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</head><body><h2 id="home"><a href="./index.html">home</a></h2>
<p><em>author: niplav, created: 2023-01-06, modified: 2024-10-17, language: english, status: maintenance, importance: 3, confidence: likely</em></p>
<blockquote>
<p><strong>Modeled after <a href="https://www.gwern.net/Nootropics">Gwern 2018</a> I've
decided to log my nootropics usage and its effects.</strong></p>
</blockquote><div class="toc"><div class="toc-title">Contents</div><ul><li><a href="#Caffeine">Caffeine</a><ul><li><a href="#Experiment_A_SelfBlinded_RCT">Experiment A: Self-Blinded RCT</a><ul><li><a href="#Statistical_Method">Statistical Method</a><ul></ul></li><li><a href="#Predictions_on_the_Outcomes_of_the_Experiment">Predictions on the Outcomes of the Experiment</a><ul></ul></li><li><a href="#Analysis">Analysis</a><ul><li><a href="#Summary_Statistics">Summary Statistics</a><ul></ul></li></ul></li><li><a href="#Conclusion">Conclusion</a><ul></ul></li></ul></li><li><a href="#Discussions">Discussions</a><ul></ul></li><li><a href="#See_Also">See Also</a><ul></ul></li></ul></li><li><a href="#Creatine">Creatine</a><ul></ul></li><li><a href="#LTheanine">L-Theanine</a><ul><li><a href="#Experiment_B_SelfBlinded_RCT">Experiment B: Self-Blinded RCT</a><ul><li><a href="#Conclusion_1">Conclusion</a><ul></ul></li></ul></li><li><a href="#Discussions_1">Discussions</a><ul></ul></li></ul></li><li><a href="#Melatonin">Melatonin</a><ul><li><a href="#Effects">Effects</a><ul><li><a href="#Reducing_Sleep_Duration">Reducing Sleep Duration</a><ul></ul></li></ul></li><li><a href="#Takeaway">Takeaway</a><ul></ul></li></ul></li><li><a href="#Nicotine">Nicotine</a><ul></ul></li><li><a href="#Vitamin_D">Vitamin D₃</a><ul><li><a href="#Experiment_C_SelfBlinded_RCT">Experiment C: Self-Blinded RCT</a><ul></ul></li></ul></li><li><a href="#See_Also_1">See Also</a><ul></ul></li><li><a href="#Appendix_A_Predictions_on_SelfBlinded_RCTs">Appendix A: Predictions on Self-Blinded RCTs</a><ul></ul></li><li><a href="#Appendix_B_The_Code_for_Analyzing_The_Caffeine_Data">Appendix B: The Code for Analyzing The Caffeine Data</a><ul><li><a href="#Meditation">Meditation</a><ul></ul></li><li><a href="#Productivity_and_Creativity">Productivity and Creativity</a><ul></ul></li><li><a href="#Mood">Mood</a><ul></ul></li><li><a href="#Flashcards">Flashcards</a><ul></ul></li><li><a href="#Likelihood_Ratios">Likelihood Ratios</a><ul></ul></li></ul></li></ul></div>
<h1 id="Nootropics"><a class="hanchor" href="#Nootropics">Nootropics</a></h1>
<!--Nootropics and meditation:
*Caffeine
* https://skemman.is/handle/1946/41957
* Maybe https://www.frontiersin.org/articles/10.3389/fpsyg.2020.610156/full accidentally reveals some info on caffeine effect on mindfulness? But probably not.
* Caffeine & L-Theanine
* http://cafeesaude.com/wp-content/uploads/2012/01/Humor-J-Bryan-et-al-Appetite-Volume-58-2012.pdf
* L-Theanine
* https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=6899536c95f528308ab27810cfd17f4ba3a96d9e
-->
<p>You could put randomized substances in your body and find out what they
do by recording the outcomes. That's what I did.</p>
<!--TODO: color for effect size?-->
<table>
<thead>
<tr>
<th>Value tracked</th>
<th>Effect size <a href="https://en.wikipedia.org/wiki/Effect_size#Cohen's_d">d</a> (<a href="https://en.wikipedia.org/wiki/Likelihood-ratio_test#General">λ</a>, <a href="https://en.wikipedia.org/wiki/P-Value">p</a>, <a href="https://en.wikipedia.org/wiki/Standard_Deviation">σ</a> change, <a href="https://en.wikipedia.org/wiki/Sample_size">k</a><sup id="fnref1"><a href="#fn1" rel="footnote">1</a></sup>)</th>
<th>Effect size d (λ, p, σ change, k)</th>
</tr>
</thead>
<tbody>
<tr>
<td></td>
<td><em>200 mg Caffeine (n=1<sup id="fnref2"><a href="#fn2" rel="footnote">2</a></sup>, m=50<sup id="fnref3"><a href="#fn3" rel="footnote">3</a></sup>)</em></td>
<td><em>500 mg L-theanine (n=1, m=50)</em></td>
</tr>
<tr>
<td>Log-score substance prediction<sup id="fnref4"><a href="#fn4" rel="footnote">4</a></sup></td>
<td>-0.6</td>
<td>-0.7</td>
</tr>
<tr>
<td>Absorption</td>
<td>0.61 (λ≈13.3, p≈0.00017, -0.072, 50)</td>
<td>0.04 (λ≈1.38, p≈0.77, -0.07, 50)</td>
</tr>
<tr>
<td>Mindfulness</td>
<td>0.58 (λ≈11.8, p≈0.0007, 0.021, 50)</td>
<td>0.12 (λ≈0.72, p≈0.89, -0.018, 50)</td>
</tr>
<tr>
<td>Productivity</td>
<td>0.58 (λ≈28.9, p≈1.3<sup>-12</sup>, 0.11, 50)</td>
<td>-0.28 (λ≈5.51, p≈0.109, 0.03, 50)</td>
</tr>
<tr>
<td>Creativity</td>
<td>0.45 (λ≈51, p≈4.6<sup>-27</sup>, 0.09, 50)</td>
<td>-0.12 (λ≈5.05, p≈0.14, -0.04, 50)</td>
</tr>
<tr>
<td>Happiness</td>
<td>0.27 (λ≈10.6, p≈0.002, 0.3, 161)</td>
<td>0.16 (λ≈3.98, p≈0.27, -0.155, 201)</td>
</tr>
<tr>
<td>Contentment</td>
<td>0.13 (λ≈7.66, p≈0.02, 0.47, 161)</td>
<td>0.25 (λ≈6.83, p≈0.04, -0.04, 201)</td>
</tr>
<tr>
<td>Relaxation</td>
<td>-0.11 (λ≈5, p≈0.15, 0.42, 161)</td>
<td>0.12 (λ≈1.5, p≈0.74, 0.02, 201)</td>
</tr>
<tr>
<td>Horniness<sup id="fnref5"><a href="#fn5" rel="footnote">5</a></sup></td>
<td>-0.14 (λ≈1.9, p≈0.64, 0.11, 161)</td>
<td>-0.03 (λ≈1.15, p≈0.8, 0.25, 201)</td>
</tr>
<tr>
<td>Subjective length of day</td>
<td>Not collected</td>
<td>-0.015 (λ≈0.35, p≈0.95, -0.015, 21)</td>
</tr>
<tr>
<td>Flashcard ease</td>
<td>0.003 (λ≈∞, p≈0, -0.009, 10949)</td>
