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A Platform to Build Mobile Health Apps: The Personal Health Intervention Toolkit (PHIT)
Personal Health Intervention Toolkit (PHIT) is an advanced cross-platform software framework targeted at personal self-help research on mobile devices. Following the subjective and objective measurement, assessment, and plan methodology for health assessment and intervention recommendations, the PHI...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications Inc.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4526892/ https://www.ncbi.nlm.nih.gov/pubmed/26033047 http://dx.doi.org/10.2196/mhealth.4202 |
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author | Eckhoff, Randall Peter Kizakevich, Paul Nicholas Bakalov, Vesselina Zhang, Yuying Bryant, Stephanie Patrice Hobbs, Maria Ann |
author_facet | Eckhoff, Randall Peter Kizakevich, Paul Nicholas Bakalov, Vesselina Zhang, Yuying Bryant, Stephanie Patrice Hobbs, Maria Ann |
author_sort | Eckhoff, Randall Peter |
collection | PubMed |
description | Personal Health Intervention Toolkit (PHIT) is an advanced cross-platform software framework targeted at personal self-help research on mobile devices. Following the subjective and objective measurement, assessment, and plan methodology for health assessment and intervention recommendations, the PHIT platform lets researchers quickly build mobile health research Android and iOS apps. They can (1) create complex data-collection instruments using a simple extensible markup language (XML) schema; (2) use Bluetooth wireless sensors; (3) create targeted self-help interventions based on collected data via XML-coded logic; (4) facilitate cross-study reuse from the library of existing instruments and interventions such as stress, anxiety, sleep quality, and substance abuse; and (5) monitor longitudinal intervention studies via daily upload to a Web-based dashboard portal. For physiological data, Bluetooth sensors collect real-time data with on-device processing. For example, using the BinarHeartSensor, the PHIT platform processes the heart rate data into heart rate variability measures, and plots these data as time-series waveforms. Subjective data instruments are user data-entry screens, comprising a series of forms with validation and processing logic. The PHIT instrument library consists of over 70 reusable instruments for various domains including cognitive, environmental, psychiatric, psychosocial, and substance abuse. Many are standardized instruments, such as the Alcohol Use Disorder Identification Test, Patient Health Questionnaire-8, and Post-Traumatic Stress Disorder Checklist. Autonomous instruments such as battery and global positioning system location support continuous background data collection. All data are acquired using a schedule appropriate to the app’s deployment. The PHIT intelligent virtual advisor (iVA) is an expert system logic layer, which analyzes the data in real time on the device. This data analysis results in a tailored app of interventions and other data-collection instruments. For example, if a user anxiety score exceeds a threshold, the iVA might add a meditation intervention to the task list in order to teach the user how to relax, and schedule a reassessment using the anxiety instrument 2 weeks later to re-evaluate. If the anxiety score exceeds a higher threshold, then an advisory to seek professional help would be displayed. Using the easy-to-use PHIT scripting language, the researcher can program new instruments, the iVA, and interventions to their domain-specific needs. The iVA, instruments, and interventions are defined via XML files, which facilities rapid app development and deployment. The PHIT Web-based dashboard portal provides the researcher access to all the uploaded data. After a secure login, the data can be filtered by criteria such as study, protocol, domain, and user. Data can also be exported into a comma-delimited file for further processing. The PHIT framework has proven to be an extensible, reconfigurable technology that facilitates mobile data collection and health intervention research. Additional plans include instrument development in other domains, additional health sensors, and a text messaging notification system. |
format | Online Article Text |
