Physical Activity Coaching via Telehealth for People With Parkinson Disease: A Cohort Study : Journal of Neurologic Physical Therapy

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Physical Activity Coaching via Telehealth for People With Parkinson Disease: A Cohort Study

Shih, Hai-Jung Steffi PT, PhD; Macpherson, Chelsea E. PT, DPT, NCS; King, Miriam MA; Delaney, Elizabeth LCSW; Gu, Yu PT, PhD; Long, Katrina MS, OTR/L, EdD; Reid, Jennifer PT, DPT, NCS; Fineman, Julie PT, EdD; Yu, Geraldine PT, DPT, OCS; Rieger, Jamie BA; Satchidanand, Ashrita MA; Shah, Hiral MD; Alcalay, Roy N. MD; Quinn, Lori PT, EdD, FAPTA

Author Information
Journal of Neurologic Physical Therapy: October 2022 - Volume 46 - Issue 4 - p 240-250
doi: 10.1097/NPT.0000000000000410

Abstract

INTRODUCTION

The management of neurodegenerative diseases such as Parkinson disease (PD) requires consideration of changing needs and functional abilities at different disease stages. Traditional models of care place less emphasis on starting rehabilitative therapy soon after diagnosis, which is incongruent with current evidence that physical activity (PA) can delay neurodegeneration and potentially modify disease progression.1,2 A recent framework suggested incorporating consultative, proactive therapy for evaluation, education, and advice starting in early disease stage.3 In consultative roles at this stage, physical therapists promote PA, encourage disease self-management, and address secondary prevention in efforts to delay the onset of activity limitations.4 Early intervention for people with PD can empower them to harness long-term benefits of PA and self-management.5

The unique and powerful role of PA—especially exercise (structured PA for health benefits)—in improving function and health outcomes in people with PD is widely demonstrated. Studies have shown that exercise improves motor performance, physical and cognitive function, and quality of life in people with PD.6–9 Furthermore, there is promising evidence that aerobic exercise and PA have the potential to modify disease progression.8–11 Exercise may have neuroprotective effects via mechanisms within the central nervous system that facilitate synaptogenesis, neurogenesis, and neurotransmitter synthesis.12,13 Symptom improvements may result from increases in cortical excitability, substantia nigra, and prefrontal brain activity after exercise in PD.13,14

Despite the many benefits of PA, individuals with PD face general and disease-specific barriers to exercise. General barriers include low health literacy,15 lack of motivation,16 lack of time,16 and the associated costs and transportation challenges.17 Additionally, disease-specific barriers such as fatigue, balance impairments, and mood disorders may prevent people from participating in PA.18 These barriers may explain why people with PD exercise less than the general population,19 and only 27% meet recommended levels of 150 minutes of moderate PA or 75 minutes of vigorous PA per week.20–22 The COVID-19 pandemic and the stay-at-home restrictions further increased barriers to exercise.23–25

Coaching to promote PA is an integral part of the consultative therapy model of care, and it is also well-suited for telehealth delivery.26,27 Physical therapists are training in motivational interviewing-style techniques and have expertise in exercise and PD management. Therefore, they are well-positioned to deliver PA coaching and consultation starting in early disease stages. Growing research in this area has led to studies using mobile health technology, home-based exercises, and coaching or peer coaching to promote exercise uptake in neurodegenerative diseases.28–34 While these trials showed promising results, many studies introduce exercise in a prescriptive manner (prescribing exercise modality, duration, frequency, and intensity) and rely on extrinsic feedback (such as mobile apps). The lack of autonomy in goal-setting and exercise modality and the extrinsic nature of feedback may limit the facilitation of intrinsic motivation for long-term exercise adherence.

Engage-PD, a 3-month telehealth coaching intervention, was developed after a pilot study with similar design demonstrated the feasibility of PA coaching intervention in PD.35 The intervention was grounded in self-determination theory36 to facilitate intrinsic or highly autonomous motivation for long-term PA uptake in people with PD.26 The intervention is defined using a logic model26 and uses behavior change techniques to engage people with early-stage PD to participate in PA as a disease self-management strategy. Engage-PD is grounded in self-determination theory to satisfy 3 basic psychological needs—autonomy, relatedness, and competence—to increase exercise self-efficacy for long-term PA sustainability.37–40 Autonomy is supported through participant-centered goal-setting and choice of exercise modality; relatedness is supported through participant-interventionist interactions and encouragements; competence is supported through experiencing success in overcoming barriers and reaching goals. Through the coaching process, we aim to increase exercise self-efficacy—people's belief in their capacity to perform exercise and overcoming barriers to exercise—a significant factor related to initial exercise uptake and long-term exercise adherence.40 Harnessing the self-determination theory, the program addresses barriers to exercise and supports progress toward goals that are purposeful and meaningful to participants. In addition, a telehealth delivery may increase accessibility and reduce costs for neurological populations.41,42

The primary purpose of this single cohort study was to determine the feasibility and preliminary efficacy of Engage-PD, a PA coaching program for people with PD delivered via telehealth. The secondary purpose was to explore whether participant characteristics at baseline were associated with changes in exercise self-efficacy and PA uptake. We expected that younger age and lower baseline levels of PA would be associated with more improvements in outcome measures post-intervention for people with PD.

METHODS

Participants

A single cohort of participants were recruited between March 2020 and March 2021 from Columbia University Irving Medical Center Parkinson's Foundation Center of Excellence in New York, New York. Potential participants were referred by movement disorder specialists and a phone screening session was used to assess eligibility and interest. Participants were included if they were between the ages of 18 and 85 years, had a neurologist-confirmed diagnosis of idiopathic PD between Hoehn and Yahr (H&Y) stages I and III, were ambulatory for indoor and outdoor mobility without assistance or use of assistive devices, and either successfully completed the Physical Activity Readiness Questionnaire (PAR-Q)43 or received medical clearance to exercise from a medical doctor. Participants were excluded if they had coexisting neurological or musculoskeletal conditions that would restrict exercise. They were also excluded if they already had more than 150 minutes of moderate to vigorous PA per week. All participants provided electronic informed consent approved by the institutional review boards at Teachers College, Columbia University, and Columbia University Irving Medical Center. This trial has been registered on ClinicalTrials.gov (NCT049222190).