<td>-0.072 (λ≈∞, p≈0, -0.01, 10248)</td>
</tr>
<tr>
<td>Flashcard ease factor</td>
<td>-0.039 (λ≈∞, p≈0, -32.7, 10949)</td>
<td>0.0026 (λ≈∞, p≈0, -18.9, 10248)</td>
</tr>
<tr>
<td>Flashcard new interval</td>
<td>0.011 (λ≈∞, p≈0, -1.88, 10949)</td>
<td>-0.016 (λ≈∞, p≈0, 3.1, 10248)</td>
</tr>
<tr>
<td>Time per flashcard<sup id="fnref6"><a href="#fn6" rel="footnote">6</a></sup></td>
<td>0.006 (λ≈∞, p≈0, 273.4, 10949)</td>
<td>0.003 (λ≈∞, p≈0, 13.66, 10248)</td>
</tr>
</tbody>
</table>
<p>I am especially interested in testing many different substances for their
effect on meditation, while avoiding negative side effects. The benefits
from high meditational attainments seem valuable to me, and could be
especially likely to benefit from chemical intervention, since the
<a href="https://gwern.net/drug-heuristic#loopholes">Algernon argument</a>
likely doesn't apply: Meditative attainments might've
not led to a fitness advantage (even, by <a href="https://en.wikipedia.org/wiki/Opportunity_cost">opportunity
cost</a>, to a fitness
disadvantage), and so were likely selected against, but most of us
don't care <em>that</em> much about inclusive genetic fitness and more about
psychological well-being. Evolutionary dynamics favor being like <a href="https://en.wikipedia.org/wiki/Ghenghis_Khan">Ghengis
Khan</a> (<a href="https://en.wikipedia.org/wiki/Family_and_descendants_of_Genghis_Khan">dozens to hundreds of
offspring</a>)
over <a href="https://en.wikipedia.org/wiki/Siddharta_Gotama">Siddharta Gautama</a>
(<a href="https://en.wikipedia.org/wiki/R%C4%81hula">one son</a>), but I'd rather
attain <a href="https://en.wikipedia.org/wiki/Sot%C4%81panna">sotāpanna</a> than
pillage and murder.</p>
<p>And meditative attainments are <em>costly</em>: they take tens to
hundreds to thousands of hours to reach, which would make simple
psychopharmacological interventions worthwhile. I also don't buy
that they miss the point of meditation—most people already struggle
enough, so some help doesn't make it a cakewalk; <a href="https://pastebin.com/xuVuVnhw">"reach heaven through
fraud"</a>. One must be careful not to fall
into the trap of taking substances that feel good but lessen sensory
clarity (which I believe was the original intent behind the <a href="https://en.wikipedia.org/wiki/Five_precepts#Fifth_precept">fifth
precept</a>,
and so I'll exclude e.g. opiates from the substances to test).</p>
<h2 id="Caffeine"><a class="hanchor" href="#Caffeine">Caffeine</a></h2>
<p>I won't dig too deep into the effects of caffeine, as other people have
done that already (<a href="https://examine.com/supplements/caffeine/">Examine</a>,
<a href="https://gwern.net/nootropic/nootropics#caffeine">Gwern</a>,
<a href="https://en.wikipedia.org/wiki/Caffeine">Wikipedia</a>).</p>
<h3 id="Experiment_A_SelfBlinded_RCT"><a class="hanchor" href="#Experiment_A_SelfBlinded_RCT">Experiment A: Self-Blinded RCT</a></h3>
<p>Variables tracked (see more <a href="./data.html">here</a>):</p>
<ul>
<li><strong>Arm Prediction</strong>: I tried to predict whether the substance I'd taken was placebo or caffeine.</li>
<li>Meditation: 45 minutes of ānāpānasati, started 0-60 minutes after taking the dose, tracking two variables.
<ul>
<li><strong>Mindfulness</strong>: How aware I was of what was going on in my head, modulo my ability to influence it.</li>
<li><strong>Absorption</strong> (often called concentration): How "still" my mind was, how easily I was swept away by my thoughts.</li>
</ul></li>
<li><strong>Productivity</strong> and <strong>creativity</strong>, recorded at the end of the day.</li>
<li><a href="./data.html#Mood">Mood</a>: Tracking 4 different variables at random points during the day, namely
<ul>
<li><strong>Happiness/Sadness</strong></li>
<li><strong>Contentment/Discontentment</strong></li>
<li><strong>Relaxation/Stress</strong></li>
<li><strong>Horniness/Chastity</strong>: Chastity being simply the opposite of horniness in this case.</li>
</ul></li>
<li><strong>Flashcard performance</strong>: Did my daily flashcards for ~20 minutes, started 0-60 minutes after finishing meditation. More explanation <a href="./data#Anki">here</a>
<ul>
<li><strong>Ease</strong>: How easy I remembered the card (1: not at all, 4: baked into the memory).</li>
<li><strong>New ease factor</strong>: How much the card will be pushed into the future if I answer it correctly next time.</li>
<li><strong>New interval</strong>: How far the card has been pushed into the future.</li>
<li><strong>Time</strong>: How long I spent on the card.</li>
</ul></li>
</ul>
<p>The total cost of the experiment is at least 21.5€:</p>
<ul>
<li>Time: The <a href="https://programs.clearerthinking.org/what_is_your_time_really_worth_to_you.html">Clearer Thinking tool</a> for the value of my time returns 15€/hour, which gives a time cost of 18.75€ for preparing the experiment.
<ul>
<li>Time for filling: 35 minutes</li>
<li>Time for preparing envelopes: 40 minutes</li>
</ul></li>
<li>Cost of caffeine pills: <code>$\frac{0.0825€}{\text{200mg caffeine pill}} \cdot \text{ 200mg caffeine pills}=2.0625€$</code></li>
<li>Cost of empty capsules: <code>$\frac{0.03€}{\text{capsule}} \cdot 25 \text{ capsules}=0.75€$</code></li>
<li>Cost of sugar: Negligible.</li>
</ul>
<p>200mg caffeine pills, placebo pills filled with sugar, of each 25.
