Truckers Drive Their Own Assessment for Obstructive Sleep Apnea: A Collaborative Approach to Online Self-Assessment for Obstructive Sleep Apnea: Difference between revisions
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The aims of this study (in addition to establishing a tool that truck drivers could use to assess their risk for OSA) were to determine if commercial drivers would actually employ an online tool to assess risk, to collect demographic data from self-selected commercial drivers, and to make correlations between drowsy driving and risk factors for OSA. We hypothesized that some truckers would, indeed, use the online tool, and that a large proportion of those who chose to do so would have a high probability for OSA. We hypothesized that those who reported classic OSA symptoms (snoring, sleepiness) would be more likely to report drowsy driving, but that objective data (BMI, hypertension history) would predict sleepy driving better than would subjective data. | The aims of this study (in addition to establishing a tool that truck drivers could use to assess their risk for OSA) were to determine if commercial drivers would actually employ an online tool to assess risk, to collect demographic data from self-selected commercial drivers, and to make correlations between drowsy driving and risk factors for OSA. We hypothesized that some truckers would, indeed, use the online tool, and that a large proportion of those who chose to do so would have a high probability for OSA. We hypothesized that those who reported classic OSA symptoms (snoring, sleepiness) would be more likely to report drowsy driving, but that objective data (BMI, hypertension history) would predict sleepy driving better than would subjective data. | ||
== Methods == | == 3. Methods == | ||
=== 3.1. Survey development and promotion === The survey instrument was a web-based version of the Berlin Questionnaire<sup>[11]</sup> as recommended by the Medical Expert Panel of the Federal Motor Carrier Safety Administration. The Berlin Questionnaire consists of a series of questions about risk factors for sleep apnea, and is presented in three sections (one about sleepiness, one about snoring, and one about BMI and hypertension). We included an automatic BMI calculator to facilitate that part of the data collection. An individual is considered at high risk if positive on 2 of 3 of the sections. This screening instrument was computerized for use on the TFAC-AWAKE website. The survey was promoted through the TFAC’s XM radio, word of mouth and trucking industry press contacts. | |||
=== 3.2. Participants === Participants could take the survey anonymously from any computer. Potential participants accessed the survey by visiting the TFAC-AWAKE website and logged onto the "Sleep Apnea Checker for Drivers" link. (http://awake.truckersforacause.com). Individuals who took the survey were identified only through their computer's IP (Internet Protocol) address; this was done to ensure anonymity and to be sure that each participant completed the survey only once. After completion of the online questionnaire, participants immediately learned whether their Berlin questionnaire score was positive or negative. If their Berlin score was positive, they also received a link to a National Sleep Foundation website list of sleep centers. | |||
=== 3.3. Data Collection === The website link was active for data collection from January 11, 2010 until September 24, 2010. After that point, the link remained active for truckers' continued usage, but it no longer stored data into the data set. This cut-off point for data collection was created because Internet Service Providers may change a user's IP address over time. Some participants may try to "game" the system to manipulate the survey results with multiple completions of the form. The survey window was open for a short time to reduce this threat to the dataset. | |||
=== 3.4. Data Analysis === We applied the R statistical package (http://r-project.org) to construct several logistic regression 13 models on our dataset. We treated the question "Have you ever nodded off or fallen asleep while driving a vehicle?" as a binary response variable. The Berlin question "Has anyone noticed that you quit breathing during your sleep?" had four possible answers, ranging from "Never or nearly never" to "Nearly every day." We transformed this variable to be binary by taking "Never or nearly never" to indicate "No" and any other answer to indicate "Yes". For both response variables (Drowsy Driving and Witnessed Apneas), we generated statistical models using logistic regression and each of the other variables in our study as univariate, independent factors. | |||
Hypertension was also treated as a binary variable, based on yes or no answers to the question, "Do you have high blood pressure?" We treated the ordinal answers to questions such as "How often do you snore?" and "How often do you feel tired or fatigued after you sleep" as continuous variables with the lowest answer ("Never or nearly never") as 0, and the highest answer ("Nearly every day") as 4. We treated these variables as continuous for the ease of reporting the results, but treating them as ordinal variables yields the same interpretation in our sample. | Hypertension was also treated as a binary variable, based on yes or no answers to the question, "Do you have high blood pressure?" We treated the ordinal answers to questions such as "How often do you snore?" and "How often do you feel tired or fatigued after you sleep" as continuous variables with the lowest answer ("Never or nearly never") as 0, and the highest answer ("Nearly every day") as 4. We treated these variables as continuous for the ease of reporting the results, but treating them as ordinal variables yields the same interpretation in our sample. | ||