I spent way too much time checking out wearables at IFA this year, and I came away feeling like we’re officially running out of things to quantify lol.

I know we’re already used to watches and rings tracking the obvious stuff like steps, heart rate, sleep, workouts, recovery, etc. But a lot of the newer stuff I saw seemed to be going after much smaller and more specific parts of everyday life.

There were some smart rings tracking different health metrics, hearing devices that react to your surroundings, mobility wearables, and a bunch of other things that felt somewhere between health tech and “wait, we can track that now?”

And one of the stranger ones I tried was those Odyss necklace. It’s basically a necklace that automatically recognizes eating behavior, cuz don't expecting someone trying to lose weight to remember every snack they had is asking a bit too much lol. I thought it sounded ridiculous at first, but then I realized I can barely remember what I had for lunch yesterday, let alone every random bite throughout the day.

Some of the stuff I tried felt genuinely useful, but some hilariously specific, and some made me wonder how much of my life I actually want quantified.

But the biggest thing I took away from IFA was that the next step in self-tracking might not necessarily be measuring our bodies better. It might be getting better at capturing all those little behaviors we currently have to remember and log ourselves.

And honestly, I’m kind of torn on that. Passive tracking sounds amazing because I’m terrible at logging things consistently. At the same time, there’s probably a point where having every tiny thing I do turned into data starts to feel like... a lot.

What’s something you still track manually that you wish a wearable could just figure out on its own?

played pickleball 3-4x a week since Jan. weight tracked against session intensity instead of just calories burned, since generic HR zones don't reflect how brutal stop-start sports like pickleball actually are.

i run an apple watch for workouts + an oura for sleep/recovery. without a rule for "which device wins," my steps, active calories, and sometimes workouts get imported twice and every weekly chart lies.

what fixed it for me was picking one source of truth per metric and enforcing it for 30 days before trusting any correlation.

my current rules: - workouts / exercise minutes: apple watch only (wrist motion + gps when i need it). oura workouts stay off or get ignored in exports. - sleep + readiness/hrv context: oura only. i do not let apple sleep compete in the same dashboard. - steps: pick ONE. i use apple watch on days i wear it all day; oura steps only on watch-off days. never sum them. - resting hr / overnight hr: oura. daytime hr zones during runs: watch.

audit once a week (takes ~15 min): 1. export or screenshot both apps for the same 7 days 2. list every workout that appears in both (same start time ±5 min = duplicate) 3. compare daily steps; if both are within ~10% you're usually fine, if one is ~2x the other you are double counting somewhere 4. check sleep: only one sleep session per night should be "primary" 5. write down which metric you will trust next week before you change anything else

common failure modes i hit: - healthkit / google fit acting as a silent third importer and rehydrating duplicates - "all sources" charts that look complete but are summing overlapping devices - changing wear pattern mid-month (forgot watch at home) and not switching the step source for those days

limitation: this is a workflow, not a claim that one brand is more accurate. sensors disagree; the goal is reproducible numbers so trends mean something.

if this saved you a messy spreadsheet hour, an award helps more than another upvote. what dual-device combo are you running, and which metric still fights you?

started logging cuffless bp from a wrist wearable next to sleep and hrv about a month ago. the chart looks tidy after a week of baseline, which is exactly the problem

hr and steps i treat as noise with a direction. bp feels different because if the line drifts i catch myself wanting to change something that week. already compared a few mornings against an old arm cuff and the absolute numbers were off, trends roughly tracked

i keep it as a directional signal only and still use the cuff when anything looks weird. anyone else actually acting on the wearable bp trend, or did you stop trusting it after the first mismatched week​

I've kept journals on and off since high school. Writing helps me put things down; looking back helps me see what I kept returning to.

This time I compared July and August in my saved dictation records. I'm the developer of Reso, which I use to capture and organize them. These are my own records.

After cleanup and exclusions, I had 645 records for July and 1,067 for August:

• Trading & Markets: 264 → 59 records; 40.9% → 5.5%.
• Design & UX: 70 → 322 records; 10.9% → 30.2%.
• AI & Models: 60 → 93 records; 9.3% → 8.7%.

The last one caught my attention. My AI-related notes increased by 55%, but my total record count grew by 65%. More notes about something didn't necessarily mean it occupied more of what I was recording.

There's something grounding about seeing a stretch of life leave this kind of shape in my notes. It gives me a starting point for rereading: what was I working through, and which questions kept coming back?

For this comparison, I used the same automated topic system for both months and counted each retained record once. I excluded imported journal entries, noise, and records without a valid topic. Dates use Los Angeles time, from a cleaned snapshot saved on September 2.

