TY - JOUR
T1 - Attempters, adherers, and non-adherers
T2 - Latent profile analysis of CPAP use with correlates
AU - Wohlgemuth, William K.
AU - Chirinos Medina, Diana Andrea
AU - Domingo, Samantha
AU - Wallace, Douglas M.
N1 - Publisher Copyright:
© 2014 Elsevier B.V.
PY - 2015/3/1
Y1 - 2015/3/1
N2 - Study objectives: To examine whether subtypes of continuous positive airway pressure (CPAP) user profiles could be identified, and to determine predictors of CPAP subgroup membership. Design: A retrospective, correlational approach was used. Subjects attended clinic where a CPAP download was performed and questionnaires were completed. Additional information was obtained from the electronic medical record. Setting: Miami VA Sleep Clinic. Participants: Obstructive sleep apnea patients (N = 207). Measurements: Three adherence variables comprised the profile: % of nights of CPAP use, % of nights of CPAP use > 4 hours and average nightly use in minutes. Predictors included age, AHI, time since CPAP therapy was initiated, CPAP pressure, residual AHI, BMI, social-cognitive variables, insomnia, sleepiness, and psychiatric and medical comorbidities. Results: Latent profile analysis was used to identify CPAP user profiles. Three subgroups were identified and labeled "Non-Adherers," "Attempters," and "Adherers". Non-Adherers (37.6% of the sample) used CPAP for an average of 37 minutes nightly, used CPAP 18.2% of nights and used CPAP > 4 hour 6.2 % of nights. Attempters (32.9%) used CPAP for 156 minutes on average, used CPAP 68.2% of nights and used CPAP > 4 hour 29.3% of nights. Adherers (29.5%) used CPAP for 392 minutes, used CPAP 95.4% of nights and used CPAP >4 hour 86.2% of nights. Self-efficacy, insomnia, AHI, time since CPAP was initiated, and CPAP pressure predicted CPAP subgroup membership. Conclusion: Sixty-seven percent of users (Non-Adherers, Attempters) had suboptimal adherence. Understanding CPAP use profiles and their predictors enable identification of those who may require additional intervention to improve adherence.
AB - Study objectives: To examine whether subtypes of continuous positive airway pressure (CPAP) user profiles could be identified, and to determine predictors of CPAP subgroup membership. Design: A retrospective, correlational approach was used. Subjects attended clinic where a CPAP download was performed and questionnaires were completed. Additional information was obtained from the electronic medical record. Setting: Miami VA Sleep Clinic. Participants: Obstructive sleep apnea patients (N = 207). Measurements: Three adherence variables comprised the profile: % of nights of CPAP use, % of nights of CPAP use > 4 hours and average nightly use in minutes. Predictors included age, AHI, time since CPAP therapy was initiated, CPAP pressure, residual AHI, BMI, social-cognitive variables, insomnia, sleepiness, and psychiatric and medical comorbidities. Results: Latent profile analysis was used to identify CPAP user profiles. Three subgroups were identified and labeled "Non-Adherers," "Attempters," and "Adherers". Non-Adherers (37.6% of the sample) used CPAP for an average of 37 minutes nightly, used CPAP 18.2% of nights and used CPAP > 4 hour 6.2 % of nights. Attempters (32.9%) used CPAP for 156 minutes on average, used CPAP 68.2% of nights and used CPAP > 4 hour 29.3% of nights. Adherers (29.5%) used CPAP for 392 minutes, used CPAP 95.4% of nights and used CPAP >4 hour 86.2% of nights. Self-efficacy, insomnia, AHI, time since CPAP was initiated, and CPAP pressure predicted CPAP subgroup membership. Conclusion: Sixty-seven percent of users (Non-Adherers, Attempters) had suboptimal adherence. Understanding CPAP use profiles and their predictors enable identification of those who may require additional intervention to improve adherence.
KW - Adherence
KW - Continuous positive airway pressure
KW - Latent profile analysis
KW - Obstructive sleep apnea
KW - Veterans
UR - http://www.scopus.com/inward/record.url?scp=84925246297&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84925246297&partnerID=8YFLogxK
U2 - 10.1016/j.sleep.2014.08.013
DO - 10.1016/j.sleep.2014.08.013
M3 - Article
C2 - 25441752
AN - SCOPUS:84925246297
SN - 1389-9457
VL - 16
SP - 336
EP - 342
JO - Sleep Medicine
JF - Sleep Medicine
IS - 3
ER -