Potential benefits of integrating ecological momentary assessment data into mHealth care systems

Abstract The advancement of wearable/ambulatory technologies has brought a huge change to data collection frameworks in recent decades. Mobile health (mHealth) care platforms, which utilize ambulatory devices to collect naturalistic and often intensively sampled data, produce innovative information...
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Autor*in:	Jinhyuk Kim [verfasserIn] David Marcusson-Clavertz [verfasserIn] Kazuhiro Yoshiuchi [verfasserIn] Joshua M. Smyth [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Mobile healthcare system mHealth Ecological momentary assessment Wearable devices

Übergeordnetes Werk:	In: BioPsychoSocial Medicine - BMC, 2007, 13(2019), 1, Seite 6
Übergeordnetes Werk:	volume:13 ; year:2019 ; number:1 ; pages:6

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1186/s13030-019-0160-5

Katalog-ID:	DOAJ051358069

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allfieldsSound	10.1186/s13030-019-0160-5 doi (DE-627)DOAJ051358069 (DE-599)DOAJa391d3b98f994a0c8102ee4736ca020e DE-627 ger DE-627 rakwb eng RC321-571 Jinhyuk Kim verfasserin aut Potential benefits of integrating ecological momentary assessment data into mHealth care systems 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The advancement of wearable/ambulatory technologies has brought a huge change to data collection frameworks in recent decades. Mobile health (mHealth) care platforms, which utilize ambulatory devices to collect naturalistic and often intensively sampled data, produce innovative information of potential clinical relevance. For example, such data can inform clinical study design, recruitment approach, data analysis, and delivery of both “traditional” and novel (e.g., mHealth) interventions. We provide a conceptual overview of how data measured continuously or repeatedly via mobile devices (e.g., smartphone and body sensors) in daily life could be fruitfully used within a mHealth care system. We highlight the potential benefits of integrating ecological momentary assessment (EMA) into mHealth platforms for collecting, processing, and modeling data, and delivering and evaluating novel interventions in everyday life. Although the data obtained from EMA and related approaches may hold great potential benefits for mHealth care system, there are also implementation challenges; we briefly discuss the challenges to integrating EMA into mHealth care system. Mobile healthcare system mHealth Ecological momentary assessment Wearable devices Neurosciences. Biological psychiatry. Neuropsychiatry David Marcusson-Clavertz verfasserin aut Kazuhiro Yoshiuchi verfasserin aut Joshua M. Smyth verfasserin aut In BioPsychoSocial Medicine BMC, 2007 13(2019), 1, Seite 6 (DE-627)522898505 (DE-600)2265705-8 17510759 nnns volume:13 year:2019 number:1 pages:6 https://doi.org/10.1186/s13030-019-0160-5 kostenfrei https://doaj.org/article/a391d3b98f994a0c8102ee4736ca020e kostenfrei http://link.springer.com/article/10.1186/s13030-019-0160-5 kostenfrei https://doaj.org/toc/1751-0759 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2086 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2019 1 6
language	English
source	In BioPsychoSocial Medicine 13(2019), 1, Seite 6 volume:13 year:2019 number:1 pages:6
sourceStr	In BioPsychoSocial Medicine 13(2019), 1, Seite 6 volume:13 year:2019 number:1 pages:6
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Mobile healthcare system mHealth Ecological momentary assessment Wearable devices Neurosciences. Biological psychiatry. Neuropsychiatry
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container_title	BioPsychoSocial Medicine
authorswithroles_txt_mv	Jinhyuk Kim @@aut@@ David Marcusson-Clavertz @@aut@@ Kazuhiro Yoshiuchi @@aut@@ Joshua M. Smyth @@aut@@
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author	Jinhyuk Kim
spellingShingle	Jinhyuk Kim misc RC321-571 misc Mobile healthcare system misc mHealth misc Ecological momentary assessment misc Wearable devices misc Neurosciences. Biological psychiatry. Neuropsychiatry Potential benefits of integrating ecological momentary assessment data into mHealth care systems
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topic_title	RC321-571 Potential benefits of integrating ecological momentary assessment data into mHealth care systems Mobile healthcare system mHealth Ecological momentary assessment Wearable devices
topic	misc RC321-571 misc Mobile healthcare system misc mHealth misc Ecological momentary assessment misc Wearable devices misc Neurosciences. Biological psychiatry. Neuropsychiatry
topic_unstemmed	misc RC321-571 misc Mobile healthcare system misc mHealth misc Ecological momentary assessment misc Wearable devices misc Neurosciences. Biological psychiatry. Neuropsychiatry
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title	Potential benefits of integrating ecological momentary assessment data into mHealth care systems
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title_sort	potential benefits of integrating ecological momentary assessment data into mhealth care systems
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title_auth	Potential benefits of integrating ecological momentary assessment data into mHealth care systems
abstract	Abstract The advancement of wearable/ambulatory technologies has brought a huge change to data collection frameworks in recent decades. Mobile health (mHealth) care platforms, which utilize ambulatory devices to collect naturalistic and often intensively sampled data, produce innovative information of potential clinical relevance. For example, such data can inform clinical study design, recruitment approach, data analysis, and delivery of both “traditional” and novel (e.g., mHealth) interventions. We provide a conceptual overview of how data measured continuously or repeatedly via mobile devices (e.g., smartphone and body sensors) in daily life could be fruitfully used within a mHealth care system. We highlight the potential benefits of integrating ecological momentary assessment (EMA) into mHealth platforms for collecting, processing, and modeling data, and delivering and evaluating novel interventions in everyday life. Although the data obtained from EMA and related approaches may hold great potential benefits for mHealth care system, there are also implementation challenges; we briefly discuss the challenges to integrating EMA into mHealth care system.
abstractGer	Abstract The advancement of wearable/ambulatory technologies has brought a huge change to data collection frameworks in recent decades. Mobile health (mHealth) care platforms, which utilize ambulatory devices to collect naturalistic and often intensively sampled data, produce innovative information of potential clinical relevance. For example, such data can inform clinical study design, recruitment approach, data analysis, and delivery of both “traditional” and novel (e.g., mHealth) interventions. We provide a conceptual overview of how data measured continuously or repeatedly via mobile devices (e.g., smartphone and body sensors) in daily life could be fruitfully used within a mHealth care system. We highlight the potential benefits of integrating ecological momentary assessment (EMA) into mHealth platforms for collecting, processing, and modeling data, and delivering and evaluating novel interventions in everyday life. Although the data obtained from EMA and related approaches may hold great potential benefits for mHealth care system, there are also implementation challenges; we briefly discuss the challenges to integrating EMA into mHealth care system.
abstract_unstemmed	Abstract The advancement of wearable/ambulatory technologies has brought a huge change to data collection frameworks in recent decades. Mobile health (mHealth) care platforms, which utilize ambulatory devices to collect naturalistic and often intensively sampled data, produce innovative information of potential clinical relevance. For example, such data can inform clinical study design, recruitment approach, data analysis, and delivery of both “traditional” and novel (e.g., mHealth) interventions. We provide a conceptual overview of how data measured continuously or repeatedly via mobile devices (e.g., smartphone and body sensors) in daily life could be fruitfully used within a mHealth care system. We highlight the potential benefits of integrating ecological momentary assessment (EMA) into mHealth platforms for collecting, processing, and modeling data, and delivering and evaluating novel interventions in everyday life. Although the data obtained from EMA and related approaches may hold great potential benefits for mHealth care system, there are also implementation challenges; we briefly discuss the challenges to integrating EMA into mHealth care system.
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title_short	Potential benefits of integrating ecological momentary assessment data into mHealth care systems
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