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Article
April 1, 2020
Open AccessLetter to the Editor

Telephone-based cognitive behavioral therapy for depression in Parkinson disease
A randomized controlled trial

April 21, 2020 issue
94 (16) e1764-e1773

Abstract

Objective

To determine whether, for patients with depression and Parkinson disease (PD), telephone-based cognitive-behavioral treatment (T-CBT) alleviates depressive symptoms significantly more than treatment as usual (TAU), we conducted a randomized controlled trial to evaluate the efficacy of a 10-session T-CBT intervention for depression in PD, compared to TAU.

Methods

Seventy-two people with PD (PWP) were randomized to T-CBT + TAU or TAU only. T-CBT tailored to PWPs’ unique needs was provided weekly for 3 months, then monthly during 6-month follow-up. CBT targeted negative thoughts (e.g., “I have no control”; “I am helpless”) and behaviors (e.g., social withdrawal, excessive worry). It also trained care partners to help PWP practice healthy habits. Blind raters assessed outcomes at baseline, midtreatment, treatment end, and 1 and 6 months post-treatment. Analyses were intent to treat.

Results

T-CBT outperformed TAU on all depression, anxiety, and quality of life measures. The primary outcome (Hamilton Depression Rating Scale score) improved significantly in T-CBT compared to TAU by treatment end. Mean improvement from baseline was 6.53 points for T-CBT and −0.27 points for TAU (p < 0.0001); gains persisted over 6-month follow-up (p < 0.0001). Improvements were moderated by a reduction in negative thoughts in the T-CBT group only, reflecting treatment target engagement.

Conclusions

T-CBT may be an effective depression intervention that addresses a significant unmet PD treatment need and bypasses access barriers to multidisciplinary, evidence-based care.

Clinicaltrials.gov identifier

NCT02505737.

Classification of evidence

This study provides Class I evidence that for patients with depression and PD, T-CBT significantly alleviated depressive symptoms compared to usual care.
Depression affects up to 50% of patients with Parkinson disease (PD),1 with widespread implications for PD management. Depression in PD (dPD) is associated with faster physical and cognitive decline,2 earlier initiation of dopaminergic replacement,3 medication nonadherence,4 greater prospective fall risk,5 and increased heath service utilization6 and costs.7 It predicts disability and distress over PD's defining motor symptoms,8 and surpasses disease severity as the strongest PD quality of life predictor.9 Optimal dPD management can restore patients' nondepressed functional baseline,10 yet spontaneous remission is rare.11
Contributing to its consequences, dPD is overlooked in over 60% of patients with significant symptoms12 and often undertreated. Though antidepressants typically constitute first-line intervention, data regarding efficacy, tolerability, and patient acceptability are mixed.13 This unmet treatment need complicates PD outcomes,14 underscoring the need for innovative care models to enhance treatment engagement.
Cognitive-behavioral therapy (CBT), a personalized, coping skills–based treatment approach,15 has shown promising results for dPD in pilots16,17 and 1 randomized controlled trial (RCT).18 Although patients may prefer nonpharmacologic depression treatments,19 access to PD-informed psychotherapy is limited by physical, geographic, and workforce barriers.20 Teleneurology is bypassing such obstacles to specialty medical care,21 as the need for patient-centered, interdisciplinary PD management is recognized.22 Telemedicine shows similar potential to facilitate personalized, neuropsychiatric dPD care,16 but there is no controlled research to this effect.
This RCT evaluated the efficacy of specialized, telephone-based CBT for depression in PD, compared to community-based treatment as usual (TAU). Acute and longer-term treatment effects, as well as moderators of treatment response, were examined.

Methods

Design

This RCT, conducted at an academic medical center, enrolled 72 people with PD (PWP) and their care partners. This study utilized an additive design to compare outcomes for an intervention group, who received telephone-based CBT (T-CBT) plus usual care, with those of an existing-practice control group, who received usual care only. This design was selected to measure T-CBT-augmented PD care against the current standard of care for this population. PWP and their care partners were randomly assigned (as dyads) to either T-CBT + TAU or TAU after eligibility requirements were confirmed, following the baseline evaluation. Randomization was stratified by baseline antidepressant medication use, such that individuals taking antidepressants were equally represented in both groups.
Allocations were determined in the order in which supervision (by R.D.D.) and scoring of each baseline assessment was completed. M.A.G. assigned participants to groups using multiple-password-protected randomization software to which he retained sole access. Allocation was stratified by antidepressant medication status only and blind to all other baseline data, such that M.A.G. did not have access to any information that could identify or in any way characterize the participant he was randomizing. See figure 1.
Figure 1 Consolidated Standards of Reporting Trials (CONSORT) diagram
Flow diagram of study participation. CBT = cognitive-behavioral therapy; MoCA = Montreal Cognitive Assessment; TAU = treatment as usual.
T-CBT was provided weekly for 10 one-hour sessions, then monthly if desired, during 6-month follow-up (16 sessions maximum). T-CBT targeted negative thoughts (e.g., “I have no control”; “I am helpless”) and behaviors (e.g., avoidance, excessive worry, lack of exercise), and trained care partners by telephone to help PWP practice healthy habits between sessions. TAU measures were defined by participants' health care teams and included psychiatric consultations, medication management, supportive psychotherapy, and all aspects of routine PD care. Condition-blind raters assessed outcomes at baseline, acute treatment midpoint, acute treatment end, and 1 and 6 months post-treatment. The 6-month follow-up evaluation occurred approximately 9 months after enrollment. No travel was required of participants, as all study procedures were conducted remotely. Individuals received $50 for each completed evaluation.

Standard protocol approvals, registrations, and patient consents

The Rutgers–Robert Wood Johnson Medical School institutional review board approved the study. Written informed consent was obtained from all participants before initiating study procedures. The study is registered at ClinicalTrials.gov (NCT02505737).