Intervention

The Engage-PD intervention consists of up to 5 personal coaching sessions delivered via telehealth, over a 3-month period.26 The number and frequency of the coaching sessions were determined based on individuals' needs and progress, with the typical interval between sessions starting from 2 weeks and gradually increased to 4 to 6 weeks. The coaching intervention was led by licensed physical therapists using Zoom Video Communications, Inc (San Jose, California). Sessions were scheduled at participants' convenience and each session consisted of individualized coaching activities (Table 1). Engage-PD is grounded in the self-determination theory44 and focused on promoting individual autonomy, competence, and relatedness to improve PA and exercise uptake.26,33,45 Therapists worked with participants to build multimodal programs incorporating aerobic, strengthening, balance, and flexibility exercises, with an emphasis on moderate- to high-intensity aerobic exercise at a minimum of 3 times per week and a total of 150 minutes.21,22

Table 1. - Overview of Engage-PD Intervention
Session Activities
Session 1 (within 2 wk of baseline assessment)
  1. Introduce the participant to the program, and the Engage-PD Physical Activity Workbook.

  2. Engage-PD Physical Activity Workbook Sections 1-4.

  3. Introduce to mCOPM and ask the participant to consider goals for next session.

  4. Discuss means of tracking PA (ie, written log or PA monitor).

  5. Summarize meeting and review upcoming plan.

Session 2
  1. Review PA log/data since the last session.

  2. Review Sections 5-8 of the Engage-PD workbook

  3. Discuss and finalize goals.

  4. Begin instruction in physical activity/exercise program as appropriate.

  5. Summarize meeting and review upcoming plan.

Sessions 3-4
  1. Review PA log/data and adjust goals as necessary.

  2. Discuss barriers and strategies for physical activity uptake.

  3. Review instruction in physical activity/exercise program as appropriate.

  4. Summarize meeting and review upcoming plan.

Last session
  1. Review PA log/data.

  2. Review and score goals.

  3. Review instruction in physical activity/exercise program as appropriate.

  4. Discuss barriers and strategies for sustained physical activity uptake.

  5. Summarize meeting and review upcoming plan.

Abbreviations: PA, physical activity; mCOPM, modified Canadian Occupational Performance Measure.
Engage-PD workbook chapters: 1. Exercise, who me? 2. Let's get moving! 3. Overcoming challenges. 4. Safety and monitoring. 5. Developing a physical activity plan. 6. Goals and targets. 7. Recording your activities and progress. 8. My physical activity plan.

Six physical therapists who were trained in PA coaching delivered the intervention. Therapists were provided a detailed coaching manual, and underwent training on motivational interviewing techniques, goal setting, and promotion of self-determination theory themes. Training consisted of a 2-hour video and at least 2 observational sessions with an experienced therapist. Therapists worked with participants to establish individualized goals, using the modified Canadian Occupational Performance Measure (mCOPM).46,47 Therapists provided guidance on overcoming motivational, social, physical, and environmental barriers to PA. Participants chose exercises and physical activities that were meaningful and enjoyable to them, and specific recommendations on exercise modifications and symptom management were provided by the therapists. Examples of exercise modality that participants chose included walking, running, stationary biking, yoga, and virtual fitness and dance programs available through community organizations online. Advice on exercise modifications was tailored based on participants' functional ability and fitness level. Moderate- to high-intensity exercise was determined as 55% to 85% maximum heart rate based on the 220 − age formula,48 although the usage of this formula may be adjusted based on individual conditions, such as taking β-blockers. Participants monitored their heart rate by taking their pulse or using available wearable devices. When heart rate monitoring was less feasible, they used the modified Borg rating of perceived exertion to achieve a general target in the moderate-/high-intensity range. We used a conservative range of 3 to 6 out of 10 (moderate intensity); however, the recommendation was individualized based on participant ability and if able participants were encouraged to achieve vigorous intensity of 7 to 8. Therapists guided individuals through exercise progressions based on existing guidelines,49 but the goals set for progressions were individualized and autonomous. Therapists used a standardized approach to help participants set goals—identify current state, identify end goal at 3 months, and determine the next achievable step in the short term. Additionally, therapists provided training on safety and monitoring during exercise, and engaged care partners when necessary.

Participants also received a disease-specific workbook that was reviewed and referenced by their therapist at the beginning of the sessions and throughout the intervention. The workbook was developed after piloting in a previous study,35 and included evidence-based recommendations for exercise pertaining to frequency, intensity, and duration for categories of aerobic, strengthening/resistance, flexibility, and neuromotor exercises.50,51 The workbook also provides education on PA monitoring by using high- or low-tech options such as wearable activity monitors, smartphones, or exercise diaries, which can help support autonomy.

Outcome Assessments

All baseline and postintervention outcome assessments were carried out over Zoom by the study coordinator and the therapists. Baseline assessments, including the Brunel Lifestyle Inventory,52 the Exercise Self-Efficacy Scale,53,54 and the mCOPM,46,47 were conducted within 2 weeks prior to the first coaching session. Postintervention assessments, including all measures from the baseline assessment and an additional exit questionnaire to assess feasibility and participant perspectives, were conducted by the study coordinator a week after the last coaching session had ended at 3 months. When administering the questionnaires, the therapist or study coordinator read each question and ensured that the participants fully understood them before recording their answers.

Feasibility

Recruitment. Recruitment rate was calculated as the percentage of referred participants from the neurologists who signed the consent form and enrolled in the study.

Retention. Retention rate was calculated as the percentage of enrolled participants who completed posttest assessments.

Adverse Events. Any new adverse events were documented by the therapists during the coaching sessions and reported to the research team.

Acceptability. A customized postintervention questionnaire was administered by the study coordinator to assess participants' acceptability of the intervention.55 The questionnaire consisted of 26 Likert scale questions (1 = strongly disagree to 5 = strongly agree, example question: “I felt satisfied with the visits from my therapist.”). Questions were categorized into 4 domains: overall intervention satisfaction, therapist interaction, workbook, and self-efficacy.

Participant Perspectives. Ten open-ended questions were asked to gain insight into participants' perspectives of the intervention (such as “what were some tools/benefits you gained from this experience that you did not expect?”).

