Evidence map›Paper›PMID 38902672›Full record

ArticleBMC medical research methodology2024

Developing survey weights to ensure representativeness in a national, matched cohort study: results from the children and young people with Long Covid (CLoCk) study.

Natalia K Rojas, Bianca L De Stavola, Tom Norris, Mario Cortina-Borja, Manjula D Nugawela, Dougal Hargreaves, Emma Dalrymple, Kelsey McOwat, Ruth Simmons, Terence Stephenson and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. "Clinical child psychology and psychiatry · 2024
    Article
  6. Observational
  7. Article
  8. Article
  9. Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Natalia K RojasDivision of Surgery & Interventional Science, Faculty of Medical Sciences, University College London, London, WC1E 6BT, UK. n.rojas@ucl.ac.uk.
Bianca L De StavolaUCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK.
Tom NorrisDivision of Surgery & Interventional Science, Faculty of Medical Sciences, University College London, London, WC1E 6BT, UK.
Mario Cortina-BorjaUCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK.
Manjula D NugawelaUCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK.
Dougal HargreavesMohn Centre for Children's Health & Wellbeing, School of Public Health, Imperial College London, London, UK.
Emma DalrympleUCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK.
Kelsey McOwatImmunisation Department, Health Security Agency, 61 Colindale Avenue, London, NW9 5EQ, UK.
Ruth SimmonsImmunisation Department, Health Security Agency, 61 Colindale Avenue, London, NW9 5EQ, UK.
Terence StephensonUCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK.
Roz ShafranUCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, WC1N 1EH, UK.
CLoCk Consortium
Snehal M Pinto PereiraDivision of Surgery & Interventional Science, Faculty of Medical Sciences, University College London, London, WC1E 6BT, UK.

Funding

NIHR and UKRI COVLT0022UK Medical Research Council MR/P020372/1
6 · The paper itself

Abstract

backgroundFindings from studies assessing Long Covid in children and young people (CYP) need to be assessed in light of their methodological limitations. For example, if non-response and/or attrition over time systematically differ by sub-groups of CYP, findings could be biased and any generalisation limited. The present study aimed to (i) construct survey weights for the Children and young people with Long Covid (CLoCk) study, and (ii) apply them to published CLoCk findings showing the prevalence of shortness of breath and tiredness increased over time from baseline to 12-months post-baseline in both SARS-CoV-2 Positive and Negative CYP.

methodsLogistic regression models were fitted to compute the probability of (i) Responding given envisioned to take part, (ii) Responding timely given responded, and (iii) (Re)infection given timely response. Response, timely response and (re)infection weights were generated as the reciprocal of the corresponding probability, with an overall 'envisioned population' survey weight derived as the product of these weights. Survey weights were trimmed, and an interactive tool developed to re-calibrate target population survey weights to the general population using data from the 2021 UK Census.

resultsFlexible survey weights for the CLoCk study were successfully developed. In the illustrative example, re-weighted results (when accounting for selection in response, attrition, and (re)infection) were consistent with published findings.

conclusionsFlexible survey weights to address potential bias and selection issues were created for and used in the CLoCk study. Previously reported prospective findings from CLoCk are generalisable to the wider population of CYP in England. This study highlights the importance of considering selection into a sample and attrition over time when considering generalisability of findings.

Indexed as

COVID-19SARS-CoV-2AdolescentChildChild, PreschoolCohort StudiesFemaleHumansLogistic ModelsMalePost-Acute COVID-19 SyndromePrevalenceSurveys and QuestionnairesUnited KingdomYoung AdultAttritionChildren and young peopleLong covidLoss to follow-upMatched cohort studyPost Covid ConditionRepresentativenessSelection biasSurvey weights

Identifiers

PMID38902672
PMCPMC11188173

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.