Clinical Trial Details
— Status: Completed
Administrative data
NCT number |
NCT04165213 |
Other study ID # |
831688 |
Secondary ID |
|
Status |
Completed |
Phase |
N/A
|
First received |
|
Last updated |
|
Start date |
June 28, 2021 |
Est. completion date |
May 31, 2024 |
Study information
Verified date |
June 2024 |
Source |
University of Pennsylvania |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Interventional
|
Clinical Trial Summary
The protocol is organized into three Phases - In Phase I an online training program will be
developed in "Care of Persons with Dementia in their Environments" (COPE) -an evidence-based
bio-behavioral dementia program -using state-of-the science simulation and best online
learning practices. In addition an automated approach to fidelity monitoring using
computational linguistics (automatic classification programs) will be developed. In Phase II,
ten long term care community-based (PACE) organizations will be randomized into two groups; 5
PACE organizations will serve as the "control" site in which staff training will be provided
via the traditional high intensity face-to-face training in the COPE program. 5 PACE
organizations will serve as the comparison and staff will be trained using the online COPE
training program. Phase II will evaluate the whether an online training program is the same
or better in improving PACE staff competency and fidelity to COPE principles and protocols
compared to a high intensity face-to-face traditional form of training. In Phase III the
efficacy of the COPE program on PACE participant outcomes by type of COPE training will be
evaluated. Each of the PACE organizations will enroll 5 persons with dementia and their
caregivers in the study. This will yield 50 family dyads (25 dyads in traditional training
sites and 25 dyads in online training sites). Dyads will be followed for 4 months.
Non-inferiority analysis will be used to assess whether dyads will yield the same or better
outcomes regardless of how PACE staff were trained.
Description:
PHASE 1a - The Online Training Program - We will develop ten self-paced online learning
modules. These modules will enable OTs and RNs to participant to have anytime/anywhere access
to content and activities to aid their learning. The modules will include rich multimedia
content and interactive assessments to keep the learner engaged. The modules will allow for
easy packaging of the content into the latest interoperability standards for such content
including the latest Shareable Content Object Reference Model (SCORM) specifications, which
will allow for repurposing and sharing with other institutions.
To accommodate diversity of learning needs, the modules will be designed using a
hyperlearning model with four dimensions. The general principles will begin with the module
learning objectives and follow with a review of core concepts and required and/or
self-directed learning activities. The mini-lecture component of the modules will include
information on the major concepts of the module. Since the modules will be self-paced, the
learner can take his/her time going through them and perform in the embedded interactive
learning activities. The clinical reasoning dimension will provide the learner with an
opportunity for problem-solving and clinical decision-making. This dimension will contain
vignettes and case studies with questions requiring analysis and synthesis. The final
dimension will be evaluation/ assessment of learning outcomes. This dimension will use
teacher-made and standardized pre-and post-tests to assess attainment of specified learning
outcomes. The self-paced modules will be highly interactive featuring integrated multimedia
content, assessments, and learner evaluations to allow PACE staff to engage with the content
at a high level and practice application in simulated scenarios. Each module will require
approximately 45-60 minutes/module for the learner to complete. Participants can use the
modules separately at different times throughout a training curriculum or they can be
assigned at the beginning of a training time by having this information front-loaded.
To develop the modules, we will work intensely in year 01 with an instructional design team
at Drexel University with specialists in dementia care, the COPE program and experts in
simulation, use of standardized patients, and training of nurses and other health
professionals from Penn, Trinity Health and Jefferson. We anticipate the modules to contain
the following content: module 1 - introduction to COPE program, research evidence, and core
principles underlying the program; module 2 - overview of delivery characteristics, role of
RN and OT, three phases (assessment, implementation, generalizability) of the COPE program,
permissible adaptations; module 3 and 4-assessment phase, introduction to clinical interview
and all assessments and forms; module 5 and 6- implementation phase including helping
caregiver identify 3 problem areas, engaging in problem solving and brainstorming, developing
and providing an assessment report and offering prescriptions (strategies) for each
identified problem area; module 7 and 8 - generalizability phase or helping caregivers use
strategies for one problem area to address another and planning for the future; module 9-
developing rapport and working with family caregivers from different backgrounds, cultures,
living environments and relationships and helping families balance caregiving with other life
roles, adjusting approach by level of readiness; module 10 - challenging cases, motivational
interviewing, how to explain the program, how to meet caregivers where they are at and
provide validation and support.
Scripts for each module will be developed and shared with OTs/RNs who are not part of the
study but work within Trinity PACE programs. This will allow for continuous feedback loops to
assure that the scenarios meet the needs of PACE staff. We will compare the online program to
our traditional 3-day face-to-face training currently used with COPE.
The 3-day training program will be conducted by Dr. Piersol using a slide deck and case
presentations as we have previously done. The comparison of the two training programs is
described in Phase 2 and 3 below.
