Sage Journals: Discover world-class research

Abstract

Background:

The results of rehabilitation clinical trials can be negatively affected by adherence to trial protocols. Adherence is multi-factorial, but studies often look at adherence factors separately. Therefore, a systematic review to appraise and synthesise the evidence is warranted to determine the barriers, facilitators and predictors associated with adherence to inpatient rehabilitation trial protocols, whether and how factors interact with one another, and how adherence to rehabilitation protocols can be optimised.

Methods:

A mixed-methods systematic review was conducted and reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Databases searched were PubMed (Ovid), EMBASE (Ovid), MEDLINE (Ovid), CINAHL (Ovid), PsycINFO (Ovid), Cochrane Library, Health Technology Assessment Database, Web of Science and grey literature up to April 2024. A cohesive, integrated methodology was employed, leveraging the Consolidated Framework for Implementation Research (CFIR) 2.0, to transform, synthesise and integrate data from various methodologies to address the review objectives.

Results:

Twenty-seven studies met the inclusion criteria (randomised controlled trials, qualitative studies related to randomised controlled trials or mixed-methods). Most of the studies were in stroke (n = 17), but other studies included neurological, respiratory, cardiovascular, post-surgical, osteoarthritis and elderly medical. Multiple factors affecting adherence protocols were identified. Adherence was measured in various ways, and setting pre-specified adherence levels was uncommon.

Conclusion:

Adherence to inpatient rehabilitation trial protocols is multi-dimensional and multi-factorial. Consensus of adherence measurement and interpretation of adherence levels is needed to make meaningful comparisons between trials. A standardised approach, including adopting a traffic light system, would enable trialists to implement changes mid-trial or stop the trial to avoid research waste. Adopting approaches from behavioural science in the design and conduct of inpatient rehabilitation trials may overcome some of the behavioural barriers identified and optimise adherence for those delivering and receiving the intervention.

Review registration:

Prospective Register of Systematic Reviews, registration number CRD42021270121.

Keywords

Adherence compliance fidelity rehabilitation clinical trials stroke rehabilitation

Background

People with stroke often experience a range of impairments affecting function and quality of life, and rehabilitation aims to promote recovery. Millions of pounds are spent on research evaluating rehabilitation interventions for people after stroke, but the results can be negatively affected by adherence to the trial protocols. Adherence is a key variable influencing the outcome of clinical trials and is the bottom-line measurement of implementation fidelity.¹ Thus, researchers need to identify ways to optimise adherence in the planning, design and delivery of stroke rehabilitation trials to ensure trial funds are well used and that trials accurately determine treatment effect and patient safety. Adherence to intervention protocols refers to the degree to which the behaviour of trial participants corresponds to the intervention assigned to them.² This implies the onus is on the participants; however, it is imperative to identify and address all factors affecting adherence in stroke rehabilitation trials, including the behaviour of those delivering and receiving the intervention and the context in which the trial is delivered.

Protocol adherence to a recently conducted multi-centre feasibility randomised controlled trial (fRCT, Standing Practice In Rehabilitation Early after Stroke (SPIRES)) for people with severe stroke during their inpatient stroke rehabilitation was low. Patient-, therapist- and organisation-factors all were identified as affecting adherence to the functional standing frame programme.³ A recommendation from the fRCT was to determine what factors affect adherence to inpatient stroke rehabilitation trial protocols before progressing to a definitive trial. Adherence is multi-factorial, but studies often look at adherence factors separately, focusing on one component only. Therefore, a systematic review was warranted to determine the barriers and facilitators to adherence in inpatient stroke rehabilitation trial protocols, and whether, and how, factors interact with one another. It was unclear whether factors affecting adherence to SPIRES³ were specific to stroke survivors; therefore, this review included all inpatient physical rehabilitation trials to determine any similarities and lessons that can be applied to future design of stroke rehabilitation inpatient trials.

The Consolidated Framework for Implementation Research (CFIR) 2.0^4,5 was used as a basis to synthesise and integrate the data. The CFIR is a meta-theoretical framework used by implementation scientists to systematically identify factors that may emerge in various, multi-level contexts that influence implementation.^3–6 The updated CFIR 2.0 includes constructs from Michie et al.’s Behaviour Change Wheel (BCW).⁷ The BCW is an evidence-based model consisting of three layers that recognise behaviour as part of an interacting system involving an individual’s capability to perform a behaviour (e.g. knowledge/skills), the opportunity (e.g. autonomy) and motivation (e.g. commitment) to carry out that behaviour. It is pertinent to both recipients and providers of inpatient rehabilitation trial protocols. Thus, the CFIR 2.0 provided a systematic way to classify factors affecting adherence and organise both qualitative and quantitative data to identify ways of optimising adherence to inpatient rehabilitation trial protocols.

The aim of this review was to determine the barriers, facilitators and predictors associated with adherence to inpatient rehabilitation trial protocols, whether and how factors interact with one another, and how adherence to rehabilitation protocols can be optimised.

Methods

The systematic review protocol was registered with the International Prospective Register of Systematic Reviews (CRD42021270121). The review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).⁸

Review question

Among adults participating in inpatient physical rehabilitation trials, what barriers, facilitators, and predictors influence adherence to trial protocols, how do these factors interact within inpatient settings, and what strategies can optimise adherence?

Eligibility

The review question and eligibility criteria were constructed using the PICCO method as follows:

Participants/population: aged ≥ 18 years participating in a physical rehabilitation trial.

Intervention(s), exposure(s): any inpatient physical rehabilitation trial which measures protocol adherence.

Comparator: Not applicable.

Context: Trials conducted in hospital-based healthcare/rehabilitation settings (e.g. rehabilitation unit/ward, hospital ward) in any country.

Outcomes: (1) Determine the barriers, facilitators and predictors associated with adherence to inpatient rehabilitation protocols; (2) determine how adherence to protocols can be optimised in inpatient rehabilitation trials, that is, how the effectiveness of an intervention can be improved, and its acceptability and feasibility be increased in practice⁹ and (3) determine whether adherence to inpatient stroke rehabilitation trial protocols differs from those in other health conditions.

Exclusions include adolescents (≤17 years of age); people whose primary reason for admission to the rehabilitation ward/unit was for mental health/psychological issues; and people not participating in an inpatient rehabilitation trial.

Searches

Searches of databases were performed by two researchers (A.L. and E.C.) in November 2021. Focused searches were conducted in PubMed, EMBASE (Ovid), MEDLINE (Ovid), CINAHL (EBSCOhost) and PsycINFO (Ovid) using database-controlled thesauruses. Each database was searched separately. The Cochrane Library, Health Technology Assessment Database, Web of Science and grey literature (Open Grey, Google Scholar, ETHOS (British Library repository)) were also searched. A search of reference lists from all studies that met the inclusion criteria was conducted. Search terms were related to the concepts of adherence, rehabilitation, clinical trial protocol, intervention and fidelity and were peer reviewed by an independent Information Specialist.¹⁰ Searches were restricted to randomised controlled trials (RCTs) and qualitative studies of those participating in RCTs to address the review objectives and English language, but not by date. The searches were repeated using the same methods in April 2024. In accordance with the PRISMA-S checklist,¹¹ see Supplementary Material for the search strategy.

Study selection

The selection process was conducted through Rayyan.¹² After removal of duplicates, four reviewers (A.L., J.M., J.F. and E.C.) independently screened the titles and abstracts of all retrieved articles to determine eligibility. Discrepancies were resolved through discussion to obtain consensus, with the option of a third reviewer if required. Screening of the full texts of preselected articles was carried out by the same researchers, but one reviewer (A.L.) screened all full texts, and all other reviewers (J.F., J.M., E.C.) independently reviewed their allocated studies.

Data extraction

The team of reviewers independently extracted data from each study using a pre-standardised data extraction template and the Template for Intervention Description and Replication (TIDieR) checklist and guide.¹³ Additional extracted data included study characteristics, participant age, gender and health condition, adherence (how this was measured and outcomes), study outcomes, themes from qualitative data and key conclusions from the study authors. One reviewer (A.L.) extracted the data from all eligible studies, and three other reviewers (J.F., J.M., E.C.) independently extracted data from their allocated studies. One author (A.L.) collated and cross-checked all extracted data. Discrepancies in the data extraction were resolved through discussion with the relevant reviewers, with the option to involve a third reviewer if required.