Intervention Outcomes

Physical Activity. The Brunel Lifestyle Inventory (Brunel) is a 10-item questionnaire that measures both planned and unplanned PA.52 Planned PA is defined as any activity that is scheduled, which may enhance health, fitness, or well-being (eg, brisk walking, cycling and team games), thus is conceptually similar to exercise. Unplanned PA is any form of PA that is excluded from planned PA (eg, heavy housework, climbing stairs, walking or cycling to work, gardening, shopping, and playing with children). The questionnaire was determined to have reasonable concurrent validity (r = 0.11-0.64) in a sample of healthy young adults.52,56 The test-retest reliability in our cohort of 14 participants with PD was good: planned PA, intraclass correlation coefficient (ICC)(2,1) = 0.77 (95% confidence interval [CI] = 0.42, 0.92); unplanned PA, ICC(2,1) = 0.80 (95% CI = 0.49, 0.93) (L Quinn et al, unpublished data, 2021).

Exercise Self-Efficacy. The Exercise Self-Efficacy Scale (ESE) is an 18-item test that measures an individual's self-efficacy to participate in exercise when social and physical barriers are present.53,54 Participants were asked to rate a 5-point Likert scale for confidence to exercise regardless of barriers, with “1” meaning “not at all confident” and “5” meaning “completely confident.” The ESE has been used in previous PD research and was sensitive to change,57 and the test-retest reliability in a cohort of 14 participants with PD was good: ICC(2,1) = 0.80 (95% CI = 0.49, 0.93) (L Quinn et al, unpublished data, 2021).

Participant Goals. The mCOPM46,47 is a tool used to evaluate perceived performance, satisfaction, and importance of individualized goals. The mCOPM is also a tool for initiating conversation about challenges faced in everyday living, which provides the basis for setting PA intervention goals. As such, when participants mentioned symptoms (such as constipation) or general mobility issues that they would like to address, therapists guided participants to set PA goals that may help address these issues (such as improved gut motility). Each individualized goal on the mCOPM is ranked on a 10-point scale, where “1” indicates the lowest level of performance, satisfaction, or importance, and “10” indicates the highest. We only analyzed the performance and satisfaction subscores for the purpose of this study. The original COPM questionnaire has been validated in the general and neurological populations.58

Statistical Analysis

Descriptive statistics were performed on participants' characteristics. We calculated recruitment and retention as percentages and calculated average score in each domain from the postintervention questionnaire. Missing data were excluded from the preliminary efficacy analyses. We determined the effect estimates for the pre-post difference of Brunel planned and unplanned PA scores, ESE, and mCOPM performance and satisfaction scores. The distribution of these variables was plotted and inspected for normality. The 95% CI of mean difference, Cohen's d, and 95% CI of Cohen's d were calculated. We chose to use an estimation method for statistical inference instead of null hypothesis testing (using P values) to provide more information about the size of the effects and to avoid drawing misleading conclusions.59

We also explored relationships between participant baseline characteristics and pre-post changes in 2 important outcomes—Brunel planned PA and ESE. Pearson's r was used to determine the strength of the association between age, baseline Brunel planned PA, and baseline ESE in relation to the pre-post changes in Brunel planned PA and ESE after missing data were excluded (Figure 1). Cohen's d was used to determine the effect of sex on the pre-post changes in Brunel planned PA and ESE. Kendall's τ b was used to determine the association between H&Y levels and the pre-post changes in Brunel planned PA and ESE. We interpreted Cohen's |d| = 0.2, 0.5, and 0.8 as small, medium, and large effect sizes, respectively.60 Pearson's |r| = 0.3, 0.5, and 0.7 were interpreted as a small, moderate, and large effect, respectively.61 Cutoffs for interpreting Kendall's τ b have not been established; therefore, we will interpret the strength of the relationship without predetermined values.

F1
Figure 1.:
CONSORT diagram, modified to represent our single cohort. This figure is available in color online (www.jnpt.org).

RESULTS

Feasibility

Recruitment and Retention

Participants were recruited between March 24, 2020, and March 16, 2021, and all posttest assessments were concluded by June 22, 2021 (Figure 1). A total of 92 patients were referred and 62 were enrolled, resulting in a 67% recruitment rate. A total of 53 participants completed the posttest assessment, resulting in a retention rate of 85%. The majority of the participants enrolled were White and had at least a college education (Table 2). There were no standardized number of sessions due to the individualized design of the intervention; however, participants completed an average (SD) of 3.94 (0.93) sessions, with an average (range) session length of 60 (30-80) minutes.

Table 2. - Participant Characteristics at Enrollment (n = 62): Mean ± SD or Counts (Percentage) Reported
Age, y 65.4 ± 9.2
Sex
Male 39 (62.9%)
Female 23 (37.1%)
Weight, kg 73.6 ± 14.2
Height, cm 172.0 ± 8.9
Race/ethnicity
White 53 (85.5%)
Black/African American 3 (4.8%)
Hispanic 1 (1.6%)
Asian 0 (0%)
Other 2 (3.2%)
Declined 3 (4.8%)
Education
High school 2 (3.2%)
College 25 (40.3%)
Associates 2 (3.2%)
Masters 15 (24.2%)
Doctorate 5 (8.1%)
Other advanced degree 7 (11.3%)
Unknown 6 (9.7%)
Missing 6 (9.7%)
H&Y
Stage I 16 (25.8%)
Stage II 25 (40%)
Stage III 21 (34%)
Time since diagnosis, y 4.7 ± 4.3
MDS-UPDRSa 25.9 ± 4.1
MoCAb 23.4 ± 12.9
Abbreviations: H&Y, Hoehn and Yahr; MDS-UPDRS, Movement Disorders Society-Unified Parkinson's Disease Rating Scale (maximum score 199 indicating worst disability from Parkinson disease); MoCA, Montreal Cognitive Assessment (maximum score 30 indicating intact cognition).
aData from only 42 participants due to availability of MDS-UPDRS on medical history.
bData from only 18 participants due to availability of MoCA on medical history.

Adverse Events

There were no adverse events reported throughout the intervention period. Around half of the participants had a care partner involved in their coaching process for general encouragement and safety monitoring.