Put each pill with a corresponding piece of paper ("C" for caffeine,
"P" for placebo) into an unlabeled envelope. Used <code>seq 1 50 | shuf</code>
to number the envelopes, and sorted them accordingly.</p>
<p>Notes on the experiment:</p>
<ul>
<li>3rd dose: Out of fear that the placebo pills have some sugar stuck
outside of them, which could de-blind the dose, I take a bit (~10 g)
of sugar with each pill.</li>
<li>7th dose: Increase time between consumption and starting to meditate to
~45 minutes, after finding out that the onset of action is 45 minutes-1
hour.</li>
<li>14th dose: Noticed that during meditation, sharpness/clarity of
attention is ~high, and relaxing after becoming mindful is easy, but
attention strays just as easily.</li>
<li>49th dose: Took the pill, meditated, lay down during meditation and fell asleep. Likely placebo<sub>90%</sub>.</li>
</ul>
<h4 id="Statistical_Method"><a class="hanchor" href="#Statistical_Method">Statistical Method</a></h4>
<p>In general, I'll be working with the <a href="https://en.wikipedia.org/wiki/Likelihood-ratio_Test">likelihood ratio
test</a> (encouraged by
<a href="https://arbital.com/p/likelihoods_not_pvalues/">this article</a>). For
this, let <code>$\mathbf{v}_P$</code> be the distribution of values of a
variable for the placebo arm, and <code>$\mathbf{v}_C$</code> the distribution
of values for a variable of the caffeine arm. (I apologise for the
<code>$C$</code> being ambiguous, since it could also refer to the <a href="https://en.wikipedia.org/wiki/Control_arm">control
arm</a>).</p>
<p>Then let <code>$\theta_0=(\mu_0, \sigma_0)=MLE_{\mathcal{N}}(\mathbf{v}_P)$</code>
be the Gaussian <a href="https://en.wikipedia.org/wiki/Maximum_likelihood_estimation">maximum likelihood
estimator</a>
for our placebo values, and
<code>$\theta=(\mu, \sigma)=MLE_{\mathcal{N}}(\mathbf{v}_C)$</code>
be the MLE for our caffeine values.</p>
<p>Then the likelihood ratio statistic <code>$\lambda$</code> is defined as</p>
<div>
$$\lambda=2 \log \frac{\mathcal{L}_C(\theta)}{\mathcal{L}_C(\theta_0)}$$
</div>
<p>where <code>$\mathcal{L}_C(\theta)$</code> is the likelihood the caffeine
distribution assigns to the parameters <code>$\theta$</code>. This test is useful
here because we fix all values of <code>$\theta_0$</code>. See <a href="https://www.goodreads.com/book/show/411722.All_of_Statistics">Wasserman 2003
ch. 10.6</a>
for more.</p>
<p>If <code>$\lambda \approx 0$</code>, then the MLE for the placebo arm is very close
to the MLE for the caffeine arm, the distributions are similar. If
<code>$\lambda>0$</code>, then the MLE for the placebo arm is quite different from
the caffeine arm (though there is no statement about which has <em>higher</em>
values). <code>$\lambda<0$</code> is not possible, since that would mean that
the MLE of the placebo distribution has a higher likelihood for the
caffeine data than the MLE of the caffeine distribution itself—not
very likely<!--TODO: sunglasses emoji?-->.</p>
<p>Note that I'm not a statistician, this is my first serious statistical
analysis, so please correct me if I'm making some important
mistakes. Sorry.</p>
<h4 id="Predictions_on_the_Outcomes_of_the_Experiment"><a class="hanchor" href="#Predictions_on_the_Outcomes_of_the_Experiment">Predictions on the Outcomes of the Experiment</a></h4>
<p>After collecting the data, but before analysing it,
I want to make some predictions about the outcome
of the experiment, similar to another attempt
<a href="./range_and_forecasting_accuracy.html#Some_Predictions_About_The_Results">here</a>.</p>
<p>Moved <a href="#Caffeine_1">here</a>.</p>
<h4 id="Analysis"><a class="hanchor" href="#Analysis">Analysis</a></h4>
<p>We start by setting everything up and loading the data.</p>
<pre><code>import math
import numpy as np
import pandas as pd
import scipy.stats as scistat
substances=pd.read_csv('../..//data/substances.csv')
meditations=pd.read_csv('../../data/meditations.csv')
meditations['meditation_start']=pd.to_datetime(meditations['meditation_start'], unit='ms', utc=True)
meditations['meditation_end']=pd.to_datetime(meditations['meditation_end'], unit='ms', utc=True)
creativity=pd.read_csv('../../data/creativity.csv')
creativity['datetime']=pd.to_datetime(creativity['datetime'], utc=True)
productivity=pd.read_csv('../../data/productivity.csv')
productivity['datetime']=pd.to_datetime(productivity['datetime'], utc=True)
expa=substances.loc[substances['experiment']=='A'].copy()
expa['datetime']=pd.to_datetime(expa['datetime'], utc=True)
</code></pre>
<p>The mood data is a bit special, since it doesn't have timezone info,
but that is easily remedied.</p>
<pre><code>mood=pd.read_csv('../../data/mood.csv')
alarms=pd.to_datetime(pd.Series(mood['alarm']), format='mixed')
mood['alarm']=pd.DatetimeIndex(alarms.dt.tz_localize('CET', ambiguous='infer')).tz_convert(tz='UTC')
dates=pd.to_datetime(pd.Series(mood['date']), format='mixed')
mood['date']=pd.DatetimeIndex(dates.dt.tz_localize('CET', ambiguous='infer')).tz_convert(tz='UTC')
</code></pre>
<p>This data can now be plotted unwieldly:</p>
<p><img alt="" src="./img/nootropics/caffeine_results.png"/></p>
<h5 id="Summary_Statistics"><a class="hanchor" href="#Summary_Statistics">Summary Statistics</a></h5>
<p>We can first test how well my predictions fared:</p>
<pre><code>probs=np.array(expa['prediction'])
substances=np.array(expa['substance'])
outcomes=np.array([0 if i=='sugar' else 1 for i in substances])
</code></pre>
<p><em>drumroll</em></p>
<pre><code>>>> np.mean(list(map(lambda x: math.log(x[0]) if x[1]==1 else math.log(1-x[0]), zip(probs, outcomes))))
-0.5991670759554912
</code></pre>
<p>At least this time I was better than chance:</p>
<pre><code>>>> np.mean(list(map(lambda x: math.log(x[0]) if x[1]==1 else math.log(1-x[0]), zip([0.5]*40, outcomes))))
-0.6931471805599453
</code></pre>
<p>After <a href="#Appendix_B_The_code_for_Analyzing_The_Caffeine_Data">finishing the coding for this
experiment</a>,
I decided it'd be easier if for the future I could call a single
function to analyze all my data for me. The result can be found
<a href="./code/experiment/load.py">here</a>, the function is
<code>analyze(experiment, substance, placebo)</code>.</p>
<p>To analyze this specific experiment, I simply call
<code>caffeine_results=analyze('A', 'caffeine', 'sugar')</code> and get this nice
DataFrame:</p>
