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 21 September 2026 and assigned it the closest of 31 fixed categories, at 54% 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 why it has no browse page of its own yet.
Growth
6 measurements spanning 66 days, net -2. 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 467–470 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Oct 2026, 01:09
468
+1
2 Oct 2026, 13:59
467
-1
11 Sept 2026, 22:41
468
-1
21 Aug 2026, 11:14
469
-1
8 Aug 2026, 04:46
470
no change
7 Aug 2026, 15:52
470
first reading
Engagement
20 posts held, back to 7 September 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 5 May 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
4m 57s
Average length
1m 14s
Measured directly from 4 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
254 reactions across 17 posts, in 12 distinct kinds. The most used accounts for 35.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
90
35.4%
❤
71
28.0%
👍
69
27.2%
👏
9
3.54%
🤣
6
2.36%
👌
3
1.18%
✍
1
0.394%
❤🔥
1
0.394%
🎄
1
0.394%
🎉
1
0.394%
🙏
1
0.394%
🥰
1
0.394%
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 17 of the 20 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 254 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 7 September 2025 to 5 May 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.
Telegram Stars
Stars received
3
across the posts below
Posts paid on
2
of 20 we hold a reading for · 10%
Most on one post
2
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @Yanatrener. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 20 most recent posts we hold for this entry, published 7 September 2025 to 5 May 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
СВОЯ НОША НЕ ТЯНЕТ? Да еще как!
Друзья, я вновь возвращаюсь к тому, в чем я вам могу быть полезной: к поиску верных решений в работе.
Я недавно (да и до сих пор еще) была в зоне высокой турбулентности, переехав в совершенно чужой огромный город без работы. Это было тяжко, хотя это я теперь могу позволить себе это сказать, тогда просто пришлось «упереться рогом».
Но я, конечно, не только «чувствую» вас. Я знаю мето…
Никак не получалось донести до врачей моих -что в консультации пациентов нужно использовать не только рентген-снимок и рассказы о диагнозах, но и дополнительные средства визуализации.
Пациент, слушая медицинские термины впервые и вглядываясь в паутину сосудов и затемнений на снимке медленно, но верно впадает в анабиоз.
Сегодня я принесла стоматологам…ноты. И с жаром рассказала о произведении, написанном гениальны…
Друзья, у меня отличные новости!!!!
Нейросетка Deep seek теперь воспринимает голосовые сообщения! Правда, пока что только на телефоне)
Но все равно рада сильно, процесс работы ускорился в разы! Надеюсь, вы уже вовсю привлекаете нейросети в вашу работу?)
Вчера выступала на семинаре для управляющих клиник.
Тема семинара: роль координатора в клинике.
Люди собрались со всей России, от Хабаровска и до Москвы.
Заинтересованная, живая аудитория.
Получила отзыв: «Спасибо вам! Я управлявшая клиники, но теперь подумываю- может самой пойти в координаторы»)
Это дает понимание того, что моя миссионерская цель, как тренера : ВДОХНОВЛЯТЬ на шаг в еще неизвестное -достигнута
Когд…
Друзья, приветствую.
Долго собиралась, вот собралась.
Создала мой личный канал, и если вам интересна моя жизнь и Я как человек -приглашаю : https://t.me/Varshavskaya_zhiza
❣️🙏
Ох други…. Вы спрашиваете - почему я заглохла….
Ну, во -первых, я полностью увлечена сейчас своей работой, а именно: тренировкой врачей и администраторов в стом. Клиниках и их у меня сейчас четыре ( клиники). То есть, если вы работаете со сферой услуг а тем более в красоте или медицине -ой у меня много чего уже есть для вас 📝
Во-вторых, мне бы от вас узнать -какие темы вам сейчас актуальны из моих специализаций ( к…
Завтра начинаю работать в режиме индивидуального коучинга для обучения врача -наставника.
🔠🔠🔠🔠🔠🔠
свою работу за разнообразие форматов!
А эта задача еще и вызов.
Расскажу почему:
Так как хороший спортсмен -не всегда хороший тренер. Равно, кстати, как и наоборот.
Для наставника нужен ряд качеств, таких как: сопереживание, эмпатия, терпение, вера в ученика.
И некоторые из этих качеств могут вступать в противоречи…
Фаберликовцы! Спасибо за опыт!
А вот тут, как я и обещала, конспекты и парочка приготовленных вкусняшек для вас:
https://drive.google.com/drive/folders/1Cbb6BvOLpF_dACF4yiINtMdlAN41qkq1?usp=sharing
Качните материалы себе, удалю с диска в четверг 🙂
🔡🔡
🔡🔡🔡🔡🔡
🔡🔡🔡🔡🔡🔡
Представьте: у меня в руках — идеально отлаженный механизм. Не железный, а живой — тренинг. Я его создавала для 30 человек.
3️⃣0️⃣— это магия.
Это тот самый максимум, где ты видишь глаза каждого, ловишь кивок, чувствуешь, когда кто-то отключается.
30 — это когда ты не вещаешь, а ведёшь за собой.
Всё было договорено, выверено и согласовано.
И вот за пару дней до часа «Х» мне сообщают : «Яна, позд…
❤18👏4🔥2
Signed Яна Варшавская
Showing the 12 most recent of 20 posts we hold for @Yanatrener. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Mentions
Names
Channels on the register whose handles appear in this channel's posts.
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.
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 13 October 2026 — this
entry's latest reading, not the date you are reading this.
“Варшавская Яна. Тренер и наставник” (@Yanatrener), 468 subscribers as measured 13 October 2026. Telegram Register, tgregister.com/channel/Yanatrener.
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.
