NCT03991650

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.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
44

participants targeted

Target at P25-P50 for all trials

Timeline
Completed

Started Feb 2019

Shorter than P25 for all trials

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

February 1, 2019

Completed
5 months until next milestone

First Submitted

Initial submission to the registry

June 17, 2019

Completed
2 days until next milestone

First Posted

Study publicly available on registry

June 19, 2019

Completed
5 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

November 5, 2019

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

November 5, 2019

Completed
Last Updated

January 25, 2023

Status Verified

January 1, 2023

Enrollment Period

9 months

First QC Date

June 17, 2019

Last Update Submit

January 24, 2023

Conditions

Keywords

wearablesensoranxietymonitoringehealthAlcohol Use Disorderdepression

Outcome Measures

Primary Outcomes (10)

  • Change in Self-reported Anxiety symptoms assessed with the State-Trait Anxiety Inventory (STAI)

    Taken through the application "Ushine". Participants receive STAI scores ranging from 0-60, 0 being lowest amount of symptoms, and 60 being the greatest amount of symptoms, which are then transformed into percentiles according to age and sex.

    One month, questionnaire taken 4 times (1/week)

  • Sleep pattern

    Monitoring of circadian rhythm using a motion sensor Fitbit and cardiac activity sensor

    One month

  • REM sleep time

    monitoring of REM sleep patterns using a motion sensor Fitbit and cardiac activity sensor

    One month

  • Heart Rate

    monitoring of heart rate using Fitbit sensor

    One month

  • Step count

    Monitoring of daily step count using motion sensor FitBit

    One month

  • Distance travelled

    Monitoring of distance travelled using GPS phone

    One month

  • Mobile device usage

    Monitoring how often the patient's mobile device is used, determined by tracking the presence of a signal from their device

    One month

  • Sociability (number of incoming an outgoing calls and text messages)

    The number of incoming and outgoing calls and text messages will be monitored using the UShine app algorithm

    One month

  • Change in Self-reported Depression symptoms assessed with the Beck's Depression Inventory (BDI-II)

    Taken through the application "Ushine". Participants receive BDI-II scores ranging from 1-63, with a score of 0-13 indicating minimal depression, 14-19 indicating mild depression, 20-28 indicating moderate depression, and 29-63 indicating severe depression.

    One month, questionnaire taken 4 times (1/week)

  • Change in Self-reported Alcohol Abuse Symptoms assesed with the Alcohol Use Disorders Identification Test (AUDIT)

    Taken through the application "Ushine". Participants receive AUDIT scores ranging from 0-40. A score of 8 or more is associated with harmful or hazardous drinking, a score of 13 or more in women, and 15 or more in men, is likely to indicate alcohol dependence.

    One month, questionnaire taken 4 times (1/week)

Secondary Outcomes (2)

  • Usability of the mobile application

    One month

  • Satisfaction with the application

    One month

Study Arms (2)

Control

n=30 healthy participants will be recruited using social networks and leaflets of information distributed by the research team at the Hospital Cliníc de Barcelona. The participants will be monitored over the course of one month using the humanITcare app "U-Shine," which will track participant's sociability, device usage, and location frequency using mobile sensors. Participants' data will also be monitored with a FitBit device to track sleep schedules, heart rate, and step count. During the weekly follow-up, they will have to complete the three clinical questionnaires taken at the initial visit.

Behavioral: Monitoring with a device

Experimental

The recruitment process will be carried out in patients of external consultations and the day hospital of the Addictions Unit at the Hospital Clinic of Barcelona. n=30 patients with Anxiety and Alcohol Use Disorder. The participants will be monitored over the course of one month using the humanITcare app "U-Shine," which will track participant's sociability, device usage, and location frequency using mobile sensors. Participants will also be monitored using a FitBit device to track sleep schedules, heart rate, and step count. During the weekly follow-up, they will have to complete the three clinical questionnaires taken at the initial visit.

Behavioral: Monitoring with a device

Interventions

Participants will be monitored by an App.

ControlExperimental

Eligibility Criteria

Age18 Years - 65 Years
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

There will be a sample n = 60, with 30 healthy control subjects and 30 afflicted experimental subjects.

You may qualify if:

  • 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.

You may not qualify if:

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

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Hospitcal Clínic de Barcelona

Barcelona, 08036, Spain

Location

Related Publications (17)

  • 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.

    PMID: 29356216BACKGROUND
  • 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.

    PMID: 21896369BACKGROUND
  • 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.

    PMID: 28236288BACKGROUND
  • 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.

    PMID: 24671165BACKGROUND
  • 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.

    PMID: 21799550BACKGROUND
  • 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.

    PMID: 27630736BACKGROUND
  • 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.

    PMID: 26747695BACKGROUND
  • 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.

    PMID: 28973224BACKGROUND
  • 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.

    PMID: 28682534BACKGROUND
  • 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.

    PMID: 26487813BACKGROUND
  • 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.

    PMID: 26180009BACKGROUND
  • 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.

    PMID: 28798010BACKGROUND
  • 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.

    PMID: 29884610BACKGROUND
  • 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.

    PMID: 26543914BACKGROUND
  • 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.

    PMID: 26818126BACKGROUND
  • 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.

    PMID: 27491723BACKGROUND
  • 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.

    BACKGROUND

Related Links

MeSH Terms

Conditions

Anxiety DisordersAlcoholismDepressive DisorderDepression

Condition Hierarchy (Ancestors)

Mental DisordersAlcohol-Related DisordersSubstance-Related DisordersChemically-Induced DisordersMood DisordersBehavioral SymptomsBehavior

Study Officials

  • Antoni Gual, MD

    Director of Addictions Unit. Hospital Clínic de Barcelona

    PRINCIPAL INVESTIGATOR
  • Elsa Caballeria

    Clinic Foundation for Biomedical Research

    STUDY CHAIR
  • Hugo Lopez-Pelayo, MD

    Addictions Unit, Hospital Clínic de Barcelona

    STUDY CHAIR
  • Nuria Pastor Hernandez, MSc

    humanITcare, FollowHealth SL

    STUDY DIRECTOR
  • Unai Sanchez Luque, MSc

    humanITcare, FollowHealth SL

    STUDY DIRECTOR
  • Elizabeth Katayoun Khalilian

    humanITcare, University of Texas at Austin

    STUDY CHAIR

Study Design

Study Type
observational
Observational Model
CASE CONTROL
Time Perspective
PROSPECTIVE
Target Duration
1 Month
Sponsor Type
NETWORK
Responsible Party
SPONSOR

Study Record Dates

First Submitted

June 17, 2019

First Posted

June 19, 2019

Study Start

February 1, 2019

Primary Completion

November 5, 2019

Study Completion

November 5, 2019

Last Updated

January 25, 2023

Record last verified: 2023-01

Data Sharing

IPD Sharing
Will share

Individual participant data sets that underlie results in the final study report will be available for sharing.

Shared Documents
STUDY PROTOCOL, SAP, ICF, CSR
Time Frame
IPD will be available by the estimated date of September 2019, when study results are expected to be published
Access Criteria
Participants can access their own individual data records, only hospital researchers can access the aggregated data sets.

Locations