Acceptability

The intervention was well accepted and perceived by the participants. The average score for overall intervention satisfaction was 4.85 (95% CI = 4.77, 4.93) out of 5; for therapist interaction was 4.97 (95% CI = 4.95, 4.99) out of 5; for the workbook was 3.54 (95% CI = 3.31, 3.77) out of 5; for self-efficacy was 4.85 (95% CI = 4.79, 4.91) out of 5.

Participant Perspectives

Responses to the open-ended questions revealed that motivation, mood, weather, and other commitments were the top barriers that kept participants from engaging in regular exercise. Common motivations to join the study included interest in learning alternative strategies to manage PD, referral from a specialist, and searching for alternative therapies during the COVID-19 pandemic. Fifty-four percent of participants indicated they would have not joined the intervention if virtual sessions were not an option. Participants appreciated the informative communication and support from the therapists. Therapists' knowledge on PD, exercise resources, and goal setting strategies were highly valued by participants. Participants' intended to continue working toward the goals set in the program and develop future exercise plans. There was a mixed response to using technology in the program. While most participants found the virtual sessions and online resources to be accessible, some participants had difficulties using Zoom and other exercise-related applications. To reduce technological barriers and increase the sense of connectedness, participants commonly suggested it would have been beneficial to have 1 or 2 in-person sessions to enhance program delivery.

Intervention Outcomes

Physical Activity

There was an improvement in mean Brunel planned PA scores from pre- to postintervention with a small effect size (Table 3 and Figure 2). There was also an increased Brunel unplanned PA score with a medium effect size (Table 3 and Figure 2).

F2
Figure 2.:
Pre- and postintervention Brunel planned physical activity and exercise self-efficacy scores. PA, physical activity. This figure is available in color online (www.jnpt.org).
Table 3. - Mean Difference and Effect Sizes Pre- and Post-intervention
Variable n Pre (Mean ± SD) Post (Mean ± SD) Difference Post-Pre (Mean ± SD) 95% CI of Difference Effect Size Cohen's d 95% CI of Effect Size
Brunel planned PA 52 3.86 ± 0.93 4.11 ± 0.55 0.25 ± 0.81 0.03, 0.49 0.33 −0.058, 0.73
Brunel unplanned PA 52 2.32 ± 0.76 2.70 ± 0.69 0.38 ± 0.77 0.16, 0.60 0.52 0.12, 0.91
Exercise self-efficacy 52 56.00 ± 18.04 74.60 ± 12.29 18.81 ± 16.06 14.34, 23.28 1.20 0.78, 1.63
mCOPM—performance 50 4.12 ± 2.00 7.06 ± 2.25 3.26 ± 2.68 2.49, 4.02 1.63 1.17, 2.09
mCOPM—satisfaction 50 3.97 ± 2.02 6.93 ± 2.16 3.29 ± 2.68 2.53, 4.05 1.70 1.23, 2.16
Abbreviations: Brunel, Brunel Lifestyle Inventory; CI, confidence interval; mCOPM, modified Canadian Occupational Performance Measure; PA, physical activity; SD, standard deviation.

Exercise Self-Efficacy

There was an improvement in mean ESE from pre- to postintervention with a large effect size (Table 3 and Figure 2).

Participant Goals

There was an increase in mean performance and satisfaction scores for individualized goals from pre- to postintervention with large effect sizes (Table 3).

Relationship Between Baseline Characteristics and Outcomes

After excluding missing data, we explored the relationship between baseline characteristics and the change in Brunel planned PA and ESE (Table 4). Contrary to our expectations, there was no relationship between age and the change in Brunel planned PA (Figure 3A), or change in ESE (Figure 3B). On the other hand, there was a strong relationship indicating participants with lower baseline Brunel planned PA experienced greater improvements in Brunel planned (Figure 3C), and that participants with lower baseline ESE experienced greater improvements in ESE (Figure 3D). This was consistent with our expectations that lower baseline PA levels would be associated with greater improvements in PA. Additionally, there were no apparent influences of sex, H&Y levels, or time since diagnosis on the changes in outcomes (Table 4).

F3
Figure 3.:
Relationships between baseline characteristics and outcomes. Blue dots indicate data points; black lines indicate the least square line to represent trends. PA, physical activity; ESE, exercise self-efficacy. This figure isavailable in color online (www.jnpt.org).
Table 4. - Exploratory Relationships Between Baseline Characteristics and Outcomes (n = 55 Analyzed)
Variables Effect Size Statistics vs Change in Brunel Planned PA 95% CI vs Change in Exercise Self-Efficacy 95% CI
Age Pearson's r −0.076 −0.34, 0.20 0.22 −0.05, 0.46
Sex (male vs female) Cohen's d −0.07 −0.64, 0.50 −0.20 −0.77, 0.38
Hoehn and Yahr Kendall's τ b 0.0019 −0.23, 0.23 0.079 −0.14, 0.30
Time since diagnosis Pearson's r 0.14 −0.14, 0.40 0.071 −0.21, 0.34
Baseline Brunel planned PA Pearson's r −0.81 −0.80, −0.70 −0.26 −0.50, 0.010
Baseline exercise self-efficacy Pearson's r −0.12 −0.38, 0.16 −0.75 −0.85, −0.60
Abbreviations: Brunel, Brunel Lifestyle Inventory; CI, confidence interval; PA, physical activity.

DISCUSSIONS

We conducted a single cohort study to examine the feasibility and preliminary efficacy of Engage-PD, a telehealth PA coaching program for people with PD. Our findings showed that the Engage-PD program, conducted during the first year of the COVID-19 pandemic, had high recruitment and retention rates and was well accepted and perceived by a cohort of participants with early-to-mid stage PD. In addition, participants increased their planned and unplanned PA, ESE, and performance and satisfaction scores regarding personalized goals with small to large effect sizes. We also explored the relationship between participant characteristics at baseline with observed changes in ESE and PA uptake after the intervention. Lower baseline planned PA was strongly associated with greater improvements in planned PA, whereas lower baseline ESE was strongly associated with greater improvements in ESE.

