Lag responses in mood reports to changes in the weather matrix
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Correlations were calculated between daily self-evaluated mood reports (4 reports/day) of 10 student subjects and 10 meteorological-geophysical variables over a 90-day period. The variables included mean and/or change measures of temperature, barometric pressure, relative humidity, sunshine hours, wind speeds and global geomagnetic activity. Multiple regression analyses indicated that the weather matrix used could account for not more than 35% of the mood variance on the day of the evaluation. Lag correlations over the previous week clearly indicated a greater number of significant correlations between mood reports and weather of the previous two days. The mean correlation coefficient was 0.27. In general, "lower moods" were associated with fewer sunshine hours, higher relative humidity, and smaller humidity variations than "higher moods". It was concluded that mood reports can show weak responsivity to antecedent weather fluctuations.
KeywordsRelative Humidity Wind Speed Multiple Regression Analysis Geomagnetic Activity Change Measure
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