Higher Increased Appetite Predicts Moderately Lower Inspiration for Population
Contents

Variables

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Increased Appetite 86
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Inspiration 1050

Categories

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Symptoms 13336
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Emotions 2028

Actions

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Your Data

Tags

Low Confidence
Weak Effect Size
Negative Relationship
Population Study
cause image gauge image effect image
Participants reported a 6% average decrease in Inspiration following above average Increased Appetite.
Abstract

Abstract

Inspiration was generally 1% higher than average after an average of 1.25 out of 5 of Increased Appetite over the previous 7 days.

Aggregated data from 1 study participants suggests with a LOW degree of confidence (p=0.335, 95% CI -0.626 to -0.068) that Increased Appetite has a moderately negative predictive relationship (R=-0.347) with Inspiration.

The highest quartile of Inspiration measurements were observed following an average 1.2 out of 5 Increased Appetite.

The lowest quartile of Inspiration measurements were observed following an average 1.57 out of 5 of Increased Appetite.

After an onset delay of 0 seconds, Inspiration is typically 2% lower than average over the 7 days following around 1.57 out of 5 Increased Appetite.

Objective

Objective

The objective of this study is to determine the nature of the relationship (if any) between Increased Appetite and Inspiration. Additionally, we attempt to determine the Increased Appetite values most likely to produce optimal Inspiration values.
Participant Instructions

Participant Instructions

Manual Recording Option

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


Manual Recording Option

A Create a reminder for Inspiration 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 1 participants. Thus, the study design is equivalent to the aggregation of 1 separate n=1 observational natural experiments.

Data Analysis

Data Analysis

Increased Appetite Pre-Processing

Increased Appetite measurement values below 1 out of 5 were assumed erroneous and removed. Increased Appetite measurement values above 5 out of 5 were assumed erroneous and removed. No missing data filling value was defined for Increased Appetite so any gaps in data were just not analyzed instead of assuming zero values for those times.

Inspiration Pre-Processing

Inspiration measurement values below 1 out of 5 were assumed erroneous and removed. Inspiration measurement values above 5 out of 5 were assumed erroneous and removed. No missing data filling value was defined for Inspiration 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 Increased Appetite would produce an observable change in Inspiration.

It was assumed that Increased Appetite could produce an observable change in Inspiration for as much as 7 days 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 Inspiration is not statistically significant at a 95% confidence interval. This suggests that the Increased Appetite value does not have a significant influence on the Inspiration value.

After treatment, a 6% decrease (-0.0925 out of 5) from the mean baseline 3.82 out of 5 was observed. The relative standard deviation at baseline was 5.2%. The observed change was 0.46355 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

Increased Appetite 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.

Inspiration 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 moderately negative (R = -0.347) relationship between Increased Appetite and Inspiration.

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. 12 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Increased Appetite 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 Increased Appetite and Inspiration.

0 humans feel that any relationship observed between Increased Appetite and Inspiration 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 Increased Appetite and Inspiration is coincidental.

Relationship Statistics

Property Value
Cause Variable Name Increased Appetite
Effect Variable Name Inspiration
Sinn Predictive Coefficient 0.033021416213784
Confidence Level LOW
Confidence Interval 0.27948
Forward Pearson Predictive Coefficient -0.347
Critical T Value 1.782
Average Increased Appetite Over Previous 7 days Before ABOVE Average Inspiration 1.2 out of 5
Average Increased Appetite Over Previous 7 days Before BELOW Average Inspiration 1.57 out of 5
Duration of Action 7 days
Effect Size moderately negative
Number of Paired Measurements 12
Optimal Pearson Product 0.16253717312708
P Value 0.33518
Statistical Significance 0.0051
Strength of Relationship 0.27948
Study Type population
Analysis Performed At 2021-08-30
Number of Participants 1

Increased Appetite Info

Property Value
Variable Name Increased Appetite
Aggregation Method MEAN
Analysis Performed At 2020-10-09
Duration of Action 24 hours
Kurtosis 2.9791334010742
Maximum Allowed Value 5 out of 5
Mean 2.70835 out of 5
Median 2.5 out of 5
Minimum Allowed Value 1 out of 5
Number of Aggregate Predictors 55
Number of Aggregate Outcomes 31
Number of Measurements 13
Number of Measurements (including those generated by tagged, joined, or child variables) 13
Public true
Onset Delay 0 seconds
Standard Deviation 0.39648073054938
Unit 1 to 5 Rating
User Variables 2
UPC 862516000079
Variable Category Symptoms
Variable ID 87369
Variance 0.31439393939394

Inspiration Info

Property Value
Variable Name Inspiration
Aggregation Method MEAN
Analysis Performed At 2020-10-11
Duration of Action 24 hours
Kurtosis 1.9445163556302
Maximum Allowed Value 5 out of 5
Mean 2.443560781967 out of 5
Median 2.4107853769992 out of 5
Minimum Allowed Value 1 out of 5
Number of Aggregate Predictors 934
Number of Aggregate Outcomes 116
Number of Measurements 21838
Number of Measurements (including those generated by tagged, joined, or child variables) 21668
Public true
Onset Delay 0 seconds
Standard Deviation 0.54709683163225
Unit 1 to 5 Rating
User Variables 1342
UPC 0
Variable Category Emotions
Variable ID 1355
Variance 0.6033744215066

Principal Investigator

Cite This Study

APA Format
Sinn, M. P. (2026). Higher Increased Appetite Predicts Moderately Lower Inspiration for Population. The Journal of Citizen Science. https://studies.crowdsourcingcures.org/study/cause-87369-effect-1355-population-study
BibTeX
@misc{sinn_cause_87369_effect_1355_population_study_2026,
  author = {Sinn, Mike P.},
  title = {Higher Increased Appetite Predicts Moderately Lower Inspiration for Population},
  year = {2026},
  publisher = {The Journal of Citizen Science},
  url = {https://studies.crowdsourcingcures.org/study/cause-87369-effect-1355-population-study},
  note = {Accessed: January 3, 2026}
}
Chicago/Turabian
Sinn, Mike P. "Higher Increased Appetite Predicts Moderately Lower Inspiration for Population." The Journal of Citizen Science. Accessed January 3, 2026. https://studies.crowdsourcingcures.org/study/cause-87369-effect-1355-population-study.