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Channel

Research in Medical Education

@Research_SCMED_Mubabol

On this record: Growth · Engagement · Reactions · Posts · Polls · Citations · Cite this entry

104subscribers

+12 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1004458473675
TypeChannel
Username@Research_SCMED_Mubabol
CreatedBetween 1 June 2026 and 16 July 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded9 August 2026
Last confirmed live13 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/Research_SCMED_Mubabol

Growth

92104986 August 2026 — 92 subscribers7 August 2026 — 102 subscribers9 August 2026 — 102 subscribers13 August 2026 — 104 subscribers6 August 202613 August 2026
4 measurements spanning 7 days, net +12. 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 90–106 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 14:58104+2
9 Aug 2026, 09:47102no change
7 Aug 2026, 03:08102+10
6 Aug 2026, 12:2292first reading

Engagement

20 posts held, back to 16 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
229.0%
avg views ÷ 104 subscribers
Avg views / post
238
19 posts measured
Reaction rate
2.78%
reactions ÷ views · ER floor
Posts in window
19
of 20 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. It is computed over the 16 of 19 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 7 August 2026
Posts held20 (16 July 20267 August 2026)
Views total4,526
Reactions total116
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken9 Aug 2026, 09:47 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.

Reaction mix

122 reactions across 17 posts, in 7 distinct kinds. The most used accounts for 80.3% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
9880.3%
👏86.56%
👍75.74%
💯32.46%
21.64%
🔥21.64%
🤩21.64%

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 122reactions 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 16 July 2026 to 7 August 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

7 Aug 2026, 08:40 UTC35 views6 reactionsread 9 August 2026
Photo

بازی ➕ پژوهش💥‼️ 📌جواب جدول در کانال قرار داده می‌شود. #پژوهش #جدول #بازی 🔎〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️ 🆔Research_SCMED_Mubabol 🆔SCMED_BMU

3🤩2🔥1

5 Aug 2026, 15:22 UTC859 views22 reactionsread 9 August 2026
File

📝چهارشنبه ها با پژوهش! 💡عنوان پادکست: چرا دانشجویان پزشکی با وجود دسترسی به همه منابع، کمتر مطالعه عمیق می‌کنند؟ #چهارشنبه_ها_با_پژوهش #پادکست #پژوهش 🔎〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️ 🆔Research_SCMED_Mubabol 🆔SCMED_BMU

192👍1

4 Aug 2026, 09:53 UTC79 views8 reactionsread 9 August 2026

امروز دانشجویان پزشکی بیش از هر زمان دیگری به منابع آموزشی دسترسی دارند. 📚 کتاب‌های مرجع، مقالات، ویدئوهای آموزشی، پلتفرم‌های آنلاین و حتی هوش مصنوعی، همه تنها با چند کلیک در دسترس هستند. اما یک سؤال مهم... ⁉️ چرا با وجود این همه منابع، مطالعه عمیق کمتر از گذشته به نظر می‌رسد؟ آیا حجم زیاد اطلاعات باعث سردرگمی شده است؟ یا عادت کرده‌ایم به جای یادگیری عمیق، فقط سریع‌تر به جواب برسیم؟ شاید هم سبک آموزش و ارزشیابی دا

5👍3

2 Aug 2026, 15:11 UTC125 views7 reactionsread 9 August 2026

📚 مطالعه نیمه‌تجربی (Quasi-Experimental Study) مطالعه نیمه‌تجربی نوعی مطالعه مداخله‌ای است که در آن پژوهشگر برای بررسی اثر یک اقدام، مداخله‌ای را اجرا کرده و تغییرات حاصل از آن را ارزیابی می‌کند. ⬅️در این نوع مطالعه معمولاً: 🔹 ابتدا وضعیت افراد قبل از مداخله اندازه‌گیری می‌شود. 🔹 سپس مداخله (مانند آموزش، درمان یا اجرای یک برنامه جدید) انجام می‌شود. 🔹 در پایان، همان متغیر دوباره اندازه‌گیری شده و نتایج قبل و بعد با