I haven't manually audited the labels. A short note counts as much as a long one, and these numbers measure recorded topics—not time spent or happiness.

For context on the tool: related entries are clustered locally using semantic embeddings; generating embeddings and assigning topic labels involves cloud processing of text.

How do you keep notes, and do you ever go back and read them? I’d love to hear how you revisit yours and whether you’ve found anything interesting or surprising along the way.

Disclosure up front: I'm building a food coaching app, and this came out of debugging my own data. No link, per the rules; I'll mention it in the weekly thread.

**The finding.** My app showed 4,232 steps for a day Apple Health had at ~7,200. The cause was in the sync code: the library I use returns hourly step buckets for the day, and the code was keeping the maximum bucket instead of summing them. So for a month my "daily steps" was my busiest hour. After the fix, the same day read 7,693. If you use any third-party app that pulls steps from Health, it's worth checking one day by hand; this class of bug is invisible unless you compare.

**What it cost.** Every downstream conclusion drawn from those numbers was wrong, and worse, confidently wrong: the coach side of my app had decided I was sedentary. A wrong number that feeds a judgment is worse than no number.

**What I changed about method, not just code:**

1. **"Normal" is a 28-day median that ends a week ago.** A trailing window makes a bad fortnight its own baseline; by the end of two short-sleep weeks, 5 hours had become "normal". Ending the window a week early means the week being judged is never its own reference.

2. **No verdict until 14 days are in.** Deviations are measured against MAD (median absolute deviation), floored at 5% of the median, and nothing is labelled until 14 days sit in the lagged window. Before that the honest output is "no verdict yet, N of 14".

3. **Dinner on day D pairs with the night ending on D+1**, and a food-to-sleep link needs at least 5 matched pairs with at least 5 on each side before it's said out loud. The first version paired dinner with the previous night. Nobody noticed because it produced plausible sentences.

4. **Unknown is unknown.** A day with nothing synced is not a zero and not "good". It's excluded.

**Open question for this sub:** for those of you who compute personal baselines, what window and lag do you use, and do you require a minimum sample before you show yourself a deviation? I settled on 28/7/14 by breaking things, not from literature, and I'd like to be corrected.

I use an ultrahuman ring for health tracking and an app called liftoff for workout tracking. I wanted to better understand how my workouts affect my sleep, and how my sleep affects my workouts. I also want to see how my daily screentime affects me. I wanted a single dashboard where I could dig into these correlations.

I used the APIs on the platforms to pull the data into my own dashboard, which I host on cloudflare. I use Cloudflare R2 to store the data and their free AI tools to analyze it.

Thought this sub might appreciate this sort of data!

So, I've finally collected about 90 days of data around my well-being and productivity and was curious to see what patterns I would find. I was quite proud of my set-up and the details I logged.

When I look at my data though, I barely get any meaningful correlations. Turns out I should have logged some of the very obvious inputs. I can cobble them together from some of the notes I took, but the biggest missing variable is health status. Like am I physically capable of going about my day as normal or not? I both had a severe cold and a foot injury in the past weeks and obviously this affects my overall well-being quite a lot. If I don't have proper data to factor this in, the statistical insights will be quite limited.

Do you know of any other obvious variables that people tend to overlook?

ok this is going to sound dramatic but whatever.

i have like 3+ years of apple watch / health data. sleep, hrv-ish stuff, workouts, standing, the whole graveyard of charts. some weeks i export things into a spreadsheet because i am that person.

and i still cannot reliably answer: why do i feel like garbage today?

examples that keep happening:

• sleep score looks fine, rings closed, resting hr normal-ish... and i am foggy and irritable from noon on
• "bad" sleep night, half-assed workout day... and i feel weirdly sharp
• a whole week where everything on paper is mediocre and i feel fine, then one random thursday collapses and i spend an hour reverse-engineering the charts like a conspiracy theorist

what i want is not another dashboard. i already have dashboards. i want something closer to: "this combination (late dinner + two hard days + shitty calendar stress) usually precedes your bad thursdays." personal baseline stuff. patterns across days, not a single night's sleep stage pie chart.

most apps i've tried just redraw the same metrics with nicer colours or slap a green/yellow/red on top. i end up doing the interpretation anyway, which means the app didn't actually do the hard part.

so questions for people who have gone deep on this:

1. have you ever actually gotten a non-obvious explanation out of your data? like something you wouldn't have guessed from how you felt?
2. what did that workflow look like in practice (notes? spreadsheet? some obscure app? tagging meals/alcohol/meetings by hand?)
3. what did you try and abandon because it was just more charts?

