Clinical trial NCT03991650: Monitoring Telemedicine Platform in Patients With Anxiety Symptoms and Alcohol Use Disorder
Official title: REMOTE: Monitoring Telemedicine Platform in Patients With Anxiety Symptoms and Alcohol Use Disorder: Smartphone and Wearable Sensors
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Anxiety Disorders
Alcohol Use Disorder
Depressive Disorder
Keywords: wearable
sensor
anxiety
monitoring
ehealth
Alcohol Use Disorder
depression
Lead sponsor: humanITcare
Sponsor class: NETWORK
Collaborators: name: Hospital Clinic of Barcelona
name: European Institute of Innovation and Technology
First posted: 2019-06-19
Enrollment: 44
Sex: ALL
Minimum age (years): 18
Maximum age (years): 65
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: There will be a sample n = 60, with 30 healthy control subjects and 30 afflicted experimental subjects.

Brief summary: The objective of this study is to analyze the physiological patterns of two groups of patients, one control and one with anxiety disorder and alcoholic abuse disorder using sensor data from mobile devices and wearables. This data will be compared to the data presented by three clinical questionnaires: State-trait Anxiety Inventory (STAI), the Alcohol Use Disorders Identification Test (AUDIT), and the Beck's Depression Inventory (BDI-II) in order to determine the feasibility of remote collected data.

Detailed description: The objective of this study is to analyze the physiological patterns of two groups of patients, one control and one with anxiety disorder and alcoholic abuse disorder using sensor data from mobile devices and wearables. This data, collected by sensors, will be compared to the data presented by three clinical questionnaires: State-trait Anxiety Inventory (STAI), the Alcohol Use Disorders Identification Test (AUDIT), and the Beck's Depression Inventory (BDI-II) in order to determine the feasibility of using remote collected data in routine clinical practice. Furthermore, patient satisfaction with the app will be evaluated after the data collection phase.

This is a unicentric, case-controlled, longitudinal, evaluational, national study with two groups, one control of healthy individuals without symptoms of anxiety or depression, and another experimental group in which participants fulfill the given selection criteria for the trial. There are a total of 60 participants split evenly between the two groups.

Eligibility criteria: Inclusion Criteria:

* 18-65 years of age.
* Alcohol use disorder (DSM 5) as main substance.
* Anxiety (STAI \> percentile 33) and, if depressive symptoms, not clinically relevant as to accomplish DSM5 diagnostic criteria for mood disorders (major depressive disorder, bipolar disorder...).
* Having a mobile phone compatible with Android.
* Sign informed consent.

Exclusion Criteria:

* Mood disorder diagnoses (DSM5).
* Cognitive deficits that prevent the participation.
* Active intake of other substances (except for nicotine).