The intervention was feasible and well-accepted by participants. Although intervention components differed, our high retention rate and no adverse events were similar to previous coaching studies with remote exercise programs.28,29,32 Among the feedback we received, participants were most satisfied with the positive interactions with the therapist. By providing individualized coaching sessions, the intervention addressed multiple barriers to engage in PA reported by people with PD in the literature.15,17,62,63 Participants acknowledged that the intervention provided useful insights on knowledge of appropriate exercise, addressing the social aspects of exercise and motivation to exercise regularly. The Engage-PD workbook provides education and guidance for therapists and participants to engage in discussions related to exercise especially during the first couple coaching sessions, and it may be most helpful for those who have lower health literacy. As participants become familiar with the workbook contents, emphasis is shifted to therapist-participant interactions and collaborative problem-solving—which may explain why the workbook was not as well-perceived by participants. This highlights the importance of motivational coaching: despite lack of knowledge being a common barrier for exercise engagement,63 addressing knowledge alone is not enough to promote PA.44 Our intervention used coaching grounded in self-determination theory to address multiple aspects of the behavior change process to promote long-term PA uptake beyond the completion of intervention. The emphasis on therapist-participant interaction and autonomous goal setting is in contrast with other studies that have used mobile health to prescribe and monitor remote exercise programs.28–32

Coaching is well-suited to be delivered via telehealth, and may decrease the barriers in transportation and time.26 Using telehealth to deliver the intervention was crucial for recruiting the majority of the participants, which highlights the potential of telehealth to increase the accessibility of care for people with chronic diseases. A recent study by Flynn and colleagues64 also demonstrated feasibility for telehealth-delivered exercise programs for people with PD. However, in our study, many participants noted they would prefer to have some in-person components integrated into the program, suggesting that a hybrid model may be beneficial to increase connectedness and incorporate hands-on instructions while maintaining the ease of access provided by a telehealth approach.

There were large effect sizes on the changes in mCOPM and ESE scores, and small to medium effects for PA uptake following the intervention. Results from the mCOPM, similar to other forms of goal setting, are subject to participant bias. However, participants in our study identified specific, measurable outcomes related to individualized PA uptake. Self-efficacy is thought to be an important mediator to lasting PA behavior change,39,40 and the large effect size seen in this study is encouraging. This finding may suggest that participants have a high chance of continuing PA after the study ends. It is also important to note that, even without a standardized exercise prescription in Engage-PD, participants demonstrated increase in self-reported PA that is consistent with previous reports of increased self-reported or objective PA in remote exercise management programs.28,29,31 While the effect size for planned PA was smaller than unplanned PA, we believe this may have been due to a ceiling effect for our participants (57% of our participants scored ≥4 out of 5 for baseline planned PA). Alternatively, the greater effect on unplanned PA may reflect that coaching increased participants' awareness to incorporate more unplanned PA in their daily activities.

Interventions are not “one-size-fits-all,” and the exploratory analyses in this study may help determine the subgroups of people who will most benefit from telehealth PA coaching. Individuals with lower baseline planned PA levels saw greater increases in planned PA levels after the intervention; likewise, ESE increased more in individuals with lower baseline ESE. These construct-specific relationships suggest planned PA levels and ESE are independently modulated, and that the Engage-PD intervention may help improve both constructs, especially in people who start off with lower scores. People who have a higher baseline PA levels or ESE also reported perceived benefits, which may not have been captured by the assessments that we used due to potential ceiling effects. Interestingly, we did not see a relationship between age, H&Y stages, and time since diagnosis with the outcomes. Thus, it is possible that Engage-PD may be similarly helpful in improving self-reported PA for people in later disease stages with more severe disabilities.65 In fact, there is a relationship trend indicating that people who are older may improve more in ESE. This further illustrates that the benefits of Engage-PD are not exclusive to the younger, more technologically literate cohort.

Limitations

Results of this study should be interpreted with some limitations in mind. This single cohort study has inherent limitations in study design—no control group and no blinding of the participants, therapists, or outcome assessors. This design was sufficient to determine feasibility and preliminary efficacy of the intervention, but a fully powered randomized controlled trial in the future is necessary to draw conclusions about effectiveness. Furthermore, we did not include any objective measures of PA such as accelerometry data, and therefore recognize that self-reported PA measure may not adequately represent true PA behavior.66 Therefore, future studies should incorporate objective PA measures when possible to provide a more direct insight into PA uptake. In addition, a ceiling effect with the Brunel Lifestyle Inventory may have limited the amount of improvements that could be detected. This study did not include individuals with H&Y levels IV or V, or those who use assistive devices due to safety concerns; however, given the potential benefits of increased PA in this population, future trials should expand to those with more severe physical impairments and those who use assistive devices where appropriate. Additionally, since Montreal Cognitive Assessment was only available for 18 out of 62 participants, we were not able to determine the effect of cognitive impairments on this remote coaching program although we anticipate some difficulties with implementation if cognitive impairment is severe.65

Our participant sample was predominantly White and the majority had higher than a college level of education, which may limit the generalizability of our findings. This is particularly important since individuals with PD who belong to a racial or ethnic minority community or have low socioeconomic status are more likely to be diagnosed later,67 have inadequate access to specialist care,68 and are less likely to exercise or participate in physical therapy.69 Additionally, those with a lower socioeconomic status may have greater barriers accessing PA infrastructure, such as gyms, equipment, and walkable environments. Telehealth PA coaching may be a promising tool to address disparities in access to care among those with PD, given that technological barriers are appropriately addressed.70,71 Our group has increased community-based efforts to ensure inclusion of a more diverse population in future studies.

Future Directions

Coaching for PA is not currently standard practice in neurologic physical therapy, and there are many barriers to implementation in real-world clinical settings. These barriers include the underdevelopment of telehealth infrastructure (insurance and internet coverage), insufficient training on coaching for physical therapists and other medical professionals, as well as safety concerns. There is growing research evaluating the implementation of similar coaching programs for PD,72 but more research is warranted to assess the effectiveness and cost-effectiveness of large-scale implementation of these programs.

CONCLUSIONS

We demonstrated that a telehealth PA coaching program delivered by physical therapists for people with PD is feasible and shows potential benefits in facilitating PA uptake and exercise self-efficacy. People who have a lower baseline PA level and ESE may benefit more from a PA coaching intervention. This demonstrates the promising role of telehealth PA coaching as part of a consultative model of care starting early in the disease process.