Participants

Participants were recruited from August 2015 through September 2017 from the Departments of Neurology and Psychiatry at Rutgers–Robert Wood Johnson Medical School, local PD support groups, and Fox Trial Finder (a clinical trial match tool). Follow-up ended when the last evaluation was completed in June 2018.
Prospective participants with PD and depressive symptoms called the study team in response to advertisements, flyers, and referrals by their treating neurologist or psychiatrist. Inclusion criteria were (1) PD by National Institute of Neurological Disorders and Stroke research criteria23; (2) DSM-524 depressive disorder diagnosis per Structured Clinical Interview for DSM Disorders25; (3) age 35–85 years; (4) stable PD and mental health treatment ≥6 weeks (movement disorder drugs, antidepressants, other psychotropics, and community-based psychotherapy); and (5) family member or friend willing to participate. National Institute of Mental Health guidelines regarding dPD diagnosis were followed.26 Exclusion criteria were (1) possible dementia or marked cognitive impairment (Montreal Cognitive Assessment score <2127); (2) active suicidal plans or intent by first author's assessment (R.D.D.); (3) unstable serious medical conditions (e.g., cancer); or (4) primary psychotic, bipolar, or substance abuse disorder per DSM-5 criteria.24

Measures

Change in Hamilton Depression Rating Scale (HAM-D)28 score was the primary outcome. Secondary outcomes included responder status (defined a priori as depression very much improved or much improved on the Clinical Global Impression Improvement Scale [CGI-I], score ≤2),29 depression severity (Beck Depression Inventory [BDI]),15 anxiety (Hamilton Anxiety Rating Scale [HAM-A]),30 and quality of life (Medical Outcomes Study Short Form–36 [SF-36]31 mental health composite score [MCS]). In addition to mood and energy levels, the MCS reflects the extent to which health interferes with daily functioning (e.g., socializing, chores) and captures cognitions about general health and wellness associated with proactive self-care.32 Negative thinking, a key intervention target, was assessed with the Inference Questionnaire.33 The CGI-I assessment protocol required clear evidence of adaptive functional consequences of mood improvements to score ≤2 (treatment response). All measures and scoring criteria were prespecified.

Interventions

Study conditions

Control: enhanced treatment as usual
TAU was defined as routine medical and psychiatric treatment from participants' medical and mental health providers (e.g., neurologists, psychiatrists, therapists), without the study team's input. TAU was enhanced via clinical monitoring by study staff and provision of a resource list including major PD foundations and national and local mental health resources. As described in the Results, TAU for the majority of participants (in both study conditions) included taking antidepressant medication or receiving psychotherapy in the community from any provider of their choosing. All control participants had the opportunity to receive the PD-informed T-CBT intervention after completion of the 6-month follow-up evaluation. Study staff did not interact with care partners in TAU, apart from incidental telephone contact for administrative purposes, such as ensuring return of mailed self-report surveys and payment vouchers.
Intervention: T-CBT + enhanced TAU
The CBT group received the study intervention and TAU. Treatment was guided by the Chronic Care Model34 to enhance PD self-management. In this systematic, patient-centered approach to chronic illness management, patients proactively collaborate with their providers to problem-solve about illness-related challenges and enhance their quality of life through self-care. The manual-guided CBT intervention was tailored to the needs of the dPD population, with modules focusing on behavioral activation, cognitive restructuring, anxiety management, and sleep hygiene (manual available on request). The manual, which was also designed for future implementation in direct patient care settings as well as clinical trials, also served as a participant workbook to supplement treatment. Within the manualized domains, emphases were personalized to individuals' symptom presentations and preferences. Care partners received telephone-based coaching in how to support and encourage PWPs' use of new CBT coping skills between therapy sessions. Of note, care partner coaching was intended to supplement T-CBT for the PWP; it was not a targeted intervention for caregiver distress. Treatment was provided by Masters-level therapists supervised by R.D.D. Participants received a 10-chapter CBT for dPD workbook (available on request) to supplement treatment.
In addition to coping skills to ameliorate depression, T-CBT emphasized strategies for optimizing PD care (e.g., exercise, medication adherence, facilitating referrals and follow-through for ancillary therapies). Primary intervention targets included PD-specific concerns (e.g., fear of falling, reactions to “on”–“off” fluctuations, levodopa phobia), and thoughts blocking PD self-management (e.g., “I have no control”; “I am helpless”). Treatment was personalized to improve adaptive responding to individuals' most pressing concerns, with the goals of improving mood- and health-related outcomes.

Statistical analyses

Data were analyzed with SAS 9.0 using an intent-to-treat approach. Linear mixed models analyses were used to examine treatment effects on the dependent variables of interest. Each model included 1 between-group variable (T-CBT vs TAU), 1 repeated-measure variable (time), and a group-by-time interaction (effect of interest). We considered several covariance structures between repeated measures and determined the best structure (variance components) using the Akaike Information Criterion.
For each dependent variable, we analyzed the group-by-time effect of interest separately at each post-randomization assessment point, only when the omnibus test was significant at p < 0.01, to control for number of comparisons. Fisher exact test was used to compare T-CBT and TAU treatment response rates.
To test whether the treatment target reduction in negative thoughts moderated treatment effects (CBT vs TAU) on HAM-D scores, we used PROCESS,35 a computational tool for conducting path-analysis-based moderation and mediation analyses, either alone or in combination, with bootstrap estimates of confidence intervals (CIs). The PROCESS macro can be implemented in both SAS and SPSS. Changes in HAM-D and Inference Questionnaire scores, respectively, were operationalized as end-of-treatment scores, partialing out enrollment scores.