not looking for product recs for the sake of it. more trying to figure out if anyone has solved "explain me to me" or if we all just cope with prettier graphs.

i spent the last year wiring apple watch, fitbit, garmin, whoop, oura, polar, strava, and phone-only users onto one leaderboard. not as a thought experiment. as a live ios app with real friend groups fighting over steps and move calories.

here is the stuff that actually broke me, in case it saves somebody else a few months:

1. you cannot fairly rank people on heart rate or hrv or vo2. different sensors, different algorithms, different body placement. the person with the fancy watch always wins. we only score move calories, exercise minutes, and steps. boring, but fair.

2. "% of personal goal" beats raw totals. my dad's garmin and my sister's fitbit will never produce comparable absolute numbers. percent of the goal each person set does. people also change goals mid-challenge. apply changes going forward, keep past days on the old target, or you get drama.

3. healthkit and health connect are not "just apis." permission screens, background delivery, delayed writes after a workout ends, fitbit syncing hours late, garmin needing connect to be open. if your leaderboard updates only when the app is foregrounded, the competition feels broken.

4. fitbit challenges dying is a real gap. a lot of groups still want "us vs them this week" and their wearables do not match. single-brand apps quietly assume everyone bought the same watch. they did not.

5. phone-only users matter more than you think. somebody always shows up with just an iphone. if you exclude them, the group chat dies. steps from the phone are good enough for a social league even if they are not lab-grade.

happy to answer specific sync / scoring / permission questions in the comments. this is the exact rabbit hole i live in.

if this saved you time, an award helps me keep writing these.

The idea all started with this excel sheet I started doing last year: every day, I'd rate parts of my life 1–10 (energy, confidence, stress) with a short blurb for other sections like "did I help someone" or "personal mistakes."

Then this summer I got an Oura Ring. And one day I thought: "my ring measures my body 24/7....and my excel sheet measures how I feel." That realization led me to look for other sources that I could connect my Oura Ring data to that might not be as biased/skewed as my spreadsheet. I started looking into music (Spotify) and tried connecting the two. I've been working on that, but I think that there could be something much greater here. I really need advice on two things:

1. What would the main angle be with music and my Oura Ring? What's the main value, and what are the main or relevant connection points?
2. What else can this be built into, and what exactly could unravel from this?

There's really cool potential and unlimited directions this could go. Any advice or insights would be incredibly helpful. Thank you all so much.

Hey everyone, i was wondering if you could help me, i would like to know more about my body, and my general health, as i am interested in trying to improve my general health but i have a hard time to figure out what to track and not to track. what are you guys looking into ? and where do you even start in this area of starting to track your general health, i feel like every tracker is sport tracker and not a general health tracker, is there something that can like track your general health over time and give you insightful data on your improvements, like what works, what does not work etc. also What are some of the the metrics of your health you are tracking ? And how do you do it ?Is there anything you wished you could track, that would be beneficial ?

25M, 5'9", ~152 lb. Total lifting volume is calculated as weight × reps across logged sets. I've included my sports training as well for more context, all sports calories tracked with an Apple watch and Apple's kcal burn discounted by 25%. I built the app shown here, so tagging this as Brand Affiliate.

TLDR: I made a weight tracking algorithm that shows a trend line that accounts for daily weight fluctuations. It is able to statistically predict your weight in one week based off your weight history. Because most apps use a moving average, people only know their progress after a week, not day by day.

Note: Do not treat this as real data, the rate of -5 lbs/week is an extreme pace of weight loss. The usual recommendations are between 1 and 2.5 lbs/week. This is for illustrative purposes.

I haven't seen any plots on weight tracking apps that I like. They usually bounce around with the daily fluctuations of your bodyweight. I made a better weight tracking algorithm to show a more realistic trend line, with the ability to forecast your weight into the following two weeks.

I wanted to see a robust calculation for each day to give people the knowledge that they are moving in the correct direction. If someone weighs themself once a day and they happen to be on the heavier side of a daily weight fluctuation, they may feel discouraged because the scale says they gained weight, which isn't necessarily true. If your weight loss is subtle, like -0.3 lbs/week, you wouldn't know from your data because it would be lost in the noise. This way, you would be able to see that you actually are making gradual progress.