id | pubmed-4526892 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | JMIR Publications Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-45268922015-08-11 A Platform to Build Mobile Health Apps: The Personal Health Intervention Toolkit (PHIT) Eckhoff, Randall Peter Kizakevich, Paul Nicholas Bakalov, Vesselina Zhang, Yuying Bryant, Stephanie Patrice Hobbs, Maria Ann JMIR Mhealth Uhealth Tutorial Personal Health Intervention Toolkit (PHIT) is an advanced cross-platform software framework targeted at personal self-help research on mobile devices. Following the subjective and objective measurement, assessment, and plan methodology for health assessment and intervention recommendations, the PHIT platform lets researchers quickly build mobile health research Android and iOS apps. They can (1) create complex data-collection instruments using a simple extensible markup language (XML) schema; (2) use Bluetooth wireless sensors; (3) create targeted self-help interventions based on collected data via XML-coded logic; (4) facilitate cross-study reuse from the library of existing instruments and interventions such as stress, anxiety, sleep quality, and substance abuse; and (5) monitor longitudinal intervention studies via daily upload to a Web-based dashboard portal. For physiological data, Bluetooth sensors collect real-time data with on-device processing. For example, using the BinarHeartSensor, the PHIT platform processes the heart rate data into heart rate variability measures, and plots these data as time-series waveforms. Subjective data instruments are user data-entry screens, comprising a series of forms with validation and processing logic. The PHIT instrument library consists of over 70 reusable instruments for various domains including cognitive, environmental, psychiatric, psychosocial, and substance abuse. Many are standardized instruments, such as the Alcohol Use Disorder Identification Test, Patient Health Questionnaire-8, and Post-Traumatic Stress Disorder Checklist. Autonomous instruments such as battery and global positioning system location support continuous background data collection. All data are acquired using a schedule appropriate to the app’s deployment. The PHIT intelligent virtual advisor (iVA) is an expert system logic layer, which analyzes the data in real time on the device. This data analysis results in a tailored app of interventions and other data-collection instruments. For example, if a user anxiety score exceeds a threshold, the iVA might add a meditation intervention to the task list in order to teach the user how to relax, and schedule a reassessment using the anxiety instrument 2 weeks later to re-evaluate. If the anxiety score exceeds a higher threshold, then an advisory to seek professional help would be displayed. Using the easy-to-use PHIT scripting language, the researcher can program new instruments, the iVA, and interventions to their domain-specific needs. The iVA, instruments, and interventions are defined via XML files, which facilities rapid app development and deployment. The PHIT Web-based dashboard portal provides the researcher access to all the uploaded data. After a secure login, the data can be filtered by criteria such as study, protocol, domain, and user. Data can also be exported into a comma-delimited file for further processing. The PHIT framework has proven to be an extensible, reconfigurable technology that facilitates mobile data collection and health intervention research. Additional plans include instrument development in other domains, additional health sensors, and a text messaging notification system. JMIR Publications Inc. 2015-06-01 /pmc/articles/PMC4526892/ /pubmed/26033047 http://dx.doi.org/10.2196/mhealth.4202 Text en ©Randall Peter Eckhoff, Paul Nicholas Kizakevich, Vesselina Bakalov, Yuying Zhang, Stephanie Patrice Bryant, Maria Ann Hobbs. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 01.06.2015. http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Tutorial Eckhoff, Randall Peter Kizakevich, Paul Nicholas Bakalov, Vesselina Zhang, Yuying Bryant, Stephanie Patrice Hobbs, Maria Ann A Platform to Build Mobile Health Apps: The Personal Health Intervention Toolkit (PHIT) |
title | A Platform to Build Mobile Health Apps: The Personal Health Intervention Toolkit (PHIT) |
title_full | A Platform to Build Mobile Health Apps: The Personal Health Intervention Toolkit (PHIT) |
title_fullStr | A Platform to Build Mobile Health Apps: The Personal Health Intervention Toolkit (PHIT) |
title_full_unstemmed | A Platform to Build Mobile Health Apps: The Personal Health Intervention Toolkit (PHIT) |
title_short | A Platform to Build Mobile Health Apps: The Personal Health Intervention Toolkit (PHIT) |
title_sort | platform to build mobile health apps: the personal health intervention toolkit (phit) |
topic | Tutorial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4526892/ https://www.ncbi.nlm.nih.gov/pubmed/26033047 http://dx.doi.org/10.2196/mhealth.4202 |
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