Power

Sample size was determined a priori using power analyses, which assumed 58 PWP and care partners completing the study (20% attrition rate). Observed SDs were taken from baseline control data in our prior RCT of CBT for dPD.18 The study was powered to test post-treatment group differences in HAM-D (primary outcome). Controlling for baseline scores and demographic covariates, we considered 20 scenarios: within-group SDs ranged 4–5 and within-group correlation, baseline to endpoint, ranged 0.55–0.70. At p = 0.05, median power was 0.80. We previously observed a group difference of 7.30,18 which yielded power >0.99 in all 20 scenarios.

Primary research questions and level of evidence

The primary research question was whether a 10-session course of specialized T-CBT for dPD would lead to greater reductions in depressive symptoms than community-based TAU. Secondary questions assessed the effect of T-CBT on associated psychiatric and functional outcomes such as anxiety and quality of life, the durability of treatment effects, and moderators of treatment response. The study was single-blind (assessors were blind to treatment condition) and randomized-controlled, with no baseline differences between treatment groups. Primary outcomes and inclusion/exclusion criteria were clearly defined a priori. The statistician (M.A.G.) had sole access to the randomization scheme and was blind to all study data, except baseline antidepressant status, for stratification purposes. A retention rate over 80% was observed throughout the 9-month trial. Results provide Class I evidence that T-CBT for dPD significantly surpassed usual care in providing marked, durable improvements in depression, anxiety, and quality of life.

Data availability

On publication, the following will be made available to researchers whose proposed use of the data for a specified purpose has been approved by R.D.D.: deidentified participant data, data dictionary, study protocol, informed consent form, and statistical analysis plan. These materials are available from R.D.D. ([email protected]) by request, with a signed data access agreement.

Results

Seventy-two PWP and their care partners were randomized: 37 to CBT (51%) and 35 (49%) to TAU. Sixty-three PWP (88%) completed the study. Most (n = 63 [88%]) met major depressive disorder (MDD) criteria; among those individuals, 39 (62%) reported recurrent episodes. As part of usual care, 64 PWP (89%) were taking levodopa, 50 PWP (70%) were taking antidepressants, and 10 PWP (14%) continued receiving psychotherapy from community providers of their choice throughout the trial. Forty-three PWP (60%) reported prior psychotherapy. The groups' baseline clinical and demographic factors did not differ (table 1).
Table 1 Baseline demographic and clinical information

Treatment effects

Primary outcome

T-CBT was associated with significant improvements in mood (HAM-D) compared to TAU over the course of the trial (F4,249 = 14.89, p < 0.0001) (tables 2 and 3 and figure 2). Effects at the end of treatment (p < 0.0001) were maintained at 6-month follow-up (p < 0.0001). Post-treatment, T-CBT participants' HAM-D mean score was 14.44 (95% CI, 12.97–15.93); TAU mean score was 21.33 (95% CI, 19.76–22.89). Mean improvement from baseline was 6.53 points for T-CBT (95% CI, 5.07–7.99) and −0.27 points for TAU (95% CI, −1.81 to 1.27, Cohen d = 1.69). At 6-month follow-up, T-CBT participants' HAM-D mean was 15.37 (95% CI, 13.87–16.86); TAU mean was 20.53 (95% CI, 18.96–22.09). Mean improvement from baseline for T-CBT was 5.60 (95% CI, 4.12–7.07) and for TAU was 0.53 (95% CI, −1.01 to 2.07).
Table 2 Acute outcomes: baseline to end of treatment
Table 3 Longer-term outcomes: baseline to 6-month follow-up (9 months postbaseline)
Figure 2 Magnitude of Hamilton Depression Rating Scale (HAM-D) score change over time by study condition
Participants in telephone-based cognitive-behavioral therapy (CBT) showed a marked, durable decrease in clinician-rated depression symptoms (HAM-D) over the course of the trial, compared to treatment as usual (TAU) participants' persistent depressive symptomatology.

Secondary outcomes

Treatment response rates
T-CBT had significantly more treatment responders (CGI-I ≤ 2) than TAU (p < 0.0001). At end of treatment, 15 T-CBT participants (41%) vs 0 in TAU met response criteria (number needed to treat [NNT], 2.4 [95% CI, 1.7–3.9]; absolute risk reduction [ARR], 0.42 [95% CI, 0.25–0.58]). At 6-month follow-up, 14 T-CBT participants (38%) vs 0 in TAU met response criteria (NNT, 2.6 [95% CI, 1.8–4.4]; ARR, 0.39 [95% CI, 0.23–0.55]) (figure 3). Of note, treatment responders showed mild to minimal symptomatology on the HAM-D (mean, 9.67; 95% CI, 7.86–11.48) and BDI (7.14; 95% CI, 4.63–9.65) at treatment endpoint and 6-month follow-up (HAM-D: mean, 11.21; 95% CI, 9.09–13.34; BDI: mean, 8.71; 95% CI, 5.14–12.28), reflecting clinically significant symptom change.
Figure 3 Clinical Global Impression Improvement Scale (CGI-I) distributions at end of treatment and 6-month follow-up
CGI-I score distributions at end of treatment (A; 3 months postbaseline) and 6-month follow-up (B; 9 months postbaseline) reflect the clinical significance and durability of telephone-based cognitive-behavioral therapy (CBT) treatment gains over treatment as usual (TAU).
Psychiatric and functional measures
All secondary outcomes favored T-CBT, including self-reported depressive symptoms (BDI) (F4,244 = 5.07, p < 0.001), anxiety (HAM-A) (F4,249 = 8.63, p < 0.0001), and quality of life (SF-36 MCS) (F4,241 = 3.62, p = 0.007). Effects were evident after acute treatment and maintained through 6-month follow-up (tables 2 and 3).
BDI mean scores at treatment's end were 13.09 (95% CI, 10.44–15.74) for T-CBT and 19.03 (95% CI, 16.23–21.84) for TAU. Mean improvement from BDI baseline was 7.91 (95% CI, 5.23–10.59) for T-CBT and 1.85 (95% CI, −0.98 to 4.68) for TAU (Cohen d = 0.88). At 6-month follow-up, mean BDI scores were 13.93 (95% CI, 11.25–16.59) for T-CBT and 18.49 (95% CI, 15.72–21.27) for TAU. Mean improvement from baseline was 7.07 (95% CI, 4.38–9.77) for T-CBT and 2.39 (95% CI, −0.41 to 5.20) for TAU. Anxiety and quality of life showed similar patterns (table 2).

