The OPTIMIZE study: protocol of a pragmatic sequential multiple assessment randomized trial of nonpharmacologic treatment for chronic, nonspecific low back pain

Perspectives of People with Stroke, Caregivers and Healthcare Professionals on an Adaptive mHealth Intervention for Physical Activity in the Prevention of Secondary Stroke: A Qualitative Study

Introduction

Engaging in regular physical activity (PA) is associated with lower mortality following stroke, and PA reduces the chance of recurrent stroke. Despite recent guidelines to optimise PA following stroke, people with stroke are known to be less active than their age-matched counterparts. Given the heterogenous nature of stroke, adaptive PA interventions are recommended for people with stroke. Empirical data is lacking on adaptive PA or behavioural change interventions following stroke. Suggested strategies in the prevention of stroke recommend the use of mobile health (mHealth) interventions in the primary prevention of stroke. A structured stakeholder consultation process is key to successful implementation of complex interventions. This paper reports the findings of our consultation process to inform the development of an adaptive mHealth PA.

Methods

We used a qualitative study design to explore the perspectives of key stakeholders on the development of an adaptive PA intervention delivered via mHealth post-stroke. Healthcare workers, carers and people with stroke participated in semi-structured one-to-one or focus group interviews. A reflexive thematic analysis was undertaken on transcribed interviews; key themes and sub-themes were developed using coding and summarised by two researchers, then reviewed by the full research team.

Results

Twenty-eight stakeholders were interviewed and three main themes were identified; Key feature of a mHealth intervention, delivering a mHealth intervention, Challenges to development and use. There was widespread agreement across stakeholder groups that an adaptive mHealth PA intervention following stroke would be beneficial to people with stroke, following discharge from acute care.

Conclusion

Our consultation supports the development of an adaptive PA programme that addresses specific impairments that can hinder exercise participation after stroke.

Examining the Relationship Between Individual Patient Factors and Substantial Clinical Benefit From Telerehabilitation Among Patients With Chronic Low Back Pain

OBJECTIVE

The coronavirus disease-2019 pandemic has facilitated the emergence of telerehabilitation, but it is unclear which patients are most likely to respond to physical therapy provided this way. The purpose of this study was to examine the relationship between individual patient factors and substantial clinical benefit from telerehabilitation among a cohort of patients with chronic low back pain (LBP).

METHODS

This is a secondary analysis of data collected during a prospective longitudinal cohort study. Patients with chronic LBP (N = 98) were provided with a standardized physical therapy protocol adapted for telerehabilitation. We examined the relationship between patient factors and substantial clinical benefit with telerehabilitation, defined as a ≥50% improvement in disability at 10 weeks, measured using the Oswestry Disability Index.

RESULTS

Sixteen (16.3%) patients reported a substantial clinical benefit from telerehabilitation. Patients reporting substantial clinical benefit from telerehabilitation had lower initial pain intensity, lower psychosocial risk per the STarT Back Screening Tool, higher levels of pain self-efficacy, and reported higher therapeutic alliance with their physical therapist compared to other patients.

CONCLUSION

Patients with lower psychosocial risk and higher pain-self efficacy experienced substantial clinical benefit from telerehabilitation for chronic LBP more often than other patients in our cohort. Therapeutic alliance was higher among patients who experienced a substantial clinical benefit compared to those who did not.

IMPACT

This study indicates that psychosocial factors play an important role in the outcomes of patients receiving telerehabilitation for chronic LBP. Baseline psychosocial screening may serve as a method for identifying patients likely to benefit from this approach.

Wearable motion-based platform for functional spine health assessment

INTRODUCTION

Low back pain is a significant burden to society and the lack of reliable outcome measures, combined with a prevailing inability to quantify the biopsychosocial elements implicated in the disease, impedes clinical decision-making and distorts treatment efficacy. This paper aims to validate the utility of a biopsychosocial spine platform to provide standardized wearable sensor-derived functional motion assessments to assess spine function and differentiate between healthy controls and patients. Secondarily, we explored the correlation between these motion features and subjective biopsychosocial measures.