<pre><code> absorption mindfulness productivity creativity sublen happy content relaxed horny ease factor ivl time
d 0.698257 0.638603 6.397757e-01 5.115835e-01 NaN 0.270813 0.129624 -0.114858 -0.140795 -9.669700e-03 -4.105022e-02 1.270295e-02 8.172521e-03
λ 13.309889 11.791000 3.075927e+01 5.634296e+01 0.0 10.644193 7.660893 5.007775 1.964261 inf inf inf inf
p 0.000167 0.000724 1.053268e-13 7.030572e-31 NaN 0.002074 0.024625 0.150156 0.639840 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
dσ -0.072088 0.021868 1.073141e-01 9.825115e-02 NaN 0.295592 0.473630 0.415262 0.108356 -5.938866e-03 -3.267464e+01 -1.877563e+00 2.733943e+02
k 50.000000 50.000000 5.000000e+01 5.000000e+01 0.0 161.000000 161.000000 161.000000 161.000000 1.094900e+04 1.094900e+04 1.094900e+04 1.094900e+04
</code></pre>
<h4 id="Conclusion"><a class="hanchor" href="#Conclusion">Conclusion</a></h4>
<p>Caffeine appears helpful for everything except relaxation (and it <em>maybe</em>
makes me hornier, which I'm neutral about). I'd call this experiment a
success and will be running more in the future, while in the meantime
taking caffeine before morning meditations.</p>
<h3 id="Discussions"><a class="hanchor" href="#Discussions">Discussions</a></h3>
<ul>
<li><a href="https://www.lesswrong.com/posts/DQvuSBquC8ccwPhBo/self-blinded-caffeine-rct">LessWrong</a></li>
</ul>
<h3 id="See_Also"><a class="hanchor" href="#See_Also">See Also</a></h3>
<ul>
<li><a href="https://www.gleech.org/stims">Stimulant tolerance, or, the tears of things (Leech, 2020)</a></li>
<li><a href="https://mdickens.me/2024/03/02/caffeine_tolerance/">Avoiding Caffeine Tolerance (Dickens, 2024)</a>
<ul>
<li><a href="https://mdickens.me/2024/06/24/continuing_caffeine_self_experiment/">Continuing My Caffeine Self-Experiment (Michael Dickens, 2024)</a></li>
</ul></li>
</ul>
<h2 id="Creatine"><a class="hanchor" href="#Creatine">Creatine</a></h2>
<p><a href="https://examine.com/supplements/creatine/">Examine</a>. I
follow the loading procedure detailed
<a href="https://examine.com/supplements/creatine/#NJj4E2e-do-i-need-to-load-creatine">here</a>:</p>
<blockquote>
<p><a href="https://examine.com/supplements/creatine/">Creatine</a> is a supplement that is known for having a 'loading' phase followed by a 'maintenance' phase. A typical creatine cycle has three parts to it.</p>
<ul>
<li>Take 20-25g (or 0.3g/kg) for 5-7 days (Loading)</li>
<li>Then take 5g daily for 3-4 weeks (Maintenance)</li>
<li>Take a week or two off creatine, and then repeat (Wash-out)</li>
</ul>
</blockquote>
<p>First dose was taken on 2023-01-06.</p>
<p>I'm especially interested in the effects of
creatine on my cognition (it <a href="https://examine.com/supplements/creatine/">might increase IQ in
vegetarians</a>
(or it <a href="https://gwern.net/creatine">might not</a>?), and I'm a
<a href="https://en.wikipedia.org/wiki/Lacto-vegetarianism">lacto-vegetarian</a>),
my exercising performance and my meditation ability.</p>
<h2 id="LTheanine"><a class="hanchor" href="#LTheanine">L-Theanine</a></h2>
<blockquote>
<p>L-Theanine is synergistic with caffeine in regards to attention
switching<sup><a href="https://examine.com/supplements/caffeine/research/#ref-318">[318]</a></sup>
and
alertness<sup><a href="https://examine.com/supplements/caffeine/research/#ref-319">[319]</a><a href="https://examine.com/supplements/caffeine/research/#ref-320">[320]</a></sup>
and reduces susceptibility to distractions
(focus).<sup><a href="https://examine.com/supplements/caffeine/research/#ref-320">[320]</a><a href="https://examine.com/supplements/caffeine/research/#ref-320">[321]</a></sup>
However, alertness seems to be relatively subjective
and may not be a reliable increase between these two
compounds,<sup><a href="https://examine.com/supplements/caffeine/research/#ref-318">[318]</a></sup>
and increases in mood are either present or<!--TODO: correct?-->
absent.<sup><a href="https://examine.com/supplements/caffeine/research/#ref-322">[322]</a><a href="https://examine.com/supplements/caffeine/research/#ref-318">[318]</a><a href="https://examine.com/supplements/caffeine/research/#ref-323">[323]</a></sup>
This may be due to theanine being a relatively subpar
nootropic in and of itself pertaining to the above parameters,
but augmenting caffeine's effects; some studies do note
that theanine does not affect the above parameters in and of
itself.<sup><a href="https://examine.com/supplements/caffeine/research/#ref-324">[324]</a></sup>
Due to this, any insensitivity or habituation to caffeine would reduce
the effects of the combination as L-theanine may work through caffeine.</p>
<p>L-Theanine does not appear to be synergistic with caffeine
in regards to attention to a prolonged and monotonous
task.<sup><a href="https://examine.com/supplements/caffeine/research/#ref-325">[325]</a></sup>
<!--Foxe JJ, et al. Assessing the effects of caffeine and theanine on the maintenance of vigilance during a sustained attention task.--></p>
</blockquote>
<p><em>—Kamal Patel, <a href="https://examine.com/supplements/caffeine/research/#3JD9zlr-nutrient-nutrient-interactions_3JD9zlr-l-theanine">“Caffeine”</a>, 2023</em></p>
<p>See again <a href="https://examine.com/supplements/theanine/research/">Examine</a>,
<a href="https://en.wikipedia.org/wiki/Theanine">Wikipedia</a> and
<a href="https://gwern.net/Nootropics#L-Theanine">Gwern</a>.</p>
<p><a href="./doc/meditation/science/classification_of_human_brain_attention_focused_on_meditation_effected_by_l-theanine_acid_in_oolong_tea_srimaharaj_et_al_2018.pdf">Sitiprapaporn et al. 2018</a>
test the effect of an unspecified quantity of L-theanine via Oolong tea
on meditation on 10 university students (non-randomized, it seems). Data
collected via EEG and indicates statistically significantly more alpha
waves during meditation (although it is unclear how long the meditation
was).</p>
<p>This paper is bad. The english is so horrendous it feels like I'm having
a stroke while I'm reading it, but that would be fine if they were good
at reporting methods, which they are not (missing amounts of L-theanine
and duration of meditation, they also mention reading earlier in the
article, which I assumed was the control activity, but it doesn't come
up again?). Also they report differences between scores, not effect
sizes, and some figures are screenshotted images from a Windows Vista
clustering application.</p>
<p><a href="https://examine.com/supplements/theanine/research/">Examine</a> agrees on
