Higher Very Unproductive Score Predicts Very Slightly Higher Headache Severity for Population
Contents
Mike Sinn
PRINCIPAL INVESTIGATOR
Mike Sinn

Variables

A
Very Unproductive Score 241
A
Headache Severity 1498

Categories

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Goals 126
A
Symptoms 13336

Actions

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Your Data

Tags

Low Confidence
Very Weak Effect Size
Positive Relationship
Population Study
cause image gauge image effect image
Participants reported a 43.7% average increase in Headache Severity following above average Very Unproductive Score.
Abstract

Abstract

Headache Severity was generally 8.1% lower than average after 0.505 percent of Very Unproductive Score per 24 hours.

Aggregated data from 2 study participants suggests with a LOW degree of confidence (p=0.396, 95% CI -0.19 to 0.354) that Very Unproductive Score has a very weakly positive predictive relationship (R=0.0818) with Headache Severity.

The highest quartile of Headache Severity measurements were observed following an average 0.99 percent Very Unproductive Score.

The lowest quartile of Headache Severity measurements were observed following an average 0.53 percent of Very Unproductive Score.

After an onset delay of 0 seconds, Headache Severity is typically 0% lower than average over the 24 hours following around 0.53 percent Very Unproductive Score.

Objective

Objective

The objective of this study is to determine the nature of the relationship (if any) between Very Unproductive Score and Headache Severity. Additionally, we attempt to determine the Very Unproductive Score values most likely to produce optimal Headache Severity values.
Participant Instructions

Participant Instructions

Very Unproductive Score Automatic Import of Very Unproductive Score via RescueTime

A Get RescueTime here and use it to record your Very Unproductive Score. Then, A import your data here .

Manual Recording Option

A Create a reminder for Very Unproductive Score here and record it daily by enabling notifications or using A the reminder inbox here .


Manual Recording Option

A Create a reminder for Headache Severity here and record it daily by enabling notifications or using A the reminder inbox here .

Design

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

Data Analysis

Very Unproductive Score Pre-Processing

No minimum allowed measurement value was defined for Very Unproductive Score. No maximum allowed measurement value was defined for Very Unproductive Score. It was assumed that any gaps in Very Unproductive Score data were unrecorded 0 percent measurement values.

Headache Severity Pre-Processing

Headache Severity measurement values below 1 out of 5 were assumed erroneous and removed. Headache Severity measurement values above 5 out of 5 were assumed erroneous and removed. No missing data filling value was defined for Headache Severity 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 Very Unproductive Score would produce an observable change in Headache Severity.

It was assumed that Very Unproductive Score could produce an observable change in Headache Severity for as much as 24 hours after the stimulus event.

Statistical Significance

Statistical Significance

Using a two-tailed t-test with alpha = 0.05, it was determined that the change in Headache Severity is not statistically significant at a 95% confidence interval. This suggests that the Very Unproductive Score value does not have a significant influence on the Headache Severity value.

After treatment, a 43.7% increase (-0.102 out of 5) from the mean baseline 1.26 out of 5 was observed. The relative standard deviation at baseline was 64.1%. The observed change was 0.12685 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

Data Sources

Very Unproductive Score data was primarily collected using RescueTime. Detailed reports show which applications and websites you spent time on. Activities are automatically grouped into pre-defined categories with built-in productivity scores covering thousands of websites and applications. You can customize categories and productivity scores to meet your needs.

Headache 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

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 very weakly positive (R = 0.0818) relationship between Very Unproductive Score and Headache 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. 90 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Very Unproductive Score 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 Very Unproductive Score and Headache Severity.

0 humans feel that any relationship observed between Very Unproductive Score and Headache 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.

Plausibility

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 Very Unproductive Score and Headache Severity is coincidental.

Relationship Statistics

Property Value
Cause Variable Name Very Unproductive Score
Effect Variable Name Headache Severity
Sinn Predictive Coefficient 0.014827824195097
Confidence Level LOW
Confidence Interval 0.27177
Forward Pearson Predictive Coefficient 0.0818
Critical T Value 1.66
Average Very Unproductive Score Over Previous 24 hours Before ABOVE Average Headache Severity 0.99 percent
Average Very Unproductive Score Over Previous 24 hours Before BELOW Average Headache Severity 0.53 percent
Duration of Action 24 hours
Effect Size very weakly positive
Number of Paired Measurements 90
Optimal Pearson Product 0.050776723105502
P Value 0.39628
Statistical Significance 0.7312
Strength of Relationship 0.27177
Study Type population
Analysis Performed At 2021-08-30
Number of Participants 2

Very Unproductive Score Info

Property Value
Variable Name Very Unproductive Score
Aggregation Method MEAN
Analysis Performed At 2020-10-11
Duration of Action 24 hours
Filling Value 0
Kurtosis 25.311779979718
Mean 0.4385353065176 percent
Median 0.090475598290598 percent
Number of Aggregate Predictors 190
Number of Aggregate Outcomes 51
Number of Measurements 931
Number of Measurements (including those generated by tagged, joined, or child variables) 77
Public true
Onset Delay 0 seconds
Standard Deviation 0.6020795343691
Unit Percent
User Variables 26
Variable Category Goals
Variable ID 6057116
Variance 0.6757506944964

Headache Severity Info

Property Value
Variable Name Headache Severity
Aggregation Method MEAN
Analysis Performed At 2021-04-22
Duration of Action 24 hours
Kurtosis 2.6188505753424
Maximum Allowed Value 5 out of 5
Mean 2.7185156626506 out of 5
Median 2.6872903614458 out of 5
Minimum Allowed Value 1 out of 5
Number of Aggregate Predictors 1317
Number of Aggregate Outcomes 181
Number of Measurements 5408
Number of Measurements (including those generated by tagged, joined, or child variables) 5408
Public true
Onset Delay 0 seconds
Standard Deviation 0.41171668487351
Unit 1 to 5 Rating
User Variables 351
UPC 0
Variable Category Symptoms
Variable ID 87323
Variance 0.48864093917025