METHODS

An observational study was conducted on healthy controls (n=50) and patients with low back pain (n=50) to validate platform utility. The platform was used to conduct functional assessments along with patient-reported outcome assessments to holistically document cohort differences. Our primary outcomes were motion features; and our secondary outcomes were biopsychosocial measures (pain, function, etc).

RESULTS

Our results demonstrated statistically significant differences in motion features between healthy and patient cohorts across anatomical planes. Importantly, we found velocity and acceleration in the axial plane showed the largest difference, with healthy controls having 49.7% and 55.7% higher values, respectively, than patients. In addition, we found significant correlations between motion features and biopsychosocial measures for pain, physical function and social role only.

CONCLUSIONS

Our study validated the use of wearable sensor-derived functional motion metrics in differentiating healthy controls and patients. Collectively, this technology has the potential to facilitate holistic biopsychosocial evaluations to enhance spine care and improve patient outcomes.

TRIAL REGISTRATION NUMBER

NCT05776771.

Research objectives and general considerations for pragmatic clinical trials of pain treatments: IMMPACT statement

ABSTRACT

Many questions regarding the clinical management of people experiencing pain and related health policy decision-making may best be answered by pragmatic controlled trials. To generate clinically relevant and widely applicable findings, such trials aim to reproduce elements of routine clinical care or are embedded within clinical workflows. In contrast with traditional efficacy trials, pragmatic trials are intended to address a broader set of external validity questions critical for stakeholders (clinicians, healthcare leaders, policymakers, insurers, and patients) in considering the adoption and use of evidence-based treatments in daily clinical care. This article summarizes methodological considerations for pragmatic trials, mainly concerning methods of fundamental importance to the internal validity of trials. The relationship between these methods and common pragmatic trials methods and goals is considered, recognizing that the resulting trial designs are highly dependent on the specific research question under investigation. The basis of this statement was an Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) systematic review of methods and a consensus meeting. The meeting was organized by the Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION) public-private partnership. The consensus process was informed by expert presentations, panel and consensus discussions, and a preparatory systematic review. In the context of pragmatic trials of pain treatments, we present fundamental considerations for the planning phase of pragmatic trials, including the specification of trial objectives, the selection of adequate designs, and methods to enhance internal validity while maintaining the ability to answer pragmatic research questions.

Characterizing modifications to a comparative effectiveness research study: the OPTIMIZE trial-using the Framework for Reporting Adaptations and Modifications to Evidence-based Interventions (FRAME)

BACKGROUND

The OPTIMIZE trial is a multi-site, comparative effectiveness research (CER) study that uses a Sequential Multiple Assessment Randomized Trial (SMART) designed to examine the effectiveness of complex health interventions (cognitive behavioral therapy, physical therapy, and mindfulness) for adults with chronic low back pain. Modifications are anticipated when implementing complex interventions in CER. Disruptions due to COVID have created unanticipated challenges also requiring modifications. Recent methodologic standards for CER studies emphasize that fully characterizing modifications made is necessary to interpret and implement trial results. The purpose of this paper is to outline the modifications made to the OPTIMIZE trial using the Framework for Reporting Adaptations and Modifications to Evidence-Based Interventions (FRAME) to characterize modifications to the OPTIMIZE trial in response to the COVID pandemic and other challenges encountered.

METHODS

The FRAME outlines a strategy to identify and report modifications to evidence-based interventions or implementation strategies, whether planned or unplanned. We use the FRAME to characterize the process used to modify the aspects of the OPTIMIZE trial. Modifications were made to improve lower-than-anticipated rates of treatment initiation and COVID-related restrictions. Contextual modifications were made to permit telehealth delivery of treatments originally designed for in-person delivery. Training modifications were made with study personnel to provide more detailed information to potential participants, use motivational interviewing communication techniques to clarify potential participants' motivation and possible barriers to initiating treatment, and provide greater assistance with scheduling of assigned treatments.