Primary outcomes:
measure: Change in Self-reported Anxiety symptoms assessed with the State-Trait Anxiety Inventory (STAI)
timeFrame: One month, questionnaire taken 4 times (1/week)
measure: Sleep pattern
timeFrame: One month
measure: REM sleep time
timeFrame: One month
measure: Heart Rate
timeFrame: One month
measure: Step count
timeFrame: One month
measure: Distance travelled
timeFrame: One month
measure: Mobile device usage
timeFrame: One month
measure: Sociability (number of incoming an outgoing calls and text messages)
timeFrame: One month
measure: Change in Self-reported Depression symptoms assessed with the Beck's Depression Inventory (BDI-II)
timeFrame: One month, questionnaire taken 4 times (1/week)
measure: Change in Self-reported Alcohol Abuse Symptoms assesed with the Alcohol Use Disorders Identification Test (AUDIT)
timeFrame: One month, questionnaire taken 4 times (1/week)
Secondary outcomes:
measure: Usability of the mobile application
timeFrame: One month
measure: Satisfaction with the application
timeFrame: One month
Other outcomes:
Locations:
city: Barcelona
country: Spain
facility: Hospitcal Clínic de Barcelona
Study officials:
affiliation: Director of Addictions Unit. Hospital Clínic de Barcelona
name: Antoni Gual, MD
role: PRINCIPAL_INVESTIGATOR
affiliation: Clinic Foundation for Biomedical Research
name: Elsa Caballeria
role: STUDY_CHAIR
affiliation: Addictions Unit, Hospital Clínic de Barcelona
name: Hugo Lopez-Pelayo, MD
role: STUDY_CHAIR
affiliation: humanITcare, FollowHealth SL
name: Nuria Pastor Hernandez, MSc
role: STUDY_DIRECTOR
affiliation: humanITcare, FollowHealth SL
name: Unai Sanchez Luque, MSc
role: STUDY_DIRECTOR
affiliation: humanITcare, University of Texas at Austin
name: Elizabeth Katayoun Khalilian
role: STUDY_CHAIR
References:
citation: Alonso J, Liu Z, Evans-Lacko S, Sadikova E, Sampson N, Chatterji S, Abdulmalik J, Aguilar-Gaxiola S, Al-Hamzawi A, Andrade LH, Bruffaerts R, Cardoso G, Cia A, Florescu S, de Girolamo G, Gureje O, Haro JM, He Y, de Jonge P, Karam EG, Kawakami N, Kovess-Masfety V, Lee S, Levinson D, Medina-Mora ME, Navarro-Mateu F, Pennell BE, Piazza M, Posada-Villa J, Ten Have M, Zarkov Z, Kessler RC, Thornicroft G; WHO World Mental Health Survey Collaborators. Treatment gap for anxiety disorders is global: Results of the World Mental Health Surveys in 21 countries. Depress Anxiety. 2018 Mar;35(3):195-208. doi: 10.1002/da.22711. Epub 2018 Jan 22.
citation: Wittchen HU, Jacobi F, Rehm J, Gustavsson A, Svensson M, Jonsson B, Olesen J, Allgulander C, Alonso J, Faravelli C, Fratiglioni L, Jennum P, Lieb R, Maercker A, van Os J, Preisig M, Salvador-Carulla L, Simon R, Steinhausen HC. The size and burden of mental disorders and other disorders of the brain in Europe 2010. Eur Neuropsychopharmacol. 2011 Sep;21(9):655-79. doi: 10.1016/j.euroneuro.2011.07.018.
citation: Barrio P, Ortega L, Lopez H, Gual A. Self-management and Shared Decision-Making in Alcohol Dependence via a Mobile App: a Pilot Study. Int J Behav Med. 2017 Oct;24(5):722-727. doi: 10.1007/s12529-017-9643-6.
citation: Gustafson DH, McTavish FM, Chih MY, Atwood AK, Johnson RA, Boyle MG, Levy MS, Driscoll H, Chisholm SM, Dillenburg L, Isham A, Shah D. A smartphone application to support recovery from alcoholism: a randomized clinical trial. JAMA Psychiatry. 2014 May;71(5):566-72. doi: 10.1001/jamapsychiatry.2013.4642.
citation: Reddy MS. Depression: the disorder and the burden. Indian J Psychol Med. 2010 Jan;32(1):1-2. doi: 10.4103/0253-7176.70510. No abstract available.
citation: Menger V, Spruit M, Hagoort K, Scheepers F. Transitioning to a Data Driven Mental Health Practice: Collaborative Expert Sessions for Knowledge and Hypothesis Finding. Comput Math Methods Med. 2016;2016:9089321. doi: 10.1155/2016/9089321. Epub 2016 Aug 17.
citation: Hsin H, Torous J, Roberts L. An Adjuvant Role for Mobile Health in Psychiatry. JAMA Psychiatry. 2016 Feb;73(2):103-4. doi: 10.1001/jamapsychiatry.2015.2839. No abstract available.
citation: Insel TR. Digital Phenotyping: Technology for a New Science of Behavior. JAMA. 2017 Oct 3;318(13):1215-1216. doi: 10.1001/jama.2017.11295. No abstract available.
citation: Bernert RA, Hom MA, Iwata NG, Joiner TE. Objectively Assessed Sleep Variability as an Acute Warning Sign of Suicidal Ideation in a Longitudinal Evaluation of Young Adults at High Suicide Risk. J Clin Psychiatry. 2017 Jun;78(6):e678-e687. doi: 10.4088/JCP.16m11193.
citation: Bandelow B, Michaelis S. Epidemiology of anxiety disorders in the 21st century. Dialogues Clin Neurosci. 2015 Sep;17(3):327-35. doi: 10.31887/DCNS.2015.17.3/bbandelow.
citation: Saeb S, Zhang M, Karr CJ, Schueller SM, Corden ME, Kording KP, Mohr DC. Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study. J Med Internet Res. 2015 Jul 15;17(7):e175. doi: 10.2196/jmir.4273.
citation: Saeb S, Lattie EG, Kording KP, Mohr DC. Mobile Phone Detection of Semantic Location and Its Relationship to Depression and Anxiety. JMIR Mhealth Uhealth. 2017 Aug 10;5(8):e112. doi: 10.2196/mhealth.7297.
citation: Sano A, Taylor S, McHill AW, Phillips AJ, Barger LK, Klerman E, Picard R. Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study. J Med Internet Res. 2018 Jun 8;20(6):e210. doi: 10.2196/jmir.9410.
citation: Torous J, Staples P, Shanahan M, Lin C, Peck P, Keshavan M, Onnela JP. Utilizing a Personal Smartphone Custom App to Assess the Patient Health Questionnaire-9 (PHQ-9) Depressive Symptoms in Patients With Major Depressive Disorder. JMIR Ment Health. 2015 Mar 24;2(1):e8. doi: 10.2196/mental.3889. eCollection 2015 Jan-Mar.
citation: Onnela JP, Rauch SL. Harnessing Smartphone-Based Digital Phenotyping to Enhance Behavioral and Mental Health. Neuropsychopharmacology. 2016 Jun;41(7):1691-6. doi: 10.1038/npp.2016.7. Epub 2016 Jan 28. No abstract available.
citation: Trautmann S, Rehm J, Wittchen HU. The economic costs of mental disorders: Do our societies react appropriately to the burden of mental disorders? EMBO Rep. 2016 Sep;17(9):1245-9. doi: 10.15252/embr.201642951. Epub 2016 Aug 4.
citation: Ghandeharioun, A., Fedor, S., Sangermano, L., Ionescu, D., Alpert, J., Dale, C., ... & Picard, R. (2017, October). Objective assessment of depressive symptoms with machine learning and wearable sensors data. In Affective Computing and Intelligent Interaction (ACII), 2017 Seventh International Conference on (pp. 325-332). IEEE.