the cognitive effects of l-theanine (if not on meditation specifically):</p>
<blockquote>
<p>L-Theanine supplementation in the standard dosages (50-250mg)
has been repeatedly noted to increase α-waves in otherwise healthy
persons. This may only occur in persons with somewhat higher baseline
anxiety<sup><a href="https://examine.com/supplements/theanine/research/#ref-25">[25]</a><a href="https://examine.com/supplements/theanine/research/#ref-26">[26]</a></sup>
or under periods of stress
(positive<sup><a href="https://examine.com/supplements/theanine/research/#ref-14">[14]</a></sup>
and
negative<sup><a href="https://examine.com/supplements/theanine/research/#ref-27">[27]</a></sup>
results), but has been noted to occur during closed eye
rest<sup><a href="https://examine.com/supplements/theanine/research/#ref-5">[5]</a></sup>
as well as during visuospatial
tasks<sup><a href="https://examine.com/supplements/theanine/research/#ref-16">[16]</a></sup>
around 30-45 minutes after
ingestion.<sup><a href="https://examine.com/supplements/theanine/research/#ref-5">[5]</a><a href="https://examine.com/supplements/theanine/research/#ref-4">[4]</a></sup>
It appears that only the α-1 wave (8-10Hz)
is affected, with no influence on α-2 wave
(11-13Hz).<sup><a href="https://examine.com/supplements/theanine/research/#ref-4">[4]</a></sup></p>
</blockquote>
<p><em>Bill Willis, <a href="https://examine.com/supplements/theanine/research/">“Theanine”</a>, 2022</em></p>
<p>Although I'm confused about the increased α-waves in "otherwise healthy
patients"‽</p>
<p>Additionally, it notes that memory was slightly increased:</p>
<blockquote>
<p>One study using a supplement called LGNC-07 (360mg of green tea extract
and 60mg theanine; thrice daily dosing for 16 weeks) in persons with
mild cognitive impairment based on MMSE scores, supplementation was
associated with improved delayed recognition and immediate recall
scores with no effect on verbal and visuospatial memory (Rey-Kim
test).<sup><a href="https://examine.com/supplements/theanine/research/#ref-17">[17]</a></sup></p>
</blockquote>
<p><em>Bill Willis, <a href="https://examine.com/supplements/theanine/research/">“Theanine”</a>, 2022</em></p>
<h3 id="Experiment_B_SelfBlinded_RCT"><a class="hanchor" href="#Experiment_B_SelfBlinded_RCT">Experiment B: Self-Blinded RCT</a></h3>
<p>This time I explicitely divided my meditation into a concentration part
(first 15 minutes) and a mindfulness part (last 30 minutes).</p>
<ul>
<li>Time for preparation: 93 minutes</li>
<li>Cost of l-theanine pills: <code>$\frac{~0.25€}{\text{500mg L-theanine pill}} \cdot 25 \text{ 500mg L-theanine pills}=6.25€$</code></li>
<li>Cost of empty capsules: <code>$0.75€$</code></li>
</ul>
<p>Notes during consumption:</p>
<ul>
<li>1st dose: Made a mistake while filling the envelopes, accidentally deblinded myself.</li>
<li>19th dose: Took L-Theanine & did my routine, then took a nap and woke up 3 hours later.</li>
<li>43rd dose: Woke up with "brain fog", meditation was dull & all over the place. Maybe because I'd been drying laundry in my room during the night? Also took nicotine later the day to kickstart some work on a project that needed to be finished.</li>
</ul>
<p>Ran the experiment from 2023-06-22 to 2023-09-28, sometimes with pauses inbetween samples.</p>
<p>I use the same <a href="#Statistical_Method">statistical techniques as in the caffeine
experiment</a>, and start, as usual, with my predictions
about the content of the pill:</p>
<pre><code>>>> substances=pd.read_csv('../../data/substances.csv')
>>> experiment='B'
>>> substance='l-theanine'
>>> placebo='sugar'
>>> expa=substances.loc[substances['experiment']==experiment].copy()
>>> expa['datetime']=pd.to_datetime(expa['datetime'], utc=True)
>>> probs=np.array(expa['prediction'])
>>> substances=np.array(expa['substance'])
>>> outcomes=np.array([0 if i=='sugar' else 1 for i in substances])
>>> np.mean(list(map(lambda x: math.log(x[0]) if x[1]==1 else math.log(1-x[0]), zip(probs, outcomes))))
-0.705282842369643
</code></pre>
<p>This is not great. In fact, it's slightly worse than chance (which would
be about -0.693). Not a great sign for L-theanine, and, in fact, it gets
worse. I use the <a href="#Generalising_the_Code">generalized and compacted code</a>
from the last experiments to get the other results, and they don't point
a rosy picture for L-theanine:</p>
<pre><code>>>> analyze('B', 'l-theanine', 'sugar')
absorption mindfulness productivity creativity sublen happy content relaxed horny ease factor ivl time
d 0.045554 0.151308 -0.278448 -0.116001 -0.014761 0.164261 0.254040 0.119069 -0.031665 -7.212364e-02 2.600861e-03 -1.710969e-02 4.301906e-03
λ 1.378294 0.720780 5.517769 5.049838 0.345219 3.983760 6.833004 1.496601 1.148131 inf inf inf inf
p 0.765758 0.894798 0.109735 0.146420 0.955745 0.266491 0.045270 0.740705 0.813279 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
dσ -0.067847 -0.017736 0.039855 -0.043241 -0.014962 -0.155797 -0.046668 0.019655 0.251454 -1.654203e-02 -1.890185e+01 3.108518e+00 1.366082e+01
k 50.000000 50.000000 50.000000 50.000000 21.000000 201.000000 201.000000 201.000000 201.000000 1.024800e+04 1.024800e+04 1.024800e+04 1.024800e+04
</code></pre>
<p>It worsens productivity and creativity (though not <em>quite</em> statistically
significantly, but it's on the way there), but at least it improves my
mood somewhat (though those results, besides contentment, might as well be
due to random chance). No clear effect sizes with the flashcards either.</p>
<p><img alt="" src="./img/nootropics/l-theanine_results.png"/></p>
<h4 id="Conclusion_1"><a class="hanchor" href="#Conclusion_1">Conclusion</a></h4>
<p>So a hard pass on L-theanine, I think. My current best
guess is that as a night owl in the morning I'm still quite
tired, and lack energy, with l-theanine just making me more
sleepy than I already am. But then again, under <a href="https://en.wikipedia.org/wiki/Bonferroni_correction">Bonferroni
correction</a> none of
the p-values are statistically significant, so it looks like l-theanine
just doesn't do anything. Maybe it's better when combined with caffeine?</p>
<h3 id="Discussions_1"><a class="hanchor" href="#Discussions_1">Discussions</a></h3>
<ul>
<li><a href="https://old.reddit.com/r/QuantifiedSelf/comments/17lase8/selfblinded_ltheanine_rct_niplav_2023/">/r/QuantifiedSelf</a></li>
