Exploring the Use of Pictorial Approaches in the Development of Paediatric Patient-Reported Outcome Instruments: A Systematic Review
Bibliographic record
Abstract
INTRODUCTION: Children may find self-reporting health-related quality of life (HRQoL) using patient-reported outcome measures (PROMs) presented in text-based formats difficult, particularly younger children and children with developmental delays or chronic illness. In such cases, pictorial PROMs (where pictorial representations are used alongside or to replace text) may offer a valid alternative. AIM: This systematic literature review focused on identifying and describing paediatric PROMs that incorporate pictorial approaches, providing children with more effective means to express their HRQoL. METHODS: Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Seven electronic databases were searched from inception to 1 March 2022. There were no country restrictions applied to the search; all English-language studies were considered for inclusion in the review. Characteristics and development methods of the identified pictorial PROMs were evaluated against context-specific good practice guidelines published by The Professional Society for Health Economics and Outcomes Research (ISPOR). RESULTS: A total of 22 paediatric pictorial PROMs, comprising 28 unique versions, were identified. These PROMs were predominantly developed in the USA and the UK, targeting children aged 3-18 years. Likert scales with pictorial anchors, particularly happy-sad faces, were commonly used for response options, appearing in 15 (54%) of the PROMs. Various graphic methods, such as happy-sad faces, cartoons, and thermometers, were adapted to specific content domains. These PROMs covered a wide range of domains, including physical and emotional health and social functioning. Emphasis was placed on content validity, including active child participation in developing pictorial elements. Notably, children's participation was sought during the development of the pictorial elements for 13 (46%) of the PROMs. Various development methods were employed, with 43% of paediatric PROMs using literature reviews, 43% using focus groups, and 32% involving expert consultation. Interviews emerged as the primary method, being employed in 61% of the studies. Additionally, three measures specifically addressed cross-cultural considerations. CONCLUSION: Paediatric pictorial PROMs offer child-friendly tools for assessing HRQoL for application with children who find reading and understanding text-based PROMs challenging. There is some evidence that pictorial PROMs facilitate self-report in this population and improve measurement properties compared to text-only PROMs. Further research is needed to develop, validate, and test paediatric pictorial PROMs, with an emphasis on including children from the inception in the co-design process.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".