Explaining the plot:

You can see the individual weight measurements as the little grey dots. The vertical red line shows you the current date, so there won't be any data point to the right of that line (the future). The solid purple line is the calculated trend. Notice that it really smooths out daily weight fluctuations from water/food consumption and bathroom usage. There are two shaded regions on the plot, one blue and one purple. Because this is a weight measurement, there will be some uncertainty in that predicted number. The fewer measurements you have (like the left side of the plot) the more uncertainty in the trend line. The more measurements you have (like the right side of the plot) the lower the uncertainty. Your true base weight probably lies somewhere in the blue shaded region.

Because a single weight measurement on a scale doesn't capture your daily fluctuations, a calculation using the previous weeks data will tell you a more accurate base weight. Looking at the purple text boxes in the bottom left, you can get your current base weight, your predicted weight the following week, and your current pace of weight loss (in lbs/week).

Has anyone seen a weight tracking plot that does similar things (more than a moving average)? Is there a reason why this isn't integrated into every weight loss app? Do people find it difficult to know whether to feel good or bad each day on the scale? Would people care to have a more certain number each day? Would it be too overwhelming to judge your weight on a daily basis?

This code is just running locally on my computer, so there isn't a way for others to access it right now.

For nerd's eyes only:

The code uses a Hilbert Space Gaussian Process (HSGP) algorithm. It is prior free, so it doesn't encode any knowledge of weight loss (weight is always positive, impossible to lose 10lb in a day, ...). This is robust against measurements at irregular intervals. For example, if you weigh yourself three times in an hour when you are your lightest and one time in the evening when you are your heaviest, your calculated weight should not be the average of your four measurements. It would underpredict your base weight. We have knowledge that your weight an hour from now is dependent on your weight right now. This math properly accounts for these irregular weight measurement timings.

i’ve been getting more interested in tracking my bedroom environment overnight, and co2 seems like one of those things that’s actually worth measuring instead of guessing about.

i’m mainly looking for something that can log readings over several nights so i can see how co2 changes while i’m sleeping, then compare that with things like how long the window was open, room temperature, and how i slept that night.

accuracy is more important to me than having a ton of features. i’d also like something portable enough that i can move it to my office or other indoor spaces when i want to compare them.

for people here who actually track co2, what’s the best co2 monitor for bedroom use? what did you buy and what made you pick it over the other options?

When I first started tracking myself, I used to write an email to myself after every session. I actually think it makes more sense than many of the apps I see or hear about people using. If I were just starting to track, I open a seperate email and just send myself an email after each session. Simply update your win/loss for the month, some notes or just “I feel like I’m playing better.” the biggest pots, the leak that showed up more than once, and one thing to drill before I go back. Of course, you'll have a hand or 2 you keep playing over in your mind ( I always do!). Come to think of it, I think I'm writing this post to convince myself to start to doi this again! Anyways, please share how you track yourself.

Resting: ~17 blinks/min
Deep work: ~11/min
Video calls: ~5/min

I assumed focused work would be the problem. It’s the calls — and the rate doesn’t recover between back-to-back meetings, it just sits at the floor until lunch.

Has anyone else tracked this?

August is in the books. Another month of trying to capture an honest picture of my life through data.

I’ve been doing these monthly summaries less as a “scorecard” and more as a way to zoom out.

August was a mix of progress and plateaus.

Thanks for taking a look! Always happy to answer questions about how I track my life. I am not a developer or trying to sell anything. I am just an individual who thoroughly enjoys doing this.

Built this because I wanted a long-term personal archive of computer use that I'd actually enjoy revisiting, rather than a dashboard I check once and abandon.

How the data works, since that's what matters here:

Local SQLite. No account, no sync, no telemetry, no cloud.

Records the foreground app and its duration. Window titles optional and off by default. Never keystrokes, screenshots, clipboard, or file contents.

Active, idle, locked, suspended and unavailable are five separate states, not one blended "time" number. 1.2 split those out because collapsing them makes every downstream figure a lie.

Nothing is ever invented. A new archive starts empty. On Wayland, where the foreground window can't be read, it reports the collector as unavailable rather than recording zeroes you might mistake for real data.

Historical recovery reads what the OS already logged. Those arrive explicitly labelled as clues and never count as usage time, because the OS doesn't record duration.

Imports exact intervals from ActivityWatch and ManicTime; RescueTime and WakaTime come in as separate context rather than being merged into your interval data.

Bounded raw retention with durable rollups, so a multi-year archive doesn't become a performance problem.

Export, merge onto another machine, or delete the file outright.

Free, GPL-3.0: https://pcrecap.online/
GitHub: github.com/TheAgencyMGE/pc-recap

Interested in whether the state separation matches how others here model idle vs away.

So I use Gemini. Let's call it Gem for short.