<li><a href="https://www.lesswrong.com/posts/Am9oRbY3bgwE55TxL/self-blinded-l-theanine-rct">LessWrong</a></li>
</ul>
<h2 id="Melatonin"><a class="hanchor" href="#Melatonin">Melatonin</a></h2>
<!--TODO: Claude chat on Melatonin tolerance + effectiveness experiment: https://claude.ai/chat/d9232a96-e71c-4602-974c-5e8b9bc7a60a-->
<p>After being bullied into it by <a href="https://www.gwern.net/Melatonin" title="Melatonin">Gwern
2019</a> and
reading more about dosage & administration in <a href="https://slatestarcodex.com/2018/07/10/melatonin-much-more-than-you-wanted-to-know/" title="Melatonin: Much More Than You Wanted To Know">Scott Alexander
2018</a>,
I decided to tackle my irregular sleeping rhythm and my late bedtimes
by taking Melatonin.</p>
<p>Getting enough high-quality sleep had been quite a problem for most of my
life, I just <em>could not</em> find the willpower to actually go to bed early on
most days. Most other advice relied on exactly bringing up this willpower
(just read before going to bed/just stay away from screens/just do sports
in the morning/just spend more time outside/just masturbate (actually
counter-productive in my case!)); Gwern's framing as an enforcement
mechanism appealed to me, and the cost-benefit analysis seemed sound.</p>
<p>I first tried buying Melatonin at a pharmacy, only to find out that
it is prescription only in my country. A friend told me he had bought
his from Ebay as a food supplement (laws have interesting loopholes),
I ordered 100 3mg pills for ~30€ and they arrived, together with around
10g of protein powder.</p>
<h3 id="Effects"><a class="hanchor" href="#Effects">Effects</a></h3>
<p>I experimented around with administration time & dosage, finding out
that 1/8th (≈0.375g) of a pill, administered at ~20:00, was usually
sufficient to make me sleepy enough at 23:00 to actually go to bed
(though the pills are kind of hard to cut well). I also realized that it was
not necessary to take Melatonin every evening, once a good rhythm had
been established, a dosage every 2 or 3 days was usually enough to keep
the habit of going to bed early.</p>
<p>In the last couple of weeks I've felt like 1/8th of a pill is not enough,
perhaps this is adaption to the substance (though I remember reading
that adaption is negligible). Alternatively, the placebo effect might
be wearing off.</p>
<p>While I haven't experiencde more vivid dreams from Melatonin (which I'd
consider an <a href="./increasing.html#Dreams">advantage</a>), sometimes my sleep
on Melatonin is very light, bordering on dozing, and I also sometimes
experience sleep paralysis while on melatonin. This is in stark contrast
with my normal sleep on melatonin, which I'd guess is deeper than my
normal sleep.</p>
<h4 id="Reducing_Sleep_Duration"><a class="hanchor" href="#Reducing_Sleep_Duration">Reducing Sleep Duration</a></h4>
<p>One large (potential) advantage of Melatonin would be a reduction in <a href="https://www.gwern.net/Melatonin#tempus-fugit">the
amount of time slept</a>.
2½ months after getting a wearable tracker, I decided to analyze
my data on this. I'll spare you the details of data conversion (and
will just say that it's kind of annoying that pandas <code>merge</code> doesn't
implement the <a href="https://en.wikipedia.org/wiki/Antijoin">antijoin</a>)
and cut straight to the chase (of which the code can be found
<a href="./code/melatonin/load.py">here</a>):</p>
<pre><code>>>> melatonin_sleep['minutes_asleep'].mean()
395.5652173913044
>>> non_melatonin_sleep['minutes_asleep'].mean()
387.2142857142857
>>> non_melatonin_sleep['minutes_asleep'].var()
17452.53506493507
>>> melatonin_sleep['minutes_asleep'].var()
5158.620553359683
>>> len(non_melatonin_sleep)
56
>>> len(melatonin_sleep)
23
</code></pre>
<p>It doesn't look like Melatonin has a large effect on sleep durations,
at least with the current (meagre) sample sizes).</p>
<p>Maybe it helps if we filter out sleep that starts later than 6:00 in
the morning (which excludes naps)?</p>
<pre><code>>>> non_nap_melatonin_sleep=melatonin_sleep.loc[(melatonin_sleep['start_time'].dt.hour<6) & (melatonin_sleep['start_time'].dt.hour<18)]
>>> non_nap_melatonin_sleep['minutes_asleep'].mean()
395.5652173913044
>>> non_nap_non_melatonin_sleep=non_melatonin_sleep.loc[(non_melatonin_sleep['start_time'].dt.hour<6) & (non_melatonin_sleep['start_time'].dt.hour<18)]
>>> non_nap_non_melatonin_sleep['minutes_asleep'].mean()
419.29545454545456
>>> len(non_nap_melatonin_sleep)
23
>>> len(non_nap_non_melatonin_sleep)
44
>>> lr=likelihood_ratio_test(placebo_likelihood_ratio(non_nap_melatonin_sleep['minutes_asleep'], non_nap_non_melatonin_sleep['minutes_asleep']))
6.363562898136653
>>> llrt_pval(lr)
0.06284859113951252
</code></pre>
<p>Here it looks like there is a medium-sized advantage to taking
melatonin, with ~25 minutes shorter sleep (at the edge of '<a href="https://en.wikipedia.org/wiki/Statistically_significant#Limitations">statistical
significance</a>').</p>
<p>While Melatonin has been very useful at enforcing bedtimes, the advantage
of sleeping less has been moderate, and potentially just caused by noise.</p>
<!--TODO: check bedtime enforcement!-->
<!--TODO: check whether melatonin consumption just increases sleep debt-->
<h3 id="Takeaway"><a class="hanchor" href="#Takeaway">Takeaway</a></h3>
<p>I am very glad that I've bought & tried Melatonin; it has to a large
degree fixed a significant problem in my life. I am now happier in
the morning when I wake up, less tired during the course of the day,
and don't have to feel guilty at 04:00 because I stayed up too late.</p>
<p>At my current usage, my stash will last me
<code>$95 \hbox{ pills } \cdot 8\frac{\hbox{dosages}}{\hbox{pill}} \cdot 2\frac{\hbox{days}}{\hbox{dosage}}=1520 \hbox{ days}$</code>:
more than 4 years! Even if the future effects are just half as good as
the past effects, this investment was completely worth it.</p>
<h2 id="Nicotine"><a class="hanchor" href="#Nicotine">Nicotine</a></h2>
<p>I started taking nicotine (in the form of nicotine chewing gum with 2mg of
active ingredient) in high-pressure situations (e.g. I'm procrastinating
on an important task and have anxiety around it, or during exams). So
far, it seems especially useful to break me out of an akratic rut.</p>
<h2 id="Vitamin_D"><a class="hanchor" href="#Vitamin_D">Vitamin D₃</a></h2>
