Literature Review Time Estimator

A literature review time estimator calculates the hours, calendar weeks, and dollar value of conducting a systematic literature review based on database count, expected search hits, screening team size, and full-text review rate. This calculator uses screening-rate benchmarks of 25 abstracts and 3 full-text papers per reviewer-hour and shows how much time AI assistance could save across all seven review phases.

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What is a literature review time estimator?

A literature review time estimator turns five inputs (database count, expected hits, team size, full-text review rate, hourly rate) into a phase-by-phase hours estimate, calendar duration, and dollar cost. The math is grounded in published benchmarks: dual-independent title-abstract screening averages 25 abstracts per reviewer-hour, full-text review averages three papers per reviewer-hour, and final inclusion typically lands near 60 percent of full-text-screened papers. Most researchers underestimate review time by 40 to 60 percent. A quantified baseline prevents that mistake.

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How the calculator works

The estimator splits a literature review into seven phases and assigns hours to each based on your inputs:

  1. Protocol development. Fixed 20 hours plus 4 hours per database — registering a search strategy that holds up under PROSPERO review takes real time.
  2. Database search. Six hours per database, including iteration, dedup, and reference-manager imports.
  3. Title-abstract screening. Total hits divided by the screening rate (25 per hour), multiplied by 1.25 for dual-independent review.
  4. Full-text review. Your full-text rate applied to hits, divided by the full-text rate (3 per hour), with the same team multiplier.
  5. Data extraction. Fifteen hundredths of an hour per included study at the low end — extraction templates vary by study design.
  6. Synthesis. A 40-hour base plus 0.8 hours per included study, covering thematic coding or meta-analytic effect aggregation.
  7. Writing. An 80-hour base plus 0.4 hours per included study, covering drafting, supervisor rounds, and pre-submission polish.

Hours convert to weeks at 20 dedicated review hours per week. Dollar value comes from multiplying total hours by your hourly rate (defaulting to PhD stipend medians by country).

When to use this estimator

Use the calculator before starting a literature review to:

  • Set realistic expectations with your supervisor before committing to a deadline.
  • Justify funding requests when the cost of a manual review approaches the cost of better tools.
  • Decide between review types — a 600-hour systematic review versus a 200-hour scoping review is a meaningful trade-off.
  • Quantify the case for AI assistance when manual screening dominates the timeline.

Use it again at the end of your title-abstract screening phase, after you have measured your actual screening rate. Plug your real rate into the math and the remaining-time forecast tightens substantially.

Key data we used to build this

Three benchmarks anchor the calculator:

  • 25 title-abstract screenings per reviewer-hour is the median across dual-independent SR teams. A 2021 review of automation in SR work cites a range of 18–32 per hour depending on inclusion-criteria complexity.
  • Three full-text papers per reviewer-hour holds across medicine, public health, and education research, dropping to 2 per hour when criteria require nested judgement.
  • 60 percent final-inclusion yield from full-text-screened papers matches the PRISMA 2020 reporting standard’s published yields.

These three benchmarks alone explain the bulk of the hours total. The remaining phase estimates (protocol, search, extraction, synthesis, writing) draw on the Cochrane Handbook plus internal observations from Fynman’s user base.

Frequently asked questions

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Frequently Asked Questions

Find answers to common questions about this topic.

Estimates come from published benchmarks: 20–30 title-abstract screenings per reviewer-hour, 2–4 full-text reviews per reviewer-hour, and standard PRISMA yield of 60 percent at full-text. Real reviews vary by 30 percent up or down depending on topic complexity, abstract quality, and team experience. Treat the output as a planning baseline, not a contract.
Time has a real opportunity cost — a PhD candidate’s stipend, a postdoc salary, or your billable rate as a researcher. Showing the dollar figure forces the conversation about whether spending 600 hours on manual screening is the highest-value use of that time, especially when AI tools can reduce screening hours by half or more.
No. Dual independent screening adds about 25 percent coordination overhead per reviewer-hour, not 100 percent, because both reviewers screen in parallel. Three-plus reviewer teams add roughly 40 percent overhead from consensus meetings. The calculator applies these multipliers automatically when team size is greater than one.
Fynman runs locally on your machine and applies AI to the screening, extraction, and synthesis phases without uploading PDFs anywhere. The saved-hours estimate uses conservative phase-level reductions: 55 percent on title-abstract screening, 30 percent on full-text review, 60 percent on data extraction, and 40 percent on synthesis. These reflect measured time savings on real reviews, not vendor marketing.
The hourly rate defaults to PhD stipend medians, which vary widely (~$22/hr in the US, ~$17/hr in the UK, ~$6/hr in India). Detecting your timezone lets the calculator pick a sensible default. You can override with your actual hourly rate anytime — the country picker is a starting point, not a constraint.
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Yes, with caveats. Scoping reviews typically have lower full-text rates (5–10 percent) and skip formal data extraction, so the extraction-phase output overstates that work. Narrative reviews skip dual screening entirely, so set team size to 1. The calculator gives a directional estimate; adjust your expectations downward for less formal review types.
The previous tools (research-timeline-calculator and paper-screening-time-estimator) split the same problem across two pages with overlapping math. This consolidated estimator covers the full SR workflow — protocol through writing — in one place, with the hourly-rate input and dollar-value output added to make trade-offs concrete. The old URLs redirect here.