Public Health

Community-led educational interventions to reduce non-prescription antibiotic sales in retail pharmacies: a systematic review.

Skills / interests: Data analysis and organisation, Data extraction

Methodological skills / interests: Artificial intelligence, Comparing multiple interventions (network meta-analysis and overviews), Individual participant data meta-analysis, GRADEing

The detailed description of the task are as follows:

Phase 1: The Protocol (Months 1–6)

Before we look at a single trial's results, we must publish our "rules of engagement." This prevents us from changing our mind later to make the data look better.

  • Defining PICO: We must specify exactly who counts (e.g., only adults? only children?), what the intervention is (e.g., specifically a 10-minute blood test), and what success looks like (e.g., total prescriptions written vs. actual clinical recovery).

  • Search Strategy: We will work with a Cochrane Information Specialist to write a "Search String"—a massive, complex list of keywords used to scan databases like PubMed, Embase, and CENTRAL.

  • Peer Review: The Protocol itself will be peer-reviewed and published.

Phase 2: The Search & Screen (Months 6–9)

Once the protocol is live, you hit "Go" on the search.

  • The "Haystack": Our search might return 8,000 to 12,000 abstracts.

  • Sifting: Two authors must independently read every single title and abstract to decide if it fits your PICO. If anyone disagree, a third author breaks the tie.

  • Full-Text Review: We’ll likely whittle those thousands down to 50–100 papers that you must read in full to ensure they meet your strict quality criteria.

Phase 3: Data Extraction & "Risk of Bias" (Months 9–15)

This is the most labor-intensive part of the task.

  • Extraction: We will create a massive spreadsheet (or use RevMan) to pull data from every study: How many patients? What dose? How many got antibiotics? What were the side effects?

  • Risk of Bias (RoB 2): We must judge the quality of every study. Did the doctors know which patient got the test? Was the randomization truly random? If a study is "low quality," its data will carry less weight in your final result.

Phase 4: The Meta-Analysis (Months 15–18)

This is where the math happens.

  • Pooling Data: We have to use a statistical method to combine the results of all the small studies into one giant "Forest Plot."

  • Heterogeneity: we have to calculate I^2 to see if the studies are too different to be compared. If I^2 > 75%, you have a problem—the studies are telling very different stories.

  • GRADE Assessment:  To provide a "Certainty of Evidence" (High, Moderate, Low, or Very Low) to each outcome.

     

     

Phase 5: Writing & Final Peer Review (Months 18–24)

  • Plain Language Summary (PLS): We will write a version of our findings that a regular patient or a journalist can understand.

  • The "Editorial Gauntlet": The Cochrane Group will tear the draft apart, checking every calculation and every citation. It may take 2 or 3 rounds of heavy revisions.

The Workload Reality

  • Team Size: Usually 8 to 10 people.

  • Software:  RevMan Web, COVIDENCE, GRADE pro

  • Evidence-Based Medicine: We will not just say that "antibiotic misuse is bad." We will find out the process "How to reduces antibiotic initiation by 22% (95% CI 18% to 26%) with high-certainty evidence.”

Ideal applicant

The ideal applicant is already familiar with (or ready to master) the Cochrane Handbook for Systematic Reviews of Interventions, You should show that you know how to use: RevMan Web, Covidence and GRADE.

Think you've got what it takes to get the job done for MIHIR?

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Questions & comments

I would be eager to know the status of my inclusion in the team

Default profile Puspen Ghosh - 10 hours ago