Intervention Protocol

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Virtual reality for rehabilitation in Parkinson's disease

  1. Kim Dockx1,*,
  2. Veerle Van den Bergh1,
  3. Esther MJ Bekkers1,
  4. Pieter Ginis1,
  5. Lynn Rochester2,
  6. Jeffrey M Hausdorff3,
  7. Anat Mirelman3,
  8. Alice Nieuwboer1

Editorial Group: Cochrane Movement Disorders Group

Published Online: 15 OCT 2013

DOI: 10.1002/14651858.CD010760


How to Cite

Dockx K, Van den Bergh V, Bekkers EMJ, Ginis P, Rochester L, Hausdorff JM, Mirelman A, Nieuwboer A. Virtual reality for rehabilitation in Parkinson's disease (Protocol). Cochrane Database of Systematic Reviews 2013, Issue 10. Art. No.: CD010760. DOI: 10.1002/14651858.CD010760.

Author Information

  1. 1

    KU Leuven, Department of Rehabilitation Sciences, Heverlee, Belgium

  2. 2

    Newcastle University, Institute for Ageing and Health, Newcastle upon Tyne, UK

  3. 3

    Tel-Aviv Sourasky Medical Center, Department of Neurology, Tel Aviv, Israel

*Kim Dockx, Department of Rehabilitation Sciences, KU Leuven, Tervuursevest 101, Postbus 1501, Heverlee, 3001, Belgium. Kim.dockx@faber.kuleuven.be.

Publication History

  1. Publication Status: New
  2. Published Online: 15 OCT 2013

SEARCH

 

Background

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Appendices
  6. Contributions of authors
  7. Declarations of interest
  8. Sources of support
 

Description of the condition

Parkinson’s disease (PD) is one of the most common neurodegenerative disorders worldwide (Muangpaisan 2011). It is mainly associated with a loss of dopaminergic neurons in the basal ganglia, causing a wide variety of motor symptoms such as bradykinesia, rest tremor, rigidity and postural instability, as well as non-motor symptoms (Hawkes 2010; Lees 2009). Important consequences of the disease are physical inactivity, loss of independence and an increased risk of falls, all of which have a negative impact on quality of life (Allen 2011; Van Nimwegen 2011).

Recently, exercise has become an established part of PD treatment and overall management. In order to adequately address the symptoms related to PD, physical rehabilitation is focused particularly on gait, balance and global motor function. The short-term effects of exercise were demonstrated in a Cochrane review by Tomlinson et al in which 39 trials involving 1827 patients were included (Tomlinson 2012). Significant benefits of exercise intervention were found for nine outcome measures, namely gait speed, the six-minute walk test, 'Timed Up and Go' test, functional reach test, Berg Balance Scale, freezing of gait score and Unified Parkinson's Disease Rating Scale (UPDRS) motor score. Even though the short-term positive effects of exercise are well-established, its long-term effects remain unclear and whether patients are able to sustain an exercise program and transfer exercise effects to tasks in daily life need further investigation (Nieuwboer 2009; Van Nimwegen 2011).

 

Description of the intervention

Virtual reality (VR) technology is rapidly becoming a popular intervention for physical rehabilitation. Bisson et al defined virtual reality as a computerized simulation which allows users to interact with images and virtual objects that appear in the virtual environment in real-time through multiple sensory modalities (Bisson 2007). This general definition that is used in the literature implies immersion in a virtual environment.

VR training has many advantages compared to standard physical rehabilitation interventions (Holden 2005). It offers augmented feedback about performance, enables individualized repetitive practice of motor function, and stimulates both motor and cognitive processes simultaneously. Thus, VR interventions provide an ideal context for learning new motor strategies of movement and re-learning impaired motor functions. At the same time, they offer a safe and motivational environment for practice, making VR technology, at least theoretically, an ideal tool for intervention in neurodegenerative conditions such as PD (Taylor 2011).

Although significant training effects can be achieved following rehabilitation, specificity of training remains an important issue and transfer to other functional tasks is often limited, especially in patients with PD (Nieuwboer 2009). A degree of realism inherent in VR environments and the feedback-based learning permit individuals to safely learn specific functional tasks that are useful in everyday life. However, whether these learned skills are transferred to daily life outside the virtual environment remains unclear (dos Santos Mendes 2012).

 

Why it is important to do this review

VR combined with physical training is a promising new rehabilitation approach with wide future applications. Research in this area is growing and investigates how VR may be optimally adjusted to the specific needs of various patient populations and can lead to optimal effects. Patients with PD benefit from physical training in the short term and VR technology may be a helpful tool to sustain exercise benefits, motivate patients to perform exercise, and transfer exercise effects to daily life. We will therefore perform this systematic review with the aim of investigating the effectiveness of VR for rehabilitation in patients with PD.

