<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03268187</url>
  </required_header>
  <id_info>
    <org_study_id>009/2017</org_study_id>
    <nct_id>NCT03268187</nct_id>
  </id_info>
  <brief_title>Biofeedback-based Relaxation Training or Self-alert Training to Alleviate Fatigue in Multiple Sclerosis Patients.</brief_title>
  <official_title>Biofeedback-based Relaxation Training or Self-alert Training to Alleviate Fatigue in Multiple Sclerosis Patients.</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Rehazentrum Wilhelmshaven</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Rehazentrum Wilhelmshaven</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      The presented study compares the effectiveness of a biofeedback-based relaxation training&#xD;
      with the effectiveness of a biofeedback-based self-alert training on the reduction of fatigue&#xD;
      in multiple sclerosis patients using a between groups design. Furthermore, the relation of&#xD;
      fatigue in multiple sclerosis patients and autonomic potentials as well as the performance in&#xD;
      a vigilance task will be examined.&#xD;
&#xD;
      The relaxation training is based on the principle of progressive muscle relaxation according&#xD;
      to Jacobsen. The patient is asked to tense all muscles in their face and perceive consciously&#xD;
      the relaxation afterwards according to verbal cues. In the self-alert training condition, the&#xD;
      patient will hear verbal cues to increase their attention. In both conditions the external&#xD;
      cues given will be reduced in four phases until the patient has to cue himself. The patient&#xD;
      is advised to track the changes in the skin resistance mirrored by biofeedback on a screen.&#xD;
&#xD;
      In both conditions the training will be split on two days. During the whole examination heart&#xD;
      rate and skin resistance will be recorded. The allocation to the training happens randomly.&#xD;
      On the first day the patient will complete questionnaires to survey depression and apathy and&#xD;
      do a baseline vigilance task. Before and after the vigilance task the current fatigue status&#xD;
      will be assessed using a visual analogue scale. Afterwards an introduction in the treatment&#xD;
      method will be given.&#xD;
&#xD;
      On the second day the introduction into the training will be repeated. Afterwards a short&#xD;
      time vigilance task will be done and questionnaires to survey fatigue and sleep behaviour and&#xD;
      quality will be completed. Subsequently the last part of the training (no external cues) will&#xD;
      be done. The examination will be completed by a long-time vigilance task. Before and after&#xD;
      the vigilance task the current fatigue status will be assessed using a visual analogue scale.&#xD;
&#xD;
      It is hypothesised that especially the biofeedback-based self-alert training has a positive&#xD;
      effect on fatigue and the vigilance performance in multiple sclerosis patients, as it&#xD;
      increases the ectodermal activity and increases the sympathetic activation. It was shown that&#xD;
      phasic changes of the skin resistance are correlated with an increase of neuronal activity in&#xD;
      the brain areas relevant for vigilance (Critchley et al., 2002; Nagai et al., 2004). The&#xD;
      relaxation training will reduce the sympatho-adrenergic excitation disposition and reduce the&#xD;
      level of activity. Consequently, we do not expect an alleviation of the perceived fatigue&#xD;
      according to our underlying model (Hanken et al., 2016). In addition, it is hypothesized&#xD;
      that, independent from the treatment, autonomic potentials correlate with fatigue.&#xD;
    </textblock>
  </brief_summary>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">July 17, 2017</start_date>
  <completion_date type="Actual">October 18, 2018</completion_date>
  <primary_completion_date type="Actual">June 9, 2018</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Parallel Assignment</intervention_model>
    <primary_purpose>Treatment</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Reaction Time of Vigilance Task (TAP)</measure>
    <time_frame>Vigilance is measured at the beginning of the first day before the training introduction as well as after the training at the second day.</time_frame>
    <description>Changes of the reaction time in the vigilance task</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Subjective Fatigue (VAS)</measure>
    <time_frame>Before and after the long-term vigilance tasks at day 1 and 2</time_frame>