PHASE 1b -The Fidelity Monitoring Program- We seek to develop a scalable approach to assess
fidelity to the COPE Program when it is implemented in a real-world setting such as PACE
using computational linguistics techniques (e.g. natural language processing). The essence of
fidelity to the Core Principles of COPE program will be captured by using automatic
classification programs that evaluate both the content that should be included in COPE
sessions, and the style of delivery. While automatic classification programs have been
applied to measure quality metrics of transcribed narratives in the field of psychotherapy
(21), it has not been used to measure other aspects of quality- namely fidelity to
evidence-based practices or dementia care and caregiver supportive programs. The development
of the automated Fidelity Monitoring Program will occur in three steps and will be carried
out by a technical team consisting of an expert in content analysis, Dr. Ani Nenkova, and a
consultant expert in speech recognition and prosody, Dr Mari Ostendorf. Co- I Nenkova has
worked extensively on automatic summarization, evaluation of automatic summarization and
readability and linguistic style. The ultimate goal of our efforts is to develop a system
that- given a recording of a COPE delivery session (e.g. in real time immediately after
interaction between the clinician and the caregiver)- produces a three-tiered score,
indicating if the fidelity was 'excellent', 'acceptable' or 'problematic'. Special emphasis
will be given to the accuracy of identifying 'problematic' COPE fidelity which is not fateful
to training and may not produce the same desired outcomes as intervention delivered with
higher fidelity. First, we will obtain n-best list speech recognition of the COPE interaction
. This will help mitigate recognition errors in the next stage. Until recently, audio
recording transcription was fraught with challenges particularly in sessions involving two or
more speakers. Advances in audio signaling and speech recognition have brought technology for
automating language analysis within reach. Recent research has suggested that text based
features may be more effective than using audio features alone when classifying fidelity in
behavioral research (47). Automatic speech recognition software will be used to transcribe
sessions and the resulting words will be used in a text-based model of fidelity. All COPE
training, practice and implementation sessions will be audio taped with participant consent.
There are several of automatic speech recognition tools that we can use. We will pick the one
that best balances accuracy of recognition in our domain and privacy.Once the transcripts are
obtained, there are two approaches that we will develop and contrast: (1) comparison with a
reference delivery and (2) a supervised classification approach. The first has the advantage
of needing only a small number of excellent deliveries and several acceptable deliveries, for
each of the seven dimensions, while the other needs a larger set of labeled data but would
potentially lead to higher accuracy of prediction.
Comparison or similarity to reference (Steps A and B): Our approach will leverage techniques
widely used in the evaluation of automatically produced content, such as machine translation
and automatic text summarization. In these applications it is not feasible to track system
improvement with human judgments of quality. Instead, most of the progress is measured by
computing similarity between a set of sample reference text (i.e. what a 'good' translation
or a 'good' summary would be) and the system output. Such automatic evaluation approaches are
widely used for machine translation (48) and summarization (49). While there have been some
concerns that the automatic measures are not fine enough to distinguish between levels of
very good context, these measures show strong ability to distinguish 'very bad' content
(50,51), (or poor fidelity) aligns with the needs of our project.
In Step A we will compile 10 examples of 'excellent' COPE fidelity deliveries, with the
regions where desired aspects is expressed will be explicitly marked, i.e. marked parts where
person-environment fit is discussed, or parts of the interaction where the clinician asks
open ended questions or confirms the caregiver understanding of the content. Next, new
interactions will be ranked by their similarity with the reference 'excellent' interactions
(52). In Step 2 we will identify 'problematic' fidelity deliveries. We will make use of 10
negative examples of 'acceptable' but imperfect deliveries. If the new interaction ranks
lower than most of these, it will be considered unacceptable or 'problematic'. Parameters and
decision rules will be developed at this step to determine cut-off levels for declaring an
interaction problematic.
Determination of "excellent" versus "problematic" fidelity ratings of the audio recordings
will be assessed by Drs Hirshman and Renz (who were not the original developers of COPE and
thus they offer an independent review) using the COPE Adherence Scale developed for the
original clinical trial in order to evaluate the extent to which core treatment principles
were implemented effectively. Ratings from the Adherence Scale have been standardized such
that 1.00 represents perfect fidelity and 0.00 represent complete non-fidelity. The scale was
previously modeled off of the NIH REACH I and II fidelity approach. Findings from the
combined fidelity ratings will be used to refine the automated fidelity program into a "best
model" to be tested in Step C (53).
Supervised classification (Step C) For this approach, we will need to examine all recorded
sessions (600+). We will train a supervised classifier or a regression model to predict the
score (1 to 3, corresponding to excellent, acceptable and problematic) of a given
interaction. We will experiment with a number of classifiers, including deep learning
frameworks and more traditional support vector machine and (logistic) regression models.The
resulting final validation set of 100 labeled interactions will serve to finalize the best
model for fidelity prediction.
PHASE 2 - Evaluation of Online Training Program in Interventionist Uptake and Fidelity Phase
2 of this study involves a series of activities designed to evaluate the whether an online
training program is the same or better in improving interventionist uptake of- and fidelity
to- COPE principles and protocols compared to a high intensity face-to-face traditional form
of training.
PHASE 3 (Aim 3) - Efficacy of COPE on PACE participant outcomes by type of COPE training.
This aim will be accomplished by evaluating dyad outcomes of the COPE program under the two
different training approaches. Following training, each of the PACE organizations will enroll
5 persons with dementia and their caregivers in the study. This will yield 50 family dyads
(25 dyads in traditional training sites and 25 dyads in online training sites).
The recruitment plan includes the following goals:
25% recruitment complete by August 1, 2022 50% recruitment complete by October 31, 2022 75%
recruitment complete by December 28, 2022 100% recruitment complete by February 28, 2023 Data
analysis completed by April 28, 2023