 

Objectives

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Appendices
  6. Contributions of authors
  7. Declarations of interest
  8. Sources of support

To evaluate the effectiveness of virtual reality (VR) exercise interventions for rehabilitation in patients with Parkinson’s disease (PD). VR exercise interventions will be compared with usual care, a placebo control intervention, or any other exercise intervention without VR. Our primary objective is to determine the effect of VR exercise interventions on gait and balance in patients with PD. Our secondary objectives are to determine the effects of VR exercise interventions on (1) global motor function, (2) cognitive function, (3) activities of daily living, (4) quality of life, (5) number and types of adverse events, and (6) therapy adherence in patients with PD.

 

Methods

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Appendices
  6. Contributions of authors
  7. Declarations of interest
  8. Sources of support
 

Criteria for considering studies for this review

 

Types of studies

All randomised controlled trials where at least one of the interventions was an ongoing program of VR exercise or training will be considered for inclusion in the study. Both random and quasi-random methods of allocation will be allowed.

 

Types of participants

We will include studies with patients with a clinically definite diagnosis of idiopathic Parkinson’s disease (PD) as defined by the UK Parkinson’s Disease Society Brain Bank or other diagnostic criteria. No restrictions will be made with regards to gender, age or disease duration. We will include trials reporting an intervention carried out in a mixed sample of participants if data are provided separately for patients with PD.

 

Types of interventions

The effectiveness of VR exercise interventions for rehabilitation versus an alternative intervention such as usual care, a placebo control intervention, or any other exercise intervention without VR will be assessed. All VR interventions need to have a main focus on exercise and motor rehabilitation. No restrictions will be made with regards to frequency and duration of these VR interventions. A VR intervention will be defined as a computerized simulation which allows users to interact with images and virtual objects that appear in the virtual environment in real-time through multiple sensory modalities (Bisson 2007). This general definition that is used in the literature implies immersion in a virtual environment. A study will be included if it includes: 1) a user-computer interface, 2) immersion in the virtual environment, and 3) a focus on motor rehabilitation. Studies that are aimed at studying serious gaming and 'exergaming' will also be included. Serious gaming will be defined as a mental contest, played with a computer in accordance with specific rules, that uses entertainment to further motor performance (Zyda 2005).

We will exclude studies which are aimed to study the following interventions: 1) cueing, 2) visual or auditory references provided by a computer interface without providing immediate feedback on motor performance, 3) video games without a clear motor rehabilitation goal.

 

Types of outcome measures

We will only include trials related to motor rehabilitation in PD as the primary goal.

 

Primary outcomes

  • Gait and balance function
    • Gait:
      • direct measures of gait that include GAITRite indicators such as gait speed.
      • indirect measures of gait including the two-minute walk test, six-minute walk test.

    • Balance:
      • direct measures of balance that include force platform indicators such as centre of pressure behaviour.
      • indirect measures of balance such as Berg Balance Scale (BBS), Timed Up and Go (TUG) and (mini-)BESTest.

 

Secondary outcomes

  • Global motor function:
    • Unified Parkinson’s Disease Rating Sale (UPDRS), part III.

  • Cognitive function:
    • Mini-Mental State Examination (MMSE).
    • Montreal Cognitive Assessment (MoCA).
    • Trail Making Test (TMT).
  • Activities of daily living:
    • as measured by accelerometer.
    • Physical Activity Scale for the Elderly (PASE).
    • Barthel Index of Activities of Daily Living.

  • Quality of life:
    • Short Form (SF)-36.
    • Falls Efficacy Scale (FES-I).
    • Activities-specific Balance Confidence (ABC) scale.

  • Number and type of adverse events:
    • such as falls or addiction.
  • Therapy adherence:
    • withdrawal.
    • satisfaction questionnaires.

If possible, we will consider the minimally important difference or threshold for appreciable change for the primary outcome measures. Furthermore, in order to take into account possible long-term effects of VR training, follow-up results will be included within this review.

 

Search methods for identification of studies

We will use the search strategy recommended by the Cochrane Movement Disorders Group to identify relevant articles.

 

Electronic searches

We will search the Cochrane Movement Disorders Group Trials Register. In addition, relevant articles will be identified by electronic searches of the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library, latest issue), MEDLINE (1950 to present), EMBASE (1980 to present), CINAHL (1982 to present) and the Physiotherapy Evidence Database (PEDro).

The full search strategy can be found in Appendix 1.

