Higher Brain Performance Index From Lumosity BPI Predicts Significantly Higher Body Weight for Population
Contents
Mike Sinn
PRINCIPAL INVESTIGATOR
Mike Sinn

Variables

A
Brain Performance Index From Lumosity BPI 56
A
Body Weight 1140

Categories

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Cognitive Performance 19
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Physique 41

Actions

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Your Data

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High Confidence
Very Strong Effect Size
Positive Relationship
Population Study
cause image gauge image effect image
Participants reported a 1.6% average increase in Body Weight following above average Brain Performance Index From Lumosity BPI.
Abstract

Abstract

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Body Weight was generally 1% higher than average after an average of 630 index of Brain Performance Index From Lumosity BPI over the previous 24 hours.

Aggregated data from 2 study participants suggests with a HIGH degree of confidence (p=0.001, 95% CI 0.477 to 1.188) that Brain Performance Index From Lumosity BPI has a strongly positive predictive relationship (R=0.832) with Body Weight.

The highest quartile of Body Weight measurements were observed following an average 1 index Brain Performance Index From Lumosity BPI.

The lowest quartile of Body Weight measurements were observed following an average 929 index of Brain Performance Index From Lumosity BPI.

After an onset delay of 0 seconds, Body Weight is typically 1% lower than average over the 24 hours following around 929 index Brain Performance Index From Lumosity BPI.

Objective

Objective

The objective of this study is to determine the nature of the relationship (if any) between Brain Performance Index From Lumosity BPI and Body Weight. Additionally, we attempt to determine the Brain Performance Index From Lumosity BPI values most likely to produce optimal Body Weight values.
Participant Instructions

Participant Instructions

Manual Recording Option

A Create a reminder for Brain Performance Index From Lumosity BPI here and record it daily by enabling notifications or using A the reminder inbox here .


Body Weight Automatic Import of Body Weight via Fitbit

A Get Fitbit here and use it to record your Body Weight. Then, A import your data here .

Manual Recording Option

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

Body Weight Automatic Import of Body Weight via Google Fit

A Get Google Fit here and use it to record your Body Weight. Then, A import your data here .

Body Weight Automatic Import of Body Weight via Withings

A Get Withings here and use it to record your Body Weight. Then, A import your data 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

Brain Performance Index From Lumosity BPI Pre-Processing

Brain Performance Index From Lumosity BPI measurement values below 0 index were assumed erroneous and removed. No maximum allowed measurement value was defined for Brain Performance Index From Lumosity BPI. No missing data filling value was defined for Brain Performance Index From Lumosity BPI so any gaps in data were just not analyzed instead of assuming zero values for those times.

Body Weight Pre-Processing

Body Weight measurement values below 0 pounds were assumed erroneous and removed. Body Weight measurement values above 1000 pounds were assumed erroneous and removed. No missing data filling value was defined for Body Weight 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 Brain Performance Index From Lumosity BPI would produce an observable change in Body Weight.

It was assumed that Brain Performance Index From Lumosity BPI could produce an observable change in Body Weight 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 Body Weight is statistically significant at 95% confidence interval.

Data Sources

Data Sources

Brain Performance Index From Lumosity BPI 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.

Body Weight data was primarily collected using Fitbit. Fitbit makes activity tracking easy and automatic.

Limitations

Limitations

The accuracy of this study may be limited by the fact that

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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 strongly positive (R = 0.8324) relationship between Brain Performance Index From Lumosity BPI and Body Weight.

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. 71 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Brain Performance Index From Lumosity BPI 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 Brain Performance Index From Lumosity BPI and Body Weight.

0 humans feel that any relationship observed between Brain Performance Index From Lumosity BPI and Body Weight 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 Brain Performance Index From Lumosity BPI and Body Weight is coincidental.

Relationship Statistics

Property Value
Cause Variable Name Brain Performance Index From Lumosity BPI
Effect Variable Name Body Weight
Sinn Predictive Coefficient 0.075444262738485
Confidence Level HIGH
Confidence Interval 0.35574081421578
Forward Pearson Predictive Coefficient 0.8324
Critical T Value 1.664
Average Brain Performance Index From Lumosity BPI Over Previous 24 hours Before ABOVE Average Body Weight 1 index
Average Brain Performance Index From Lumosity BPI Over Previous 24 hours Before BELOW Average Body Weight 929 index
Duration of Action 24 hours
Effect Size strongly positive
Number of Paired Measurements 71
Optimal Pearson Product 1.3565409646733
P Value 0.001
Statistical Significance 0.7351
Strength of Relationship 0.35574081421578
Study Type population
Analysis Performed At 2021-08-30
Number of Participants 2

Brain Performance Index From Lumosity BPI Info

Property Value
Variable Name Brain Performance Index From Lumosity BPI
Aggregation Method MEAN
Analysis Performed At 2020-09-15
Duration of Action 24 hours
Kurtosis 3.3674757649788
Mean 1025.9089041096 index
Median 1034 index
Minimum Allowed Value 0 index
Number of Aggregate Predictors 46
Number of Aggregate Outcomes 10
Number of Measurements 146
Number of Measurements (including those generated by tagged, joined, or child variables) 73
Public true
Onset Delay 0 seconds
Standard Deviation 125.24473302572
Unit Index
User Variables 2
UPC 811213027247
Variable Category Cognitive Performance
Variable ID 1274
Variance 15686.243150685

Body Weight Info

Property Value
Variable Name Body Weight
Aggregation Method MEAN
Analysis Performed At 2020-09-23
Duration of Action 7 days
Kurtosis 29.271534088526
Maximum Allowed Value 1000 pounds
Mean 168.9619340574 pounds
Median 168.27481272906 pounds
Minimum Allowed Value 0 pounds
Number of Aggregate Predictors 883
Number of Aggregate Outcomes 257
Number of Measurements 108822
Number of Measurements (including those generated by tagged, joined, or child variables) 21092
Public true
Onset Delay 0 seconds
Standard Deviation 8.7190661755282
Unit Pounds
User Variables 417
UPC 875011003902
Variable Category Physique
Variable ID 1486
Variance 594.35417755402