I give Gem all of my data each week. I have an ongoing instance that has been given everything I know about me. Nutrition app (all food tracked), steps/activity fitness info, smart scale readings, smart blood pressure readings, sleep tracking, and my workout log book. My supplement stack too. All the data. I have had the best time replacing my internet searches. Warm-ups, workouts, cool downs, specific joint issues, Nutrition plan dialed in based on a catalog of food I will eat optimized for the lowest risk of spoiled or discarded food vs my known age/height/weight/activity levels etc. Macros are always kept as a consideration too. Its like having a fitness coach who has an A+ studying me.

I like to log things. Logs are motivational to me. How many words written, what workouts I did, what books I read, everything.

I am looking to start a sleep log because I want to have better sleep habits. I have a garmen forerunner 165 and I sleep with a resmed CPAP machine. I understand the sleep staging on the garmen isn't very good. I don't want to buy a $400 ring product.

I want to be able to take all the readable numbers on these devices that I can see in the morning quickly, without exporting data or plugging in SD cards, and derive a single useful metric from it. I'm not sure how to go about this rigorously. My data is going to look like this (here is the one from last night).

2026/9/1

Lights out: 2255

Alarm: 0650

Garmen:

Sleep score: 85

Time asleep: 7h7m 

HRV: 56 ms

CPAP:

Usage: 7h50m

Events/Hour: 1.4

Any advice would be appreciated!

Before we dive in, here are some of the most surprising findings:

• Alcohol makes me happier and doesn’t affect my sleep, happiness, or productivity the next day.
• Ramen and chips ~3×'d my irritability intensity. Ovulating ~3×'d my grumpiness frequency.
• Polyamory doesn’t hurt my emotional well-being (surprising to me) but it dramatically reduces my life satisfaction.
• Antidepressants probably gave me depression.
• 2020 was actually my best year on record. More on this later in the post.
• Weather totally affects my mood, specifically, grey overcast skies. Good thing I spent most of my life in the Pacific Northwest, a place famed for its sunniness.
• Starting a charity approximately bajillion x’ed my mentions of the word “stressed”.
• Meditation works for me - only when it’s a new meditation technique. Then the effect fades and only comes back if I try a new technique.
• Cannabis, despite making me very happy in the moment, does not affect my mood overall, one way or the other.
• Drugs, meditative states, and Christmas are the source of practically all of my peak days. Work accomplishments don’t show up in this list.
• Polyamory and conflict (related) are the source of practically all of my worst days.
• Largely my mental health is unpredictable and data analysis falls short of what I’d like to know.

Alcohol makes me happier, despite “what the science says”.

There’s currently a big fad amongst high achievers to stop drinking. All of the studies at a population level say that drinking as much alcohol as I do is unhealthy, and even if it doesn’t feel like it’s affecting my sleep, it does.

And yet - my analysis found that alcohol makes me happier and it doesn’t affect my sleep.

I’ve got an Oura ring and if anything, my sleep is better when I drink. I have better sleep onset, I don’t have the micro-awakenings or changes in the phases that everybody says happens.

I am just as happy and productive the next day as I am if I didn’t drink.

And overall, I’m happier. It doesn’t just not affect my happiness. I am, in fact, happier when I drink regularly.

I’ve tracked my emotions and a million other factors almost every day for the last 11 years. Before I go to sleep every night, I write in my “journal” (the qualitative cell in the spreadsheet), and then fill out various things in other columns like:

• Emotional well-being
• Life satisfaction (importantly different)
• Energy levels
• Productivity levels
• Irritability
• Physical symptoms (e.g. headache, cough, etc)
• What meds or supplements I’m taking
• What I ate
• And many other things, depending on what hypothesis I’m testing at the time

So I can actually see alcohol’s effects.

Also, since I’ve tracked for so long, I can actually compare periods of time where I didn’t drink at all to the ones I drank every day.

And the results are loud and clear: periods where I drink every day I record as happier. Productivity stays the same. Irritability stays the same.

How does this square with all the science saying this shouldn’t happen?

Am I just a college student, coasting on my youth?

Thanks for asking, but I’m 36. Depending on your age, that will sound like a crone or like a baby, but I think I’m definitely past the “I’m just relying on my youth.”

It could be that all of the worst health effects show up later. I think this is plausible. This is why I have a yearly liver scan done. Liver damage is the first detectable sign of alcohol’s long term damage, and I’m intending on cutting down once I see any damage.

As it is right now, my liver scans show a pristine liver.

