Tamina Levy1, Kate Laver1, Maggie Killington1, Natasha Lannin2,3, Maria Crotty1. 1. 1 Flinders University, Adelaide, SA, Australia. 2. 2 School of Allied Health, La Trobe University, Melbourne, VIC, Australia. 3. 3 Alfred Health, Melbourne, VIC, Australia.
Abstract
OBJECTIVE: : To review methods for measuring adherence to exercise or physical activity practice recommendations in the stroke population and evaluate measurement properties of identified tools. DATA SOURCES:: Two systematic searches were conducted in eight databases (MEDLINE, CINAHL, PsycINFO, Cochrane Library of Systematic Reviews, Sports Discus, PEDro, PubMed and EMBASE). Phase 1 was conducted to identify measures. Phase 2 was conducted to identify studies investigating properties of these measures. REVIEW METHODS: : Phase 1 articles were selected if they were published in English, included participants with stroke, quantified adherence to exercise or physical activity recommendations, were patient or clinician reported, were defined and reproducible measures and included patients >18 years old. In phase 2, articles were included if they explored psychometric properties of the identified tools. Included articles were screened based on title/abstract and full-text review by two independent reviewers. RESULTS: : In phase 1, seven methods of adherence measurement were identified, including logbooks ( n = 16), diaries ( n = 18), 'record of practice' ( n = 3), journals ( n = 1), surveys ( n = 2) and questionnaires ( n = 4). One measurement tool was identified, the Physical Activity Scale for Individuals with Physical Disabilities ( n = 4). In phase 2, no eligible studies were identified. CONCLUSION: : There is not a consistent measure of adherence that is currently utilized. Diaries and logbooks are the most frequently utilized tools.
OBJECTIVE: : To review methods for measuring adherence to exercise or physical activity practice recommendations in the stroke population and evaluate measurement properties of identified tools. DATA SOURCES:: Two systematic searches were conducted in eight databases (MEDLINE, CINAHL, PsycINFO, Cochrane Library of Systematic Reviews, Sports Discus, PEDro, PubMed and EMBASE). Phase 1 was conducted to identify measures. Phase 2 was conducted to identify studies investigating properties of these measures. REVIEW METHODS: : Phase 1 articles were selected if they were published in English, included participants with stroke, quantified adherence to exercise or physical activity recommendations, were patient or clinician reported, were defined and reproducible measures and included patients >18 years old. In phase 2, articles were included if they explored psychometric properties of the identified tools. Included articles were screened based on title/abstract and full-text review by two independent reviewers. RESULTS: : In phase 1, seven methods of adherence measurement were identified, including logbooks ( n = 16), diaries ( n = 18), 'record of practice' ( n = 3), journals ( n = 1), surveys ( n = 2) and questionnaires ( n = 4). One measurement tool was identified, the Physical Activity Scale for Individuals with Physical Disabilities ( n = 4). In phase 2, no eligible studies were identified. CONCLUSION: : There is not a consistent measure of adherence that is currently utilized. Diaries and logbooks are the most frequently utilized tools.
Evidence demonstrates that higher doses of therapy are associated with better
outcomes after stroke.[1-3] However,
providing high doses of therapy in practice is challenging and therapists face a
number of barriers including limited resources and low tolerance among stroke
survivors to participate in high-intensity therapy.[4,5] Therapists are encouraged to
establish independent practice outside of supervised therapy time as a way of
increasing therapy dose.[3]The benefits of increasing therapy dose by prescribing independent practice, however,
depend on adherence to the prescribed programme; studies suggest that adherence
reduces over time.[6] Adherence has been defined as ‘the extent to which a person’s behaviour –
taking medication, following a diet, and/or executing lifestyle changes, corresponds
with agreed recommendations from a healthcare provider’.[7] Adherence to exercise programmes has been shown to be especially challenging
after stroke,[8] with between 30% and 50% of patients ceasing their exercise programmes within
the first year.[9]Measurement tools that quantify adherence to exercise programmes provide information
for therapists about what the client is doing, in many cases, during times of the
day when therapists are unable to observe the practice. Measurement of adherence can
take various forms and there is no acknowledged gold standard.[10] Previous systematic reviews have assessed adherence to home-based rehabilitation,[11] self-reported measures of home-based rehabilitation,[12] patient or provider adherence questionnaires in physiotherapy[10] and measures assessing non-pharmacological self-management in musculoskeletal conditions.[13] These previous reviews have concluded that trials included largely
self-developed questionnaires that lacked sufficient evidence of psychometric
properties.[10,12,13] However, to date, no review has summarized methods of
measurement of adherence to exercise and physical activity recommendations in
stroke.It is important to use a method of measurement of adherence that is valid in the
specific population, that is, the tool measures what it is supposed to measure.[14] Given the important role adherence plays in determining the efficacy of an
intervention, the adherence measurement methods chosen should be guided by the
specific patient diagnosis group and by evidence of their measurement properties
when tested within this group.With limited understanding of the best methods of measuring adherence (and associated
psychometric properties of these methods) for the stroke population, the primary aim
of this study was to identify adherence measurement methods used to quantify
adherence to exercise and physical activity recommendations. The secondary aim was
to report on the psychometric properties of the identified methods and synthesize
findings to provide recommendations for both clinical and research use.