Target engagement

Using PROCESS35 as described above to test whether reduction in negative thoughts moderated T-CBT effects (vs TAU) on depressive symptoms (HAM-D), we found R2 = 0.55, F3,68 = 27.5, p < 0.0001, for the moderation model. The interaction of change in negative thoughts with treatment group (T-CBT vs TAU) yielded a significant R2 increase of 9%, F1,68 = 14.0, p = 0.0004. T-CBT had its most potent ameliorative effects on depression when negative thoughts showed the most pronounced decline, whereas its effects were attenuated when negative thoughts persisted.

Discussion

dPD is common and often undertreated, with broad, deleterious consequences for disease management. To address this unmet need, much remains to be learned about effective dPD interventions and strategies for leveraging access to specialty mental health care. In the first RCT of a telemedicine intervention for dPD, a 3-month course of dPD-informed T-CBT was associated with significant symptom reduction compared to TAU at the end of treatment on clinician-administered (HAM-D) and self-report (BDI) depression measures. In T-CBT, 15 participants (41%) met a stringent, a priori treatment-response threshold of depression “much improved” (CGI-I ≤ 2) at treatment's end, reflecting a marked impact of symptom reduction on daily functioning. The NNT was 2.4 with an ARR of 42%. All acute gains were maintained over 6-month follow-up. In TAU, by contrast, no participants met response criteria, and group mean depression scores were unchanged from baseline.
The use of an existing practice control group highlights the substantial, incremental mood improvements gained by adding the T-CBT intervention to current dPD care (TAU) over the outcomes of TAU alone.36 Secondary outcomes likewise favored T-CBT, reflecting significant improvements in anxiety and quality of life. Moderation analyses demonstrated target engagement of negative thoughts, as T-CBT exerted its strongest effects on depression when negative thoughts showed the most marked decline. The intervention was feasible and highly acceptable, yielding an 88% retention rate over the 9-month trial.
The large effect sizes of T-CBT on clinician-rated (d = 1.69) and self-reported (d = 0.88) measures of depression were comparable to those observed in the only prior RCT of CBT for dPD (HAM-D: d = 1.59; BDI: d = 1.10), which examined face-to-face treatment.18 The current results reflect comparable effectiveness of telephone-based treatment, a modality with the potential to surmount obstacles limiting specialized depression care in the PD population. These effect sizes approach the upper bound of those in RCTs of CBT for depression in chronic neurologic disorders (d = 0.39–2.07)37 and exceed the upper bound in many RCTs of CBT for depression in older adults (d = 0.70–1.34)38 and in a recent, large (n = 469), multisite RCT of CBT added to pharmacotherapy for treatment-resistant depression (d = 0.53–0.77).39 These findings are notable in this sample characterized by multiple treatment-refractory factors including high anxiety, medical comorbidities, chronic pain, insomnia, depression chronicity (current episode mean 2.87 years), relapses (n = 39, 62% of those with MDD), and limited prior treatment response.40
As PD progresses, illness management requires proactive self-care, to which depression poses major challenges41: following a precise medication regimen, initiating and engaging in therapies (e.g., speech, physical therapy), and exercising regularly, while responding to unpredictable symptom fluctuations. The current results suggest that telephone-delivered CBT can beneficially augment standard neurologic care by addressing the specific psychosocial consequences of depression that thwart these complex PD management demands. PD-informed T-CBT targets the negative, health-related cognitions that interfere with daily activities and impede adaptive coping with PD challenges, as well as the avoidant behaviors that typify dPD42 and maintain negative mood.43 The T-CBT-related functional improvements observed in this trial reflect the potential for effective dPD treatment to help PWP engage with their care team to optimize PD self-management. Improved routine self-care, in turn, empowers PWP to choose adaptive means of coping with daily symptom fluctuations and acute health challenges,44 reducing barriers to the meaningful activities that support positive mood.
Several limitations bear on the interpretation of these findings. For one, these results may not generalize to individuals with more advanced PD and dementia.
Second, an existing-practice control condition (TAU) was utilized in order to compare intervention outcomes to the current standard of care. While this design has been described as “indispensable in randomized effectiveness trials that evaluate whether new interventions can replace or augment existing practices,”36 and provides direct policy guidance on the additive value of T-CBT to current practice, TAU may also enhance effect sizes relative to other types of comparison conditions.
Third, it is not possible to fully disaggregate the effects of this T-CBT intervention from nonspecific factors (e.g., therapeutic relationship, time, attention) that likely contribute to all psychotherapy outcomes.45 This is important to highlight as T-CBT provided, on average, more contact with mental health providers than TAU did. Routine PD care does not incorporate a standardized psychotherapy intervention (telemedicine or in-person), and TAU was broadly comparable between study conditions. However, the marked, durable decline in depressive symptoms in the T-CBT group only—and the relationship of this pattern of change to reduction in negative thoughts, reflecting successful target engagement—significantly reduce the likelihood that results are solely attributable to nonspecific factors like clinician attention. Moreover, spontaneous remission of dPD is rare.11 PD is a chronic stressor, and disease progression tends to exacerbate psychosocial and neurobiological contributions to depressive symptomatology.46
Fourth, this protocol included an a priori test of T-CBT's effectiveness at reducing negative thoughts, a key treatment target, but it was not designed to assess the relative contributions of specific components of the intervention (e.g., cognitive, behavioral, and caregiver engagement strategies) or other clinical factors (e.g., antidepressant medication status) to the overall treatment effect, which will be the focus of future dismantling studies. Though the small number of participants not taking antidepressant medications (n = 22 [30%]) also precludes meaningful exploratory analyses of the effect of ADM on T-CBT response in the current study, evidence from prior work (with a more balanced sample with respect to ADM use) reflected greater benefits of antidepressants for somatic symptoms of dPD only, in the context of combined treatment.47 In addition, prior research has shown that caregiver involvement in dPD treatment enhances patient response,48 indicating a need for further investigation into the nature and magnitude of this effect.
Fifth, while 41% of T-CBT participants met or surpassed the stringent criteria of depression “much improved” (CGI-I ≤ 2), and mean HAM-D scores decreased more than 1.5 SDs in the T-CBT group, this arm in aggregate reported moderate residual symptoms post-treatment (HAM-D, mean 14.45). Though in clear contrast to the more severe symptoms persisting in TAU (HAM-D, mean 21.33), this finding is likely attributable to the resemblance between some symptoms of PD and depression (e.g., fatigue, psychomotor slowing) and the use of strict inclusive scoring protocols.26 On the BDI, which emphasizes cognitive over somatic symptoms, CBT participants self-reported mild, subthreshold symptomatology post-treatment (mean 13.09). Overall, these findings parallel our prior RCT of CBT for dPD, in which targeted cognitive and behavioral symptoms improved more than somatic symptoms.47
Finally, while remote delivery of interdisciplinary PD services is growing and increasingly recognized as critical for advancing care, limitations remain on insurance coverage for telemental health services like T-CBT. At this time, 36 states and Washington, DC, require private insurers to provide coverage parity for in-person and telemedicine-delivered care, while 21 states and Washington, DC, have such policies in Medicaid,49 with the availability of specific telemental health services subject to states' scope-of-practice laws. Reimbursement also remains subject to state-specific limitations on the telehealth eligibility of patients and originating sites. However, it is increasingly common for mental health providers to offer telemental health services on a sliding-scale, fee-for-service basis. In addition, all major PD foundations are engaged in grassroots and legislative efforts to improve access to telemedicine by increasing coverage, including federal reimbursement.50
This RCT provides Class I evidence that specialized T-CBT significantly improves depression, anxiety, and quality of life in PD compared to usual care; that these treatment effects are durable; and that improvements in depression are moderated by the reduction of negative thoughts, reflecting target engagement. T-CBT may be an effective depression intervention that can bypass access barriers to multidisciplinary, evidence-based PD care in order to address a significant unmet treatment need. While preliminary, these findings support the promise of telemedicine to expand the reach of evidence-based, PD-informed depression treatment, and its substantial benefits for PD self-management, into routine neurologic care. Findings also address 2 generalizability questions central to the goal of extending access to dPD care. That is, individuals need not live near specialized mental health services or be able to travel to weekly therapy appointments to benefit from these PD-informed interventions.
Innovations in telemedicine that are expanding access to interdisciplinary, evidence-based services now stand ready to improve quality of care—and quality of life—for many more PWP and their families. To that end, further research is necessary to understand the potential contributions of specialized telemental health to PD management, and to support policy changes that facilitate optimal, patient-centered PD care. As depression is associated with greater physical, cognitive, and functional decline, accessible, evidence-based dPD treatment may enhance global PD outcomes.