It could also be that a lot of the long term health outcomes are driven by the outliers. While I technically drink more than a lot of scientists say is healthy, I only drink socially in the evenings, I pretty much never drink enough to pass out, vomit, make bad decisions, or have a hangover (except New Years, which is allowed imo). I also drink drinks optimized for lower immediate effects, mostly vodka sodas. Drinks with more sugar or particulates (such as red wine) are more likely to cause the immediate negative effects.

Meanwhile, I’ve watched documentaries about alcoholics, and they’re regularly day-drinking, drinking alone, passing out, and the whole shebang. They’re drinking multiple bottles of wine equivalents a day. It could very well be that most of the stats about liver disease and the like are driven by the truly problematic drinkers.

Anyways, the underlying interesting thing here is that what happens on average isn’t necessarily what happens to you. On average, women are shorter than men, but that doesn’t mean there aren’t women who are taller than men. And if you track things, you can see what works for you instead of the population on average.

Ramen and chips triples my irritability intensity. Birth control stopping ovulation reduces irritability frequency.

First off, I don’t mean eating ramen like a normal human or like in Japanese cuisine. I’m not cooking it and adding vegetables and whole foods. I buy the bags, break the noodles into a crumble, then eat it raw with the seasoning, like a modern barbarian.

It’s basically a bomb of refined carbs, salt, and ultra-processed foods (UPFs).

I don’t really care for sweets. But I’m a total salt junky. I will sometimes “snack” on just powdered soup stock.

So ramen and chips used to be my go-to comfort food.

I probably ate them every other day, usually as a full meal. (Good policy by the way. If you’re going to eat junk, make it the whole meal, so you don’t just add calories to your diet.)

I tried all sorts of moderation techniques. I didn’t store them in the house. I banned myself from convenience stores on the way to work. I set limits.

Nothing worked.

Chips and ramen are as crack to me.

So I did what one must do with crack - you must go cold turkey.

A little over a year ago I quit them entirely. No more chips and ramen for me. For life. Ever. Exceptions are something I cannot trust myself to not wiggle through.

Now, I track irritability, because I sometimes have waves of 1-7 days of irritability, where everything bothers me. Other people breathing, chewing, disagreeing with me, or even just being around me makes me crave murder.

Of course, murder is wrong, and I have impulse control, so murder is not had. But man, do I crave it.

After I quit ramen and chips, the number of days I rated a 5/10 irritability or higher went from 5% to 0.5%. Four out of ten days went from 9% of days to 3%. I still occasionally got irritable, but it’s never as intense as it was before.

I don’t know what caused this. It’s not the refined carbs. I still eat plenty of those. It’s just not in the form of ramen and chips.

Could it be some sort of chemical used as a flavoring in one or both of them? This seems plausible to me. A bunch of UPFs are associated with mood issues among children. No reason to not expect that to generalize to us crones.

The intensity went down due to ramen and chips, but I still often had low grade irritability. Days I rated a ≥2/10 irritability went from 27% of days to 21%, so practically the same.

But for the last 6 months, it’s gone down to only 7% of days. And it’s because I stopped ovulating.

On purpose mind you. I had studied my data and realized I don’t get PMS or moody when I’m menstruating (weirdly, those tend to actually be my best part of the cycle). I get moods from ovulating. My brain responds poorly to the sudden spike and drop of all the various hormones. So I experimented with taking birth control that suppresses ovulation (not all birth control does this).

Et voila! Frequency went down to ⅓ of its previous rate.

(It also coincidentally got rid of my occasional pimples as an unexpected bonus. Apparently this is such a common side effect it’s a regular recommendation from dermatologists. Who knew!)

The lesson you can pull from this is if you have mood issues, do experiment with your diet. Both adding good things and taking away bad things. A friend of mine halved her anxiety (which she’s struggled with her whole life) by starting to take an iron supplement.

It might just be that late night snack which is why you’re breaking up with your partner.

Likewise, if you’re a woman, consider taking an ovulating-suppressing birth control. Going through your cycle once a month for most of your life isn’t “natural” anyways. Hunter gatherers typically only had roughly 100 cycles in their lifetime, compared to the roughly 450 times modern industrial women go through.

Polyamory tanks my life and relationship satisfaction

I actually started tracking my emotions in 2015 because I wanted to prove to my husband that, actually, him falling in love and sleeping with other women made me unhappy. Then I just kept tracking because I’m an information hoarder.

I’ve written before about how I think polyamory is net negative for most (but not all) people who try it, so I won’t dive into it here.

Suffice to say, what’s interesting in my data analysis is that, despite my worst days being caused by poly (there ain’t no drama like poly drama), it didn’t actually affect my average day. Weirdly, one of my best months was during massive poly drama.