6👏1

1 Aug 2026, 11:15 UTC76 views5 reactionsread 9 August 2026
Poll

در یک پژوهش آموزشی، ابتدا سطح دانش دانشجویان اندازه‌گیری می‌شود، سپس یک روش تدریس جدید اجرا شده و در پایان دوباره همان آزمون گرفته می‌شود. این طراحی مطالعه به کدام گزینه نزدیک‌تر است؟

  1. مطالعه مقطعی0%
  2. مطالعه توصیفی15%
  3. مطالعه نیمه‌تجربی38%
  4. مطالعه مورد-شاهدی46%

Shares as published, totalling 99%. No per-option vote count is published by Telegram, so none is shown.

5

31 Jul 2026, 09:40 UTC89 views7 reactionsread 9 August 2026

📚 مرور مقاله 🏥 تأثیر اعتباربخشی بیمارستانی بر کیفیت خدمات سلامت؛ یک مرور نظام‌مند اعتباربخشی بیمارستان‌ها یکی از مهم‌ترین ابزارهای ارزیابی و ارتقای کیفیت خدمات سلامت در جهان است. اما آیا اجرای استانداردهای اعتباربخشی واقعاً کیفیت خدمات درمانی و پیامدهای بیماران را بهبود می‌بخشد؟ 🤔 در این مطالعه مرور نظام‌مند، پژوهشگران با جست‌وجو در پایگاه‌های معتبر علمی از جمله PubMed، Scopus، MEDLINE و EMBASE، تعداد 17,830 مقاله

7

29 Jul 2026, 16:47 UTC746 views6 reactionsread 9 August 2026
File

📝چهارشنبه ها با پژوهش! 💡عنوان پادکست: پزشک آینده چه مهارت‌هایی خواهد داشت که امروز آموزش داده نمی‌شود؟ #چهارشنبه_ها_با_پژوهش #پادکست #پژوهش 🔎〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️ 🆔Research_SCMED_Mubabol 🆔SCMED_BMU

6

28 Jul 2026, 14:48 UTC117 views5 reactionsread 9 August 2026

امروزه با ورود هوش مصنوعی، ابزارهای دیجیتال و تحول سریع فناوری، تعریف «پزشک موفق» کم‌کم در حال تغییر است. و این ما را به یک سؤال مهم می‌رساند... ⁉️ پزشک آینده چه مهارت‌هایی خواهد داشت که امروز در دانشگاه‌ها کمتر آموزش داده می‌شود؟ آیا مهم‌ترین مهارت آینده، کار کردن با هوش مصنوعی است؟ یا توانایی تصمیم‌گیری، تفکر انتقادی، ارتباط مؤثر با بیمار و یادگیری مداوم، ارزش بیشتری پیدا خواهند کرد؟ 🤔 دوست داریم قبل از پادکست،

5

27 Jul 2026, 18:43 UTC102 views7 reactionsread 9 August 2026

پیش از اینکه یک مقاله را بخوانید یا یک طرح پژوهشی بنویسید، باید بتوانید متغیرهای مطالعه را تشخیص دهید. تقریباً در تمام پژوهش‌ها با دو متغیر اصلی روبه‌رو هستیم: 🔹 متغیر مستقل (Independent Variable) متغیری که پژوهشگر آن را تغییر می‌دهد یا اثرش را بررسی می‌کند. به بیان ساده، علت یا مداخله در مطالعه است. 🔹 متغیر وابسته (Dependent Variable) متغیری که اندازه‌گیری می‌شود تا مشخص شود تحت تأثیر متغیر مستقل قرار گرفته است یا