Glossary

ARR
absolute risk reduction
BDI
Beck Depression Inventory
CBT
cognitive-behavioral therapy
CGI-I
Clinical Global Impression Improvement Scale
CI
confidence interval
dPD
depression in Parkinson disease
DSM-5
Diagnostic and Statistical Manual of Mental Disorders, 5th edition
HAM-A
Hamilton Anxiety Rating Scale
HAM-D
Hamilton Depression Rating Scale
MCS
mental health composite score
MDD
major depressive disorder
NNT
number needed to treat
PWP
people with Parkinson disease
PD
Parkinson disease
RCT
randomized controlled trial
SF-36
Short Form–36
T-CBT
telephone-based cognitive-behavioral therapy
TAU
treatment as usual

Appendix Authors

Footnote

Editorial, page 691

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Letters to the Editor
13 April 2020
Author response: Telephone-based cognitive behavioral therapy for depression in Parkinson disease: A randomized controlled trial
Roseanne D. Dobkin, Professor of Psychiatry | Rutgers University

We thank Dr. Braillon for commenting on our article1 and for highlighting several advantages of increasing Parkinson disease (PD) patients’ access to nonpharmacologic depression treatments. We share his interest in multidisciplinary PD care and his concern about the scarcity of such resources. Evidence-based, PD-informed depression treatment is critical to this approach, yet it remains largely inaccessible for several reasons, beyond considerable underdiagnosis of PD depression.2 People with PD (PWP) face a dearth of PD-informed clinicians, often live far from specialized care centers, and contend with disability and transportation barriers to attending appointments.3,4 In studying PWPs’ mental health care preferences (N=769), we found that these factors contribute to strong interest in telehealth: 85% reported a preference for telehealth-to-home over clinic-based care, given the choice.4 We likewise view telehealth treatment not as a resource-poor alternative, but as a set of flexible, scalable, patient-centered modalities for extending the reach of specialized mental health care5 as it is in medicine.6 The large effects of telephone-based cognitive-behavioral therapy—comparable to in-clinic treatment—suggest an exciting, near-term means of helping more patients alleviate depressive symptoms and improve PD self-management. We believe mental telehealth shows potential to begin countering inequities in community-based, interdisciplinary PD resources, and thereby to advance personalized care by increasing patients’ choice.

