OBJECTIVES: To create a profile of individuals nonadherent to their medications in an age-stratified sample (ages 34-84) of community-dwelling rheumatoid arthritis patients. The relative contributions of age, cognitive function, disability, emotional state, lifestyle, and beliefs about illness to nonadherence were assessed. DESIGN: A direct observation approach was used in conjunction with structural equation modeling. All participants were administered a preliminary assessment battery. Medications were then transferred to vials with microelectronic caps that recorded medication events for all medications for the next 4 weeks. PARTICIPANTS AND SETTING: A volunteer sample of 121 community-dwelling rheumatoid arthritis (RA) patients were recruited from newspaper ads, posters, and via informal physician contact from private rheumatology practices in Atlanta and Athens, Georgia. Written verification of the RA diagnosis and a disease severity rating were obtained from personal physicians before patients were enrolled in the study. Patients were tested in a private physician's office, and their medication adherence was monitored electronically for a month in their every-day work and home settings. MEASUREMENTS AND RESULTS: Structural equation modeling techniques were used to develop a model of adherence behavior. Cognitive and psychosocial measures were used to construct latent variables to predict adherence errors. The model of medication adherence explained 39% of the variance in adherence errors. The model demonstrated that older adults made the fewest adherence errors, and middle-aged adults made the most. A busy lifestyle, age, and cognitive deficits predicted nonadherence, whereas coping with arthritis-related moods predicted adherence. Illness severity, medication load, and physical function did not predict adherence errors. Omission of medication accounted for nearly all errors. CONCLUSION: Despite strong evidence for normal, age-related cognitive decline in this sample, older adults had sufficient cognitive function to manage medications. A busy lifestyle and middle age were more determinant of who was at risk of nonadherence than beliefs about medication or illness. Thus, practicing physicians should not assume that older adults have insufficient cognitive resources to manage medications and that they will be the most likely to make adherence errors. Very busy middle-aged adults seem to be at the greatest risk of managing medications improperly.
OBJECTIVES: To create a profile of individuals nonadherent to their medications in an age-stratified sample (ages 34-84) of community-dwelling rheumatoid arthritispatients. The relative contributions of age, cognitive function, disability, emotional state, lifestyle, and beliefs about illness to nonadherence were assessed. DESIGN: A direct observation approach was used in conjunction with structural equation modeling. All participants were administered a preliminary assessment battery. Medications were then transferred to vials with microelectronic caps that recorded medication events for all medications for the next 4 weeks. PARTICIPANTS AND SETTING: A volunteer sample of 121 community-dwelling rheumatoid arthritis (RA) patients were recruited from newspaper ads, posters, and via informal physician contact from private rheumatology practices in Atlanta and Athens, Georgia. Written verification of the RA diagnosis and a disease severity rating were obtained from personal physicians before patients were enrolled in the study. Patients were tested in a private physician's office, and their medication adherence was monitored electronically for a month in their every-day work and home settings. MEASUREMENTS AND RESULTS: Structural equation modeling techniques were used to develop a model of adherence behavior. Cognitive and psychosocial measures were used to construct latent variables to predict adherence errors. The model of medication adherence explained 39% of the variance in adherence errors. The model demonstrated that older adults made the fewest adherence errors, and middle-aged adults made the most. A busy lifestyle, age, and cognitive deficits predicted nonadherence, whereas coping with arthritis-related moods predicted adherence. Illness severity, medication load, and physical function did not predict adherence errors. Omission of medication accounted for nearly all errors. CONCLUSION: Despite strong evidence for normal, age-related cognitive decline in this sample, older adults had sufficient cognitive function to manage medications. A busy lifestyle and middle age were more determinant of who was at risk of nonadherence than beliefs about medication or illness. Thus, practicing physicians should not assume that older adults have insufficient cognitive resources to manage medications and that they will be the most likely to make adherence errors. Very busy middle-aged adults seem to be at the greatest risk of managing medications improperly.
Authors: Natalia Mena-Vazquez; Sara Manrique-Arija; Lucía Yunquera-Romero; Inmaculada Ureña-Garnica; Marta Rojas-Gimenez; Carla Domic; Francisco Gabriel Jimenez-Nuñez; Antonio Fernandez-Nebro Journal: Rheumatol Int Date: 2017-06-19 Impact factor: 2.631
Authors: M Vervloet; P Spreeuwenberg; M L Bouvy; E R Heerdink; D H de Bakker; L van Dijk Journal: Eur J Clin Pharmacol Date: 2013-04-16 Impact factor: 2.953