Method
This review was conducted in two parts. An initial search was conducted to identify
adherence measurement methods to exercise or physical activity in the stroke
population. Following this, a second search was conducted to identify studies
investigating the psychometric properties of the methods identified in phase 1. This
review is reported in accordance with the PRISMA guidelines.[15]
Phase 1: identification of adherence measurement methods
A search in eight electronic databases (MEDLINE, CINAHL, PsycINFO, Cochrane
Library of Systematic Reviews, Sports Discus, PEDro, PubMed and EMBASE) was
conducted in July 2017 and updated in September 2018 to identify adherence
measurement methods. The search strategy for MEDLINE is included in Supplemental Appendix 1. An equivalent search strategy was
individualized for all other databases and no limits were placed on publication
dates.Studies were included if they were (1) published in English, (2) included
participants diagnosed with stroke (or greater than 80% of study population was
diagnosed with stroke), (3) quantified adherence to exercise or physical
activity recommendations, (4) were patient or clinician reported measures, (5)
were defined and replicable measures and (6) were tested in patients
>18 years old. Studies were included if they were conducted in any
therapeutic setting including inpatient, outpatient and community settings.
Studies using objective tools (which are not patient or clinician reported) such
as accelerometers were excluded. Conference abstracts which described eligible
adherence measurement methods were included.Once duplicates were removed, titles and abstracts of all identified studies were
reviewed for inclusion by two independent reviewers and agreement achieved
through discussion when needed. The same two reviewers screened the full-text
articles for the inclusion and exclusion criteria. A third reviewer was
available to resolve differences. Data extracted included the population that
the tool had been used with, the setting the tool had been used in, the type of
intervention it was measuring, whether it was patient or clinician administered
and study and measurement-specific information.
Phase 2: properties of included adherence measurement methods
To identify the psychometric properties of included adherence measurement
methods, a search in eight electronic databases (MEDLINE, CINAHL, PsycINFO,
Cochrane Library of Systematic Reviews, Sports Discus, PEDro, PubMed and EMBASE)
was conducted in February 2018 and updated in September 2018. The search
strategy for MEDLINE is included in Supplemental Appendix 2. An equivalent search strategy was
individualized for all other databases and no limits were placed on publication
dates.Studies were included if they (1) were published in English, (2) included
participants diagnosed with stroke (or greater than 80% of study population was
diagnosed with stroke) and (3) reported research investigating at least one
psychometric property for an adherence measurement method identified in phase 1.
The primary psychometric property of interest was validity.Once duplicates were removed, titles and abstracts of all identified studies were
reviewed for inclusion by two independent reviewers and agreement was checked.
The same two reviewers screened the full-text articles for the inclusion and
exclusion criteria. A third reviewer was available to resolve differences.Papers identified in phase 1 were grouped according to the type of adherence
measurement method used. For phase 2, we planned to assess measurement
properties following the recommendations of the COnsensus-based Standards for
the selection of health Measurement INstruments (COSMIN).[16]
Results
The review process for both searches is shown in the flowchart (Figure 1). Phase 1 identified a total of 48
articles for inclusion in our review, which included seven different adherence
measurement methods (several studies evaluated multiple tools). Phase 2 failed to
identify any articles which identified the psychometric properties of included
adherence measurement methods for inclusion in our review.
Figure 1.
Flowchart showing selection process for phases 1 and 2. Phase 1 -
identification of adherence measurement methods and phase 2 - measurement
properties of adherence measurement methods.