Synthesis method

A convergent integrated approach was used to transform, synthesise and integrate data from different data and methods of analysis to address the review questions, following the Joanna Briggs Institute (JBI) methodological guidance for the conduct of mixed-methods systematic reviews.¹⁴ The CFIR 2.0^4,5 was used as a basis to synthesise, integrate and visually display the data. Quantitative data were transformed into textual descriptions to qualitise the data. The author of one study was contacted to request additional data.

Quality assessment

The Mixed-Methods Appraisal Tool (MMAT)¹⁵ was used to assess the methodological quality (risk of bias) of all included studies before data extraction. Each study was independently assessed by two authors. The MMAT was used due to its ability to evaluate study selection bias, study design, data collection methods, sample size, intervention integrity and analysis across multiple study designs. Previous versions of the MMAT have included allocating a methodological rating score, but a more detailed presentation of the ratings in each criterion is preferred¹⁵ to better inform the quality of the studies.

Results

Of the 5188 records in the initial searches and 483 in the repeated searches (Figure 1), 27 studies were included in the review: 24 from the initial searches, two from reference lists and one from the repeated searches.

Figure 1.

PRISMA diagram.

Characteristics of the included studies are shown in Table 1.

Table 1.

Characteristics of included studies.

First author and year	Study description	Condition & study design	Age and gender	Ability/disability and outcome measures
Ahn et al.¹⁶	Effect of exercise on length of stay in patients with colon cancer	Post-colorectal surgery; RCT	Mean age 20-70 y; n = 17 male, n = 14 female	Able to walk (no formal measure)
Aries et al.¹⁷	Sensory stimulation of the foot and ankle early post-stroke	Stroke; mixed-methods	Mean age 73.2 y (SD 12.2); n = 18 male, n = 16 female	NIHSS 1-6 plus FAC 3
Bernhardt et al.¹⁸	A very early rehabilitation trial for stroke (AVERT)	Stroke; RCT	Mean age 74.7 y (SD 12.5); n = 33 female, n = 38 male	42% mild, 34% moderate, 24% severe stroke
Bowden et al.¹⁹	Lessons learned: The difficulties of incorporating intensity principles into inpatient stroke rehabilitation	Stroke	Intervention: Mean age 67.2 y (SD 17.4); n = 6 female, n = 10 male Control: Mean age 70.3 y (SD 14.2); n = 10 female, n = 9 male	Moderate disability measured by FIM
Buhagiar et al.²⁰	Inpatient rehabilitation versus a monitored home-based programme in patients with total knee arthroplasty	Osteoarthritis	Mean age 66.9 y (SD 8); n = 56, 69% female	Able to walk; 6-min walk test, 15-m walk test
Collier and Bernhardt²¹	Achieving treatment dose within a rehabilitation trial	Stroke	Mean age 74.7 y; n = 38 male, n = 33 female	75% NIHSS 10 (moderate stroke)
Connell et al.²²	Delivering intensive rehabilitation in stroke: Factors influencing implementation	Stroke staff	Mean age 37 y (SD 9.2); gender not reported	Not applicable
Dorsch et al.²³	EMG-triggered electrical stimulation to multiple arm muscles in people early after stroke	Stroke; feasibility RCT	Mean age 66 y, (range 50-85); n = 18 male, n = 15 female	< grade 3 strength in at least three out of four muscle groups of the UL
Greening et al.²⁴	Early rehabilitation intervention to enhance recovery during hospital admission for an exacerbation of chronic respiratory disease	Chronic obstructive respiratory disease; RCT	Intervention: Mean age 71.1 y (SD 9.4); n = 88 male, n = 108 female Control: Mean age 71.2 y (SD 10); n = 85 male, n = 108 female	Able to walk incremental and endurance shuttle walk tests
Hersche et al.²⁵	Inpatient energy management education for persons with multiple sclerosis-related fatigue	Multiple Sclerosis; feasibility RCT	Intervention: Mean age 51.2 y (SD 1.7); 66.7% female Control: Mean age 51.8 y (SD 2.2); 65.2% female	EDSS score ≤ 6.5 (able to walk 20 m without resting using walking aids)
Hojskov et al.²⁶	Early physical and psycho-educational rehabilitation in patients with coronary artery bypass grafting	Coronary artery bypass graft; RCT	Intervention: Mean age 65 y (SD 9.1); 87% male Control: Mean age 65.1 y (SD 8.4); 86% male	Able to walk (no formal measure)
Horne et al.²⁷	Staff’s views on delivering patient-led therapy during inpatient stroke rehabilitation	Stroke staff; qualitative	Not applicable	Not applicable
Kattenstroth et al.²⁸	Daily repetitive sensory stimulation of the paretic hand for the treatment of sensorimotor deficits in patients with subacute stroke	Stroke; sham RCT	Intervention: Mean age 64 y (range 34-86); n = 18 male, n = 5 female Control: Mean age 59 y (range 43-89); n = 16 male, n = 7 female	Mild to moderate stroke according to mRS and NIHSS
Langhorne et al.²⁹	A very early rehabilitation trial after stroke (AVERT)	Stroke; RCT	Intervention: Mean age 72.3 y (IQR 62.3-80.3); n = 411 female, n = 643 male Control: Mean age 72.7 y (IQR 63.4-80.4); n = 407 female, n = 643 male	56% mild, 30% moderate and 14% severe stroke (NIHSS)
Louie et al.³⁰	Exoskeleton-based physical therapy programme for non-ambulatory patients during subacute stroke rehabilitation	Stroke; RCT	Intervention: Mean age 59.6 y (SD 15.8); n = 16 male Control: Mean age 55.2 y (SD 10.6); n = 10 male	Unable to walk without substantial assistance (FAC rating of 0 or 1)
Luker et al.³¹	Qualitative process evaluation of AVERT RCT	Stroke staff; qualitative	Not applicable	Not applicable
Lupo et al.³²	Balance skills and patient compliance of biofeedback training with inertial measurement units and exergaming in subacute stroke	Stroke; pilot RCT	Intervention: Mean age 52.56 y (SD 13.92); 33.3% female Control: Mean age 65.66 y (SD 9.64); 16.6% female	Able to walk with supervision; BBS, Modified Rivermead Index, NIHSS, BI.
Mcleod et al.³³	Sprint interval training versus moderate-intensity continuous training during inpatient rehabilitation	Spinal cord injury; RCT	MICT: Mean age 45 y (SD 17); n = 5 male SIT: Mean age 47 y (SD 15); n = 10 male	Tetraplegic or paraplegic
Nydahl et al.³⁴	PROtocol-based Mobilisation on intensive care units	Critically ill (intensive care unit); cluster RCT pilot	Intervention: Mean age 74 y (range 61-81); n = 51 female Control: Mean age 70 y (range 58-79.7); n = 71 female	≥ level 3 on the ICU Mobility Scale, e.g. sitting on edge of bed or higher
Ostermann et al.³⁵	Enhanced recovery programme for elderly patients after colorectal surgery	Post-colorectal surgery; RCT	Intervention: Mean age 80 y (range 70-91); n = 26 male, n = 49 female Control: Mean age 78 y (range 70-90); n = 35 male, n = 40 female	Able to walk (no function measure reported)
Pedersen et al.³⁶	Promote in-hospital mobility among older medical patients – the WALK-Copenhagen project	Medical patients ≥ 65 y; mixed-methods	Mean age 77.4 y (SD 7.6); 44% female	Able to walk with or without aid
Richards et al.³⁷	Development, implementation, and clinician adherence to a standardised sensorimotor assessment toolkit	Stroke; mixed-methods	Mean age 60.3 y (SD 15.4), n = 166 male, n = 98 female;	FIM
Sosnowski et al.³⁸	Impact of the ABCDE bundle on quality of life in ICU survivors	Critically Ill (intensive care unit); RCT	Intervention: Mean age 54.9 y (SD 15.9); n = 6 female Control: Mean age 60.6 y (SD 11.0); n = 11 female	PFIT-s and FIM
Stock et al.³⁹	Constraint-induced therapy multi-site trial: Adherence to treatment protocol applied early after stroke	Stroke; RCT	Mean age 65.3 y (SD 8.0); n = 5 female, n = 19 male	SSS arm motor 2–5 or hand motor 2–4; FM 43-59
Tyson et al.⁴⁰	Patient-led mirror therapy and lower-limb exercises during inpatient stroke rehabilitation	Stroke; RCT	Intervention: Mean age 64 y (SD 15); n = 37 male Control: Mean age 64 y (SD 13); n = 23 male	MI, grip strength, MAS, Rivermead Sensory, UL Box and Block, ARAT, RMI.
van Bloemendaal et al.⁴¹	Gait training assisted by multichannel functional electrical stimulation in early stroke rehabilitation	Stroke; pilot RCT	Intervention: Mean age 57 y (SD 8.7); n = 15 male, n = 4 female Control: Mean age 58.7 y (SD 10.2); n = 14 male, n = 4 female.	Need assistance to walk (FAC-dependent gait)
Wall et al.⁴²	Electromechanical gait training of patients with severe limitations in walking	Stroke; RCT	Intervention: Median age 55 y [IQR 48.25-62.5]; n = 13 male, n = 3 female Control: Median 57.5 y [IQR 54.5-60.75]; n = 13 male, n = 3 female	Unable to walk or needing continuous support to walk (e.g. FAC score 0–1)

