Objective: To determine whether video-based coping skills (VCS) training with telephone coaching reduces psychosocial and biological markers of distress in primary caregivers of a relative with Alzheimer's disease or related dementia (ADRD).
Methods: A controlled clinical trial was conducted with 116 ADRD caregivers who were assigned, alternately as they qualified for the study, to a Wait List control condition or the VCS training arm in which they viewed two modules/week of a version of the Williams LifeSkills Video adapted for ADRD family care contexts, did the exercises and homework for each module presented in an accompanying Workbook, and received one telephone coaching call per week for 5 weeks on each week's two modules. Questionnaire-assessed depressive symptoms, state and trait anger and anxiety, perceived stress, hostility, caregiver self-efficacy, salivary cortisol across the day and before and after a stress protocol, and blood pressure and heart rate during a stress protocol were assessed before VCS training, 7 weeks after training was completed, and at 3 months' and 6 months' follow-up.
Results: Compared with controls, participants who received VCS training plus telephone coaching showed significantly greater improvements in depressive symptoms, trait anxiety, perceived stress, and average systolic and diastolic blood pressures that were maintained over the 6-month follow-up period.
Conclusions: VCS training augmented by telephone coaching reduced psychosocial and biological indicators of distress in ADRD caregivers. Future studies should determine the long-term benefits to mental and physical health from this intervention.
Trial Registration: http://www.clinicaltrials.gov; #NCT00396825.
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http://dx.doi.org/10.1097/PSY.0b013e3181fc2d09 | DOI Listing |
Clin Pediatr (Phila)
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Department of Biochemistry, School of Medicine, Marmara University, Istanbul, Turkey.
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Australian Catholic University, North Sydney, NSW, Australia.
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Tor Vergata University of Rome, Department of Chemical Sciences and Technologies, Rome 00133, Italy.
A consistent part of gas sensor research activities aims to improve sensing performances by synthesizing new sensing materials, improving the selection of elements in arrays, and optimizing the feature extraction and classification algorithms. This paper combines most of these aspects to confer selectivity to a low-selectivity sensor by using feature extraction algorithms applied to the sensor response kinetics. Several algorithms were employed to represent the kinetic behavior of the sensor response during the adsorption and desorption phases.
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