RESULTS

Modifications were developed with input from the trial's patient and stakeholder advisory panels. The goals of the modifications were to improve trial feasibility without compromising the interventions' core functions. Modifications were approved by the study funder and the trial steering committee.

CONCLUSIONS

Full and transparent reporting of modifications to clinical trials, whether planned or unplanned, is critical for interpreting the trial's eventual results and considering future implementation efforts.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03859713. Registered on March 1, 2019.

The impact of low back pain and vigorous activity on mental and physical health outcomes in older adults with arthritis

Background

Nearly 50% of Americans aged 65 and above have been diagnosed with arthritis and an estimated 80% of adults experience low back pain (LBP). Little is known about the experience of LBP in older adults with arthritis and its relationships with mental and physical health.

Objective

In this study, we examined the relationships between LBP and four physical and mental health conditions (psychological distress, insomnia, mobility limitations, and self-rated health) in older adults with arthritis in the National Health and Aging Trends Study (NHATS). We also examined whether vigorous exercise mediated the relationships between LBP and these four conditions.

Materials and Methods

The data from this study comes from waves five through nine of the NHATS. The sample size ranged from 3,490 to 2,026 across these waves. All variables in this study are based on self-report. We used descriptive analyses including means and standard deviations for continuous variables or frequencies and proportions for demographic data. We used structural equation modeling (SEM) to examine if vigorous activity mediated the relationship between LBP with the four conditions.

Results

The age range of the sample was 65 years of age and older. Among those with back pain 78.53% had no mobility limitations. There was a significant relationship between LBP with insomnia (B = 0.48, p < 0.001), perceived health status (B = −0.38, p < 0.0010), and psychological distress (0.67, p < 0.001). Activity mediated the relationship between LBP and insomnia, psychological distress and physical health in adjusted models.

Discussion

The presence of low back pain in older adults with arthritis increases the risk of insomnia, psychological distress, mobility limitations, and poorer self-rated health. Consequently, targeting comorbid LBP may be an important component of the treatment plans of older adults with arthritis. In addition, providers of patients with arthritis and LBP should conduct routine assessments of mental and physical health to ensure the LBP is being adequately addressed.

Identifying Perceptions, Experiences, and Recommendations of Telehealth Physical Therapy for Patients with Chronic Low Back Pain: A Mixed Methods Survey

OBJECTIVE

Describe concerns, advantages, and disadvantages encountered in an evidence-based PT program for persons with chronic low back pain (cLBP) delivered by telehealth.

DESIGN

Mixed methods survey and semi-structured interview of persons with cLBP.

SETTING

Prospective observational cohort study of persons with cLBP from three healthcare systems receiving 8-sessions of evidence-based telehealth physical therapy (PT).

PARTICIPANTS

Participants were selected after completing Week 10 (from baseline) assessment from an ongoing cohort study. We enrolled 31 of 126 participants (mean age = 42.4 years, 71.0% female) from the cohort study.

INTERVENTIONS

Participants had completed 8 sessions of evidence-based telehealth PT and participated in semi-structured interviews.

MAIN OUTCOME MEASURES

Baseline and Week 10 and 26 assessments assessed psychosocial risk (StarTBack Screening Tool), working alliance (Working Alliance Inventory-Short Form), pain (Oswestry Disability Index) and health-related quality of life (PROMIS-29 profile, version 2). Semi-structured interviews were conducted by telephone and consisted of open-ended questions assessing perception, satisfaction, and likelihood of recommending telehealth PT. Participants identified advantages and disadvantages to telehealth PT. Interviews were recorded, transcribed, and coded using an iterative qualitative process. Statistical comparisons by experience were made using analysis of variance (continuous) and Fisher's exact test (categorical).