SD: standard deviation; y: year; RCT: Randomised Controlled Trial; NIHSS: National Institutes of Health Stroke Scale; EDSS: Expanded Disability Status Scale; mRS: modified Rankin Scale; BBS: Berg Balance Scale; BI: Barthel Index; FIM: Functional Independence Measure; MI: Motricity Index; Rivermead Sensory: Rivermead Assessment of Sensory Perception; MAS: Modified Ashworth Scale; ARAT: Action Research Arm Test; RMI: Rivermead Mobility Index; UL: upper limb; SSS: Scandinavian Stroke Scale; FM: Fugl-Meyer; FAC: Functional Ambulation Categories; PFIT-S: Physical Function ICU Test-scored.

Quality appraisal

All included studies were appraised for quality using the MMAT (Supplementary Table S1). The studies generally met the MMAT quality criteria, and in the case of the qualitative studies, all the criteria were met. Of the three mixed-methods studies, only one provided data to respond to all five of the criteria. Most of the RCTs met the criteria, apart from the outcome assessors being blinded. Overall, 85% (n = 23) of the studies met 60%–100% of the MMAT checklist, suggesting moderate to high quality.

Measuring adherence

Measurement of adherence varied greatly across trials in all health conditions and included adherence of both patient participants as well as staff (Supplementary Table S2). The most common adherence measure was the number of sessions (n = 17 studies; 10 out of the 14 stroke studies, two neurological condition studies, two post-surgical studies, one osteoarthritis, one chronic respiratory disease and one acute medical elderly study). Five of the six studies measuring duration of session (min) were in stroke. Only three studies used patient-reported measures (one stroke, one osteoarthritis, one post-surgical). Only seven of the included studies reported pre-specified adherence level(s). Pre-specified adherence levels included completing/attending a minimum number of sessions, delivering the protocol on a minimum number of days, the minimum/maximum duration of intervention sessions, the minimum patient satisfaction score and delivering a minimum percentage of the protocol activities. A rationale for the pre-specified adherence level was provided by one study.³⁴

Barriers and facilitators to intervention protocol adherence

Barriers and facilitators are presented in Tables 2 –4 using the CFIR 2.0 components.^4,5 Most of the data in Tables 2 –4 are from stroke studies. Non-stroke data references are marked with †.

Table 2.

Barriers and facilitators to intervention protocol adherence (Innovation, Outer Setting and Inner Setting).

INNOVATION (the intervention)
The intervention and its evidence-base:
BARRIERS	Practical experience of using the intervention tended to outweigh published evidence²³ Intervention not suitable for all patients in the clinical setting where research is being delivered²³
FACILITATORS	More selective inclusion criteria and exclusion of participants whose cognitive, mood, motor or balance impairments precluded participation²⁸ No one-size-fits-all all approach to rehabilitation which needs to be reflected in the intervention protocol²⁸
Adaptability
BARRIERS	Lack of information about how the intervention protocol can be adapted to individuals’ needs. The need to adapt to clinical needs and priorities, and the need to change practice to overcome barriers. Frequency and duration of the intervention and the intervention not suited to everyone²⁸
FACILITATORS	Intervention protocol needs to be adaptable for clinical reality²⁸ Flexibility within the intervention protocol to adapt to local context, e.g. ‘clinical reality’ as some patients needed to focus on their upper limb, others education²³ Imperative that researchers are explicit regarding key intervention components and what can be adapted to help ensure implementation fidelity²³ Implement learning from implementation science into trial protocols, e.g. define the essential aims, objectives and elements of the interventions and work iteratively with clinical staff to identify strategies, overcome boundaries to flexibility and build confidence²⁸
Complexity
BARRIERS	The test and equipment made the intervention difficult to implement. The frequency and duration of sessions was considered difficult to implement outside of the study in terms of staffing²³ Intervention frequency (protocol mandated high frequency for people with milder strokes) and the number of staff needed to deliver the intervention with people with severe impairments³⁰ Complexity of participant selection criteria²⁰ Methodological differences in intervention compared to usual clinical practice, e.g. direct supervision versus patient-led therapy⁴¹ Perceived intervention complexity by healthcare staff delivering the intervention. Some staff may find a new intervention basic and simple, whereas others may consider the same intervention complex and challenging^37†
FACILITATORS	Future trials, particularly of patient-led therapy, should include strategies to maximise adherence⁴¹ Graded exercise test and the monitoring of heart rates enabled therapists to push patients harder than they normally would have, giving the therapists self-efficacy²³
Design
BARRIER	REDCap lacked detailed data entry and longitudinal patient tracking²⁰
FACILITATORS	Design quality and packaging of intervention: Structure and detail of the manual and paperwork, plus tips and ideas to help different therapists treat the same patient²³
OUTER SETTING (the setting in which the inner setting exists, e.g. hospital system)
Hospital system systems
BARRIERS	No data found
FACILITATORS	Context is key to ensure that external policies and guidelines are considered, e.g. Canadian guidelines state a graded exercise test should be done for all²³
Local conditions
BARRIERS	Lack of clinical utility of the data entry software tool²⁰
FACILITATORS	No data found
INNER SETTING (the setting the intervention is delivered, e.g. hospital wards/rehabilitation units)
Ward/rehabilitation unit
BARRIERS	Acute model and culture–rapid pace and focus on early discharge of acute hospitals rendered rehabilitation a low priority.^30,32 Competing organisational priorities such as discharge pressure, accreditation work and transfer policies were commonly reported as being a challenge.³⁰ Competing demands/clinical priorities and dilemmas over how to prioritise trial interventions compared to their usual therapy and other clinical demands.^28,32 Insufficient staffing (Connell et al.²²).
FACILITATORS	Shift in how therapists prioritise treatment and buy-in from all therapists and managers³²
Leadership
BARRIER	Lack of support from management in the recruitment process²⁰
FACILITATORS	Leadership support and engagement^23,28 to champion and encourage the trial within their units³⁰
Team working
BARRIERS	Team challenges – poor MDT working, e.g. poor communication, planning; organisational barrier³² Lack of established interdisciplinary team working practices³⁰
FACILITATORS	Teamwork central to implementation success, this includes communication and coordination. Getting staff on-board which linked to education, training and leadership, shift in culture and control and working differently, staffing model changes, visible leadership^30,32 Strong interdisciplinary relationships²⁸ Flexible working practices, shared interdisciplinary roles and mutual trust³⁰
Physical environment
BARRIERS	The ward environment, e.g. lack of space to deliver the intervention, lack of equipment such as chairs^28,30,32 Lack of available bed in acute stroke unit delayed intervention delivery^30,32
FACILITATORS	Availability of equipment^23,30
Staffing
BARRIERS	Inadequate staffing levels affected consistent intervention delivery particularly in the face of competing demands³⁰ High turnover of staff,^32,41 with experienced staff leaving and replaced with untrained staff and/or those who were less committed to the trial ³² Frequency and duration of sessions considered difficult to implement by staff on top of existing high workloads³² Reduced out-of-hours staffing caused additional difficulties with weekend and night nurses tending to have less training, confidence or priority for providing the intervention³² Staffing issues and organisational issues such as management and staff restructuring³⁸
FACILITATORS	To help with staff turnover, the training package needs to be available in the long term (possibly using electronic learning methods)⁴¹ Intermittent training updates scheduled for each site throughout the trial and at periods of high staff changeover²²
Communication
BARRIERS	No data found
FACILITATORS	Communication important to ensure treatment schedules work to allow for longer sessions³²
Culture
BARRIERS	Therapists prior experience of research. Staff readiness for implementing the protocol³⁰
FACILITATORS	Therapists who have worked in research intensive departments²³ Establishing a routine when delivering the intervention to help it become normal practice²⁸
Access to knowledge and information
BARRIERS	Staff not recognising they had received training and felt their preparation to deliver the interventions and deal with difficulties was incomplete⁴¹ Staff reported lack of confidence to deliver the new intervention, especially adapting to individual participants, some stated they felt ill-equipped²⁸
FACILITATORS	Time and support for staff to develop the skills, strategies and confidence to identify suitable patients, deliver new treatments, adapt the intervention to individuals’ needs and balance the demands of delivering the trial intervention according to the treatment protocol with other clinical and professional priorities²⁸ TRAINING Formal training package, possibly with time away from the clinical environment, certificates of attendance and ongoing support to overcome difficulties as they occurred, may have more effectively enabled staff to build their confidence and skills to deliver the interventions. Objective monitoring and feedback on competence²⁸ Include elements to promote and support self-efficacy and autonomy while teaching patients how to undertake the therapy. This also needs to be explicitly addressed in the training package for staff, with strategies on how to manage patient’s expectations⁴¹ Experienced and trained staff³⁰ Intermittent training updates are scheduled for each site throughout the trial and at periods of high staff changeover²²

Table 3.

