Charts
Trait Correlation Between Blood Pressure (Diastolic - Bottom Number) and Jitteriness
Blood Pressure Charts
Daily Distribution
Average by Day of Week
Average by Month
Average by Year
Jitteriness Charts
Daily Distribution
Average by Day of Week
Average by Month
Average by Year
Relationship Charts
Jitteriness Following Blood Pressure (Diastolic - Bottom Number)
Correlation Between Blood Pressure (Diastolic - Bottom Number) and Jitteriness by Duration of Action
Correlation Between Blood Pressure (Diastolic - Bottom Number) and Jitteriness by Onset Delay
Average Blood Pressure (Diastolic - Bottom Number) Preceding Jitteriness
Average Jitteriness by Previous Blood Pressure (Diastolic - Bottom Number)
Abstract
Jitteriness was generally 0% higher than average after 87.1 millimeters merc of Blood Pressure per 7 days.
Aggregated data from 2 study participants suggests with a LOW degree of confidence (p=0.384, 95% CI -0.371 to 0.715) that Blood Pressure has a weakly positive predictive relationship (R=0.172) with Jitteriness.
The highest quartile of Jitteriness measurements were observed following an average 83.3 millimeters merc Blood Pressure.
The lowest quartile of Jitteriness measurements were observed following an average 82.1 millimeters merc of Blood Pressure.
After an onset delay of 0 seconds, Jitteriness is typically 2% lower than average over the 7 days following around 82.1 millimeters merc Blood Pressure.
Objective
Participant Instructions
Automatic Import of Blood Pressure (Diastolic - Bottom Number) via Withings
Get Withings here
and use it to record your Blood Pressure (Diastolic - Bottom Number). Then,
import your data here
.
Manual Recording Option
Create a reminder for Blood Pressure (Diastolic - Bottom Number) here
and record it daily by enabling notifications or using
the reminder inbox here
.
Manual Recording Option
Create a reminder for Jitteriness here
and record it daily by enabling notifications or using
the reminder inbox here
.
Design
This study is based on data donated by 2 participants. Thus, the study design is equivalent to the aggregation of 2 separate n=1 observational natural experiments.
Data Analysis
Blood Pressure (Diastolic - Bottom Number) Pre-Processing
Blood Pressure (Diastolic - Bottom Number) measurement values below 1 millimeters merc were assumed erroneous and removed. Blood Pressure (Diastolic - Bottom Number) measurement values above 100000 millimeters merc were assumed erroneous and removed. No missing data filling value was defined for Blood Pressure (Diastolic - Bottom Number) so any gaps in data were just not analyzed instead of assuming zero values for those times.
Jitteriness Pre-Processing
Jitteriness measurement values below 1 out of 5 were assumed erroneous and removed. Jitteriness measurement values above 5 out of 5 were assumed erroneous and removed. No missing data filling value was defined for Jitteriness so any gaps in data were just not analyzed instead of assuming zero values for those times.
Predictive Analytics
It was assumed that 0 seconds would pass before a change in Blood Pressure (Diastolic - Bottom Number) would produce an observable change in Jitteriness.
It was assumed that Blood Pressure (Diastolic - Bottom Number) could produce an observable change in Jitteriness for as much as 7 days after the stimulus event.
Statistical Significance
Using a two-tailed t-test with alpha = 0.05, it was determined that the change in Jitteriness is not statistically significant at a 95% confidence interval. This suggests that the Blood Pressure value does not have a significant influence on the Jitteriness value.
After treatment, a 3% increase (-0.0126 out of 5) from the mean baseline 1.48 out of 5 was observed. The relative standard deviation at baseline was 27.65%. The observed change was 0.172558 times the standard deviation.
A common rule of thumb considers a change greater than twice the baseline standard deviation on two separate pre-post experiments may be considered significant. This occurrence would have only a 5% likelihood of resulting from random fluctuation (a p-value < 0.05).
Data Sources
Blood Pressure (Diastolic - Bottom Number) data was primarily collected using Withings. Withings creates smart products and apps to take care of yourself and your loved ones in a new and easy way. Discover the Withings Pulse, Wi-Fi Body Scale, and Blood Pressure Monitor.
Jitteriness data was primarily collected using QuantiModo. QuantiModo allows you to easily track mood, symptoms, or any outcome you want to optimize in a fraction of a second. You can also import your data from over 30 other apps and devices. QuantiModo then analyzes your data to identify which hidden factors are most likely to be influencing your mood or symptoms.
Limitations
As with any human experiment, it was impossible to control for all potentially confounding variables. Correlation does not necessarily imply causation. We can never know for sure if one factor is definitely the cause of an outcome. However, lack of correlation definitely implies the lack of a causal relationship. Hence, we can with great confidence rule out non-existent relationships. For instance, if we discover no relationship between mood and an antidepressant this information is just as or even more valuable than the discovery that there is a relationship.
We can also take advantage of several characteristics of time series data from many subjects to infer the likelihood of a causal relationship if we do find a correlational relationship. The criteria for causation are a group of minimal conditions necessary to provide adequate evidence of a causal relationship between an incidence and a possible consequence.
Criteria For Causal Inference
Strength (A.K.A. Effect Size)
A small association does not mean that there is not a causal effect, though the larger the association, the more likely that it is causal. There is a weakly positive (R = 0.1718) relationship between Blood Pressure (Diastolic - Bottom Number) and Jitteriness.
