Evidence map›Paper›PMID 27826961›Full record

ArticleAllergy, asthma & immunology research2017

Development and Validation of an Attitudinal-Profiling Tool for Patients With Asthma.

Aileen David-Wang, David Price, Sang Heon Cho, James Chung Man Ho, Chong Kin Liam, Glenn Neira, Pei Li Teh, REcognise Asthma and LInk to Symptoms and Experience (REALISE) Asia Working Group

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Article in Allergy, asthma & immunology research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Aileen David-WangSection of Pulmonary Medicine, University of the Philippines-Philippine General Hospital, Manila, Philippines. asdavidwang1@up.edu.ph.
David PriceCentre of Academic Primary Care, University of Aberdeen, Aberdeen, UK.
Sang Heon ChoCollege of Medicine, Seoul National University, Seoul, Korea.
James Chung Man HoDepartment of Medicine, University of Hong Kong, Hong Kong Special Administrative Region, China.
Chong Kin LiamFaculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia.
Glenn NeiraMedical Affairs Department, Mundipharma Pte Ltd, Singapore.
Pei Li TehResearch Partnership Pte Ltd, Singapore.
REcognise Asthma and LInk to Symptoms and Experience (REALISE) Asia Working Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo develop a profiling tool which accurately assigns a patient to the appropriate attitudinal cluster for the management of asthma.

methodsAttitudinal data from an online survey of 2,467 patients with asthma from 8 Asian countries/region, aged 18-50 years, having had ≥2 prescriptions in the previous 2 years and access to social media was used in a discriminant function analysis to identify a minimal set of questions for the Profiling Tool. A split-sample procedure based on 100 sets of randomly selected estimation and validation sub-samples from the original sample was used to cross-validate the Tool and assess the robustness of its predictive accuracy.

resultsOur Profiling Tool contained 10 attitudinal questions for the patient and 1 GINA-based level of asthma control question for the physician. It achieved a predictive accuracy of 76.2%. The estimation and validation sub-sample accuracies of 76.7% and 75.3%, respectively, were consistent with the tool's predictive accuracy at 95% confidence level; and their 1.4 percentage-points difference set upper-bound estimate for the degree of over-fitting.

conclusionsThe Profiling Tool is highly predictive (>75%) of the attitudinal clusters that best describe patients with asthma in the Asian population. By identifying the attitudinal profile of the patient, the physician can make the appropriate asthma management decisions in practice. The challenge is to integrate its use into the consultation workflow and apply to areas where Internet resources are not available or patients who are not comfortable with the use of such technology.

Indexed as

AsiaAsthmadiscriminant analysisdisease management

Identifiers

PMID27826961
PMCPMC5102835

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