Barriers and facilitators to intervention protocol adherence (Individuals and Innovation).

INDIVIDUALS (roles and characteristics of patients, relatives and staff using COM-B)
Capability – Patients & family
BARRIERS	Participants reported discomfort and the intervention was perceived as challenging, hard work, tiring, induced fatigue, confusing or frightening by patient participants¹⁸ Assessments within the study were deemed not to apply because of patient-related factors such as lack of mobility or dexterity, severe aphasia or impaired cognition³⁸ Acuity, instability and complexity of stroke; severity of stroke; fatigue; family anxiety³² Haemodynamic/respiratory instability, sleeping, procedures, dialysis, agitation/delirium, heavily sedated, complex wound, patient paralysed, patient refusal, pain, patient position, invasive device or end-of-life care^39† Staff stated the intervention was difficult, and sometimes not feasible for some patients with cognitive impairments (such as memory, concentration, problem-solving and initiation difficulties and neglect); mood changes, e.g. severe depression and/or emotionally devastated by their sudden illness were perceived to be unable to initiate patient-led therapy; severe weakness, limited sitting balance and visual deficits (such as hemianopia) made the patient-led therapy physically challenging²⁸ Patients with respiratory limiting factors (chronic obstructive airway disease), lower-limb limiting factors (arthritis or joint replacement) or pre-morbid reduced mobility/disability¹⁹ Patient fatigue.^24,43 Participants discontinued because they did not like the exoskeleton device and did not wish to continue the training, reported persistent knee pain while using the device or severe fatigue³¹ Patients unable to achieve the ‘correct position’ which was stated in the protocol²⁸ On some occasions families raised concerns that the VEM intervention was preventing necessary rest for the patient.^30,32
FACILITATORS	Recognising/acknowledging that the intervention is not suitable for all (especially elderly and with comorbidities)²³ Involving relatives/visitors who supervised patients during their visits, student nurses/ and therapists and all members of the multi-disciplinary team was key to supporting patients to complete their therapy²⁸
Capability – Staff
BARRIERS	Severity of stroke: early delivery of the VEM protocol was viewed as challenging in patients with drowsiness or reduced cognition. They would require more staff to assist mobilisation. The challenges with milder strokes were mainly due to the high frequency mandated by the VEM protocol. Staff reported that patients commonly reported fatigue as a problem which sometimes prevented mobilisation³⁰ Readiness to/stage of change. Self-efficacy of therapists. Knowledge, skills, beliefs and behaviour about the intervention. Feeling obliged to participate²³ LACK OF CONFIDENCE Lack of confidence in the skills needed to deliver the intervention (Horne et al.,;²⁷ Langhorne et al., ²⁹) and the desire/need for more training on the intervention²⁸
FACILITATORS	No data found
Opportunity – Patients
BARRIERS	Limitations of available training time due to other team-based interventions (such as speech- and/or occupational therapy)⁴³
FACILITATORS	Involving relatives/visitors who supervised patients during their visits, student nurses/ and therapists, and all members of the multi-disciplinary team was key to supporting patients to complete their therapy²⁸
Opportunity – Staff
BARRIERS	Encouraging patients to exercise in their own time and work independently contrasted strongly with the usual way therapy was delivered, in which a therapist works with the patient in a highly controlled environment using their expertise to assist (or facilitate) the patient to move or work in a very specific way²⁸ Staff not ‘on-board’ from all staff and managers when scheduling to allow for longer sessions²³ Delivering the intervention was time consuming and staff felt this detracted from the ‘real‘ standard of care³⁰
FACILITATORS	Whole team needs to be ‘on-board’ to help with the shift in how treatments are prioritised, who to see and how to schedule²³ Getting staff on-board with the intervention. Positive attitude towards implementing the protocol, staff’s determination to work around organisational barriers fostering a culture ‘appropriate’ for the trial. Solution-focused and staff identifying innovative approaches to timetabling therapy to accommodate patient factors such as fatigue³⁰ Buy-in from all staff and managers when scheduling to allow for longer sessions³² Sufficient staffing with buy-in from the whole team and good communication²³ Personal attributes such as previous research experience²³
Motivation – Patients
BARRIERS	Staff identified difficulty with patients’ motivation and self-efficacy, stating many patients lacked motivation and had an external locus of control in relation to the intervention²⁸
FACILITATORS	Increased confidence, self-belief and reassurance plus motivation through the presence of a healthcare professional during the trial¹⁸ Giving feedback on treatment progression and structuring the intervention progression may help increase patient motivation and adherence to CIMT training⁴⁰
Motivation – Staff
BARRIERS	The intervention fits better with some staff’s belief systems than others due to conflict with quality of movement versus quantity of movement, and some therapists wanted to adapt the intervention for clinical practice to accommodate their beliefs about ensuring movement quality²³ Staff attitudes and beliefs, e.g. resistance to change of practice when delivering the intervention; staff beliefs about roles and responsibilities for delivering the intervention; staff beliefs about the consequences of the intervention, e.g. staff beliefs about the acuity and complexity of patients’ medical conditions and complex problems; severity of stroke–intervention protocol was viewed as challenging to deliver for patients with drowsiness and reduced cognition. Fatigue commonly reported as a barrier by patients which sometimes prevented intervention delivery.^30,32 Therapists’ beliefs about quality of movement and allowing participants to move in a different way were considered potentially ‘detrimental’ which raised ethical concerns. Staff were reluctant to relinquish control and continued to provide their usual intervention rather than allow patients to lead their therapy³⁰ Staff attitudes and beliefs – not ‘on-board’ with the intervention/trial, beliefs about roles and capabilities, beliefs about consequences³² Some members of the multi-disciplinary team (physicians) reluctant to promote the intervention even though they were aware of the necessity and relevance but felt it was the nurses’ role³⁷ Staff considered it was detrimental to patients’ overall progress to allow them to move in a different way. Quality of movement and relinquish control of their usual practice²⁸ Staff felt they had to manage participants’ expectations about what the protocol required patients to do (e.g. exercise in their own time)²⁸ Staff concerned about relinquishing control of the patients’ activity, particularly that patients may do the exercises incorrectly or may overdo it, as undertaking effortful activities was considered detrimental by some staff²⁸
FACILITATORS	Staff willingness to relinquish some control of traditional roles and practices³⁰ Explicit training for staff to help manage patients’ expectations including motivation and self-efficacy²⁸ Safety checks and equipment (heart rate monitors) gave staff confidence to push patients harder²³ Therapists’ belief that the intervention was beneficial for their patients²⁰ Readiness of therapists to change their practice to implement the intervention, staff beliefs about the intervention (if the intervention aligned with therapists’ beliefs, this positively affected implementing the intervention; adherence to intervention protocol when there was no conflict of quality vs. quantity)²³
IMPLEMENTATION PROCESS (the activities and strategies used to deliver the intervention)
Delivering the intervention
BARRIERS	Competing priorities and dilemmas of prioritising trial interventions and usual therapy and other clinical demands. Actual/perceived lack of training/support on trial intervention²⁸ Ability to adapt the intervention to individual needs of trial participants. Challenges with using equipment and setting up the environment. Difficulty juggling patient-led therapy with other professional priorities. Conflict with some policies such as manual handling and falls. The number of staff required to deliver the intervention, especially to patients with drowsiness and cognitive impairment³⁰ Lack of leadership support on participant recruitment, scheduling issues, lack of experience of the REDCap and delivery of the intensity-based programme (insufficient training on the intervention and trial processes)²⁰
FACILITATORS	Establishing a routine. Involving others (visitors, healthcare students and whole multi-disciplinary team)²⁸ Establishing good relationships among multi-disciplinary team.²⁷ Team working–closer working of nurses and physios³⁰ Staff education and training.^28,32 Staff education and training felt to be a cornerstone of getting staff involved³⁰ Allowing assistants to take responsibility for supervising participants²⁸ Quality and packaging of the trial, e.g. therapists liked the structure and detail of a manual and paperwork, especially tips and a bank of sample exercises that might work for different patients. The structured format helped support different therapists treating the same patients²³ Site initiation sessions to discuss and solve local barriers, provided reminders, decision tools and ongoing phone and online support for queries plus site champions with co-leadership from nurse and physiotherapist³² Clear strategies to ensure fidelity is maintained and monitored in future trials^32,41 Early adopters (e.g. champions), manuals, guidelines, training and feedback.^37†
Assessing context, reflecting and evaluating, adapting
BARRIERS	Lack of detail on how to deliver the interventions and adapt them to individuals or different contexts²⁸
FACILITATORS	It is imperative that researchers are explicit regarding key intervention components and what can be adapted to help ensure implementation fidelity²³ Monitoring and evaluation of protocol adherence and feedback to therapists on intervention targets part way through the trial increased protocol adherence²² Monitoring and feedback earlier in the trial to optimise protocol adherence²² Ensure trial is acceptable to the patient and staff who deliver it and feasible within the treatment setting during the pilot phase of trial development²²