    <description>The current perceived fatigue</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Omissions and errors of Vigilance Task (TAP)</measure>
    <time_frame>At day one before the introduction in the training and at day two after the training.</time_frame>
    <description>The number of omissions and errors made in the Vigilance Task</description>
  </secondary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Actual">61</enrollment>
  <condition>Fatigue</condition>
  <condition>Multiple Sclerosis</condition>
  <arm_group>
    <arm_group_label>Self-Alert Training</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Biofeedback-based Self-Alert Training Vigilance Task Questionnaires accessing apathy, fatigue, depression, sleep quality, sleep behavior</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Relaxation Training</arm_group_label>
    <arm_group_type>Active Comparator</arm_group_type>
    <description>Biofeedback-based Relaxation Training Vigilance Task Questionnaires accessing apathy, fatigue, depression, sleep quality, sleep behavior</description>
  </arm_group>
  <intervention>
    <intervention_type>Device</intervention_type>
    <intervention_name>Biofeedback</intervention_name>
    <description>The skin conductance of the patient is measured and fed back to the patient via screen.</description>
    <arm_group_label>Relaxation Training</arm_group_label>
    <arm_group_label>Self-Alert Training</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Self-Alert Training</intervention_name>
    <description>Self-Alert Training</description>
    <arm_group_label>Self-Alert Training</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Relaxation Training</intervention_name>
    <description>Relaxation Training</description>
    <arm_group_label>Relaxation Training</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  at least a moderate cognitive fatigue (Fatigue Scale for Motor and Cognition minimum&#xD;
             22)&#xD;
&#xD;
          -  clinical diagnosis of Multiple Sclerosis&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  psychiatric conditions independent from Multiple Sclerosis&#xD;
&#xD;
          -  Pregnancy&#xD;
&#xD;
          -  regular intake of psychostimulants&#xD;
&#xD;
          -  no relapse in the last four weeks before&#xD;
&#xD;
          -  no cortisone therapy in the last four weeks before&#xD;
&#xD;
          -  patients with schizophrenia or serious personality disorders&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>N/A</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Helmut Hildebrandt, Prof</last_name>
    <role>Study Director</role>
    <affiliation>Carl- von Ossietzky University Oldenburg</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Rehazentrum Wilhelmshaven</name>
      <address>
        <city>Wilhelmshaven</city>
        <state>Lower Saxony</state>
        <zip>26382</zip>
        <country>Germany</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Germany</country>
  </location_countries>
  <verification_date>April 2019</verification_date>
  <study_first_submitted>August 29, 2017</study_first_submitted>
  <study_first_submitted_qc>August 30, 2017</study_first_submitted_qc>
  <study_first_posted type="Actual">August 31, 2017</study_first_posted>
  <last_update_submitted>April 9, 2019</last_update_submitted>
  <last_update_submitted_qc>April 9, 2019</last_update_submitted_qc>
  <last_update_posted type="Actual">April 11, 2019</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Rehazentrum Wilhelmshaven</investigator_affiliation>
    <investigator_full_name>Carina Sander</investigator_full_name>
    <investigator_title>Psychologist</investigator_title>
  </responsible_party>
  <keyword>Cognitive Fatigue</keyword>
  <keyword>Multiple Sclerosis</keyword>
  <keyword>Biofeedback</keyword>
  <keyword>Self-Alert Training</keyword>
  <keyword>Vigilance</keyword>
  <keyword>Autonomic potentials</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Multiple Sclerosis</mesh_term>
    <mesh_term>Sclerosis</mesh_term>
    <mesh_term>Fatigue</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Undecided</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03268187
org study id: 009/2017
nct id: NCT03268187
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
The presented study compares the effectiveness of a biofeedback-based relaxation training
      with the effectiveness of a biofeedback-based self-alert training on the reduction of fatigue
      in multiple sclerosis patients using a between groups design. Furthermore, the relation of
      fatigue in multiple sclerosis patients and autonomic potentials as well as the performance in
      a vigilance task will be examined.

