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Happ, M. B.
9/1/03 - 6/30/08
5 R01 HD043988-03 NIH
Improving Communication with NonSpeaking ICU Patients
Critically ill patients are often unable to speak as a result
of respiratory tract intubation for airway management and
mechanical ventilation, which can be a traumatic life event
that is frightening, reduces patient participation in care
and decision-making, and impairs pain and symptom assessment.
No large scale communication intervention studies have been
conducted in the intensive care unit (ICU) setting.
To date,
no studies have tested the effectiveness of teaching nurses
to be facilitative communication partners of temporarily nonspeaking
patients in ICU settings. The specific aims of this study
are to:
1) test the impact of two experimental interventions:
(a) communication skills training (BCST) for nurses and (b)
AAC techniques and education for nurses with individualized
speech language pathologist consultation (AAC/SLP), on the
ease, quality, frequency, and success of communications between
nurses and nonspeaking ICU patients.
2) Compare the effects
of BCST and AAC-SLP training with a control (usual care) cohort.
This study is a prospective field experiment using a quasi-experimental
cohort design conducted in two intensive care units, medical
ICU and cardiothoracic ICU. The sample will be equally distributed
between units. Three cohorts of 30 patient participants each
and their respective nurse caregivers will be enrolled as
participants (10 RNs for each cohort; 30 total nurses, and
90 total nurse-patient dyads). Conditions will be implemented
in sequential order (control, BCST, AAC-SLP) to prevent contamination
from other intervention conditions and to systematically investigate
the effect of the intervention components. Trained observers
will measure the frequency of nurse facilitative behaviors
(quality), number of communication exchanges (frequency),
number of successful exchanges, and rate communication ease
across 4 observation sessions (2 per day) with each nurse-patient
dyad. Primary covariates include severity of illness, level
of consciousness, and physical restraint use. Statistical
analysis will involve hierarchical generalized linear modeling
(HGLM) by outcome groups and planned group comparisons using
linear contrasts within the context of the HGLM.
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