Evidence map›Paper›PMID 36322119›Full record

ArticleJMIR pediatrics and parenting2022

Data Completeness and Concordance in the FeverApp Registry: Comparative Study.

Larisa Rathjens, Ingo Fingerhut, David Martin, Sara Hamideh Kerdar, Moritz Gwiasda, Silke Schwarz, Ekkehart Jenetzky

Abstract read
In one paragraph

Article in JMIR pediatrics and parenting, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Observational
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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

7 authors.

Larisa RathjensFaculty of Health/School of Medicine, Witten/Herdecke University, Witten, Germany.ORCID https://orcid.org/0000-0002-6229-3262
Ingo FingerhutPediatric Office Kleiner Piks, Bochum, Germany.ORCID https://orcid.org/0000-0002-4577-9391
David MartinFaculty of Health/School of Medicine, Witten/Herdecke University, Witten, Germany.ORCID https://orcid.org/0000-0002-4279-3032
Sara Hamideh KerdarFaculty of Health/School of Medicine, Witten/Herdecke University, Witten, Germany.ORCID https://orcid.org/0000-0001-7479-8607
Moritz GwiasdaFaculty of Health/School of Medicine, Witten/Herdecke University, Witten, Germany.ORCID https://orcid.org/0000-0002-4104-8823
Silke SchwarzFaculty of Health/School of Medicine, Witten/Herdecke University, Witten, Germany.ORCID https://orcid.org/0000-0003-2567-2797
Ekkehart JenetzkyFaculty of Health/School of Medicine, Witten/Herdecke University, Witten, Germany.ORCID https://orcid.org/0000-0001-5415-8784

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe FeverApp registry uses ecological momentary assessment (EMA) to collect parental data on pediatric fever for scientific research. The mobile app FeverApp educates parents on safe fever management and serves as a fever diary.

objectiveThe focus of this study was to evaluate the completeness and concordance of the EMA-based FeverApp registry with regard to its data quality from a multilevel perspective.

methodsStructured descriptions of fever episodes by health care professionals from an office were used as reference. The number of children, their sociodemographic data, and agreement of fever episodes, with maximum temperature, intake of antipyretics and antibiotics, and physician visits, were compared with the entries in the corresponding physician's reference records. The data quality indicators for completeness, meaning the extent to which the necessary data for the registry has actually been submitted, and concordance, which is the correspondence of the value of a data element with a reference source, were chosen to analyze whether EMA may be a suitable method for this kind of registry.

resultsIn both data sources, 1012 children were available for comparison over 16 months. The completeness of gender (1012/1012, 100%) and date of birth (1004/1012, 99.2%) information was high, and the mismatches were 0.69% (7/1012) and 1.19% (12/1012), respectively, between the sources. Of these 1012 children, 668 (66%) registered fever episodes in FeverApp. They relate to 534 families with 953 fever episodes in the reference records and 1452 episodes in the FeverApp registry. Of the 534 families, 183 (34.3%) refrained from visiting the office during fever episodes but nevertheless documented them in FeverApp. Largest part (766/1452, 52.75%) episodes were recorded exclusively in the FeverApp registry by 371 (371/534, 69.5%) families. The remaining 686 (47.2%) episodes of 391 (58.5%) children from 351 (65.7%) families were comparable with the reference data source in terms of physician visits, medication, and temperature. The completeness ranged, depending on the kind of variable, from 11.5% to 65% in the registry and from 7.6% to 42.6% in the office. The 953 fever episodes reported by the reference office consisted of 681 (71.5%) acute and 272 (28.5%) past episodes. In FeverApp, most past (262/272, 96.3%) but less acute (424/681, 62.3%) episodes have been entered. The concordance rates were varied: 90.2% for antibiotic use, 66.6% for antipyretic use, 61.7% for physician visits, and 16% for the highest temperature during the fever episode.

conclusionsBoth sources delivered only partial data, and the rates of completeness and concordance depended on the kind of variable. However, the FeverApp registry showed higher documentation and precision rates than professional records for all considered variables. Therefore, EMA may play a unique supplement for research in ambulatory care. FeverApp could support pediatric offices, especially during the pandemic.

Indexed as

completenessconcordancedata qualityecological momentary assessmentregistry

Identifiers

PMID36322119
PMCPMC9669892

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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.