[imzadi]

This is only talking about therapy and not medication. The original study is a bit light on details https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD...

> For the 57 trials (2189 participants) comparing exercise with no treatment or a control intervention, the pooled SMD for depressive symptoms at the end of treatment was −0.67 (95% confidence interval (CI) −0.82 to −0.52; low‐certainty evidence), showing that exercise may result in a reduction in depressive symptoms. When we included only the seven trials (447 participants) with adequate allocation concealment, intention‐to‐treat analysis and blinded outcome assessment, the pooled SMD was smaller (SMD −0.46, 95% CI −0.88 to −0.04). Pooled data from the nine trials (405 participants) with long‐term follow‐up provided very uncertain evidence about the effect of exercise on depressive symptoms (SMD −0.53, 95% CI −1.11 to 0.06; very low certainty evidence).

Like, what does -0.67 really mean in this context. I read the study and it is not really explained. Maybe I'm too dumb to get it, though.

[unparagoned]

Other metas show exercise is more effective than both therapy and drugs.

ssri don’t fix any underlying condition and barely work long term, that if they really work at all.

[fastasucan]

What if medication helps people being able to exercise?

[verteu]

It's a standardized mean difference, which I believe can roughly be interpreted as: "treated groups had 0.67 stddev lower depression score than control groups."

That's a pretty substantial improvement - consider someone who's more depressed than 75% of the population becoming completely average. (Because the 75th percentile is about 0.67stddev above the median.)

[D-Machine]

You cannot say if this is a substantial change or not, because you need to know by how much the groups actually differ on average, i.e. you need the unstandardized effect size, expressed as a mean difference in the scale sum scores, or as an actual percentage of symptoms reduced, or etc. In general, there are monstrous issues with standardized mean differences, even setting aside the interpretability issues [1-3].

See also my response to GP.

[1] https://journals.plos.org/mentalhealth/article?id=10.1371/jo...

[2] https://bpspsychub.onlinelibrary.wiley.com/doi/abs/10.1348/0...).

[3] https://www.tandfonline.com/doi/abs/10.1080/00031305.2018.15...

[verteu]

Good point. Would it be roughly accurate to say: "consider someone who's more depressed than 75% of the *study treated* population becoming completely average *among the study treated population*"?

[D-Machine]

Nope, you can't say how many people return to average from standardized effect sizes. I wish we had a standardized effect size that was more useful and actually meant something. Cohen actually proposed something called a U3 statistic that told us the percent overlap of two distributions, but that still doesn't tell us anything meaningful about practical significance.

You can't make decisions / determine clinical value from standardized effect sizes sadly, so when I see studies like this, my assumption is unfortunately that the researchers care only about publishing, and not about making their findings useful :(

[D-Machine]

It means nothing, standardized effect sizes have no clinical meaning here, they are purely statistical. To measure if these kinds of changes matter, you need to determine the Minimal (Clinically) Important Difference [1-2]. I.e. can clinicians (or patients) even notice the observed statistical difference.

In practice, this is a change of about 3-5 points on most 20+ item rating scales, or a relative reduction of 20-30% of the total (sum) score of the scale [1-2]. Unfortunately, anti-depressants are under or just barely reach this threshold [3-4], and so should be widely to be considered ineffective or only borderline effective, on average. Of course this is complicated by the fact that some people get worse on these treatments, and some people experience dramatic improvements, but, still, the point is, depression is extremely hard to treat.

Unfortunately, this also means that if exercise is only nearly as effective as therapy for depression, it may mean that the benefits of exercise are not actually really clinically observable, if measured properly and not just based on arbitrary statistical significance.

EDIT: There is less data on MCIDs for therapy, but at least one review suggests therapy effects can be in the 10+ point range [5]. But the way the exercise study is presented, with standardized effect sizes, we have no idea if the results matter at all [6].

[1] Button, et al. (2015). Minimal clinically important difference on the Beck Depression Inventory - II according to the patient’s perspective. Psychological Medicine, 45(15), 3269–3279. https://doi.org/10.1017/S0033291715001270 [https://www.cambridge.org/core/journals/psychological-medici...]

[2] Masson, S. C., & Tejani, A. M. (2013). Minimum clinically important differences identified for commonly used depression rating scales. Journal of clinical epidemiology, 66(7), 805-807. [https://www.jclinepi.com/article/S0895-4356(13)00056-5/fullt...]

[3] Hengartner, M. P., & Plöderl, M. (2022). Estimates of the minimal important difference to evaluate the clinical significance of antidepressants in the acute treatment of moderate-to-severe depression. BMJ Evidence-Based Medicine, 27(2), 69-73. https://doi.org/10.1136/bmjebm-2020-111600 [https://ebm.bmj.com/content/27/2/69.abstract]

[4] Jakobsen, J. C., Gluud, C., & Kirsch, I. (2020). Should antidepressants be used for major depressive disorder?. BMJ evidence-based medicine, 25(4), 130-130. https://doi.org/10.1136/bmjebm-2019-111238 [https://ebm.bmj.com/content/25/4/130.abstract]

[5] Cuijpers, P., Karyotaki, E., Weitz, E., Andersson, G., Hollon, S. D., & van Straten, A. (2014). The effects of psychotherapies for major depression in adults on remission, recovery and improvement: a meta-analysis. Journal of affective disorders, 159, 118–126. https://doi.org/10.1016/j.jad.2014.02.026 [https://pubmed.ncbi.nlm.nih.gov/24679399/]

[6] Pogrow, S. (2019). How Effect Size (Practical Significance) Misleads Clinical Practice: The Case for Switching to Practical Benefit to Assess Applied Research Findings. The American Statistician, 73(sup1), 223–234. https://doi.org/10.1080/00031305.2018.1549101