<p><a href="https://en.wikipedia.org/wiki/Vitamin_D3">Vitamin D₃</a> just seems
good in general (<a href="https://en.wikipedia.org/wiki/Vitamin_D-3">Wikipedia</a>,
<a href="https://examine.com/supplements/vitamin-d/?show_conditions=false">Examine</a>,
<a href="https://gwern.net/nootropic/nootropics#vitamin-d">Gwern</a>) and potentially
increases <a href="https://gwern.net/longevity#vitamin-d">longevity</a>.<!--TODO:
COVID-19, others?--></p>
<h3 id="Experiment_C_SelfBlinded_RCT"><a class="hanchor" href="#Experiment_C_SelfBlinded_RCT">Experiment C: Self-Blinded RCT</a></h3>
<p>After ingestion I wait for ~30 minutes, and then start meditating for
30 minutes—15 minutes absorption on the breath, 15 minutes bodyscanning.</p>
<p>Started 2024-08-29.</p>
<p>Notes on the experiment:</p>
<ul>
<li>6th dose: Pill opened up inside the envelope, accidentally mostly de-blinding the dose (I'm pretty sure<sub>85%</sub> it was placebo).</li>
</ul>
<h2 id="See_Also_1"><a class="hanchor" href="#See_Also_1">See Also</a></h2>
<!--TODO: something by kanzure?-->
<ul>
<li><a href="https://pad.riseup.net/p/nootgc-research-2023-keep">Nootchat notes</a></li>
<li><a href="https://troof.blog/posts/nootropics/">troof 2022</a></li>
</ul>
<h2 id="Appendix_A_Predictions_on_SelfBlinded_RCTs"><a class="hanchor" href="#Appendix_A_Predictions_on_SelfBlinded_RCTs">Appendix A: Predictions on Self-Blinded RCTs</a></h2>
<p>Predicting the outcomes of personal experiments give a useful way to
train ones own calibration, I take it a step further and record the
predictions for the world to observe my idiocy. The probabilities
link to PredictionBook/Fatebook.</p>
<table>
<thead>
<tr>
<th>Question</th>
<th>Caffeine probability</th>
<th>Caffeine outcome</th>
<th>L-Theanine probability</th>
<th>L-Theanine outcome</th>
<th>Vitamin D₃ probability</th>
<th>Vitamin D₃ outcome</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>Prediction of Arm</strong></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<td>My prediction about the content of the pill is more accurate than random guesses</td>
<td><a href="https://predictionbook.com/predictions/211893">80%</a></td>
<td>Yes</td>
<td><a href="https://fatebook.io/q/my-prediction-about-the-content-of-the--cln3mqldv0001mj08z5l8hryz">65%</a></td>
<td>No</td>
<td>50%</td>
<td></td>
</tr>
<tr>
<td>My prediction about the content of the pill has a log score of more than -0.5</td>
<td><a href="https://predictionbook.com/predictions/211894">60%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/my-prediction-about-the-content-of-the--cln3mrb2x0003mj08tfxhuvh4">40%</a></td>
<td>No</td>
<td>30%</td>
<td></td>
</tr>
<tr>
<td><strong>Meditation</strong></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<td>On intervention days, my average mindfulness during meditation was higher on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211895">60%</a></td>
<td>Yes</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-my-average--cln3mrtwq0005mj080hxfovnk">45%</a></td>
<td>Yes</td>
<td>55%</td>
<td></td>
</tr>
<tr>
<td>On intervention days, my average absorption during meditation was higher on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211896">40%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-my-average--cln3msvxw0007mj08v6v0thr6">55%</a></td>
<td>Yes</td>
<td>55%</td>
<td></td>
</tr>
<tr>
<td>On intervention days, the variance of values for mindfulness during meditation was lower than on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211897">55%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-the-variance-of--cln3mtcp60009mj08w2tttjcs">60%</a></td>
<td>No</td>
<td>45%</td>
<td></td>
</tr>
<tr>
<td>On intervention days, the variance of values for absorption during meditation was lower than on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211898">35%</a></td>
<td>Yes</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-the-variance-of--cln3mtrxc000bmj08gsnbuo2a">65%</a></td>
<td>No</td>
<td>45%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<1$</code> for mindfulness values</td>
<td><a href="https://predictionbook.com/predictions/211899">20%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/-1-for-the-mindfulness-values--cln3muaor0001jx08qm23vbcu">7%</a></td>
<td>Yes</td>
<td>40%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<1$</code> for absorption values</td>
<td><a href="https://predictionbook.com/predictions/211900">25%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/-1-for-the-absorption-values-for--cln3mv8020001m808r7qfhxvr">5%</a></td>
<td>No</td>
<td>40%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<4$</code> for mindfulness values</td>
<td><a href="https://predictionbook.com/predictions/211901">82%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/-4-for-the-mindfulness-values-for--cln3mw7710003l808hhlwezyn">15%</a></td>
<td>Yes</td>
<td>70%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<4$</code> for absorption values</td>
<td><a href="https://predictionbook.com/predictions/211902">88%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/-4-for-the-absorption-values-for--cln3mvlv40001l50807gv6orv">20%</a></td>
<td>Yes</td>
<td>70%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<10$</code> for mindfulness values</td>
<td></td>
<td></td>
<td><a href="https://fatebook.io/q/-10-for-the-mindfulness-values--cln3n0zqf0001lb08kbdkgsn9">65%</a></td>
<td>Yes</td>
<td>95%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<10$</code> for absorption values</td>
<td></td>
<td></td>
<td><a href="https://fatebook.io/q/-10-for-the-absorption-values--cln3n1erx0003jt08myozekxy">60%</a></td>
<td>Yes</td>
<td>95%</td>
<td></td>
</tr>
<tr>
<td><strong>Mood</strong></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<td>On intervention days, my average happiness was higher on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211903">65%</a></td>
<td>Yes</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-my-average-happiness--cln3n20dw0003jx08d97b25tv">55%</a></td>
<td>Yes</td>
<td>55%</td>
<td></td>
</tr>
<tr>
<td>On intervention days, my average contentment was higher on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211904">45%</a></td>
<td>Yes</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-my-average--cln3n2cp80003m808lwhhbhj2">60%</a></td>
<td>Yes</td>
<td>55%</td>
<td></td>
</tr>
<tr>