Table 4.

Staff and patient experiences of inpatient rehabilitation trials.

STAFF EXPERIENCES
Buhagiar et al.²⁰	Quantitative survey with therapists to understand the barriers to rehabilitation trial protocol implementation • 100% disagreed that it was difficult to integrate the intensity-based programme into their clinical practice • 60% agreed and 20% strongly agreed it was challenging to recruit patients • 100% agreed that once enrolled, patients responded favourably to the intensity-based approach • 60% strongly agreed and 40% agreed that involvement in the study positively impacted their practice now
Dorsch et al.²³	Semi-structured interviews to determine factors influencing implementation of intensive stroke rehabilitation • Generally had positive experiences regarding the intervention However, therapists felt they would adapt the protocol to accommodate their beliefs about ensuring the quality of movement • Not always sure how to deliver the intervention but were keen to increase patients’ intensity of practice • Thought the patients really enjoyed the intervention, and some therapists were surprised how much patients could tolerate the intensive regime.
Kattenstroth et al.²⁸	Focus groups to determine views in delivering a patient-led multi-centre inpatient stroke rehabilitation trial • Generally positive about the notion of patient-led therapy but recognised it was not feasible for all patients • Some therapists struggled with professional dilemmas of how the intervention contrasted strongly with the usual way therapy was delivered • Staff shared they were ‘worried’ and others were ‘concerned’ about the impact the intervention may have on patients’ mood and motivation.
Louie et al.³⁰	Qualitative; semi-structured interviews to determine staff experiences of delivering a multi-centre RCT • The extra work of delivering the intervention was felt to be justified by the hope that the trial might benefit stroke patient outcomes • Several staff reported a positive impact on teamwork at their site. Particularly, closer working of nurses and physiotherapists and some changes in their professional roles • Over the duration of the trial some staff perceived a change in usual practice. This was not a universal perception but was noted by a substantial minority.
Lupo et al.³²	Semi-structured interviews as part of a multi-centre stroke RCT • Delivering the intervention was time-consuming but added interest to the workday and was enjoyable. The extra work of delivering the intervention was felt to be justified by the hope that the trial may benefit patient outcomes • Several staff reported a positive impact on teamwork at their site. Particularly, closer working of nurses and physiotherapists and some changes in their professional roles • Over the duration of the trial some staff perceived a change in usual practice with patients being mobilised earlier and more intensively. This was not a universal perception but was noted by a substantial minority.
PATIENT EXPERIENCES
Bernhardt et al.¹⁸	Patient daily diaries and focus groups to determine patient acceptability and feasibility and experience of the intervention • Participants generally liked wearing the insoles, and wore them regularly throughout the day, some even wearing them all day. Some participants reported comfort, others discomfort when wearing • Task-specific gait training was described by some participants as ‘hard work’, ‘tiring’, ‘confusing’, ‘frightening’, ‘enjoyable’, ‘challenging’. • Participants felt a sense of achievement, relating that to ‘increased confidence’, ‘increased strength’, ability to walk/run and return to ‘normal daily activities’ • Other patient experiences were related to the home-based section of the study which are not relevant for this review.

Protocol adherence in inpatient rehabilitation trials of stroke versus other health conditions

Protocol adherence in inpatient rehabilitation trials varied across all conditions, as well as across all stroke trials (see Supplementary Table S3).

Staff and patient experiences

Six studies captured staff and patient experiences of participating in inpatient rehabilitation trials.^{17,19,22,27,29,31} Only one study¹⁷ captured patient experiences, via daily diaries and focus groups. The other five studies captured staff experiences via semi-structured interviews, focus groups or a quantitative survey (Table 4). No studies captured both patient and staff experiences.

Predictors of adherence

Only one study highlighted predictors of protocol adherence.⁴⁰ This stroke study identified demographic and clinical characteristics as predictors of protocol adherence (age, side of weakness, time since stroke, treatment group, neglect and sensation). Two other stroke studies identified patient demographic and clinical characteristics that should be considered in future inpatient rehabilitation trial protocols, although they were not specifically reported as predictors. Connell et al.²² identified concerns about the suitability of the intervention in patients who were elderly or with comorbidities, and Stock et al.³⁹ suggested consideration of modifying protocols according to patients’ age, sex and stage after stroke.

Discussion

Adherence is a key variable influencing the outcome of clinical trials, and appropriate consideration of adherence is widely recommended.^13,43,44 To accurately determine treatment effect and inform clinical practice, it is imperative that rehabilitation trialists identify ways to optimise adherence in the planning, design and delivery of physical rehabilitation trials, as well as the reporting of results. This systematic review highlights that adherence to inpatient rehabilitation trial protocols is complex and a multitude of factors influence adherence across all constructs of the CFIR: innovation, outer setting (hospital system), inner setting (hospital ward/rehabilitation unit), individual (those receiving and those delivering the intervention) and implementation process. These factors have been identified in several systematic reviews of physical exercise;^45–47 thus, they are not isolated to inpatient rehabilitation trial protocols. Rehabilitation trials depend on behaviours of people such as those delivering or receiving a trial intervention, as well as team and organisational behaviour.⁴⁸

Adherence to intervention protocols refers to how closely the behaviour of trial participants aligns with the intervention assigned to them.² Conversely, intervention fidelity refers to how closely an intervention protocol is delivered by staff.⁴⁹ These definitions are somewhat simplistic and do not capture the complexity of the behaviours of those receiving and delivering the rehabilitation trial protocols and the context in which the trial is delivered. As such, behavioural science theories and frameworks have been used to understand and improve adherence to health interventions, including the Health Belief Model, the Theory of Reasoned Action and the Theory of Planned Behaviour, as summarised by Brawley and Culos-Reed.⁵⁰ A more recent framework, the BCW⁵¹ provides a practice framework to design interventions that may optimise adherence to inpatient rehabilitation trial protocols. The BCW is incorporated into CFIR 2.0,⁴ and we have mapped the barriers and facilitators to adherence to capacity, motivation and opportunity in this systematic review. This may help rehabilitation trialists understand and modify adherence behaviours, thereby informing protocol development and trial training to optimise adherence.