Consistency (A.K.A. Reproducibility)
Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect. Furthermore, in accordance with the law of large numbers (LLN), the predictive power and accuracy of these results will continually grow over time. 27 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Blood Pressure (Diastolic - Bottom Number) values, the observed strength of the relationship will decline until it is below the threshold of significance. To it another way, in the case that we do find a spurious correlation, suggesting that banana intake improves mood for instance, one will likely increase their banana intake. Due to the fact that this correlation is spurious, it is unlikely that you will see a continued and persistent corresponding increase in mood. So over time, the spurious correlation will naturally dissipate.
Specificity
Causation is likely if a very specific population at a specific site and disease with no other likely explanation. The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship.
Temporality
The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay). The confidence in a causal relationship is bolstered by the fact that time-precedence was taken into account in all calculations.
Biological Gradient
Greater exposure should generally lead to greater incidence of the effect. However, in some cases, the mere presence of the factor can trigger the effect. In other cases, an inverse proportion is observed: greater exposure leads to lower incidence.
Plausibility
A plausible bio-chemical mechanism between cause and effect is critical. This is where human brains excel.
Based on our responses so far,
0 humans feel that there is a plausible mechanism of action for a relationship between Blood Pressure (Diastolic - Bottom Number) and Jitteriness.
0 humans feel that any relationship observed between Blood Pressure (Diastolic - Bottom Number) and Jitteriness is coincidental.
Coherence
Coherence between epidemiological and laboratory findings increases the likelihood of an effect. It will be very enlightening to aggregate this data with the data from other participants with similar genetic, diseasomic, environmentomic, and demographic profiles.
Experiment
All of human life can be considered a natural experiment. Occasionally, it is possible to appeal to experimental evidence.
Analogy
The effect of similar factors may be considered.
Plausibility
A plausible bio-chemical mechanism between cause and effect is critical. This is where human brains excel. Based on our responses so far, 0 humans feel that there is a plausible mechanism of action and 0 feel that any relationship observed between Blood Pressure (Diastolic - Bottom Number) and Jitteriness is coincidental.
Relationship Statistics
| Property | Value |
|---|---|
| Cause Variable Name | Blood Pressure (Diastolic - Bottom Number) |
| Effect Variable Name | Jitteriness |
| Sinn Predictive Coefficient | 0.031142057066348 |
| Confidence Level | LOW |
| Confidence Interval | 0.54292895309195 |
| Forward Pearson Predictive Coefficient | 0.1718 |
| Critical T Value | 1.81 |
| Average Blood Pressure ( Diastolic - Bottom Number) Over Previous 7 days Before ABOVE Average Jitteriness | 83.3 millimeters merc |
| Average Blood Pressure ( Diastolic - Bottom Number) Over Previous 7 days Before BELOW Average Jitteriness | 82.1 millimeters merc |
| Duration of Action | 7 days |
| Effect Size | weakly positive |
| Number of Paired Measurements | 27 |
| Optimal Pearson Product | 0.085968327291399 |
| P Value | 0.38390717201153 |
| Statistical Significance | 0.0534 |
| Strength of Relationship | 0.54292895309195 |
| Study Type | population |
| Analysis Performed At | 2021-08-30 |
| Number of Participants | 2 |
Blood Pressure (Diastolic - Bottom Number) Info
| Property | Value |
|---|---|
| Variable Name | Blood Pressure (Diastolic - Bottom Number) |
| Aggregation Method | MEAN |
| Analysis Performed At | 2020-09-15 |
| Duration of Action | 7 days |
| Kurtosis | 8.2941066433719 |
| Maximum Allowed Value | 100000 millimeters merc |
| Mean | 4862.2075101351 millimeters merc |
| Median | 4863.1873888889 millimeters merc |
| Minimum Allowed Value | 1 millimeters merc |
| Number of Aggregate Predictors | 1048 |
| Number of Aggregate Outcomes | 105 |
| Number of Measurements | 8497 |
| Number of Measurements (including those generated by tagged, joined, or child variables) | 5162 |
| Public | true |
| Onset Delay | 0 seconds |
| Standard Deviation | 30.417322766767 |
| Unit | Millimeters Merc |
| User Variables | 58 |
| UPC | 0 |
| Variable Category | Vital Signs |
| Variable ID | 5554981 |
| Variance | 24447.586420368 |
Jitteriness Info
| Property | Value |
|---|---|
| Variable Name | Jitteriness |
| Aggregation Method | MEAN |
| Analysis Performed At | 2020-09-17 |
| Duration of Action | 24 hours |
| Kurtosis | 2.6367465767175 |
| Maximum Allowed Value | 5 out of 5 |
| Mean | 2.3890969570152 out of 5 |
| Median | 2.3481002216861 out of 5 |
| Minimum Allowed Value | 1 out of 5 |
| Number of Aggregate Predictors | 1107 |
| Number of Aggregate Outcomes | 119 |
| Number of Measurements | 28220 |
| Number of Measurements (including those generated by tagged, joined, or child variables) | 27853 |
| Public | true |
| Onset Delay | 0 seconds |
| Standard Deviation | 0.50486515916989 |
| Unit | 1 to 5 Rating |
| User Variables | 1414 |
| UPC | 0 |
| Variable Category | Emotions |
| Variable ID | 1361 |
| Variance | 0.57863573304335 |
Principal Investigator
Cite This Study
@misc{sinn_cause_5554981_effect_1361_population_study_2026,
author = {Sinn, Mike P.},
title = {Higher Blood Pressure (Diastolic - Bottom Number) Predicts Slightly Higher Jitteriness for Population},
year = {2026},
publisher = {The Journal of Citizen Science},
url = {https://studies.crowdsourcingcures.org/study/cause-5554981-effect-1361-population-study},
note = {Accessed: January 3, 2026}
}