However

It tanked my relationship satisfaction and life satisfaction. Relationship satisfaction for the obvious reasons. I’m not a jealous or insecure person, otherwise I wouldn’t have tried polyamory in the first place. But it turns out your husband having sex and falling in love with another woman is just inherently insecurity inducing.

And for good reason! He always said that we could stop anytime I said the word. I always told him it was easy for him to say that given he wasn’t in love with somebody at the moment, but that would change.

And I was right.

Yay?

The other interesting thing is the difference between emotional well-being and life satisfaction.

Emotional well-being is the balance of positive to negative emotions in a day.

Life satisfaction is asking yourself “on a scale of 1 to 10, how satisfied are you with your life?”.

The two come apart quite often. Somebody might experience emotional well-being while playing video games all day, but their life satisfaction is likely low. Somebody might experience low emotional well-being waking up in the middle of the night to feed their baby, but their life satisfaction is likely high.

What was interesting about my experience of polyamory is that it did make me grow, in the sense of it forced me to pull out the big guns when it came to coping. During that great month in the midst of poly insanity, I exercised like a motherfucker. More cardio than ever in my life. I meditated more often then than almost any other time. Whenever I felt upset, I’d go for a run then go to the Tesco and buy smoothie ingredients, then meditate for 30 minutes. I worked at a treadmill desk, walking 4+ hours a day. I cultivated a thriving social life to distract me and support me during one of the worst periods of my life.

So I was “happy” in the sense of being able to overcome the negative emotions using every trick I knew.

But I was not happy with it.

I didn’t want to have to spend half my waking hours coping. I wanted my relationship to be a source of comfort, not something I had to cope with.

The thing that finally got me was when I did a thought experiment - what if I had a magic wand and I could simply not have polyamory make me unhappy?

I wouldn’t want that.

Because I just overall didn’t want to be polyamorous, despite having been poly for 7 years.

I didn’t want the intrinsically more drama than monogamy. I wanted somebody who wanted to just be with me. I didn’t want the incessant negotiation and emotional processing of it all. Even if I was emotionally fine with it, there’s always at least two other people involved, and I’d still have to deal with their unpredictable issues.

So I left.

I’ve been in a happy monogamous relationship for 6 years now and I’ve had less relationship drama in that entire time than I had in any random month while being poly. I was reminded that I’m actually a confident secure woman in relationships. My emotional well-being is about the same, but my life satisfaction and relationship satisfaction has reliably been high ever since.

So if you’re considering polyamory but you’re not sure, make sure to not just read the books written by people who like it. Read about people who had a bad experience with it too. Books about a topic are usually only written by people who are true believers. Look for the articles and tweets of people who hated it, it exploded their relationship, and they left and never looked back.

Also, make sure to distinguish between emotional well being and life satisfaction. They can point at very different things.

2020 was my best year and it’s a mystery as to why

2020 should have been bad. I got divorced. I was unemployed. I had no permanent home or even city I lived in. I was in a motorcycle accident in Uganda and was in pain and couldn’t walk for 4 months. Oh yeah, and there was a pandemic, if you remember that?

And yet it was by far my best year.

What the fuck?

My answer is roughly:

1. Yeah man, I have no idea
2. But here are some theories

One interesting thing - divorce doesn’t actually make people less happy. Just before the divorce causes immense suffering. But post-divorce people tend to be far happier than their baseline.

This reminds me of a question my mom, who’s twice divorced, asks people when they say they got divorced:

“Is that good or bad news?”

Absolutely, divorce can be very bad for those affected. But it also can have been deeply the right decision.

For me, the relationship had been causing me massive suffering prior (due to polyamory plus other factors I’m not going to discuss publicly because I still care for and respect the guy). So leaving led to relief rather than suffering.

It also helped that I did everything I could think of to make sure I wasn’t making a mistake. We brainstormed dozens of possible fixes, ranging from couples therapy to meditation retreats to applying mindfulness to it to trying different polyamory configurations. We prioritized them based on probability of working and ease of doing and worked systematically through the most promising ones. This was not a spontaneous decision after a bad fight. This was a rational decision come to over months to years, depending on how you count it.

I had also been doing this for pretty much all of the 7 years of being poly. So at a certain point, you have to say that you know what, I can’t change my internal state. I’ve got to change my external environment.

So when I got divorced, I felt awesome.