Staff beliefs were a common barrier to rehabilitation trial protocol adherence. Beliefs have been described as ‘a cognitive process resulting in a concrete cognition of how we think things are’⁵² and determines a person’s behaviour, in this case, clinical decision-making concerning adherence to rehabilitation trial protocols. Staff beliefs have been cited as a barrier to implementing evidence-based stroke rehabilitation as recommended in national clinical guidelines.^53,54 This may be due to unconscious (implicit) biases that are intuitively held preferences or stereotypes of which we are unaware.⁵⁵ The presence of unconscious bias among healthcare professionals has been identified as a concern because it affects clinical decision-making and treatment selection.⁵⁶ When staff are delivering rehabilitation trial interventions, the research may challenge their biases if the intervention or potential outcome conflicts with their beliefs. Some of these issues could be related to the staff’s knowledge and understanding of research and their role in clinical trials. If staff lack knowledge of the core purpose of research and their role in clinical trials, they may not fully appreciate the importance of preventing their beliefs from impacting upon their behaviour, which can affect trial adherence.⁵⁶ Staff behaviour in rehabilitation trials is therefore acknowledged as being particularly challenging, but training to increase knowledge may overcome some of the barriers identified in our review.

There is no agreement on what comprises effective training, which is attributed to the heterogeneity of rehabilitation trial interventions. However, common barriers and facilitators were identified that could be used to develop a core set of standards for training in stroke and other rehabilitation trials. For example, beliefs and behaviours of those delivering and receiving the intervention and how they influence trial adherence, staff’s confidence in delivering the intervention, and their knowledge on the core purpose of research, roles and responsibilities in conducting rehabilitation clinical trials. These core standards have the potential to optimise adherence and facilitate recruitment, retention and intervention fidelity. However, consideration needs to be given to when and how the training is delivered. Data from these included studies suggest multi-modal training and support may facilitate adherence to trial protocols.

Multi-modal training and support could incorporate online resources,⁵⁷ vignettes,⁵⁸ mentoring⁵⁹ peer support,⁶⁰ a secure forum to share ideas or ask questions of other staff involved in the trial, and more in-depth training before commencing recruitment, could benefit adherence to inpatient trial protocols. Web-based training for staff delivering the intervention has been effectively used in rehabilitation trials, which have delivered information in multi-modal learning formats.⁶¹ An advantage of web-based training is that it minimises training costs without compromising quality and effectiveness, allowing it to be delivered at the start and at regular intervals throughout the trial to maintain momentum and accommodate new staff.

In the United Kingdom, all staff involved in any clinical trial activities must complete Good Clinical Practice (GCP) training.⁶² Currently, GCP training does not incorporate aspects that may optimise protocol adherence, such as clinical and personal equipoise,⁶³ gatekeeping⁶⁴ and unconscious bias.⁵⁵ Integrating these topics within a standardised multi-modal training package for rehabilitation trials offers a way of optimising adherence. There is a paucity of evidence on patient perspectives of adhering to inpatient rehabilitation trial protocols. It is possible that patient perspectives were sought from patient and public involvement and engagement partners⁶⁵ during trial design and development of studies included in our systematic review. Issues associated with the patients’ capability, opportunity and motivation were reported by staff, not patient participants themselves. Staff reported that intervention delivery was difficult and sometimes not feasible due to patient impairments, such as cognitive or communication impairments, mood changes, severe weakness, visual deficits, patient fatigue, and the general acuity of the patient’s condition. The lack of data from patient participants in the included studies makes it difficult to know whether patients and staff held different perceptions about barriers to adhering to the trial protocols.

Health conditions

This review included inpatient rehabilitation trials in stroke and other non-stroke conditions to determine whether adherence to the stroke trial protocols differs from those in other health conditions. It is important to acknowledge the individual different disease courses, for example, sudden (e.g. stroke, spinal cord injury, cancer or surgery), versus chronic conditions (e.g. respiratory disease or neuro-degenerative such as Multiple Sclerosis) and factors related to the condition and the individual, for example, physical, cognitive, psychological, demographic and socioeconomic. For example, in stroke and neurological conditions, cognitive and communication impairments, mood changes, fatigue and severe weakness/disability were reported as barriers to protocol adherence. However, trials in non-stroke health conditions identified similar barriers and facilitators in terms of the acuity of the patients’ condition and comorbidities. This suggests that the trajectories and disease characteristics of individual health conditions are of lesser importance when determining adherence to inpatient rehabilitation research protocols. However, rehabilitation trial protocols need to be adaptable to accommodate the varying severity of physical, cognitive and psychological impairments associated with neurological conditions. This in turn should be reflected in the rehabilitation protocol design and training provided to staff.

Adherence measures and levels of adherence

The variability of adherence measures makes comparison between studies or inclusion within a meta-analysis difficult. High variability of adherence measures and the absence of published standardised guidelines for measuring adherence in RCTs have been identified in a systematic review of current practice in the measurement and interpretation of adherence in RCTs.⁶⁶

There are no guidelines for categorising levels of adherence in rehabilitation or other non-pharmacological clinical trials. Only seven studies set and reported a pre-specified adherence level, with only one study providing a rationale for the specified level. It is unclear whether rehabilitation trialists are not considering protocol adherence and the impact it may have on trial results and implementation, or whether the lack of consensus of adherence levels means currently there is no benefit to categorising patients into arbitrary levels without evidence-based rationale. Acceptable adherence levels have been defined as 80%, but this does not appear to be based on a sound theoretical framework.⁶⁵ The development of evidence-based adherence levels is needed to apply to future inpatient rehabilitation trials.

Predictors of adherence

There is a lack of evidence evaluating predictors of inpatient trial protocol adherence in the included studies. The World Health Organization² identified multiple predictors of adherence and suggested adherence is multi-dimensional with a series of factors, rather than one single factor, determining adherence. They highlight the interplay of five dimensions, social and economic, health-care team and system-related, condition-related, therapy-related and patient-related, which align with the CFIR domains. Identifying factors that predict adherence to inpatient rehabilitation trial protocols and how these factors interact would be helpful in designing and implementing inpatient rehabilitation trials to optimise protocol adherence.

Implications for future research

This systematic review has highlighted the following implications for future research:

Using behavioural science methodologies and frameworks like the BCW and CFIR 2.0 during the design and formulation of inpatient rehabilitation trial protocols could help address identified behavioural challenges. This approach may enhance adherence among both providers and recipients of the intervention, potentially boosting its effectiveness and improving participants’ quality of life.

Consensus of adherence level categorisation would aid in interpretation of results. For example, a traffic light system, similar to that used for progression criteria⁶⁷ could be useful to standardise adherence levels. This would minimise research waste by implementing changes to improve adherence or stop the trial.

Designing and implementing inpatient rehabilitation trial protocols with consideration for the various dimensions of adherence and how they intersect may enhance adherence.

Standardised training in inpatient rehabilitation trials would provide consistency and may overcome multiple barriers and improve adherence; as yet this does not exist.

There is an absence of data related to outer settings such as hospital systems. Clinical trials operate within the broader context of a system, which faces its own stresses and demands for delivering healthcare (as distinct from research). For instance, UK hospitals are increasingly reaching Operations Pressure Escalation Level 4,⁶⁸ indicating a state where they are deemed ‘unable to deliver comprehensive care and patient safety is at risk’. Consequently, hospital staff are compelled to prioritise discharge, compromising research delivery unless additional funding is allocated to address staffing requirements. Trialists must assess how this situation impacts on adherence to overall trial delivery and consider this when designing research protocols.

Strengths and limitations

This is a comprehensive systematic review of adherence to inpatient rehabilitation trial protocols which identified published studies over the last 16 years. Adhering to the JBI Methodological guidance for the conduct of mixed-methods systematic reviews, utilising the MMAT and PRISMA reporting checklist, this review provides a robust synthesis of protocol adherence in inpatient rehabilitation trial literature. The review includes authors being contacted for raw data when this was not provided in the published article. Identifying relevant text within studies was a lengthy process because the language and definitions used were not standardised. This required subjective judgement and is open to interpretation. Other researchers could have reached different conclusions and mapped data to different CFIR constructs. The findings that some constructs had no barriers or facilitators mapped to them could be because of the mapping process itself. Only including studies published in English may be a limitation.

Conclusion

Adherence to inpatient rehabilitation trial protocols is multi-dimensional, with many factors interacting with one another. There are multiple barriers and facilitators to adherence to inpatient rehabilitation trial protocols, most related to the individual in terms of capability, opportunity and motivation. The beliefs of staff delivering the intervention appear to be a common barrier to protocol adherence. Understanding factors affecting adherence and how these interact with one another is key in the design, implementation and reporting of future inpatient rehabilitation trial protocols. Adherence in stroke and other health conditions appears to be similar. An absence of consensus on adherence measures and levels makes meaningful comparisons between trials difficult. A consensus about the categorisation of adherence levels, with a traffic light system would facilitate trialists to minimise research waste by systematically considering the need to either implement changes during the trial to improve adherence or to stop the trial.

