Health & wellness — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.
Channels linked by matching posts
This channel is in a group of 2 registered channels linked by matching posts. Links are found by comparing text fingerprints across every channel on the register.
Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
60 measurements spanning 96 days, net -237. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 19,536–19,845 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 60
Measured (UTC)
Subscribers
Change
10 Nov 2026, 15:05
19,572
-3
9 Nov 2026, 02:49
19,575
+1
7 Nov 2026, 17:10
19,574
-6
6 Nov 2026, 12:46
19,580
-8
5 Nov 2026, 12:28
19,588
-5
4 Nov 2026, 13:48
19,593
+1
3 Nov 2026, 14:16
19,592
-5
2 Nov 2026, 12:18
19,597
-3
1 Nov 2026, 15:21
19,600
-4
29 Oct 2026, 15:30
19,604
-7
28 Oct 2026, 16:30
19,611
-3
27 Oct 2026, 14:01
19,614
-1
25 Oct 2026, 14:48
19,615
-3
24 Oct 2026, 14:40
19,618
-10
23 Oct 2026, 13:46
19,628
-8
22 Oct 2026, 13:48
19,636
-2
21 Oct 2026, 05:09
19,638
-9
20 Oct 2026, 02:08
19,647
-4
19 Oct 2026, 05:05
19,651
-3
18 Oct 2026, 06:27
19,654
first reading
Engagement
164 posts held, back to 30 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 75 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
7.92%
avg views ÷ 19,572 subscribers
Avg views / post
1,550
45 posts measured
Reaction rate
1.92%
reactions ÷ views · ER floor
Posts in window
45
of 164 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 10 November 2026
Posts held
164 (30 July 2026 – 10 November 2026)
Views total
69,718
Reactions total
1,340
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
11 Nov 2026, 16:00 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Photos
≈5,020
Videos
≈1,770
Links
≈3,240
Lifetime counters from Telegram’s own channel header, read 11 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
1h 48m
Average length
1m 17s
Measured directly from 85 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
5,363 reactions across 164 posts, in 26 distinct kinds. The most used accounts for 51.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
2,760
51.5%
👍
1,028
19.2%
🔥
430
8.02%
💯
369
6.88%
🙏
187
3.49%
🤬
101
1.88%
🤮
81
1.51%
⚡
67
1.25%
😱
48
0.895%
👏
45
0.839%
😢
42
0.783%
🤯
39
0.727%
🤣
32
0.597%
❤🔥
28
0.522%
👎
19
0.354%
😁
19
0.354%
🤔
17
0.317%
👀
14
0.261%
🥰
14
0.261%
🏆
12
0.224%
6 further kinds
11
0.205%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 164 of the 164 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 5,363 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 164 most recent posts we hold, published 30 July 2026 to 10 November 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Recent posts
Telegram’s own ‘edited’ marker: 1 of 45 posts held from the last 30 days (2.22%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
For my American friends, Nurofen is the UK’s Advil. 💊🇬🇧
And this woman just dissolved a WEEK’S worth of it in water after learning that the black “ink” material on the tablets may be graphene oxide.
What she pulls out of that glass is exactly why I keep telling people:
QUESTION EVERYTHING. 👁️
Graphene oxide is a carbon-based nanomaterial used for electronics, sensors, and more recently, biomedical technology and …
🚨‼️📞 CALL TODAY: Support Greg Steube for House Republican Conference Chair.
Rep. Steube's record demonstrates decisive action for health freedom:
✅ Religious & medical freedom champion: Introduced the GRACE Act to withhold federal education funding from schools and education agencies that deny students religious exemptions from vaccine requirements.
✅ Military medical choice: Cosponsored legislation to prohibit ma…
They don’t just want artificial intelligence. They want an artificial WORLD. 🤖🌎
For more than 30 years, I’ve been researching the poisoning and synthetic transformation of our environment.
🥬 The food.
🚰 The water.
☁️ The air.
📡 Electromagnetic frequencies.
🧫 Geoengineering.
☠️ Chemicals.
And now, the human body itself.
But since COVID, the transhumanism agenda is no longer just about technology around us.
It is …
TONIGHT!
