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    GlossaryCausal Inference

    determining if one factor directly affects another

    Causal inference is the process of determining whether a cause-and-effect relationship exists between two variables. For example, in the context of hair loss (alopecia), researchers might use causal inference to determine if a specific treatment directly leads to hair regrowth. This involves using statistical methods and study designs, such as randomized controlled trials, to rule out other factors and establish a direct link.

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      community Another clueless guy fearmongering and spreading misinformation

      in Chat  251 upvotes 1 year ago
      The conversation discusses hair loss treatments, with some users advocating for finasteride and minoxidil, while others express concerns about potential side effects of finasteride. A social media influencer is criticized for promoting scalp massages and minoxidil over finasteride, which some believe is misinformation.

      community EU Shouldn't Ban Fin & Dut: PFS is NOT REAL.

      in Research/Science  9 upvotes 5 months ago
      Finasteride and Dutasteride do not cause depression or "Post Finasteride Syndrome," with concerns often linked to the nocebo effect and preexisting mental health issues. The EU is unlikely to ban these drugs, but access may become more restricted due to ongoing debates.

      community Male pattern baldness, and mental health

      in Finasteride/Dutasteride  332 upvotes 1 year ago
      A 48-year-old man has been using minoxidil for 15 years and considered finasteride but stopped due to potential side effects. He is concerned about his mental health and the impact of hair loss on self-image, and he encourages support among men experiencing hair loss.