Disclosure

The author reports no relevant disclosures. Contact [email protected] for full disclosures.

References

  1. Dobkin RD, Mann SL, Gara MA, Interian A, Rodriguez KM, Menza M. Telephone-based cognitive behavioral therapy for depression in Parkinson disease: A randomized controlled trial. Neurology 2020 Epub Apr 1.
  2. Lachner C, Armstrong MJ, Gruber-Baldini AL, et al. Discordance between physician assessment and patient-reported depressive symptoms in Parkinson disease. J Geriatr Psychiatry Neurol 2017;30:191–195.
  3. Dorsey ER, Vlaanderen FP, Engelen LJ, et al. Moving Parkinson care to the home. Mov Disord 2016;31:1258–1262.
  4. Dobkin RD, Rubino JT, Friedman J, et al. Barriers to Mental Health Care Utilization in Parkinson’s Disease. J Geriatr Psychiatry Neurol 2013;26:105–116.
  5. Swalwell C, Pachana NA, Dissanayaka NN, et al. Remote delivery of psychological interventions for Parkinson's disease. Int Psychogeriatr 2018;30:1783–1795.
  6. Dorsey ER, Glidden AM, Holloway MR, et al. Teleneurology and mobile technologies: the future of neurological care. Nat Rev Neurol 2018;14:285–297.
3 April 2020
Reader response: Telephone-based cognitive behavioral therapy for depression in Parkinson disease: A randomized controlled trial
Alain Braillon, Senior consultant | University Hospital, 80000 (Amiens, France)

Dobkin et al.1 deserve commendations for their well-designed trial in patients with depression and Parkinson disease showing telephone-based cognitive behavioral treatment improved by 7 points using the Hamilton Depression Rating Scale, over a 6-month follow-up.

At first glance, this is good news: a) industry-independent research is possible; and b) results are reliable, clinically relevant, and actionable in the real-life setting. Dobkin et al.’s trial contrasts with other trials in various conditions that promote antidepressants use. There are too many prescribers being misled by: a) statistically significant—but, clinically irrelevant—improvements (2 points on the scale or 3 at best, meaning a Cohen's d effect sizes of 0.4) in subjective symptoms on a scale with only 1/17 item measuring well-being;2 and b) a semblance of safety from a few-week follow-up in highly selected patients without poly-pharmacy. Among adverse effects too frequently overlooked is the withdrawal syndrome whose seriousness was denied by the UK Royal College of Psychiatrists until October 2019, despite a long crusade.3,4

However, are resources so scare and our countries so poor that developing alternative by-passing face-to-face care is now an achievement?5 Those vulnerable patients need community-based programs with integrated multidisciplinary care for medical, psychological, physical, occupational, and social issues.

Disclosure

The authors report no relevant disclosures. Contact [email protected] for full disclosures.

References

  1. Dobkin RD, Mann SL, Gara MA, Interian A, Rodriguez KM, Menza M. Telephone-based cognitive behavioral therapy for depression in Parkinson disease: A randomized controlled trial. Neurology 2020 Epub Apr 1.
  2. Hengartner MP, Plöderl M. Statistically Significant Antidepressant-Placebo Differences on Subjective Symptom-Rating Scales Do Not Prove That the Drugs Work: Effect Size and Method Bias Matter! Front Psychiatry 2018;9:517.
  3. Kinderman P, Davies J, Moore J, et al. Purpose, humility, civility, and science. Lancet Psychiatry 2018;5:964–965.
  4. Davies J, Read J, Hengartner MP, et al. Clinical guidelines on antidepressant withdrawal urgently need updating. BMJ 2019;365:l2238.
  5. Pontone GM, Mills KA. A call for better depression treatment in people with Parkinson disease. Neurology 2020 Epub Apr 1.

Information & Authors

Information

Published In

Neurology®
Volume 94Number 16April 21, 2020
Pages: e1764-e1773
PubMed: 32238507

Publication History

Received: August 13, 2019
Accepted: November 18, 2019
Published online: April 1, 2020
Published in print: April 21, 2020

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Disclosure

R.D. Dobkin received a research grant from the Michael J. Fox Foundation for Parkinson's Research and the Parkinson's Alliance (Parkinson's Unity Walk) to support this project. S.L. Mann, M.A. Gara, A. Interian, K.M. Rodriguez, and M. Menza report no relevant disclosures. Go to Neurology.org/N for full disclosures.

Study Funding

This study was funded by the Michael J. Fox Foundation for Parkinson's Research and the Parkinson's Alliance (Parkinson's Unity Walk).