ACKNOWLEDGMENTS

The authors would like to thank the participants for their time and participation. We also thank Bria Bartsch and Jehan Alomar for their assistance in this project and neurologist from the Parkinson's Disease Center of Excellence at Columbia University Irving Medical Center for their support. Finally, we would like to acknowledge the Engage-PD Advisory Group members: Lynn Hagerbrant, Chuck Hendrick, Holly Fisher, and Saul Zuchman.

REFERENCES

1. Campos C, Rocha NBF, Lattari E, Paes F, Nardi AE, Machado S. Exercise-induced neuroprotective effects on neurodegenerative diseases: the key role of trophic factors. Expert Rev Neurother. 2016;16(6):723–734. doi:10.1080/14737175.2016.1179582.
2. Mahalakshmi B, Maurya N, Lee SD, Bharath Kumar V. Possible neuroprotective mechanisms of physical exercise in neurodegeneration. Int J Mol Sci. 2020;21(16):5895. doi:10.3390/ijms21165895.
3. Rafferty MR, Nettnin E, Goldman JG, MacDonald J. Frameworks for Parkinson's disease rehabilitation addressing when, what, and how. Curr Neurol Neurosci Rep. 2021;21(3):12. doi:10.1007/s11910-021-01096-0.
4. Quinn L, Morgan D. From disease to health: physical therapy health promotion practices for secondary prevention in adult and pediatric neurologic populations. J Neurol Phys Ther. 2017;41(suppl 3, IV STEP Spec Iss):S46–S54. doi:10.1097/NPT.0000000000000166.
5. Ellis T, Motl RW. Physical activity behavior change in persons with neurologic disorders: overview and examples from Parkinson disease and multiple sclerosis. J Neurol Phys Ther. 2013;37(2):85–90. doi:10.1097/NPT.0b013e31829157c0.
6. Lauzé M, Daneault JF, Duval C. The effects of physical activity in Parkinson's disease: a review. J Parkinsons Dis. 2016;6(4):685–698. doi:10.3233/JPD-160790.
7. da Silva FC, da Rosa Iop R, dos Santos PD, de Melo LMAB, Filho PJBG, da Silva R. Effects of physical-exercise-based rehabilitation programs on the quality of life of patients with Parkinson's disease: a systematic review of randomized controlled trials. J Aging Phys Act. 2016;24(3):484–496. doi:10.1123/japa.2015-0162.
8. Schenkman M, Moore CG, Kohrt WM, et al. Effect of high-intensity treadmill exercise on motor symptoms in patients with de novo Parkinson disease: a phase 2 randomized clinical trial. JAMA Neurol. 2018;75(2):219–226. doi:10.1001/jamaneurol.2017.3517.
9. Moore CG, Schenkman M, Kohrt WM, Delitto A, Hall DA, Corcos D. Study in Parkinson disease of exercise (SPARX): translating high-intensity exercise from animals to humans. Contemp Clin Trials. 2013;36(1):90–98. doi:10.1016/j.cct.2013.06.002.
10. Frazzitta G, Maestri R, Ghilardi MF, et al. Intensive rehabilitation increases BDNF serum levels in parkinsonian patients: a randomized study. Neurorehabil Neural Repair. 2014;28(2):163–168. doi:10.1177/1545968313508474.
11. Frazzitta G, Maestri R, Bertotti G, et al. Intensive rehabilitation treatment in early Parkinson's disease: a randomized pilot study with a 2-year follow-up. Neurorehabil Neural Repair. 2015;29(2):123–131. doi:10.1177/1545968314542981.
12. Paillard T, Rolland Y, de Souto, Barreto P. Protective effects of physical exercise in Alzheimer's disease and Parkinson's disease: a narrative review. J Clin Neurol. 2015;11(3):212–219. doi:10.3988/jcn.2015.11.3.212.
13. Kelly NA, Wood KH, Allendorfer JB, et al. High-intensity exercise acutely increases substantia nigra and prefrontal brain activity in Parkinson's disease. Med Sci Monit. 2017;23:6064–6071. doi:10.12659/MSM.906179.
14. Fisher BE, Wu AD, Salem GJ, et al. The effect of exercise training in improving motor performance and corticomotor excitability in people with early Parkinson's disease. Arch Phys Med Rehabil. 2008;89(7):1221–1229. doi:10.1016/j.apmr.2008.01.013.
15. Afshari M, Yang A, Bega D. Motivators and barriers to exercise in Parkinson's disease. J Parkinsons Dis. 2017;7(4):703–711. doi:10.3233/JPD-171173.
16. Ellis T, Cavanaugh JT, Earhart GM, et al. Factors associated with exercise behavior in people with Parkinson disease. Phys Ther. 2011;91(12):1838–1848. doi:10.2522/ptj.20100390.
17. Schootemeijer S, van der Kolk NM, Ellis T, et al. Barriers and motivators to engage in exercise for persons with Parkinson's disease. J Parkinsons Dis. 2020;10(4):1293–1299. doi:10.3233/JPD-202247.
18. Politis M, Wu K, Molloy SG, Bain P, Chaudhuri KR, Piccini P. Parkinson's disease symptoms: the patient's perspective. Mov Disord. 2010;25(11):1646–1651. doi:10.1002/mds.23135.
19. Mantri S, Fullard ME, Duda JE, Morley JF. Physical activity in early Parkinson disease. J Parkinsons Dis. 2018;8(1):107–111. doi:10.3233/JPD-171218.
20. Benka Wallén M, Franzén E, Nero H, Hagströmer M. Levels and patterns of physical activity and sedentary behavior in elderly people with mild to moderate Parkinson disease. Phys Ther. 2015;95(8):1135–1141. doi:10.2522/ptj.20140374.
21. Carty C, van der Ploeg HP, Biddle SJH, et al. The first global physical activity and sedentary behavior guidelines for people living With disability. J Phys Act Health. 2021;18(1):86–93. doi:10.1123/jpah.2020-0629.
22. US Department of Health and Human Services. Physical Activity Guidelines for Americans. 2nd ed. Washington, DC: US Department of Health and Human Services; 2018.
23. Helmich RC, Bloem BR. The impact of the COVID-19 pandemic on Parkinson's disease: hidden sorrows and emerging opportunities. J Parkinsons Dis. 2020;10(2):351–354. doi:10.3233/JPD-202038.