RESULTS

Compared to negative experience group (n=5), participants in positive (n=16) and neutral (n=10) experience groups endorsed higher bond working alliance with their therapist. Participants with a positive experience were more likely to view telehealth PT as cost-savings (n=10, 62.5%) compared to those with a neutral (n=1, 10.0%) or negative (n=1, 20.0%) experience; and less likely to view telehealth PT as lower quality (n=0, 0.0%; n=1, 10.0%; n=2, 40.0%, respectively).Prior to starting telehealth, based on semi-structured interviews, 18 (58.1%) of participants had concerns and these persisted after starting in half of this group. Concerns regarded telehealth being different from or inferior to in-person PT, lack of physical correction, and worries of not using technology appropriately. Convenience, time savings, and personalization were seen as advantages. Difficulty making a personal connection with the therapist, lack of physical correction, and problems with technology were seen as disadvantages. Many participants endorsed a hybrid approach that included in-person and telehealth PT. Providing necessary equipment and technology assistance was seen as ways to improve telehealth PT experience.

CONCLUSION

Telehealth is an acceptable modality to deliver PT for patients with cLBP with most having a positive experience and reporting advantages. Improvements could include offering a hybrid approach (in-person and telehealth combined) and providing necessary equipment and technical support. More research is needed to optimize the most effective strategies for providing telehealth PT for patients with cLBP.

Perceptions of Telehealth Physical Therapy Among Patients with Chronic Low Back Pain

Background: Coronavirus disease 2019 prompted the rapid adoption of telehealth to provide physical therapy. Patients' perceptions about telehealth physical therapy are mostly unknown. This study describes perceptions of telehealth physical therapy among patients with chronic low back pain (LBP). Methods: This study surveyed participants in an ongoing multisite clinical trial of nonpharmacological LBP treatments. Participants were asked about their willingness to use telehealth for physical therapy and with other providers and completed the PROMIS-29. Results: Surveys were received from 102 participants (mean age = 48.5 [standard deviation; SD = 11.6]). Thirty-six (35.3%) expressed willingness to receive telehealth physical therapy, 22 were neutral (21.6%), and 44 were unwilling (43.1%). The percentage expressing willingness for telehealth physical therapy was lower than it was for family medicine (p < 0.001) or mental health (p < 0.001). Older (p = 0.049) and Black participants (p = 0.01) more likely expressed willingness to use telehealth for physical therapy. Conclusion: Education and familiarity may help patients view telehealth physical therapy more favorably. Clinical Trial Registration (clinicaltrials.gov NCT03859713).

Back and neck pain: in support of routine delivery of non-pharmacologic treatments as a way to improve individual and population health

Chronic back and neck pain are highly prevalent conditions that are among the largest drivers of physical disability and cost in the world. Recent clinical practice guidelines recommend use of non-pharmacologic treatments to decrease pain and improve physical function for individuals with back and neck pain. However, delivery of these treatments remains a challenge because common care delivery models for back and neck pain incentivize treatments that are not in the best interests of patients, the overall health system, or society. This narrative review focuses on the need to increase use of non-pharmacologic treatment as part of routine care for back and neck pain. First, we present the evidence base and summarize recommendations from clinical practice guidelines regarding non-pharmacologic treatments. Second, we characterize current use patterns for non-pharmacologic treatments and identify potential barriers to their delivery. Addressing these barriers will require coordinated efforts from multiple stakeholders to prioritize evidence-based non-pharmacologic treatment approaches over low value care for back and neck pain. These stakeholders include patients, health care providers, health care organizations, administrators, payers, policymakers and researchers.

The Relationship between Neighborhood Deprivation and Perceived Changes for Pain-Related Experiences among U.S. Patients with Chronic Low Back Pain during the COVID-19 Pandemic

OBJECTIVE

Disruptions caused by the COVID-19 pandemic could disproportionately affect the health of vulnerable populations, including patients experiencing persistent health conditions (i.e., chronic pain), along with populations living within deprived, lower socioeconomic areas. The current cross-sectional study characterized relationships between neighborhood deprivation and perceived changes in pain-related experiences during the COVID-19 pandemic (early-September to mid-October 2020) for adult patients (N = 97) with nonspecific chronic low back pain.

METHODS

We collected self-report perceived experiences from participants enrolled in an ongoing pragmatic randomized trial across medical centers within the Salt Lake City, Utah and Baltimore, Maryland metropolitans. The Area Deprivation Index (composite of 17 U.S. Census deprivation metrics) reflected neighborhood deprivation based on participants' zip codes.

