教学创新中心

Generative Artificial Intelligence

Use Case Sharing: Navigating Literature Reviews with Perplexity

Background Story

Sarah, a master’s student in Public Health, is drafting her thesis on the long-term health impacts of the COVID-19 pandemic. Her biggest challenge? The overwhelming volume of academic literature—thousands of papers on post-COVID physical/mental health, demographic disparities, and rehabilitation strategies. She struggled to sift through irrelevant studies, synthesize key findings, and identify research gaps efficiently. To streamline her literature review (a core thesis component), she turned to Perplexity for AI-powered research support.
 

Tool Used

Perplexity (AI-powered academic search & synthesis tool)
 

Step-by-Step Implementation

  1. Follow Sarah’s actionable workflow to replicate her success with your own research:Clarify research scope & core questionsFirst, narrow your focus to avoid overly broad results. Sarah’s key questions:
    • What are the acute and long-term physical/mental health consequences of COVID-19? 
    • How do these impacts vary across demographic (age, gender) and socioeconomic groups?
    • What interventions effectively support long-term recovery for COVID-19 survivors?
  2. Compile targeted keywords & phrasesBrainstorm terms aligned with your questions to refine searches: Example (Sarah’s list): COVID-19 long-term health impacts, post-COVID syndrome, mental health disparities, COVID rehabilitation interventions, socioeconomic factors post-COVID.
  3. Initiate a structured query in PerplexityOpen Perplexity and frame your request to be specific, academic, and action-oriented (avoid vague prompts).
  4. Engage with responses & ask follow-up questionsPerplexity returned summaries of 20+ high-relevance studies, highlighting key methodologies (meta-analyses, longitudinal surveys) and themes (e.g., “young adults face higher mental health risks than previously thought”). Sarah asked follow-ups like:
    • “Can you expand on the gaps in research on low-income communities?”
    • “Are there recent meta-analyses (2023–2024) on rehabilitation strategies?”
  5. Refine search parameters & repeatBased on follow-up insights, Sarah added filters like “2020–2024” (timeframe) and “peer-reviewed only” to her prompts, ensuring results were up-to-date and rigorous.
  6. Synthesise & structure your literature reviewUse Perplexity’s themed summaries to organise your review into sections (e.g., “Physical Health Impacts,” “Demographic Disparities,” “Intervention Efficacy”). She cross-referenced Perplexity’s cited sources with Lingnan’s library databases to validate accuracy.

Example Prompt (Copy & Adapt!)

 

“I’m a master’s student drafting a literature review for my thesis on the long-term health impacts of the COVID-19 pandemic. Please help me:

  1. Search peer-reviewed academic literature (2020–2024) on three topics:

    • Acute and long-term physical/mental health consequences of COVID-19 infection

    • Variations in impacts across age, gender, and socioeconomic groups

    • Effective rehabilitation interventions for COVID-19 survivors

  2. Provide a structured summary of key themes, methodologies, and unresolved research gaps (organize this to fit a thesis literature review section).

  3. Suggest frameworks or analytical approaches to strengthen my review, and explain how my study can address the identified gaps.

  4. Cite all sources (include DOI links if possible) for cross-verification.”

Pro Tips for Students

  • Add timeframes (“2020–2024”) and source types (“peer-reviewed,” “meta-analyses”) to filter low-quality results.

  • Always cross-check Perplexity’s cited sources with official databases (e.g., Web of Science, Lingnan Library) to ensure academic rigor.

  • Use follow-up prompts to dive deeper into gaps—this is where your thesis can add unique value!