Flowchart showing selection process for phases 1 and 2. Phase 1 -
identification of adherence measurement methods and phase 2 - measurement
properties of adherence measurement methods.A total of 6130 citations were identified using the search strategy; of these,
179 articles were selected for full-text review and 48 studies were identified
as being eligible for inclusion. These 48 articles contained seven separate
adherence measurement methods. Table 1 provides a summary of adherence
measurement methods and study design. We found that researchers used different
terms for their adherence measurement methods and there is no widely accepted
terminology; we describe the adherence measurement methods based on the
terminology used by the researcher within the study description. Supplemental Table 1 presents the method and characteristics of
the included adherence measurement methods.
Table 1.
Types of adherence measurement method and type of study in which the
method was used.
Type of adherence measurement method
Number of studies identified using the
method
Experimental studies (study reference)
Descriptive studies (study reference)
Diary
18
17–30
31–34
Logbook
16
35–45
46–50
Record of practice
3
51–53
Journal
1
54
Survey
2
55, 56
Questionnaire
4
57–60
PASIPD
4
61–64
PASIPD: The Physical Activity Scale for Individuals with Physical
Disabilities.
Types of adherence measurement method and type of study in which the
method was used.PASIPD: The Physical Activity Scale for Individuals with Physical
Disabilities.Of the adherence measurement methods identified, diaries and logbooks were used
most frequently. Studies seldom described the content within the
diaries/logbooks. Some studies identified the parameters of exercise or activity
that were recorded. The duration and frequency of exercise or physical activity
were most frequently recorded in the diary or logbook.Diaries were used in 18 of the identified studies. All home diaries were
completed by the patient. Three of the identified studies utilized diaries as a
component of the constraint-induced movement therapy (CIMT), where the focus was
on recording the amount of activity performed with the affected upper
limb.[17,31,32] Many of the included studies used diaries to record the
duration or frequency of exercise or physical activity that was
performed.[18-28,31] The type of physical
activity performed was included in the diary in seven studies.[17,18,20,23,27,31,32] The
specific method of recording in the diaries was not described in six of the
identified studies.[21,28-30,33,34]Logbooks or daily activity logs were used as adherence measurement methods in 16
of the included studies. Four of the studies used a log to record time of
functional activity and/or adherence to mitt use during CIMT.[35,36,46,47] A further
study used a logbook to record type of activity performed during a goal-directed
upper limb activity programme.[37] The most frequently recorded exercise or activity parameter was
duration.[35,36,38-40,46-50] Other parameters recorded
in the logbooks included weekly step activity,[41] intensity[38] and number of sets and repetitions of exercise.[42,49,50] Other studies did not
provide any specific details regarding method of recording in the
logbooks.[43,44]Three of the included studies reported that subjects were asked to keep a ‘record
of practice’ or recording sheet indicating how often they exercised.[51-53] In the study reported by
Malagoni et al.,[52] participants were asked to fill out a daily training record indicating
exercise completion and any adverse events. This record was then used by the
authors to produce an adherence percentage (‘retention rate’), where the number
of planned sessions relative to the recorded sessions was calculated. It was not
clear whether this methodology was developed by the authors or based on previous
research.Hayward et al.[54] utilized a journal for recording adherence in their case study.
Repetitions and a quality reflection were recorded.This review identified a survey exploring exercise beliefs and adherence,
originally developed by Miller.[65] The written exercise survey collected data including whether or not
participants recalled being provided with a home exercise programme. For those
that indicated a ‘yes’ response, data on adherence, non-adherence, reasons for
non-adherence, perception of loss of function since discharge and exercise
attitudes were collected.[55] This survey was developed after a literature review and was pilot tested
and reviewed by experts in the field. The author acknowledged that a limitation
of their study was a lack of information about the validity of the survey. An
additional study included in this review used a phone survey to assess
adherence; however, no details of the survey were available.[56]Four papers included in this review used questionnaires as adherence measurement
methods. Jurkiewicz et al.[57] developed a 16-item questionnaire comprising questions about the type and
amount of exercise performed, factors that motivated patients to participate and
reasons why they missed their workout. Touillet et al.[58] described using a semi-structured activity questionnaire, which explored
type of activity as well as duration and frequency. In a study exploring
longitudinal patterns of adherence to exercises in people with stroke, Yao et al.[59] utilized the Questionnaire of Exercise Adherence, a 14-item questionnaire
consisting of three dimensions: adherence to exercise, effective supervision and
advice seeking. An additional study included in this review developed a
questionnaire that examined consistency between prescribed treatment and
exercises completed.[60]The Physical Activity Scale for Individuals with Physical Disabilities (PASIPD)
was included in four papers identified in this review.[61-64] The PASIPD is a 13-item
self-report tool that assesses physical activity in three domains: recreation,
household and occupational activities.
