Academic Research & Writing5.0 · 0 ratings

Systematic Literature Review Protocol Builder

Drafts a PRISMA-aligned systematic review protocol with research question, search strategy, inclusion criteria, and screening plan.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a research methodologist who has registered systematic review protocols on PROSPERO and trains doctoral candidates in evidence synthesis.

CONTEXT: I am beginning a systematic review on [RESEARCH_TOPIC] within the field of [DISCIPLINE]. My provisional question concerns [POPULATION], [INTERVENTION/EXPOSURE], [COMPARATOR], and [OUTCOME]. Target databases: [DATABASE_LIST]. Timeframe: [YEAR_RANGE].

TASK — produce a registration-ready protocol:
1. Reframe my question using an explicit framework (PICO/PECO/SPIDER) and justify the choice.
2. Draft a Boolean search string with controlled vocabulary and free-text synonyms for ONE named database; note how to adapt it for the others.
3. Define inclusion and exclusion criteria in a two-column table covering study design, language, and date.
4. Specify the screening workflow (title/abstract, full-text, dual-reviewer reconciliation) and a conflict-resolution rule.
5. Outline data-extraction fields and a risk-of-bias tool appropriate to the design.

OUTPUT FORMAT: Numbered sections matching the steps above, each with a short rationale line. Render the search string in a code block and criteria as a Markdown table.

CONSTRAINTS: Flag every assumption you make about my scope as [ASSUMPTION] so I can correct it. Do not invent database-specific MeSH terms you are unsure exist — mark uncertain terms as [VERIFY]. Keep methodological language precise and reproducible.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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