<td>On intervention days, my average relaxation was higher on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211905">35%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-my-average--cln3n2nnq0002kx08dcu5x00j">65%</a></td>
<td>Yes</td>
<td>52%</td>
<td></td>
</tr>
<tr>
<td>On intervention days, my average chastity was higher on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211906">50%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-my-average-chastity--cln3n2yqg0001jy08aeb48b0b">50%</a></td>
<td>No</td>
<td>50%</td>
<td></td>
</tr>
<tr>
<td>On intervention days, the variance of values for happiness was lower than on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211907">55%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-the-variance-of--cln3n38tm0005jx08u2pvaneg">60%</a></td>
<td>Yes</td>
<td>45%</td>
<td></td>
</tr>
<tr>
<td>On intervention days, the variance of values for contentment was lower than on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211908">30%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-the-variance-of--cln3n3ivi0001js08poq8ex63">65%</a></td>
<td>Yes</td>
<td>45%</td>
<td></td>
</tr>
<tr>
<td>On intervention days, the variance of values for relaxation was lower than on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211909">30%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-the-variance-of--cln3n3ymm0001lf08r9am2pov">65%</a></td>
<td>No</td>
<td>45%</td>
<td></td>
</tr>
<tr>
<td>On intervention days, the variance of values for chastity was lower than on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211910">50%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-the-variance-of--cln3n4an4000dmj08zgq56b5m">50%</a></td>
<td>No</td>
<td>48%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<1$</code> for happiness values</td>
<td><a href="https://predictionbook.com/predictions/211911">45%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/-1-for-the-happiness-values-for--cln3n4q7u0001l908gy0xp29b">8%</a></td>
<td>No</td>
<td>10%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<1$</code> for contentment values</td>
<td><a href="https://predictionbook.com/predictions/211912">40%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/-1-for-the-contentment-values-for--cln3n521t0001l90812jb10yc">5%</a></td>
<td>No</td>
<td>12%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<1$</code> for relaxation values</td>
<td><a href="https://predictionbook.com/predictions/211913">37%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/-1-for-the-relaxation-values-for--cln3n5cbk0003l908opgeutk5">5%</a></td>
<td>No</td>
<td>15%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<1$</code> for chastity values</td>
<td><a href="https://predictionbook.com/predictions/211914">60%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/-1-for-the-chastity-values-for--cln3n5mg30001l708fl3d4e79">10%</a></td>
<td>No</td>
<td>18%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<4$</code> for happiness values</td>
<td><a href="https://predictionbook.com/predictions/211915">85%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/-4-for-the-happiness-values-for--cln3n5zp10001lc08lu894ypb">18%</a></td>
<td>No</td>
<td>45%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<4$</code> for contentment values</td>
<td><a href="https://predictionbook.com/predictions/211916">90%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/-4-for-the-contentment-values-for--cln3n6dbj0003lc083iipq1qz">12%</a></td>
<td>No</td>
<td>50%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<4$</code> for relaxation values</td>
<td><a href="https://predictionbook.com/predictions/211917">90%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/-4-for-the-relaxation-values-for--cln3n6q7w0005lc089jtw45hd">12%</a></td>
<td>Yes</td>
<td>40%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<4$</code> for chastity values</td>
<td><a href="https://predictionbook.com/predictions/211918">95%</a></td>
<td>Yes</td>
<td><a href="https://fatebook.io/q/-4-for-the-chastity-values-for--cln3n73wr0001il08p58hm5g2">20%</a></td>
<td>Yes</td>
<td>55%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<10$</code> for happiness values</td>
<td></td>
<td></td>
<td><a href="https://fatebook.io/q/-10-for-the-happiness-values-for--cln3n7hol0005l80809dnogc9">75%</a></td>
<td>Yes</td>
<td>90%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<10$</code> for contentment values</td>
<td></td>
<td></td>
<td><a href="https://fatebook.io/q/-10-for-the-contentment-values-for--cln3n7qyk0007lc08i2y0wi03">70%</a></td>
<td>Yes</td>
<td>95%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<10$</code> for relaxation values</td>
<td></td>
<td></td>
<td><a href="https://fatebook.io/q/-10-for-the-relaxation-values-for--cln3n87cc0001jv09t114784d">70%</a></td>
<td>Yes</td>
<td>95%</td>
<td></td>
</tr>
<tr>
<td><code>$\lambda<10$</code> for chastity values</td>
<td></td>
<td></td>
<td><a href="https://fatebook.io/q/-10-for-the-chastity-values-for--cln3n8hnn0003jv098so68txn">85%</a></td>
<td>Yes</td>
<td>95%</td>
<td></td>
</tr>
<tr>
<td><strong>Productivity and Creativity</strong></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<td>On intervention days, my average productivity was higher on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211991">52%</a></td>
<td>Yes</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-my-average--cln3n8sre0001l308jya7b69i">65%</a></td>
<td>No</td>
<td></td>
<td></td>
</tr>
<tr>
<td>On intervention days, my average creativity was higher on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211992">55%</a></td>
<td>Yes</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-my-average--cln3n91s40003l308tatnv3si">55%</a></td>
<td>No</td>
<td></td>
<td></td>
</tr>
<tr>
<td>On intervention days, the variance of values for productivity was lower than on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211993">40%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-the-variance-of--cln3n9d9d0001jo080y15xrhg">70%</a></td>
<td>No</td>
<td></td>
<td></td>
</tr>
<tr>
<td>On intervention days, the variance of values for creativity was lower than on placebo days</td>
<td><a href="https://predictionbook.com/predictions/211994">65%</a></td>
<td>No</td>
<td><a href="https://fatebook.io/q/on-l-theanine-days-the-variance-of--cln3n9nbc0005l308ubxz0n6x">50%</a></td>
<td>Yes</td>
<td></td>
<td></td>
</tr>