Gender-affirming hormone treatment and cognitive function in transgender young adults: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Previous studies have examined whether steroid hormone treatment in transgender individuals may affect cognitive function; yet, their limited power does not allow firm conclusions to be drawn. We leveraged data from to-date literature aiming to explore the effect of gender-affirming hormone administration on cognitive function in transgender individuals. METHODS: A search strategy of MEDLINE was developed (through June 1, 2019) using the key terms transgender, hormone therapy and cognitive function. Eligible were (i) cohort studies examining the longitudinal effect of hormone therapy on cognition, and (ii) cross-sectional studies comparing the cognitive function between treated and non-treated individuals. Standardized mean differences (Hedges' g) were pooled using random-effects models. Study quality was evaluated using the Newcastle-Ottawa Scale. OUTCOMES: Ten studies (seven cohort and three cross-sectional) were eligible representing 234 birth-assigned males (aM) and 150 birth-assigned females (aF). The synthesis of cohort studies (n = 5) for visuospatial ability following hormone treatment showed a statistically significant enhancement among aF (g = 0.55, 95% confidence intervals [CI]: 0.29, 0.82) and an improvement with a trend towards statistical significance among aM (g = 0.28, 95%CI: -0.01, 0.58). By contrast, no adverse effects of hormone administration were shown. No heterogeneity was evident in most meta-analyses. INTERPRETATION: Current evidence does not support an adverse impact of hormone therapy on cognitive function, whereas a statistically significant enhancing effect on visuospatial ability was shown in aF. New longitudinal studies with longer follow-up should explore the long-term effects of hormone therapy, especially the effects on younger individuals, where there is greater scarcity of data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.022 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".