7

26 Jul 2026, 06:17 UTC49 views6 reactionsread 9 August 2026
Forwarded from @aimec_mubabolPhoto

🚀 در AIMEC هوش مصنوعی فقط یک فناوری نیست، یک سبک زندگیه 🤖✨ اگر می‌خوای هر روز با جدیدترین اتفاقات دنیای AI همراه باشی، اینجا دقیقاً جای توئه🤩 در AIMEC باهم: 🔥داغ‌ترین اخبار هوش مصنوعی رو دنبال می‌کنیم. 🛠 جدیدترین ابزارهای AI رو معرفی و آموزش می‌دیم. 💬 پرامپت‌های کاربردی و خلاقانه رو به اشتراک می‌ذاریم. 🎙 پادکست‌های کوتاه و آموزشی منتشر می‌کنیم. 🎮 چالش‌ها، سرگرمی‌ها و کلی محتوای جذاب خواهیم داشت. اگر می‌خوای از آین

👏42

26 Jul 2026, 05:10 UTC92 viewsread 9 August 2026
Poll

پژوهشگری قصد دارد تأثیر استفاده از شبیه‌ساز (Simulation) را بر مهارت احیای قلبی-ریوی دانشجویان پزشکی بررسی کند. متغیر وابسته کدام است؟

  1. الف) استفاده از شبیه‌ساز39%
  2. ب) مهارت احیای قلبی-ریوی دانشجویان50%
  3. ج) رشته تحصیلی دانشجویان6%
  4. د) سن دانشجویان6%

Shares as published, totalling 101%. No per-option vote count is published by Telegram, so none is shown.

Showing the 12 most recent of 20 posts we hold for @Research_SCMED_Mubabol. 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.

Polls

The 3 polls we hold for this entry, as Telegram rendered them when we read the post. A poll’s figures keep moving after that, so each one is dated.

1 Aug 2026, 11:15 UTCAnonymous Quiz13 voters

در یک پژوهش آموزشی، ابتدا سطح دانش دانشجویان اندازه‌گیری می‌شود، سپس یک روش تدریس جدید اجرا شده و در پایان دوباره همان آزمون گرفته می‌شود. این طراحی مطالعه به کدام گزینه نزدیک‌تر است؟

  1. مطالعه مقطعی0%
  2. مطالعه توصیفی15%
  3. مطالعه نیمه‌تجربی38%
  4. مطالعه مورد-شاهدی46%

Shares as published, totalling 99%. No per-option vote count is published by Telegram, so none is shown.

26 Jul 2026, 05:10 UTCAnonymous Quiz18 voters

پژوهشگری قصد دارد تأثیر استفاده از شبیه‌ساز (Simulation) را بر مهارت احیای قلبی-ریوی دانشجویان پزشکی بررسی کند. متغیر وابسته کدام است؟

  1. الف) استفاده از شبیه‌ساز39%
  2. ب) مهارت احیای قلبی-ریوی دانشجویان50%
  3. ج) رشته تحصیلی دانشجویان6%
  4. د) سن دانشجویان6%

Shares as published, totalling 101%. No per-option vote count is published by Telegram, so none is shown.

18 Jul 2026, 18:54 UTCAnonymous Quiz27 voters

در مطالعه Double-blind چه کسانی از نوع مداخله بی‌اطلاع هستند؟

  1. تحلیلگر آماری0%
  2. هم پژوهشگر و هم شرکت‌کننده81%
  3. فقط شرکت‌کننده15%
  4. فقط پژوهشگر4%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

Percentages only — there are no per-option vote counts here, because Telegram publishes none.The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.

The shares need not add up to 100.Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.

Read from the 20 most recent posts we hold, published 16 July 2026 to 7 August 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.

Citation-graph rank

Citation-graph rank — 83,840 of 1,481,217entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Republishes

Channels on the register whose posts this channel has forwarded.

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 4 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.

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 August 2026 — this entry's latest reading, not the date you are reading this.

“Research in Medical Education” (@Research_SCMED_Mubabol), 104 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/Research_SCMED_Mubabol.

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.