Testosteronspitzen werden mit einer stärkeren politischen Meinung bei Männern in Verbindung gebracht. Sowohl der Hormonspiegel als auch die Meinungen waren um 9:00 Uhr stärker als um 12:00 oder 15:00 Uhr. Jüngere Männer hatten auch höhere Testosteronwerte als ältere Teilnehmer.

I’ve linked to the news release in the post above. In this comment, for those interested, here’s the link to the peer reviewed journal article:

https://link.springer.com/article/10.1007/s40750-024-00245-2

From the linked article:

Testosterone spikes linked to stronger political opinions in men

A series of three studies on healthy men found that their political opinion changes were weakly associated with changes in testosterone levels. These changes were also somewhat associated with fluctuations in cortisol levels, though this relationship was more complex. The research was published in Adaptive Human Behavior and Physiology.

The first study showed that both hormone levels and the strength of political opinions fluctuated throughout the day. Both hormone levels and opinions were stronger at 9:00 AM than at 12:00 PM or 3:00 PM. Younger men also had higher testosterone levels than older participants.

The exercise conducted in the second study increased both hormone levels and the strength of opinions, with one exception: cortisol levels in older men at 9:00 AM remained unchanged. In contrast, viewing the sad video in the third study decreased testosterone levels and weakened the two political opinions. In both the exercise and sad-video interventions, cortisol levels increased.

“This work identifies that opinion stability, in men, varies in a manner potentially linked to relatively small physiological fluctuations in testosterone concentration and, to a lesser extent, cortisol. These links also appear to be strongly individual in nature,” the study authors concluded.

> The inter-assay coefficients of variation (CVs) were less than 10% for both kits. To eliminate measurement bias arising from inter-assay variation, each participants’ samples were tested within the same assay.

Ah so we’re fully into batch effects error now, marvellous. Would’ve liked to see a full calculation of the total error because the biological variability of hormones is tremendous.

Also looking at those figures, the overlapping confidence intervals and tiny changes in the means are uh, not exactly convincing me there’s any difference between any of their groups.