Part 2 of our investigative series delves deeper into Biodigital Convergence, their published plans and why what they refer to as "embodied computing" is essential for achieving their transhumanist goals.
Join us in 40 mins: https://rumble.com/v7f3asc-biodigital-skynet-part-2-the-convergence.html
Follow @zeeemedia
Website | X | Instagram | Rumble
Frequency Healing 💗
Long before modern cymatics gave us a way to see sound, the Shipibo-Konibo people of the Peruvian Amazon were creating intricate geometric designs known as Kené patterns deeply connected with their cultural traditions, songs, plants, healing ceremonies, and worldview.
Their sacred ícaros remind us of something powerful: sound is vibration, and vibration can influence how we experience our bodies…
This interview is insanely on-point.
Wow. Well-worth the listen/contemplation. It explains A LOT of what is REALLY happening in this crazy world.
https://rumble.com/v7i0otc-a-scientist-explains-how-elites-use-frequencies-to-control-humanity-weston-.html
Years ago, I had my own zeolite product.
But then I started digging deeper, and what I found completely changed my mind. ⚠️
Zeolites are aluminosilicates, meaning their structure contains aluminum and silicon.
Then Mike Adams released extensive research on zeolites that raised concerns about potential aluminum exposure.
Today, based on what I’ve studied around aluminum, silica, environmental toxicity, and nanotec…
What if the human body is far more than the physical structure we can see?
Ashayana Deane describes reality as a 15-dimensional matrix composed of frequency bands. Within her teachings, these frequencies are formed through Partiki particles and Keylon codes—the underlying energetic architecture from which matter, consciousness, and our multidimensional bodies emerge.
Our awareness may currently be focused within th…
The more you know…. the more you can empower yourself
👍24💯20🔥1
Showing the 12 most recent of 164 posts we hold for @drgroupofficial. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 6 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Handles this channel named that no longer answer
Dead references
5
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
5
vacant every time we have ever looked
@drgroupofficial named 5 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@banned_truth named in 4 posts, 24 August 2026 – 27 August 2026
@creatrixdiaries named in 3 posts, 6 November 2026 – 9 November 2026
@doctorofdivinebiology named in 2 posts, 9 November 2026 – 11 November 2026
@dredwardgroup named in 2 posts, 10 August 2026 – 12 August 2026
@trueskypsychology named in 1 post, 4 November 2026 – 4 November 2026
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 30 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
Jonathan Otto - Health Secret @jonathanottohealth · 28,729 Telegram ranks this channel #1 of 74 here — alongside 73 others — read 8 September 2026
Dr. Bryan Ardis @BryanArdis · 36,472 Telegram ranks this channel #5 of 73 here — alongside 72 others — read 1 September 2026
Medical Medium @MedicalMedium · 52,656 Telegram ranks this channel #10 of 76 here — alongside 75 others — read 31 August 2026
Christiane Northrup M.D @drchristianenorthrup · 40,942 Telegram ranks this channel #13 of 79 here — alongside 78 others — read 29 August 2026
GreenMedInfo @sayeregengmi · 27,442 Telegram ranks this channel #14 of 81 here — alongside 80 others — read 10 September 2026
Dr. Mercola @DoctorMercola · 30,812 Telegram ranks this channel #17 of 77 here — alongside 76 others — read 5 September 2026
Health Nut News/Erin Elizabeth @erinhealthnutnews · 20,595 Telegram ranks this channel #20 of 81 here — alongside 80 others — read 24 September 2026
The TRUTH About Cancer | Vaccines @TheTruthAboutCancer_Vaccines · 28,288 Telegram ranks this channel #45 of 74 here — alongside 73 others — read 8 September 2026
Lee Merritt MD: FreedomDoc1 @FreedomDoc1 · 24,337 Telegram ranks this channel #58 of 75 here — alongside 74 others — read 16 September 2026
Health Ranger @RealHealthRanger · 62,438 Telegram ranks this channel #69 of 82 here — alongside 81 others — read 21 August 2026
This channel appears in 10 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 10 November 2026 — this
entry's latest reading, not the date you are reading this.
“Dr. Edward Group, DC” (@drgroupofficial), 19,572 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/drgroupofficial.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.