Phase 2: psychometric properties of included adherence measurement
methods
The search for the second phase of this review, aimed at synthesizing the
published psychometric properties of the adherence measurement methods,
identified 1215 citations, and a total of 17 papers were sought in full text. Of
these studies, none of the studies met all the inclusion criteria. Hence,
analysis of the psychometric properties of the located adherence measurement
methods was not possible.
Discussion
This review identified that while there are adherence measurement methods used to
assess adherence to exercise or physical activity recommendations after stroke,
there are no published psychometric studies of these tools. Seven adherence
measurement methods have been described in the literature: diaries, logbooks, record
of practice, journal, surveys, questionnaires and the PASIPD. There is no clear
consensus on the optimal adherence measurement method to exercise or physical
activity recommendations after stroke, since it remains plausible that existing
approaches are not valid. The findings of this review are consistent with other
reviews involving other populations, demonstrating that researchers tend to use
tools that are developed and administered in an ad hoc manner, and existing measures
have not been adequately psychometrically tested.[10-13]Additional methods of monitoring were used in a number of other studies included in
this review, including telephone monitoring and follow-up face-to-face
meetings.[17,22-28,40] In addition, Gunnes et al.[23] combined participant-reported diaries with an adherence form completed by the
physiotherapist on review of the diary. The adherence form was intended as a method
of quality assurance and was completed at regular review appointments. The author
combined the two measures and expressed this as a single value representing
adherence. Given that use of a diary or logbook is commonly used, determining the
validity and reliability of these approaches seems to be an important area of future
research.While no studies met the inclusion criteria for phase 2 of the review, we excluded
one study involving a coded physical activity diary.[66] This study was not included as it described patterns of physical activity
rather than adherence to a prescribed programme. These types of coded diaries are
frequently used in stroke research activity trials; each day is divided into time
intervals and codes are provided that represent specific activities. Patients are
asked to choose the primary activity performed over the time interval. It is
hypothesized that this sort of diary use may be easier for strokepatients to comply
with as it minimizes writing, but there is as yet not research to support this
suggestion. Therapists may consider this method of diary use when aiming to measure
strokepatients’ adherence to exercise programmes, but further research should be
conducted prior to assuming that a diary of exercise represents actual exercise
completed.While participants were responsible for self-reporting in most studies, some studies
also incorporated caregiver involvement into the recording process. Caregivers were
required to either record the amount of exercise performed in the logbook or
sign-off the completed exercises.[38,45,48] Caregiver support may increase
the consistent use of adherence measurement methods; however, consideration must be
given to the demands and burden placed on the caregiver. Again, however, there were
no published studies to determine whether caregivers are more or less accurate in
their reporting of completed exercise and the role of caregivers in physical
activity and exercise studies warrants further research.Our review did locate one tool; the PASIPD is a 13-item self-report tool that
captures physical activity in three domain areas (recreation, household and
occupational activities). While we could not synthesize findings from psychometric
studies completed specifically in a stroke population, the PASIPD has published
reliability and validity coefficients (test–retest reliability .77; criterion
validity correlation .3) when used for measuring physical activity in individuals
with disabilities (mixed population).[61,67] Thus, the PASIPD may be
considered to be a tool for measuring physical activity in a population of people
with disabilities. However, it was not designed to be a tool for measuring
adherence, although it was used for this purpose in one study identified in this review.[62] To use the PASIPD as an adherence measurement method, Brown et al.[62] adapted the original assessment; however, it has not had psychometric
evaluation for this purpose. Thus, further research to understand the validity and
reliability of the PASIPD as an adherence measurement method is still required.This systematic review was deliberately limited to identifying adherence measurement
methods through methods of client or therapist report (and thus, we excluded
approaches such as the use of accelerometers). We made this decision because there
is already systematic review evidence for the role of accelerometry to monitor
physical activity after stroke, concluding that accelerometers yield valid and
reliable data about physical activity after stroke.[68] Despite this strong evidence, the uptake of accelerometers by clinicians to
monitor activity remains limited[69] and there is anecdotal evidence that independent use by stroke survivors is
difficult. Furthermore, the use of accelerometers does not allow the therapist to
monitor specific components of adherence such as counting repetitions. It is