Supplemental Material

sj-docx-1-ctj-10.1177_17407745251358262 – Supplemental material for Optimising adherence to inpatient rehabilitation trial protocols: A mixed-methods systematic review

Supplemental material, sj-docx-1-ctj-10.1177_17407745251358262 for Optimising adherence to inpatient rehabilitation trial protocols: A mixed-methods systematic review by Angela Logan, Jonathan Marsden, Jennifer Freeman, Emma Cork and Bridie Kent in Clinical Trials

Supplemental Material

sj-docx-2-ctj-10.1177_17407745251358262 – Supplemental material for Optimising adherence to inpatient rehabilitation trial protocols: A mixed-methods systematic review

Supplemental material, sj-docx-2-ctj-10.1177_17407745251358262 for Optimising adherence to inpatient rehabilitation trial protocols: A mixed-methods systematic review by Angela Logan, Jonathan Marsden, Jennifer Freeman, Emma Cork and Bridie Kent in Clinical Trials

Supplemental Material

sj-docx-3-ctj-10.1177_17407745251358262 – Supplemental material for Optimising adherence to inpatient rehabilitation trial protocols: A mixed-methods systematic review

Supplemental material, sj-docx-3-ctj-10.1177_17407745251358262 for Optimising adherence to inpatient rehabilitation trial protocols: A mixed-methods systematic review by Angela Logan, Jonathan Marsden, Jennifer Freeman, Emma Cork and Bridie Kent in Clinical Trials

Supplemental Material

sj-docx-4-ctj-10.1177_17407745251358262 – Supplemental material for Optimising adherence to inpatient rehabilitation trial protocols: A mixed-methods systematic review

Supplemental material, sj-docx-4-ctj-10.1177_17407745251358262 for Optimising adherence to inpatient rehabilitation trial protocols: A mixed-methods systematic review by Angela Logan, Jonathan Marsden, Jennifer Freeman, Emma Cork and Bridie Kent in Clinical Trials

Supplemental Material

sj-docx-5-ctj-10.1177_17407745251358262 – Supplemental material for Optimising adherence to inpatient rehabilitation trial protocols: A mixed-methods systematic review

Supplemental material, sj-docx-5-ctj-10.1177_17407745251358262 for Optimising adherence to inpatient rehabilitation trial protocols: A mixed-methods systematic review by Angela Logan, Jonathan Marsden, Jennifer Freeman, Emma Cork and Bridie Kent in Clinical Trials

Footnotes

Acknowledgements

The authors acknowledge the contribution of patient and public involvement and engagement partners in the conceptualisation and review of the manuscript. Thanks to Dr Wendy Clyne for her contribution to developing the search terms and PROSPERO protocol.

Authors’ note

The views expressed in this publication are those of the authors and not necessarily those of Royal Devon University Healthcare NHS Foundation Trust or the NHS.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship and/or publication of this article: The lead author received partial funding from the Royal Devon University Healthcare NHS Foundation Trust to prepare the manuscript.

ORCID iD

Angela Logan

Data availability

All data analysed in this systematic review are included in this published article and its supplementary materials. No primary data were collected. Additional information related to the search strategy, data extraction and analysis is available from the corresponding author upon reasonable request.

Supplemental material

Supplemental material for this article is available online.

References

Carroll

Patterson

Wood

, et al. A conceptual framework for implementation fidelity. Implement Sci 2007; 2: 40.

World Health Organization. Adherence to long-term therapies: evidence for action, http://www.who.int/chp/knowledge/publications/adherence_full_report.pdf (2012)

Logan

Freeman

Kent

, et al. Functional standing frame programme early after severe sub-acute stroke (SPIRES): a randomised controlled feasibility trial. Pilot Feasibility Stud 2022; 8(1): 50.

Damschroder

Reardon

Opra Widerquist

, et al. Conceptualizing outcomes for use with the Consolidated Framework for Implementation Research (CFIR): the CFIR Outcomes Addendum. Implement Sci 2022; 17(1): 7.

Damschroder

Reardon

Widerquist

MAO

, et al. The updated consolidated framework for implementation research based on user feedback. Implement Sci 2022; 17(1): 75.

Silver

Jones

Redmond

, et al. Facilitators and barriers to the implementation of new critical care practices during COVID-19: a multicenter qualitative study using the Consolidated Framework for Implementation Research (CFIR). BMC Health Serv Res 2023; 23(1): 272.

Michie

Atkins

West

. The behaviour change wheel: A guide to designing interventions. Sutton: Silverback Publishing 2014.

Page

McKenzie

Bossuyt

, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021; 372: n71.

Vrijens

De Geest

Hughes

, et al. A new taxonomy for describing and defining adherence to medications. Br J Clin Pharmacol 2012; 73(5): 691–705.

10.

McGowan

Sampson

Salzwedel

, et al. PRESS peer review of electronic search strategies: 2015 guideline statement. J Clin Epidemiol 2016; 75: 40–46.

11.

Rethlefsen

Kirtley

Waffenschmidt

, et al. PRISMA-S: an extension to the PRISMA statement for reporting literature searches in systematic reviews. Syst Rev 2021; 10(1): 39.

12.

Ouzzani

Hammady

Fedorowicz

, et al. Rayyan – a web and mobile app for systematic reviews. Syst Rev 2016; 5(1): 210.

13.

Hoffmann

Glasziou

Boutron

, et al. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. Gesundheitswesen 2016; 78(3): 175–188.

14.

Stern

Lizarondo

Carrier

, et al. Methodological guidance for the conduct of mixed methods systematic reviews. JBI Evid Implement 2021; 19(2): 120–129.

15.

Hong

Fabreragues

Bartlett

, et al. The mixed methods appraisal tool (MMAT) version 2018 for information professionals and researchers. Education for Information 2018; 34(4): 285–291.

16.

Ahn

Hur

Kim

, et al. The effects of inpatient exercise therapy on the length of hospital stay in stages I-III colon cancer patients: randomized controlled trial. Int J Colorectal Dis 2013; 28(5): 643–651.

17.

Aries

Pomeroy

Sim

, et al. Sensory stimulation of the foot and ankle early post-stroke: a pilot and feasibility study. Front Neurol 2021; 12: 675106.

18.

Bernhardt

Dewey

Thrift

, et al. A very early rehabilitation trial for stroke (AVERT) phase II safety and feasibility. Stroke 2008; 39(2): 390–396.

19.

Bowden

Monsch

Middleton

, et al. Lessons learned: the difficulties of incorporating intensity principles into inpatient stroke rehabilitation. Arch Rehabil Res Clin Transl 2020; 2(2): 100052.

20.

Buhagiar

Naylor

Harris

, et al. Effect of inpatient rehabilitation vs a monitored home-based program on mobility in patients with total knee arthroplasty: the HIHO Randomized clinical trial. JAMA 2017; 317(10): 1037–1046.

21.

Collier

Bernhardt

. The therapy ‘pill’: achieving treatment dose within a rehabilitation trial. Brain Impair 2008; 9(2): 191–197.

22.

Connell

Klassen

Janssen

, et al. Delivering intensive rehabilitation in stroke: Factors influencing implementation. Phys Ther 2018; 98(4): 243–250.

23.

Dorsch

Ada

Canning

. EMG-triggered electrical stimulation is a feasible intervention to apply to multiple arm muscles in people early after stroke, but does not improve strength and activity more than usual therapy: a randomized feasibility trial. Clin Rehabil 2014; 28(5): 482–490.

24.

Greening

Williams

JEA

Hussain

, et al. An early rehabilitation intervention to enhance recovery during hospital admission for an exacerbation of chronic respiratory disease: randomised controlled trial. BMJ 2014; 349: g4315.

25.

Hersche

Weise

Michel

, et al. Three-week inpatient energy management education (IEME) for persons with multiple sclerosis-related fatigue: feasibility of a randomized clinical trial. Mult Scler Relat Disord 2019; 35: 26–33.

26.

Hojskov

Moons

Egerod

, et al. Early physical and psycho-educational rehabilitation in patients with coronary artery bypass grafting: a randomized controlled trial. J Rehabil Med 2019; 51(2): 136–143.

27.

Horne

Thomas

Vail

, et al. Staff’s views on delivering patient-led therapy during inpatient stroke rehabilitation: a focus group study with lessons for trial fidelity. Trials 2015; 16: 137.

28.