24. Feeney MP, Xu Y, Surface M, et al. The impact of COVID-19 and social distancing on people with Parkinson's disease: a survey study. NPJ Parkinsons Dis. 2021;7(1):10. doi:10.1038/s41531-020-00153-8.
25. Leavy B, Hagströmer M, Conradsson DM, Franzén E. Physical activity and perceived health in people with Parkinson disease during the first wave of COVID-19 pandemic: a cross-sectional study from Sweden. J Neurol Phys Ther. 2021;45(4):266–272. doi:10.1097/NPT.0000000000000372.
26. Quinn L, Macpherson C, Long K, Shah H. Promoting physical activity via telehealth in people with Parkinson disease: the path forward after the COVID-19 pandemic? Phys Ther. 2020;100(10):1730–1736. doi:10.1093/ptj/pzaa128.
27. Rafferty MR, Held Bradford EC, Fritz S, et al. Health promotion and wellness in neurologic physical therapy: strategies to advance practice [published online ahead of print September 9, 2021]. J Neurol Phys Ther. doi:10.1097/NPT.0000000000000376.
28. Kim A, Yun SJ, Sung KS, et al. Exercise management using a mobile app in patients with Parkinsonism: prospective, open-label, single-arm pilot study. JMIR Mhealth uHealth. 2021;9(8):e27662. doi:10.2196/27662.
29. Colón-Semenza C, Latham NK, Quintiliani LM, Ellis TD. Peer coaching through mhealth targeting physical activity in people with Parkinson disease: feasibility study. JMIR mHealth and uHealth. 2018;6(2):e42. doi:10.2196/mhealth.8074.
30. Rawson KS, Cavanaugh JT, Colon-Semenza C, et al. Design of the WHIP-PD study: a phase II, twelve-month, dual-site, randomized controlled trial evaluating the effects of a cognitive-behavioral approach for promoting enhanced walking activity using mobile health technology in people with Parkinson-disease. BMC Neurol. 2020;20(1):146. doi:10.1186/s12883-020-01718-z.
31. Ridgel AL, Walter BL, Tatsuoka C, et al. Enhanced exercise therapy in Parkinson's disease: a comparative effectiveness trial. J Sci Med Sport. 2016;19(1):12–17. doi:10.1016/j.jsams.2015.01.005.
32. van der Kolk NM, de Vries NM, Kessels RPC, et al. Effectiveness of home-based and remotely supervised aerobic exercise in Parkinson's disease: a double-blind, randomised controlled trial. Lancet Neurol. 2019;18(11):998–1008. doi:10.1016/S1474-4422(19)30285-6.
33. Busse M, Quinn L, Drew C, et al. Physical activity self-management and coaching compared to social interaction in Huntington disease: results from the ENGAGE-HD randomized, controlled pilot feasibility trial. Phys Ther. 2017;97(6):625–639. doi:10.1093/ptj/pzx031.
34. Busse M, Quinn L, Dawes H, et al. Supporting physical activity engagement in people with Huntington's disease (ENGAGE-HD): study protocol for a randomized controlled feasibility trial. Trials. 2014;15(1):487. doi:10.1186/1745-6215-15-487.
35. Long KM. Pre-active PD: A Therapist Delivered Physical Activity Behavior Change Program for People With Early Stage Parkinson's Disease [doctoral thesis]. New York, NY: Teachers College, Columbia University; 2020.
36. Teixeira PJ, Carraça EV, Markland D, Silva MN, Ryan RM. Exercise, physical activity, and self-determination theory: a systematic review. Int J Behav Nutr Phys Act. 2012;9:78. doi:10.1186/1479-5868-9-78.
37. Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am Psychol. 2000;55(1):68–78. doi:10.1037//0003-066x.55.1.68.
38. Fortier MS, Duda JL, Guerin E, Teixeira PJ. Promoting physical activity: development and testing of self-determination theory-based interventions. Int J Behav Nutr Phys Act. 2012;9:20. doi:10.1186/1479-5868-9-20.
39. Marcus BH, Selby VC, Niaura RS, et al. Self-efficacy and the stages of exercise behavior change. Res Q Exerc Sport. 1992;63(1):60. doi:10.1080/02701367.1992.10607557.
40. Stevens A, Stanton R, Rebar AL. Helping people with Parkinson disease build exercise self-efficacy. Phys Ther. 2020;100(2):205–208. doi:10.1093/ptj/pzz160.
41. Chen YY, Guan BS, Li ZK, et al. Application of telehealth intervention in Parkinson's disease: a systematic review and meta-analysis. J Telemed Telecare. 2020;26(1/2):3–13. doi:10.1177/1357633X18792805.
42. Chirra M, Marsili L, Wattley L, et al. Telemedicine in neurological disorders: opportunities and challenges. Telemed J E Health. 2019;25(7):541–550. doi:10.1089/tmj.2018.0101.
43. Thomas S, Reading J, Shephard RJ. Revision of the Physical Activity Readiness Questionnaire (PAR-Q). Can J Sport Sci. 1992;17(4):338–345.
44. Teixeira PJ, Palmeira AL, Vansteenkiste M. The role of self-determination theory and motivational interviewing in behavioral nutrition, physical activity, and health: an introduction to the IJBNPA special series. Int J Behav Nutr Phys Act. 2012;9(1):17. doi:10.1186/1479-5868-9-17.
45. Quinn L, Trubey R, Gobat N, et al. Development and delivery of a physical activity intervention for people with Huntington disease: facilitating translation to clinical practice. J Neurol Phys Ther. 2016;40(2):71–80. doi:10.1097/NPT.0000000000000119.
46. Law M, Baptiste S, McColl M, Opzoomer A, Polatajko H, Pollock N. The Canadian Occupational Performance Measure: an outcome measure for occupational therapy. Can J Occup Ther. 1990;57(2):82–87. doi:10.1177/000841749005700207.
47. Dedding C, Cardol M, Eyssen IC, Beelen A, Beelen A. Validity of the Canadian Occupational Performance Measure: a client-centred outcome measurement. Clin Rehabil. 2004;18(6):660–667. doi:10.1191/0269215504cr746oa.