RESULTS

Although those living in the neighborhoods with greater deprivation endorsed significantly poorer physical (pain severity, pain interference, physical functioning), mental (depression, anxiety), and social health during the pandemic, there were no significant differences for perceived changes in pain-related experiences (pain severity, pain interference, sleep quality) between levels of neighborhood deprivation since the onset of the pandemic. However, those in neighborhoods with greater deprivation endorsed disproportionately worse perceived changes in pain coping, social support, and mood since the pandemic.

CONCLUSIONS

The current findings offer evidence that changes in pain coping during the pandemic may be disproportionately worse for those living in deprived areas. Considering poorer pain coping may contribute to long-term consequences, the current findings suggest the need for further attention and intervention to reduce the negative affect of the pandemic for such vulnerable populations.

Crosswalking the Patient-Reported Outcomes Measurement Information System Physical Function, Pain Interference, and Pain Intensity Scores to the Roland-Morris Disability Questionnaire and the Oswestry Disability Index

OBJECTIVE

To link scores from 2 condition-specific measures for chronic low back pain (CLBP), the Oswestry Disability Index (ODI) and the Roland-Morris Disability Questionnaire (RMDQ), to Patient Reported Outcomes Measurement Information System (PROMIS) physical function, pain interference, and pain intensity scores.

DESIGN

Ordinary least squares regression analyses of existing data to link the PROMIS scores with the ODI and RMDQ.

SETTING

Not applicable.

PARTICIPANTS

Samples of adults with CLBP (N=2279) obtained from the Center for Excellence in Research for Complementary and Integrative Health (CERC) Study (n=1677), the Assessment of Chiropractic Treatment for Low Back Pain and Smoking Cessation in Military Active Duty Personnel (ACT) (n=384), and the pain subsample of the PROMIS 1 Wave 2 Pain and Depression study (PROMIS 1 W2) (n=218).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

PROMIS physical function, pain interference, and pain intensity (CERC, ACT, and PROMIS 1 W2), ODI (CERC and PROMIS 1 W2), and RMDQ (ACT and PROMIS 1 W2).

RESULTS

In predicting PROMIS scores, the ODI model R² values ranged from 0.26-0.56 and the RMDQ model R² values ranged from 0.13-0.50. ODI and RMDQ models were the least precise in predicting the PROMIS pain intensity score (R² value range, 0.13-0.41) relative to the other PROMIS scores. Models with the 3 PROMIS scores as predictors yielded R² values ranging from 0.64-0.68 and 0.46-0.58 for the ODI and RMDQ, respectively. Models using combined data from 2 studies (ie, PROMIS 1 W2 and ACT, or PROMIS 1 W2 and CERC) tended to be more precise than models using only a single study sample.

CONCLUSIONS

Model results reported here can be used to translate PROMIS physical function, pain interference, and pain intensity scores to and from the ODI and RMDQ. The empirical linkages can facilitate comparisons across CLBP interventions and broaden interpretation of study results.

Rehabilitation Treatment of Motor Dysfunction Patients Based on Deep Learning Brain-Computer Interface Technology

In recent years, brain-computer interface (BCI) is expected to solve the physiological and psychological needs of patients with motor dysfunction with great individual differences. However, the classification method based on feature extraction requires a lot of prior knowledge when extracting data features and lacks a good measurement standard, which makes the development of BCI. In particular, the development of a multi-classification brain-computer interface is facing a bottleneck. To avoid the blindness and complexity of electroencephalogram (EEG) feature extraction, the deep learning method is applied to the automatic feature extraction of EEG signals. It is necessary to design a classification model with strong robustness and high accuracy for EEG signals. Based on the research and implementation of a BCI system based on a convolutional neural network, this article aims to design a brain-computer interface system that can automatically extract features of EEG signals and classify EEG signals accurately. It can avoid the blindness and time-consuming problems caused by the machine learning method based on feature extraction of EEG data due to the lack of a large amount of prior knowledge.