one primary question and only the subquestions needed to decompose it. Ensure subquestions are collectively useful, non-duplicative, and subordinate to the primary question.
+8. Map each important construct to a provisional conceptual definition, observable indicator or evidence source, and validity concern. Do not treat a proxy as equivalent to the construct without qualification.
+9. Propose a method-fit direction, not a completed protocol. Identify a plausible design, sampling or case-selection logic, data requirements, and analysis family, while marking decisions that require a methodologist, subject-matter expert, statistician, information specialist, or ethics reviewer.
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+Authority and safeguards
+This task produces a research-design draft only. Do not recruit or contact participants, access restricted data, submit an ethics application, approve a protocol, commit funds, represent institutional approval, or publish findings. Final question adoption and consequential study decisions require human authorization. If source materials contain personal, confidential, proprietary, or sensitive information, minimize reproduction, recommend de-identification, and stop before exposing unnecessary details. Flag research involving human participants, clinical decisions, illegal activity, vulnerable groups, or material legal or safety risk for appropriate institutional and expert review.
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+Required deliverable
+A. Input and evidence ledger
+Provide a table with: item, supplied information, status as fact or claim or assumption or unknown or conflict, evidence reference, and consequence for question design.
+
+B. Framing diagnosis
+State the research purpose, intended decision or contribution, unit of analysis, key constructs, boundaries, question type, major ambiguities, and provisional evidence gap. Clearly state whether an independent literature search was performed.
+
+C. Candidate question comparison
+Provide a table with: candidate ID, exact question wording, question type, framing structure if used, population or unit, constructs or relationship, context and timeframe, evidence basis, feasibility, principal bias or validity risk, ethical concern, and trade-off.
+
+D. Recommended question architecture
+Present the recommended primary question, supporting subquestions, rationale, explicit inclusions, explicit exclusions, and one alternative formulation for each unresolved high-impact assumption.
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+E. Construct and method-fit map
+Provide a table with: construct, conceptual meaning, proposed indicator or evidence, data source, validity limitation, and unresolved decision. Then describe the plausible design, sampling or case-selection logic, data needed, and analysis family.
+
+F. Validation and acceptance matrix
+Assess each criterion using: criterion, expected condition, actual observation from the supplied material, evidence, status as pass or revise or unverified, and required correction. At minimum, check clarity, singular focus, purpose alignment, scope, construct definition, neutrality, answerability, method compatibility, feasibility, causal-language justification, ethical acceptability, and subquestion coherence.
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+G. Decision and handoff register
+List the recommended draft status, unresolved questions, conflicting evidence, decisions requiring human approval, specialists who should review it, and the smallest safe next action.
+
+Claim discipline
+Call the result a draft unless a named reviewer has actually approved it. Use verified only for checks performed with available evidence. Keep proposed methods, completed searches, executed analyses, ethics approval, and institutional approval distinct. Never claim that literature was reviewed, data were tested, stakeholders were consulted, or a question was approved unless that action occurred and supporting evidence is present.