48. Fox SM, Naughton JP, Haskell WL. Physical activity and the prevention of coronary heart disease. Ann Clin Res. 1971;3(6):404–432.
49. American College of Sports Medicine. ACSM's Guidelines For Exercise Testing and Prescription Guidelines for Graded Exercise Testing and Training. 9th ed. Philadelphia, PA: Lippincott Williams and Wilkins; 2013.
50. Gallo PM, Ewing Garber C. Parkinson's disease: a comprehensive approach to exercise prescription for the health fitness professional. ACSMs Health Fit J. 2011;15(4):8–17. doi:10.1249/FIT.0b013e31821eca84.
51. Kim Y, Lai B, Mehta T, et al. Exercise training guidelines for multiple sclerosis, stroke, and Parkinson disease: rapid review and synthesis. Am J Phys Med Rehabil. 2019;98(7):613–621. doi:10.1097/PHM.0000000000001174.
52. Karageorghis CI, Vencato MM, Chatzisarantis NLD, Carron AV. Development and initial validation of the Brunel lifestyle physical activity questionnaire. Br J Sports Med. 2005;39(5):e23. doi:10.1136/bjsm.2004.014258.
53. King LA, Peterson DS, Mancini M, et al. Do cognitive measures and brain circuitry predict outcomes of exercise in Parkinson disease: a randomized clinical trial. BMC Neurol. 2015;15:218. doi:10.1186/s12883-015-0474-2.
54. Norman GJ, Vaughn AA, Roesch SC, Sallis JF, Calfas KJ, Patrick K. Development of decisional balance and self-efficacy measures for adolescent sedentary behaviors. Psychol Health. 2004;19(5):561–575. doi:10.1080/08870440410001722930.
55. Sekhon M, Cartwright M, Francis JJ. Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework. BMC Health Serv Res. 2017;17(1):88. doi:10.1186/s12913-017-2031-8.
56. Vencato MM, Karageorghis CI, Nevill AM, Priest DL. Test–retest reliability of the Brunel Lifestyle Physical Activity Questionnaire. Psychol Sport Exerc. 2017;33:24–30. doi:10.1016/j.psychsport.2017.07.003.
57. King LA, Wilhelm J, Chen Y, et al. Effects of group, individual, and home exercise in persons with Parkinson disease: a randomized clinical trial. J Neurol Phys Ther. 2015;39(4):204–212. doi:10.1097/NPT.0000000000000101.
58. Gaudet P. Measuring the impact of Parkinson's disease: an occupational therapy perspective. Can J Occup Ther. 2002;69(2):104–113. doi:10.1177/000841740206900206.
59. Herbert R. Research note: significance testing and hypothesis testing: meaningless, misleading and mostly unnecessary. J Physiother. 2019;65(3):178–181. doi:10.1016/j.jphys.2019.05.001.
60. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum; 1988.
61. Mukaka MM. Statistics corner: a guide to appropriate use of correlation coefficient in medical research. Malawi Med J. 2012;24(3):69–71.
62. Prakash P, Scott TF, Baser SM, Leichliter T, Schramke CJ. Self-reported barriers to exercise and factors impacting participation in exercise in patients with Parkinson's disease. Mov Disord Clin Pract. 2021;8(4):631–633. doi:10.1002/mdc3.13197.
63. Quinn L, Busse M, Khalil H, Richardson S, Rosser A, Morris H. Client and therapist views on exercise programmes for early-mid stage Parkinson's disease and Huntington's disease. Disabil Rehabil. 2010;32(11):917–928. doi:10.3109/09638280903362712.
64. Flynn A, Preston E, Dennis S, Canning CG, Allen NE. Home-based exercise monitored with telehealth is feasible and acceptable compared to centre-based exercise in Parkinson's disease: a randomised pilot study. Clin Rehabil. 2021;35(5):728–739. doi:10.1177/0269215520976265.
65. Lowe R, Barlow C, Lloyd B, et al. Lifestyle, exercise and activity package for people living with progressive multiple sclerosis (LEAP-MS): adaptions during the COVID-19 pandemic and remote delivery for improved efficiency. Trials. 2021;22(1):286. doi:10.1186/s13063-021-05245-1.
66. Mantri S, Wood S, Duda JE, Morley JF. Comparing self-reported and objective monitoring of physical activity in Parkinson disease. Parkinsonism Relat Disord. 2019;67:56–59. doi:10.1016/j.parkreldis.2019.09.004.
67. Dahodwala N, Karlawish J, Siderowf A, Duda JE, Mandell DS. Delayed Parkinson's disease diagnosis among African-Americans: the role of reporting of disability. Neuroepidemiology. 2011;36(3):150–154. doi:10.1159/000324935.
68. Fullard ME, Thibault DP, Hill A, et al. Utilization of rehabilitation therapy services in Parkinson disease in the United States. Neurology. 2017;89(11):1162–1169. doi:10.1212/WNL.0000000000004355.
69. Nwabuobi L, Agee J, Gilbert R. Racial and social disparities in health and health care delivery among patients with Parkinson's disease and related disorders in a multiracial clinical setting. J Cross Cult Gerontol. 2021;36(3):253–263. doi:10.1007/s10823-021-09436-w.
70. Hirko KA, Kerver JM, Ford S, et al. Telehealth in response to the COVID-19 pandemic: implications for rural health disparities. J Am Med Inform Assoc. 2020;27(11):1816–1818. doi:10.1093/jamia/ocaa156.
71. Marcin JP, Shaikh U, Steinhorn RH. Addressing health disparities in rural communities using telehealth. Pediatr Res. 2016;79(1-2):169–176. doi:10.1038/pr.2015.192.
72. Rafferty MR, MacDonald J, Byskosh A, et al. Using implementation frameworks to provide proactive physical therapy for people with Parkinson disease: case report. Phys Ther. 2019;99(12):1644–1655. doi:10.1093/ptj/pzz129.
Keywords:

behavior change; coaching; exercise; Parkinson disease; physical activity

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