 

Searching other resources

In an attempt to identify further published, ongoing and planned trials we will:

  1. inspect references of all identified studies;
  2. search trials registers such as ClinicalTrials.gov (http://clinicaltrials.gov/) and the World Health Organization (WHO) International Clinical Trials Registry Platform search portal (http://apps.who.int/trialsearch/);
  3. handsearch relevant conference proceedings.

 

Data collection and analysis

 

Selection of studies

All search results (title, abstract and descriptors) will be screened separately by KD and VVDB or EB to identify studies for possible inclusion. After the initial screening, KD and VVDB or EB will assess all included trials for eligibility, based on the full text. Any disagreements will be resolved through discussion or, if necessary, through independent arbitration by PG. Study authors will be contacted for additional information if required.

 

Data extraction and management

KD and VVDB or EB will independently extract data into a pre-tested data collection form. Detailed instructions and a training session will be provided to all authors involved in data extraction. Disagreements will be resolved through discussion or, if necessary, through independent arbitration by PG. If required, we will contact study authors for additional information.

 

Assessment of risk of bias in included studies

KD and VVDB or EB will independently assess risk of bias by using the criteria described in the Cochrane Handbook for Systematic Reviews of Interventions to assess trial quality (Higgins 2008). The following items will be assessed for each included trial: sequence generation (randomisation); allocation concealment; blinding of participants, personnel and outcome assessors; incomplete outcome data; and selective outcome reporting. We will collect this information in the data collection form and will resolve disagreements through discussion. Based on our five risk of bias items, low bias studies are studies where ‘low risk of bias’ or ‘unclear risk of bias’ was answered for all items, with a majority of ‘low risk of bias’ assessments. Moderate bias studies are studies where ‘low risk of bias’ or ‘unclear risk of bias’ was answered for all items, with a majority of ‘unclear risk of bias’ assessments. High bias studies are studies where one or more risk of bias item was answered with ‘high risk of bias’. In the case of missing data, studies will be considered low risk of bias if an intention-to-treat analysis has been performed and high risk of bias if not.

 

Measures of treatment effect

KD and VVDB or EB will independently classify outcome measures in terms of the domain assessed (gait and balance function, global motor function, cognitive function, activity limitation, quality of life, number and types of adverse events, therapy adherence). When a study presents more than one outcome measure for the same domain, we will include the measure most frequently used across studies at the longest point of follow-up. We plan to calculate risk ratios (RR) with 95% confidence intervals (CIs) for any dichotomous outcomes, if recorded. We will calculate mean differences (MD) or standardized mean differences (SMD) for continuous outcomes, as appropriate.

 

Unit of analysis issues

There may be issues concerning the design or intervention evaluated in cross-over and cluster randomised trials, which make them unsuitable for pooling with parallel group trials. We will follow the guidance on this matter given in sections 16.3.7 and 16.4.7 of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2008) and explicitly state how we have dealt with data from these types of trials.

 

Dealing with missing data

We will provide an overview of missing data from our selected studies in a table format. We will not use a cut-off as an inclusion criterion. We will contact the study authors and try to acquire data. We will consider a sensitivity analysis for studies with missing data. We will narratively address the potential impact of missing data in the review.

 

Assessment of heterogeneity

We will assess heterogeneity visually by means of forest plots and by reporting the I² statistic. Depending on the degree of heterogeneity found, we may decide against data pooling and present forest plots only along with a narrative description of the results of our review. We will carry out analyses of subgroups of studies in an attempt to explain heterogeneity by study characteristics. In the event of the search resulting in large numbers of trials (more than five) that provide information that can be pooled, we intend to carry out random-effects model meta-analysis incorporating heterogeneity in the intervention effect across studies into the standard error of the effect size so that we can determine the impact of statistical heterogeneity on our pooled results.

 

Assessment of reporting biases

We will examine the funnel plots and address any possible causes for asymmetry narratively.

 

Data synthesis

We plan to carry out a random-effects model meta-analysis. If we cannot carry out a meta-analysis because of substantial differences between the studies, or when there is only one study identified for example, we will present results in a forest plot and provide a narrative review.

 

Subgroup analysis and investigation of heterogeneity

If possible, we will perform subgroup analyses to determine whether the outcome results vary according to disease severity and type of intervention (highly specialized program designed for rehabilitation versus commercial gaming console).

 

Sensitivity analysis

Should a meta-analysis of results be possible, three sensitivity analyses will be performed:

1) including low risk of bias studies only,

2) excluding quasi-randomised trials, and

3) including only trials where data were available from published sources.

These results will be compared to the main analysis including all trials.