Authors

Affiliations & Disclosures

Roseanne D. Dobkin, PhD
From the Departments of Psychiatry (R.D.D., M.A.G., K.M.R., M.M.) and Neurology (M.M.), Rutgers–Robert Wood Johnson Medical School, Piscataway; and VA New Jersey Health Care System (R.D.D., S.L.M., A.I.), Lyons.
Disclosure
Scientific Advisory Boards:
1.
NONE
Gifts:
1.
NONE
Funding for Travel or Speaker Honoraria:
1.
NONE
Editorial Boards:
1.
NONE
Patents:
1.
NONE
Publishing Royalties:
1.
NONE
Employment, Commercial Entity:
1.
NONE
Consultancies:
1.
NONE
Speakers' Bureaus:
1.
NONE
Other Activities:
1.
NONE
Clinical Procedures or Imaging Studies:
1.
NONE
Research Support, Commercial Entities:
1.
NONE
Research Support, Government Entities:
1.
1. Health Services and Research Division (HSR&D) of the Veteran Affairs Administration. Merit Award; Telehealth Cognitive Behavioral Therapy for Depression in Parkinson's Disease; (PI: Interian); Role: Co- Investigator, 2016-2020.
Research Support, Academic Entities:
1.
NONE
Research Support, Foundations and Societies:
1.
Michael J. Fox Foundation for Parkinson's Research The Parkinson's Alliance/Parkinson's Unity Walk The Parkinson Foundation Stock/Stock Options, Medical Equipment & Materials: My husband, Eric Dobkin, is employed by Merck and Co as a financial analyst and receives stock options as part of his regular compensation. He has been employed by Merck from 2002- present.
Stock/stock Options/board of Directors Compensation:
1.
NONE
License Fee Payments, Technology or Inventions:
1.
NONE
Royalty Payments, Technology or Inventions:
1.
NONE
Stock/stock Options, Research Sponsor:
1.
NONE
Stock/stock Options, Medical Equipment & Materials:
1.
NONE
Legal Proceedings:
1.
NONE
Sarah L. Mann, PhD
From the Departments of Psychiatry (R.D.D., M.A.G., K.M.R., M.M.) and Neurology (M.M.), Rutgers–Robert Wood Johnson Medical School, Piscataway; and VA New Jersey Health Care System (R.D.D., S.L.M., A.I.), Lyons.
Disclosure
Scientific Advisory Boards:
1.
NONE
Gifts:
1.
NONE
Funding for Travel or Speaker Honoraria:
1.
NONE
Editorial Boards:
1.
NONE
Patents:
1.
NONE
Publishing Royalties:
1.
NONE
Employment, Commercial Entity:
1.
NONE
Consultancies:
1.
NONE
Speakers' Bureaus:
1.
NONE
Other Activities:
1.
NONE
Clinical Procedures or Imaging Studies:
1.
NONE
Research Support, Commercial Entities:
1.
NONE
Research Support, Government Entities:
1.
NONE
Research Support, Academic Entities:
1.
NONE
Research Support, Foundations and Societies:
1.
NONE
Stock/stock Options/board of Directors Compensation:
1.
NONE
License Fee Payments, Technology or Inventions:
1.
NONE
Royalty Payments, Technology or Inventions:
1.
NONE
Stock/stock Options, Research Sponsor:
1.
NONE
Stock/stock Options, Medical Equipment & Materials:
1.
NONE
Legal Proceedings:
1.
NONE
Michael A. Gara, PhD
From the Departments of Psychiatry (R.D.D., M.A.G., K.M.R., M.M.) and Neurology (M.M.), Rutgers–Robert Wood Johnson Medical School, Piscataway; and VA New Jersey Health Care System (R.D.D., S.L.M., A.I.), Lyons.
Disclosure
Scientific Advisory Boards:
1.
NONE
Gifts:
1.
NONE
Funding for Travel or Speaker Honoraria:
1.
NONE
Editorial Boards:
1.
NONE
Patents:
1.
NONE
Publishing Royalties:
1.
NONE
Employment, Commercial Entity:
1.
NONE
Consultancies:
1.
NONE
Speakers' Bureaus:
1.
NONE
Other Activities:
1.
NONE
Clinical Procedures or Imaging Studies:
1.
NONE
Research Support, Commercial Entities:
1.
NONE
Research Support, Government Entities:
1.
NONE
Research Support, Academic Entities:
1.
NONE
Research Support, Foundations and Societies:
1.
NONE
Stock/stock Options/board of Directors Compensation:
1.
NONE
License Fee Payments, Technology or Inventions:
1.
NONE
Royalty Payments, Technology or Inventions:
1.
NONE
Stock/stock Options, Research Sponsor:
1.
NONE
Stock/stock Options, Medical Equipment & Materials:
1.
NONE
Legal Proceedings:
1.
NONE
Alejandro Interian, PhD
From the Departments of Psychiatry (R.D.D., M.A.G., K.M.R., M.M.) and Neurology (M.M.), Rutgers–Robert Wood Johnson Medical School, Piscataway; and VA New Jersey Health Care System (R.D.D., S.L.M., A.I.), Lyons.
Disclosure
Scientific Advisory Boards:
1.
NONE
Gifts:
1.
NONE
Funding for Travel or Speaker Honoraria:
1.
NONE
Editorial Boards:
1.
NONE
Patents:
1.
NONE
Publishing Royalties:
1.
NONE
Employment, Commercial Entity:
1.
NONE
Consultancies:
1.
NONE
Speakers' Bureaus:
1.
NONE
Other Activities:
1.
NONE
Clinical Procedures or Imaging Studies:
1.
NONE
Research Support, Commercial Entities:
1.
NONE
Research Support, Government Entities:
1.
(1) VA Health Services Research & Development, IIR 14- 353, Principal Investigator, 2016-2020 (2)VA Health Services Research & Development, IIR 12- 134, Principal Investigator, 2013-2018
Research Support, Academic Entities:
1.
NONE
Research Support, Foundations and Societies:
1.
NONE
Stock/stock Options/board of Directors Compensation:
1.
NONE
License Fee Payments, Technology or Inventions:
1.
NONE
Royalty Payments, Technology or Inventions:
1.
NONE
Stock/stock Options, Research Sponsor:
1.
NONE
Stock/stock Options, Medical Equipment & Materials:
1.
NONE
Legal Proceedings:
1.
NONE
Kailyn M. Rodriguez, BA
From the Departments of Psychiatry (R.D.D., M.A.G., K.M.R., M.M.) and Neurology (M.M.), Rutgers–Robert Wood Johnson Medical School, Piscataway; and VA New Jersey Health Care System (R.D.D., S.L.M., A.I.), Lyons.
Disclosure
Scientific Advisory Boards:
1.
NONE
Gifts:
1.
NONE
Funding for Travel or Speaker Honoraria:
1.
NONE
Editorial Boards:
1.
NONE
Patents:
1.
NONE
Publishing Royalties:
1.
NONE
Employment, Commercial Entity:
1.
NONE
Consultancies:
1.
NONE
Speakers' Bureaus:
1.
NONE
Other Activities:
1.
NONE
Clinical Procedures or Imaging Studies:
1.
NONE
Research Support, Commercial Entities:
1.
NONE
Research Support, Government Entities:
1.
NONE
Research Support, Academic Entities:
1.
NONE
Research Support, Foundations and Societies:
1.
NONE
Stock/stock Options/board of Directors Compensation:
1.
NONE
License Fee Payments, Technology or Inventions:
1.
NONE
Royalty Payments, Technology or Inventions:
1.
NONE
Stock/stock Options, Research Sponsor:
1.
NONE
Stock/stock Options, Medical Equipment & Materials:
1.
NONE
Legal Proceedings:
1.
NONE
Matthew Menza, MD
From the Departments of Psychiatry (R.D.D., M.A.G., K.M.R., M.M.) and Neurology (M.M.), Rutgers–Robert Wood Johnson Medical School, Piscataway; and VA New Jersey Health Care System (R.D.D., S.L.M., A.I.), Lyons.
Disclosure
Scientific Advisory Boards:
1.
NONE
Gifts:
1.
NONE
Funding for Travel or Speaker Honoraria:
1.
NONE
Editorial Boards:
1.
NONE
Patents:
1.
NONE
Publishing Royalties:
1.
NONE
Employment, Commercial Entity:
1.
NONE
Consultancies:
1.
NONE
Speakers' Bureaus:
1.
NONE
Other Activities:
1.
NONE
Clinical Procedures or Imaging Studies:
1.
NONE
Research Support, Commercial Entities:
1.
Acadia INSYTE: Management of Parkinson’s Disease Psychosis in Actual Practice. Role – Co-Investigator, PI: Dan Schneider. 2017-2020.
Research Support, Government Entities:
1.
Telehealth Cognitive-Behavioral Therapy for Depression in Parkinson’s disease 2015-2019. Department of Veteran Affairs (HSR&D; Merit Award); Role: Co-Investigator, PI: A. Interian
Research Support, Academic Entities:
1.
NONE
Research Support, Foundations and Societies:
1.
1. Improving Access to Depression Care in Parkinson’s disease: A Telehealth Approach 2015- 2018. Michael J. Fox Foundation for Parkinson’s Research Role: Co- Investigator; PI R. Dobkin 5% salary
Stock/stock Options/board of Directors Compensation:
1.
NONE
License Fee Payments, Technology or Inventions:
1.
NONE
Royalty Payments, Technology or Inventions:
1.
NONE
Stock/stock Options, Research Sponsor:
1.
NONE
Stock/stock Options, Medical Equipment & Materials:
1.
NONE
Legal Proceedings:
1.
NONE

