Healthcare professionals’ understanding of children’s rights: a systematic review of the empirical evidence-base
Bibliographic record
Abstract
BACKGROUND: The concept of children's rights emerged during the 1980s and emphasised the role of children as active participants in matters which concern them. AIM: This review aims to identify and synthesise the empirical evidence base on healthcare professionals' (HCPs) understanding of children's rights. METHODS: Five electronic databases (PubMed, CINAHL, Embase, PsycINFO, and the Web of Science) were systematically searched in May 2023. The Mixed Methods Appraisal Tool (MMAT) was used to quality appraise full-text papers included in the review. A descriptive narrative synthesis of the studies' findings was performed. RESULTS: A total of 15 relevant studies from 10 countries were identified and included in the review. The number of participants included ranged from 6 to 1048 for HCPs with a broad range of sampling methods. Based on the narrative synthesis of the included studies, three main themes were identified: (1) Barriers to implementing children's rights in healthcare, (2) Factors that contribute to children's rights implementation, and (3) Study instruments used to measure outcomes. CONCLUSIONS: HCPs require a better understanding of children's rights to implement these rights into practice. Listening to children, building trusting relationships with children, and continuing professional development of HCPs could help to address barriers to understanding children's rights. There is a pressing need for the development of a tool that is capable of tracking changes in the understanding of children's rights in healthcare environments as efforts to increase awareness become more widely recognised.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".