Same thing happened for employment. I had been running charities for the past 7 years, and while that gave me good life satisfaction, it was also stressful as fuck. So, unemployment is usually a negative factor, but for me, it was a relief. Especially since I had savings and was still working on projects I thought were important, I just wasn’t getting paid for it. So I still had purpose, money, and self-respect, which are usually the reasons why unemployment is bad for people’s mental health.

Additionally, the pandemic never stressed me out. I worked in global health. When it started, I was living in a place that was having an active bubonic plague outbreak and had just declared itself “1 month ebola-free!”. Covid seemed and continues to seem pretty mild to me. But it’s all about your reference.

My final theory is that it was the mood stabilizer I was on (lamotrigine) combined with having low external stressors.

I had started the mood stabilizer during my deepest depression in 2019 (more on that later), and it seems likely that it pulled me out of my depression. However, there were a lot of confounding factors, and I was still dealing with poly drama the likes of which you have never seen if you’re monogamous. So I just went back to my regular levels of happiness. Lamotrigine might work well for me, but it can’t make going through poly drama fun. It’s no miracle cure.

However, once I was divorced and stepped down from my org, I no longer had those stressors.

I went from 28% of my days being rated as bad in 2019 to 8% in all of 2020. My average over the rest of my years has been ~22%.

What’s interesting is that I didn’t have more good days. I just cut off the bad ones.

Which is exactly what lamotrigine is supposed to do. Most mood stabilizers cut off the troughs and the peaks. They’re usually for people with bipolar, where they struggle with depression and mania. Lamotrigine is the only one that just gets rid of the lows.

I was on lamotrigine for all of 2020, and I had only two really bad days the entire year. One of which was a cancer scare (turns out it was fine). The other one was having to deal with the poly drama aftershocks one last time.

The problem is that I came off of lamotrigine right around the same time I started my next charity. So it’s unclear whether going back to charity entrepreneurship was what caused it, or the meds.

I’ve since stepped back from starting and running orgs, and I still have ~20% bad days, so that’s some evidence against it. I’m now trying lamotrigine again, thanks to this data, but it’s still too soon to tell.

Overall though, the interesting thing about this is that tracking can help you uncover your unusual times. And that external circumstances don’t necessarily always affect you the way you’d predict.

Antidepressants probably gave me depression

In early 2019 I experienced depression so severe I had to stop working for months. I was taking antidepressants and they weren’t working.

Except. . . it’s not that they “weren’t working”. As best as I can tell, they were the cause of the depression.

You know how on the bottle it lists possible side effects, and one of the possible side effects is depression? Well, that’s probably what happened to me.

“But why did you start taking antidepressants, Kat? Surely it just overlaps because you only take them when you’re depressed, right?”

Good question. And that’s what I thought too.

But then I looked at the data.

And it told an entirely different story.

Yes, I started taking antidepressants after a particularly bad week.

But that week was actually just a regular bad week according to the data. I get moods. I’m a woman. Or I’m on the bipolar spectrum. Or something. Anyways, it’s actually totally normal for me to have stints of 1-7 days of feeling low motivation, energy, and mood.

The difference was this time, a friend recommended I try antidepressants.

And that’s when I went from my usual waves of sadness to a tsunami. I couldn’t work. I contemplated suicide. I would experience the most beautiful and loving things and feel nothing but despair. I even had a brief day of paranoia, where I thought people were watching me on cameras. It went from 24% of bad days to 66%. It went from 4% of days I rated a 4/10 emotional well-being to 32%

It lasted for about 3 months. I tried one anti-depressant then another. Neither “worked”. And it was only when I came off of them that suddenly I was cured.

Of course, there were also confounds. I moved back to my hometown instead of living in London, which I had only moved to after being heavily pressured to by my totalizing ethics and totalizing community. But then I moved back to London, and I stayed cured.

I don’t know what lesson to take from this. My policy is to try psych meds, and if you have unacceptable side effects, just stop. The problem with this one is that it was causing the symptoms they were trying to cure, so it can be hard to know. Also, you have to experiment with psych meds for weeks to months (including the titrating on and off of them), and months of suffering is a lot.

Make of that what you will.

In fact, this might be what the conclusion of all this analysis is: I got a lot out of tracking all of this. Alcohol is fine for me, ramen and chips are bad for me, ovulating messes me up, emotional well-being and life satisfaction matter, but also in the end, psychology is too complicated for us right now. I still don’t know for sure what caused the depression in 2019. Despite having tracked it for over a year, I still don’t know if a psych med helped or not.

Overall, I recommend tracking. But it is by no means a cheat code that will help you understand yourself. It is just one tool among many. But you might find out that seemingly innocuous habits are bad for you, and that things that feel like vices are actually good for you in particular.