 

Appendices

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Appendices
  6. Contributions of authors
  7. Declarations of interest
  8. Sources of support
 

Appendix 1. MEDLINE search strategy

We will use the following search strategy for MEDLINE (PubMed) and adapt it to search the other databases:

1.      Randomised controlled trial [pt]

2.      Controlled clinical trial [pt]

3.      Randomised [tiab]

4.      Placebo [tiab]

5.      Intervention [tiab]

6.      Randomly [tiab]

7.      Trial [tiab]

8.      Groups [tiab]

9.      Random*

10.  1 OR 2 OR 3 OR 4 OR 5 OR 6 OR 7 OR 8 OR 9

11.  Parkinson Disease [mh]

12.  Parkinson* [tiab]

13.  PD [tiab]

14.  Virtual reality exposure therapy [mh]

15.  VR [tiab]

16.  Virtual [tiab]

17.  Augmented [tiab]

18.  Computer [tiab]

19.  Computerized [tiab]

20.  Software [tiab]

21.  Serious gaming [tiab]

22.  Game [tiab]

23.  User-computer interface [mh]

24.  User-computer interface [tiab]

25.  Simulation [tiab]

26.  Exergaming [tiab]

27.  Exergame [tiab]

28.  Reality system [tiab]

29.  Interactive [tiab]

30.  11 OR 12 OR 13

31.  14 OR 15 OR 16 OR 17 OR 18 OR 19 OR 20 OR 21 OR 22 OR 23 OR 24 OR 25 OR 26 OR 27 OR 28 OR 29

32.  10 AND 30 AND 31

 

Contributions of authors

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Appendices
  6. Contributions of authors
  7. Declarations of interest
  8. Sources of support

KD and AN participated in designing, writing and reviewing the protocol. VVDB, EB, PG, AM, JMH and LR participated in reviewing the manuscript. All authors read and approved the final manuscript.

 

Declarations of interest

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Appendices
  6. Contributions of authors
  7. Declarations of interest
  8. Sources of support

None known

 

Sources of support

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Appendices
  6. Contributions of authors
  7. Declarations of interest
  8. Sources of support
 

Internal sources

  • No sources of support supplied

 

External sources

  • European Commission (FP7 project V-TIME-278169), Israel.
  • European Commission (FP7 project CuPiD-288516), Italy.

References

Additional references

  1. Top of page
  2. Abstract
  3. Background
  4. Objectives
  5. Methods
  6. Appendices
  7. Contributions of authors
  8. Declarations of interest
  9. Sources of support
  10. Additional references
Allen 2011
Bisson 2007
  • Bisson E, Contant B, Sveistrup H, Lajoie Y. Functional balance and dual-tak reaction times in older adults are improved by virtual reality and biofeedback training. Cyberpsychology & Behavior 2007;10(1):16-23.
dos Santos Mendes 2012
  • dos Santos Mendes FA, Pompeu JE, Modenesi Lobo A, Guedes da Silva K, Oliveira Tde P, Peterson Zomignani A, et al. Motor learning, retention and transfer after virtual-reality-based training in Parkinson's disease--effect of motor and cognitive demands of games: a longitudinal, controlled clinical study. Physiotherapy 2012;98(3):217-23.
Hawkes 2010
Higgins 2008
  • Higgind JPT, Green S (editors). Cochrane Handbook for Systematic Reviews of Interventions Version 5.0.1 [updated September 2008]. The Cochrane Collaboration, 2008. Available from www.cochrane-handbook.org.
Holden 2005
Lees 2009
  • Lees AJ, Hardy J, Revesz T. Parkinson's disease. Lancet 2009;373(9680):2055-66.
Muangpaisan 2011
  • Muangpaisan W, Mathews A, Hori H, Seidel D. A systematic review of the worldwide prevalence and incidence of Parkinson's disease. Journal of the Medical Association of Thailand 2011;94(6):749-55.
Nieuwboer 2009
  • Nieuwboer A, Rochester L, Müncks L, Swinnen SP. Motor learning in Parkinson's disease: limitations and potential for rehabilitation. Parkinsonism and Related Disorders 2009;15 Suppl 3:S53-8.
Taylor 2011
  • Taylor MJ, McCormick D, Shawis T, Impson R, Griffin M. Activity-promoting gaming systems in exercise and rehabilitation. Journal of Rehabilitation Research and Development 2011;48(10):1171-86.
Tomlinson 2012
  • Tomlinson CL, Patel S, Meek C, Clarke CE, Stowe R, Shah L, et al. Physiotherapy versus placebo or no intervention in Parkinson's disease. Cochrance Database of Systematic Reviews 2012;8:CD002817.
Van Nimwegen 2011
  • Van Nimwege M, Speelman AD, Hofman-van Rossum EJ, Overeem S, Deeg DJ, Borm GF, et al. Physical inactivity in Parkinson's disease. Neurology 2011;258(12):2214-21.
Zyda 2005