Editorial Policy

This page explains how I create content on iGoLong: what sources I trust, how I read research, how I label confidence, and how corrections work. The goal is simple: clarity over hype.

Who I am (and what I’m not)

I’m an entrepreneur building a personal longevity and energy system after 40. I’m not a physician, not a researcher, and not your clinician. iGoLong is my disciplined learning and testing framework, published in public.

Core principles

Evidence-aware, not vibe-based
Clear separation: research vs personal experience
No medical claims (no “cure”, “prevent”, “guarantee”)
Honest uncertainty when evidence is weak or mixed
Updates when better data appears

What sources I prioritize

When possible, I prioritize:

Systematic reviews and meta-analyses
Randomized controlled trials (RCTs)
Large cohort studies (especially with long follow-up)
Clinical guidelines and consensus statements from reputable bodies
Mechanistic studies only as supporting context (not as final proof)

What I treat as weak evidence

Anecdotes as proof
“Guru certainty” without citations
Unverified blogs or screenshots as primary sources
Cherry-picked studies without context
Animal or cell studies presented as human outcomes

How I read research (simple checklist)

When I cite or summarize a study, I try to check:

Study design (RCT, cohort, case series, etc.)
Sample size and population (age, sex, health status)
Duration (weeks vs years matters)
Endpoints (hard outcomes vs proxies)
Limitations and conflicts of interest
Whether the result is replicated elsewhere

Confidence labels (Evidence Strength)

I may label key claims using:

High confidence: multiple high-quality human studies with consistent results
Moderate confidence: decent human data, but limitations or mixed findings
Low confidence: early data, small studies, indirect evidence, or uncertainty

If I don’t label it, assume it’s not a clinical recommendation—just information.

“What we still don’t know”

For topics that attract hype (supplements, protocols, biomarkers), I often include a short section on open questions, long-term unknowns, and realistic limitations. It’s not drama. It’s adult supervision.

Personal experiments

When I share a personal protocol, I aim to disclose:

My goal and why I’m testing it
What I measured (sleep, HRV, labs, performance, etc.)
The timeframe
What changed (and what didn’t)
What I would do differently next time

Personal results are not universal results.

Review and update cycle

I periodically review high-impact pages (especially YMYL topics).
I update content when new evidence changes the practical takeaway.
I may revise wording to improve clarity without changing meaning.

Corrections policy

If you spot an error:

Email me via /contact
Include the page URL and what looks wrong
If possible, include a source

If a correction is warranted, I’ll update the page and note meaningful changes where appropriate.

AI tools

AI may assist with drafting, outlining, or structuring research notes. Final content is reviewed and edited by me before publication. I treat AI output as a helper, not an authority.