therefore important for clinicians to have inexpensive, readily available, quick and
reliable adherence measurement methods that they or their patient could administer
to measure adherence. This review has identified that currently such a method does
not exist in the stroke literature.The majority of studies identified in this systematic review recruited
community-dwelling participants who were capable of participating in an unsupervised
exercise programme. Of the studies incorporating cognitive and communication
function into their inclusion and exclusion criteria, participants were excluded if
they had issues that would prevent them following instructions relating to the
intervention or method of assessment, including a lack of ability to follow two-step
commands or mild cognitive deficits. A number of studies reported a mini-mental
state examination (MMSE) cut-off score indicative of mild cognitive impairment (MMSE
18–23).[17,18,22,23,27,30-32,52,61,70] Thus, our
findings also failed to identify adherence measurement methods that may be suited to
a population with greater levels of disability.As the adherence measurement methods identified in this review varied in terms of
their format and detail, at this stage, it is not possible to recommend which is
most likely to provide the most reliable and valid information in the stroke
population. The most frequently used adherence measurement method identified in this
review is the patient diary. The main limitation of this method is the possibility
of inaccurate reporting with a bias towards over-reporting.[71] Exploration of some of the more advanced applications of diary use identified
in this review, such as a coded diary and regular therapist review, warrants further
investigation and validation.Understanding adherence is a complex concept and there are a multitude of factors
that may influence adherence in people with stroke.[72] First, the theories around behaviour change (such as the theory of planned
behaviour) show that factors such as attitude, norms and control influence intention
(and subsequently behaviour).[73] Second, work shows that the process of establishing new habits (such as
completing a self-directed programme) varies considerably among individuals and new
activities often take weeks to become routine.[74]The issue of bias was addressed in a small number of the included studies and must be
considered in analysis. Studies that rely on patient self-report can be subject to
many forms of bias including recall bias, optimism bias and social desirability
response bias.[75-78] Recall bias has been
identified as a limiting factor in survey-based studies[65] and self-report instruments such as diaries were reported to be vulnerable to
patient’s inaccuracies.[23]The findings of this review echo those conducted in other fields. A systematic review
of exercise adherence in the musculoskeletal field concluded that the measures
identified were unacceptable for use and highlighted the importance of the
development and evaluation of appropriate measures.[79] The development of a validated measure of adherence to exercise or physical
activity in people with stroke should be a priority to provide researchers and
clinicians with a greater understanding of this important concept.[80]Limitations of this systematic review include possible bias as studies not published
in English were not included. The grey literature was not searched in this
systematic review which may be a further limitation. The greatest limitation,
however, remains the lack of published psychometric studies testing whether or not
the clinical tools used to monitor adherence to physical activity and exercise
programmes for stroke survivors are sound.There is a lack of a uniform method of measurement of adherence to
exercise or physical activity recommendations in the stroke
population.This study has identified diaries and logbooks as the most frequently
used adherence measurement methods; however, there is a lack of
standardization between tools.Click here for additional data file.Supplemental material, Supplemental_Material for A systematic review of measures
of adherence to physical exercise recommendations in people with stroke by
Tamina Levy, Kate Laver, Maggie Killington, Natasha Lannin and Maria Crotty in
Clinical Rehabilitation
Authors: Gert Kwakkel; Roland van Peppen; Robert C Wagenaar; Sharon Wood Dauphinee; Carol Richards; Ann Ashburn; Kimberly Miller; Nadina Lincoln; Cecily Partridge; Ian Wellwood; Peter Langhorne Journal: Stroke Date: 2004-10-07 Impact factor: 7.914
Authors: Hidde P van der Ploeg; Kitty R M Streppel; Allard J van der Beek; Luc H V van der Woude; Miriam Vollenbroek-Hutten; Willem van Mechelen Journal: J Phys Act Health Date: 2007-01
Authors: Samuel R Pierce; Kara G Gallagher; Susan W Schaumburg; Arthur M Gershkoff; John P Gaughan; Lori Shutter Journal: Neurorehabil Neural Repair Date: 2003-12 Impact factor: 3.919
Authors: Carolee J Winstein; J Philip Miller; Sarah Blanton; Edward Taub; Gitendra Uswatte; David Morris; Deborah Nichols; Steven Wolf Journal: Neurorehabil Neural Repair Date: 2003-09 Impact factor: 3.919
Authors: Patricia McCue; Lisa Shaw; Silvia Del Din; Heather Hunter; Sue Lord; Christopher I M Price; Helen Rodgers; Lynn Rochester; Sarah A Moore Journal: Arch Physiother Date: 2022-01-04
Authors: Nadine Kerr; Juliana Sanchez; William Javier Moreno; Ofelia E Furones-Alonso; W Dalton Dietrich; Helen M Bramlett; Ami P Raval Journal: Front Aging Neurosci Date: 2022-08-17 Impact factor: 5.702