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Based on data from 14 participants, Pain Severity is generally lowest after an average of 71 percent of Outdoor Humidity over the previous 7 days.
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People with higher Outdoor Humidity usually have higher Pain Severity
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Outdoor Humidity on each day of the week.
This chart shows the typical value recorded for Outdoor Humidity for each month of the year.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Pain Severity on each day of the week.
This chart shows the typical value recorded for Pain Severity for each month of the year.

Abstract

Aggregated data from 14 study participants suggests with a medium degree of confidence (p=0.15417180054671, 95% CI -0.378 to 0.361) that Outdoor Humidity has a very weakly negative predictive relationship (R=-0.01) with Pain Severity. The highest quartile of Pain Severity measurements were observed following an average 71.79 percent Outdoor Humidity. The lowest quartile of Pain Severity measurements were observed following an average 73.577456553313 % Outdoor Humidity.

Objective

The objective of this study is to determine the nature of the relationship (if any) between Outdoor Humidity and Pain Severity. Additionally, we attempt to determine the Outdoor Humidity values most likely to produce optimal Pain Severity values.

Participant Instructions

Record your Outdoor Humidity daily in the reminder inbox or using the interactive web or mobile notifications.
Record your Pain Severity daily in the reminder inbox or using the interactive web or mobile notifications.

Design

This study is based on data donated by 14 participants. Thus, the study design is equivalent to the aggregation of 14 separate n=1 observational natural experiments.

Data Analysis

Outdoor Humidity Pre-Processing
No minimum allowed measurement value was defined for Outdoor Humidity. No maximum allowed measurement value was defined for Outdoor Humidity. No missing data filling value was defined for Outdoor Humidity so any gaps in data were just not analyzed instead of assuming zero values for those times.
Outdoor Humidity Analysis Settings

Pain Severity Pre-Processing
Pain Severity measurement values below 1 out of 5 were assumed erroneous and removed. Pain Severity measurement values above 5 out of 5 were assumed erroneous and removed. No missing data filling value was defined for Pain Severity so any gaps in data were just not analyzed instead of assuming zero values for those times.
Pain Severity Analysis Settings

Predictive Analytics
It was assumed that 0 hours would pass before a change in Outdoor Humidity would produce an observable change in Pain Severity. It was assumed that Outdoor Humidity could produce an observable change in Pain Severity for as much as 7 days after the stimulus event.
Predictive Analysis Settings

Data Sources

Outdoor Humidity 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.

Pain Severity 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.

The list of the criteria is as follows:
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 very weakly negative relationship between Outdoor Humidity and Pain Severity

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. 97 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Outdoor Humidity 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, 1 humans feel that there is a plausible mechanism of action and 0 feel that any relationship observed between Outdoor Humidity and Pain Severity 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.

Relationship Statistics

Property Value
Cause Variable Name Outdoor Humidity
Effect Variable Name Pain Severity
Sinn Predictive Coefficient 0.0038367074647239
Confidence Level medium
Confidence Interval 0.36983830611609
Forward Pearson Correlation Coefficient -0.0086
Critical T Value 1.7352142857143
Average Outdoor Humidity Over Previous 7 days Before ABOVE Average Pain Severity 71.79 percent
Average Outdoor Humidity Over Previous 7 days Before BELOW Average Pain Severity 73.577456553313 percent
Duration of Action 7 days
Effect Size very weakly negative
Number of Paired Measurements 97
Optimal Pearson Product 0.10861446864436
P Value 0.15417180054671
Statistical Significance 0.32521428749897
Strength of Relationship 0.36983830611609
Study Type population
Analysis Performed At 2019-04-06
Number of Participants 14

Outdoor Humidity Statistics

Property Value
Variable Name Outdoor Humidity
Aggregation Method MEAN
Analysis Performed At 2019-02-02
Duration of Action 7 days
Kurtosis 2.9559134700287
Mean 70.594851674938 percent
Median 71.000970573639 percent
Number of Correlations 212
Number of Measurements 1224786
Onset Delay 0 seconds
Standard Deviation 9.9872867234223
Unit Percent
Variable ID 5954744
Variance 139.10375863122

Pain Severity Statistics

Property Value
Variable Name Pain Severity
Aggregation Method MEAN
Analysis Performed At 2019-03-27
Duration of Action 7 days
Kurtosis 2.693073303007
Maximum Allowed Value 5 out of 5
Mean 3.2311353658537 out of 5
Median 3.1942886178862 out of 5
Minimum Allowed Value 1 out of 5
Number of Correlations 414
Number of Measurements 3742
Onset Delay 0 seconds
Standard Deviation 0.32646462060055
Unit 1 to 5 Rating
Variable ID 87524
Variance 0.27147267796254

Tracking Outdoor Humidity

Record your Outdoor Humidity daily in the reminder inbox or using the interactive web or mobile notifications.

Tracking Pain Severity

Record your Pain Severity daily in the reminder inbox or using the interactive web or mobile notifications.
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https://lh6.googleusercontent.com/-BHr4hyUWqZU/AAAAAAAAAAI/AAAAAAAIG28/2Lv0en738II/photo.jpg Principal Investigator - Mike Sinn