Patient-reported outcome measures for paediatric gender-affirming care: A systematic review
Bibliographic record
Abstract
Objectives: Patient needs must be comprehensively measured to offer paediatric gender-affirming care in line with clinical standards. Patient-reported outcome measures (PROMs) are self-report tools that measure outcomes deemed to be of importance to patients. PROMs may assess a single outcome or multiple outcomes simultaneously, such as symptoms, functional ability, and quality of life. This study aims to identify PROMs for paediatric gender-affirming care. Methods: This systematic review is PRISMA-compliant and was prospectively registered on PROSPERO (CRD42023461959). Six databases were searched: PubMed, Embase, MEDLINE, PsycINFO, CINAHL, and Web of Science from inception to December 16, 2022. Articles meeting the following criteria were included: 1) Original article; 2) Administers a formally-developed PROM; 3) Focuses on gender-affirming care; and 4) Focuses on paediatric populations. Screening and data extraction occurred independently and in duplicate. Data extracted include study/demographic information, and details of PROM used. Results: In total, 20 articles were included, representing a total of 5793 paediatric patients undergoing gender-affirming care. Most studies (13, 65%) focused on hormonal gender-affirming care. A total of 38 different PROMs for paediatric gender-affirming care were identified, ranging from 4 to 120 items each (mean 23 items; median 14 items). Most PROMs (n = 22) measured psychological functioning, with eight PROMs measuring quality of life, and three PROMs measuring gender-related concepts (i.e., gender dysphoria/euphoria). Commonly used PROMs include the Utrecht Gender Dysphoria Scale (n = 4; 20%), Body Image Scale (n = 5;25%), and Youth Self-Report (n = 8; 40%). Conclusions: A total of 38 PROMs were identified measuring a range of concepts for paediatric gender-affirming care.
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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 | 0.022 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".