Notes

Correspondence Dr. Dobkin [email protected]
Go to Neurology.org/N for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.
The Article Processing Charge was funded by the authors.

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Cited By
  1. The Role of Telemedicine in the Treatment of Cognitive and Psychological Disorders in Parkinson’s Disease: An Overview, Brain Sciences, 13, 3, (499), (2023).https://doi.org/10.3390/brainsci13030499
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  2. Toward objective monitoring of Parkinson's disease motor symptoms using a wearable device: wearability and performance evaluation of PDMonitor®, Frontiers in Neurology, 14, (2023).https://doi.org/10.3389/fneur.2023.1080752
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  3. Synchronous Web-Based Psychotherapy for Mental Disorders From a Health Quality Perspective: Scoping Review, Journal of Medical Internet Research, 25, (e40710), (2023).https://doi.org/10.2196/40710
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  4. Advances in the Pharmacological and Non-pharmacological Management of Non-motor Symptoms in Parkinson’s Disease: An Update Since 2017, Current Neuropharmacology, 21, 8, (1786-1805), (2023).https://doi.org/10.2174/1570159X20666220315163856
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  5. Research Advances in the Use of Telemedicine in Parkinson’s Patients, Advances in Clinical Medicine, 13, 05, (7960-7967), (2023).https://doi.org/10.12677/ACM.2023.1351115
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  6. Telemedicine treatment of patients with mental disorders during and after the first COVID-19 pandemic lockdown in Germany – an observational study on feasibility and patient satisfaction, BMC Psychiatry, 23, 1, (2023).https://doi.org/10.1186/s12888-023-05140-w
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  7. Remote cognitive behavioral therapy for older adults with anxiety symptoms: A systematic review and meta-analysis, Journal of Telemedicine and Telecare, (1357633X2311517), (2023).https://doi.org/10.1177/1357633X231151788
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  8. The effects of treatment via telemedicine interventions for patients with depression on depressive symptoms and quality of life: a systematic review and meta-analysis, Annals of Medicine, 55, 1, (1092-1101), (2023).https://doi.org/10.1080/07853890.2023.2187078
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  9. A Wellness Prescription for Parkinson's: Mid to Late-Stage Disease, The American Journal of Geriatric Psychiatry, 31, 9, (737-747), (2023).https://doi.org/10.1016/j.jagp.2023.02.049
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  10. Neurobiology of depression in Parkinson’s disease: Insights into epidemiology, molecular mechanisms and treatment strategies, Ageing Research Reviews, 85, (101840), (2023).https://doi.org/10.1016/j.arr.2022.101840
    Crossref
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