Kattenstroth

Kalisch

Sczesny-Kaiser

, et al. Daily repetitive sensory stimulation of the paretic hand for the treatment of sensorimotor deficits in patients with subacute stroke: RESET, a randomized, sham-controlled trial. BMC Neurol 2018; 18(1): 2.

29.

Langhorne

Rodgers

, et al. A very early rehabilitation trial after stroke (AVERT): a Phase III, multicentre, randomised controlled trial. Health Technol Assess 2017; 21(54): 1–120.

30.

Louie

Mortenson

Durocher

, et al. Efficacy of an exoskeleton-based physical therapy program for non-ambulatory patients during subacute stroke rehabilitation: a randomized controlled trial. J Neuroeng Rehabil 2021; 18(1): 149.

31.

Luker

Craig

Bennett

, et al. Implementing a complex rehabilitation intervention in a stroke trial: a qualitative process evaluation of AVERT. BMC Med Res Methodol 2016; 16: 52.

32.

Lupo

Cinnera

Pucello

, et al. Effects on balance skills and patient compliance of biofeedback training with inertial measurement units and exergaming in subacute stroke: a pilot randomized controlled trial. Funct Neurol 2018; 33(3): 131–136.

33.

Mcleod

Diana

Hicks

. Sprint interval training versus moderate-intensity continuous training during inpatient rehabilitation after spinal cord injury: a randomized trial. Spinal Cord 2020; 58(1): 106–115.

34.

Nydahl

Günther

Diers

, et al. PROtocol-based MObilizaTION on intensive care units: stepped-wedge, cluster-randomized pilot study (Pro-Motion). Nurs Crit Care 2020; 25(6): 368–375.

35.

Ostermann

Morel

Chalé

, et al. Randomized controlled trial of enhanced recovery program dedicated to elderly patients after colorectal surgery. Dis Colon Rectum 2019; 62(9): 1105–1116.

36.

Pedersen

Kirk

Olesen

, et al. Feasibility and implementation fidelity of a co-designed intervention to promote in-hospital mobility among older medical patients – the WALK-Copenhagen project (WALK-Cph). Pilot Feasibility Stud 2022; 8(1): 80.

37.

Richards

Malouin

Nadeau

, et al. Development, implementation, and clinician adherence to a standardized assessment toolkit for sensorimotor rehabilitation after stroke. Physiother Can 2019; 71(1): 43–55.

38.

Sosnowski

Mitchell

White

, et al. A feasibility study of a randomised controlled trial to examine the impact of the ABCDE bundle on quality of life in ICU survivors. Pilot Feasibility Stud 2018; 4: 32.

39.

Stock

Thrane

Askim

, et al. Norwegian constraint-induced therapy multisite trial: adherence to treatment protocol applied early after stroke. J Rehabil Med 2015; 47(9): 816–823.

40.

Tyson

Wilkinson

Thomas

, et al. Phase II pragmatic randomized controlled trial of patient-led therapies (Mirror therapy and lower-limb exercises) during inpatient stroke rehabilitation. Neurorehabil Neural Repair 2015; 29(9): 818–826.

41.

van Bloemendaal

Bus

Nollet

, et al. Feasibility and preliminary efficacy of gait training assisted by multichannel functional electrical stimulation in early stroke rehabilitation: a pilot randomized controlled trial. Neurorehabil Neural Repair 2021; 35(2): 131–144.

42.

Wall

Borg

Vreede

, et al. A randomized controlled study incorporating an electromechanical gait machine, the Hybrid Assistive Limb, in gait training of patients with severe limitations in walking in the subacute phase after stroke. PLoS ONE 2020; 15(2): e0229707.

43.

Barbour

Bhui

Chescheir

, et al. CONSORT Statement for randomized Trials of nonpharmacologic treatments: a 2017 update and a CONSORT extension for nonpharmacologic trial abstracts. Ann Intern Med 2017; 167(1): 40–47.

44.

Skivington

Matthews

Simpson

, et al. A new framework for developing and evaluating complex interventions: update of Medical Research Council guidance. Int J Nurs Stud 2024; 154: 104705.

45.

Jordan

Holden

Mason

, et al. Interventions to improve adherence to exercise for chronic musculoskeletal pain in adults. Cochrane Database Syst Rev 2010; 2010(1): CD005956.

46.

Dennett

Madsen

Connolly

, et al. Adherence and drop-out in randomized controlled trials of exercise interventions in people with multiple sclerosis: a systematic review and meta-analyses. Mult Scler Relat Disord 2020; 43: 102169.

47.

Mahmood

Nayak

Deshmukh

, et al. Measurement, determinants, barriers, and interventions for exercise adherence: a scoping review. J Bodyw Mov Ther 2023; 33: 95–105.

48.

Gillies

Brehaut

Coffey

, et al. How can behavioural science help us design better trials? Trials 2021; 22(1): 882.

49.

Borrelli

. The assessment, monitoring, and enhancement of treatment fidelity in public health clinical trials. J Public Health Dent 2011; 71(Suppl. 1): S52–S63.

50.

Brawley

Culos-Reed

. Studying adherence to therapeutic regimens: overview, theories, recommendations. Control Clin Trials 2000; 21(5 Suppl): 156S–163S.

51.

Michie

van Stralen

West

. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci 2011; 6: 42.

52.

Jeffrey

Foster

. A qualitative investigation of physical therapists’ experiences and feelings of managing patients with nonspecific low back pain. Phys Ther 2012; 92(2): 266–278.

53.

McCluskey

Vratsistas-Curto

Schurr

. Barriers and enablers to implementing multiple stroke guideline recommendations: a qualitative study. BMC Health Serv Res 2013; 13: 323.

54.

Van Kessel

Hiller

English

. Physiotherapists’ attitudes towards circuit class therapy and 7 day per week therapy is influenced by normative beliefs, past experience, and perceived control: a qualitative study. Physiother Theory Pract 2017; 33(11): 850–858.

55.

FitzGerald

Hurst

. Implicit bias in healthcare professionals: a systematic review. BMC Med Ethics 2017; 18(1): 19.

56.

Al-Tannir

Katan

Al-Badr

, et al. Knowledge, attitudes, practices and perceptions of clinicians towards conducting clinical trials in an academic tertiary care center. Saudi Med J 2018; 39(2): 191–196.

57.

Connell

McMahon

Harris

, et al. A formative evaluation of the implementation of an upper limb stroke rehabilitation intervention in clinical practice: a qualitative interview study. Implement Sci 2014; 9: 90.

58.

Kathiresan

Patro

. Case vignette: a promising complement to clinical case presentations in teaching. Educ Health (Abingdon) 2013; 26(1): 21–24.

59.

Craven

Holmes

Powers

, et al. Embedding mentoring to support trial processes and implementation fidelity in a randomised controlled trial of vocational rehabilitation for stroke survivors. BMC Med Res Methodol 2021; 21(1): 203.

60.

Shapiro

Galowitz

. Peer support for clinicians: a programmatic approach. Acad Med 2016; 91(9): 1200–1204.

61.

Srikesavan

Williamson

Eldridge

, et al. A web-based training resource for therapists to deliver an evidence-based exercise program for rheumatoid arthritis of the hand (iSARAH): design, development, and usability testing. J Med Internet Res 2017; 19(12): e411.

62.

National Institute for Health Research. Good Clinical Practice (GCP), https://sites.google.com/a/nihr.ac.uk/crn-learn-help/about-gcp

63.

Alderson

. Equipoise as a means of managing uncertainty: personal, communal and proxy. J Med Ethics 1996; 22(3): 135–139.

64.

McFayden

. The role of gatekeepers in research: learning from reflexivity and reflection. J Nurs Health Care 2016; 14(1): 82–88.

65.

Hayes

Buckland

Tarpey

. Briefing notes for researchers: public involvement in NHS, public health and social care research. INVOLVE, 2012.

66.

Giovanazzi

Jones

Carr

, et al. Current practice in the measurement and interpretation of intervention adherence in randomised controlled trials: a systematic review. Contemp Clin Trials 2022; 118: 106788.

67.

Herbert

Julious

Goodacre

. Progression criteria in trials with an internal pilot: an audit of publicly funded randomised controlled trials. Trials 2019; 20(1): 493.

68.

NHS England. Operational pressures escalation levels (OPEL) Framework 2023/24 Version 2.0, Contract No.: Publication reference: PRN00551, https://www.england.nhs.uk/publication/operational-pressures-escalation-levels-opel-framework-2023-24/; 2023

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.03 MB

0.02 MB