      The relaxation training is based on the principle of progressive muscle relaxation according
      to Jacobsen. The patient is asked to tense all muscles in their face and perceive consciously
      the relaxation afterwards according to verbal cues. In the self-alert training condition, the
      patient will hear verbal cues to increase their attention. In both conditions the external
      cues given will be reduced in four phases until the patient has to cue himself. The patient
      is advised to track the changes in the skin resistance mirrored by biofeedback on a screen.

      In both conditions the training will be split on two days. During the whole examination heart
      rate and skin resistance will be recorded. The allocation to the training happens randomly.
      On the first day the patient will complete questionnaires to survey depression and apathy and
      do a baseline vigilance task. Before and after the vigilance task the current fatigue status
      will be assessed using a visual analogue scale. Afterwards an introduction in the treatment
      method will be given.

      On the second day the introduction into the training will be repeated. Afterwards a short
      time vigilance task will be done and questionnaires to survey fatigue and sleep behaviour and
      quality will be completed. Subsequently the last part of the training (no external cues) will
      be done. The examination will be completed by a long-time vigilance task. Before and after
      the vigilance task the current fatigue status will be assessed using a visual analogue scale.

      It is hypothesised that especially the biofeedback-based self-alert training has a positive
      effect on fatigue and the vigilance performance in multiple sclerosis patients, as it
      increases the ectodermal activity and increases the sympathetic activation. It was shown that
      phasic changes of the skin resistance are correlated with an increase of neuronal activity in
      the brain areas relevant for vigilance (Critchley et al., 2002; Nagai et al., 2004). The
      relaxation training will reduce the sympatho-adrenergic excitation disposition and reduce the
      level of activity. Consequently, we do not expect an alleviation of the perceived fatigue
      according to our underlying model (Hanken et al., 2016). In addition, it is hypothesized
      that, independent from the treatment, autonomic potentials correlate with fatigue.
allocation: Randomized
intervention model: Parallel Assignment
primary purpose: Treatment
masking: None (Open Label)
measure: Reaction Time of Vigilance Task (TAP)
time frame: Vigilance is measured at the beginning of the first day before the training introduction as well as after the training at the second day.
description: Changes of the reaction time in the vigilance task
measure: Subjective Fatigue (VAS)
time frame: Before and after the long-term vigilance tasks at day 1 and 2
description: The current perceived fatigue
measure: Omissions and errors of Vigilance Task (TAP)
time frame: At day one before the introduction in the training and at day two after the training.
description: The number of omissions and errors made in the Vigilance Task
arm group label: Self-Alert Training
arm group type: Experimental
description: Biofeedback-based Self-Alert Training Vigilance Task Questionnaires accessing apathy, fatigue, depression, sleep quality, sleep behavior
arm group label: Relaxation Training
arm group type: Active Comparator
description: Biofeedback-based Relaxation Training Vigilance Task Questionnaires accessing apathy, fatigue, depression, sleep quality, sleep behavior
intervention type: Device
intervention name: Biofeedback
description: The skin conductance of the patient is measured and fed back to the patient via screen.
arm group label: Relaxation Training
arm group label: Self-Alert Training
intervention type: Behavioral
intervention name: Self-Alert Training
description: Self-Alert Training
arm group label: Self-Alert Training
intervention type: Behavioral
intervention name: Relaxation Training
description: Relaxation Training
arm group label: Relaxation Training
criteria: 
gender: All
minimum age: N/A
maximum age: N/A
healthy volunteers: No
last name: Helmut Hildebrandt, Prof
role: Study Director
affiliation: Carl- von Ossietzky University Oldenburg
facility: 
country: Germany
responsible party type: Principal Investigator
investigator affiliation: Rehazentrum Wilhelmshaven
investigator full name: Carina Sander
investigator title: Psychologist
mesh term: Multiple Sclerosis
mesh term: Sclerosis
mesh term: Fatigue
sharing ipd: Undecided