Evidence map›Paper›PMID 32552880›Full record

ArticleBMC pulmonary medicine2020

Data driven decision making to characterize clinical personas of parents of children with cystic fibrosis: a mixed methods study.

Rhonda D Szczesniak, Teresa Pestian, Leo L Duan, Dan Li, Sophia Stamper, Brycen Ferrara, Elizabeth Kramer, John P Clancy, Daniel Grossoehme

Abstract read
In one paragraph

Article in BMC pulmonary medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Rhonda D SzczesniakDivision of Biostatistics & Epidemiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave (MLC 5041), Cincinnati, OH, 45229, USA. rhonda.szczesniak@cchmc.org.ORCID http://orcid.org/0000-0003-0705-715X
Teresa PestianDivision of Biostatistics & Epidemiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave (MLC 5041), Cincinnati, OH, 45229, USA.
Leo L DuanDepartment of Statistics, University of Florida, Gainesville, FL, USA.
Dan LiAlzheimer's Therapeutic Research Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Sophia StamperDivision of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, USA.
Brycen FerraraDivision of Pediatric & Adolescent Gynecology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Elizabeth KramerDivision of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, USA.
John P ClancyDivision of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, USA.
Daniel GrossoehmeHaslinger Family Pediatric Palliative Care Center, Akron Children's Hospital, Akron, OH, USA.

Funding

R01- Mapping environmental contributions to rapid lung disease progression in cystic fibrosisR01HL141286 · NHLBI · CINCINNATI CHILDRENS HOSP MED CTR · PI SZCZESNIAK, RHONDA · 2019 to 2023
$2.3M
Preventing rapid decline in CF: statistical research career commitmentK25HL125954 · NHLBI · CINCINNATI CHILDRENS HOSP MED CTR · PI SZCZESNIAK, RHONDA · 2015 to 2019
$762k
Parental adherence to CF homecare: research chaplaincy career commitmentK23HD062642 · NICHD · CINCINNATI CHILDRENS HOSP MED CTR · PI GROSSOEHME, DANIEL HUCK · 2010 to 2014
$549k
NHLBI NIH HHS K25 HL125954NHLBI NIH HHS R01 HL141286NICHD NIH HHS K23 HD062642
6 · The paper itself

Abstract

backgroundBeginning at a young age, children with cystic fibrosis (CF) embark on demanding care regimens that pose challenges to parents. We examined the extent to which clinical, demographic and psychosocial features inform patterns of adherence to pulmonary therapies and how these patterns can be used to develop clinical personas, defined as aspects of adherence barriers that are presented by parents and/or perceived by clinicians, in order to enhance personalized CF care delivery.

methodsWe undertook an explanatory sequential mixed-methods study consisting of i) multivariate clustering to create clusters corresponding to parental adherence patterns (quantitative phase); ii) parental participant interviews to create clinical personas interpreted from clustering (qualitative phase). Clinical, demographic and psychosocial features were used in supervised clustering against clinical endpoints, which included adherence to airway clearance and aerosolized medications and self-efficacy score, which was used as a feature for modeling adherence. Clinical implications were developed for each persona by combing quantitative and qualitative data (integration phase).

resultsThe quantitative phase showed that the 87 parent participants were segmented into three distinct patterns of adherence based on use of aerosolized medication and practice of airway clearance. Patterns were primarily influenced by self-efficacy, distance to CF care center and child BMI percentile. The two key patterns that emerged for the self-efficacy model were most heavily influenced by distance to CF care center and child BMI percentile. Eight clinical personas were developed in the qualitative phase from parent and clinician participant feedback of latent components from these models. Findings from the integration phase include recommendations to overcome specific challenges with maintaining treatment regimens and increasing support from social networks.

conclusionsAdherence patterns from multivariate models and resulting parent personas with their corresponding clinical implications have utility as clinical decision support tools and capabilities for tailoring intervention study designs that promote adherence.

Indexed as

Decision MakingPatient ComplianceSelf EfficacyBayes TheoremChildChild, PreschoolCluster AnalysisCystic FibrosisFemaleHumansInterviews as TopicMaleMultivariate AnalysisParentsBayesianClusteringCystic fibrosisHealth-care analyticsHealth-care deliveryMixed methodsPersonalized medicineStatistical learningTheory of reasoned action

Identifiers

PMID32552880
PMCPMC7301999

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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.