Related Experiment Video
Updated: Jan 21, 2026
An Experimental Analysis of Children's Ability to Provide a False Report about a Crime
Published on: May 3, 2016
Agreement between a health claims algorithm and parent-reported asthma in young children
Jessica A Omand1, Jonathon L Maguire2,3,4,5,6, Deborah L O'Connor3,7
1Child Health Evaluative Sciences, Peter Gilgan Centre for Research and Learning, The Hospital for Sick Children, Toronto, Ontario, Canada.
Introduction:
Asthma prevalence is commonly measured in national surveys by questionnaire. The Ontario Asthma Surveillance Information System (OASIS) developed a validated health claims diagnosis algorithm to estimate asthma prevalence. The primary objective was to assess the agreement between two approaches of measuring asthma in young children. Secondary objectives were to identify concordant and discordant pairs, and to identify factors associated with disagreement.
Study Design And Setting:
A measurement study to evaluate the agreement between the OASIS algorithm and parent-reported asthma (criterion standard). Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated. Multivariable logistic regression was used to determine factors associated with disagreement.
Results:
Healthy children aged 1 to 5 years (n =3642) participating in the TARGet Kids! practice based research network 2008-2013 in Toronto, Canada were included. Prevalence of asthma was 14% and 6% by the OASIS algorithm and parent-reported asthma, respectively. The Kappa statistic was 0.43, sensitivity 81%, specificity 90%, PPV 34%, and NPV 99%. There were 3249 concordant and 393 discordant pairs. Statistically significant factors associated with asthma identified by OASIS but not parent report included: male sex, higher zBMI, and parent history of asthma. Males were less likely to have asthma identified by parent report but not OASIS.
Conclusion:
The OASIS algorithm identified more asthma cases in young children than parent-reported asthma. The OASIS algorithm had high sensitivity, specificity, and NPV but low PPV relative to parent-reported asthma. These findings need replication in other populations.
Related Concept Videos
00:55Parental Care
01:11Testing a Claim about Mean: Known Population SD
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...
01:27Parenting Styles
Authoritarian Parenting
This style is strict and controlling, with little room for open dialogue. Authoritarian parents demand obedience and often enforce rules with minimal warmth. Children raised this way may lack social skills and initiative, usually comparing themselves to others unfavorably.
Authoritative...
01:29Asthma-I: Introduction
01:24Testing a Claim about Population Proportion
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
01:19Testing a Claim about Standard Deviation
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...