A Perspective Review: State-of-the-Art on m-Health Services
Abstract mHealth has been constantly efficiently leveraging healthcare and management-specific tasks since the last decade. The recent accumulation of smartphones, especially the inclusion of APPs is immensely affecting human livelihood in all aspects. This article investigates the impact of smartph...
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| Autor*in: |
Chettri, Lekhika [verfasserIn] Rai, Rebika [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2024 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: SN Computer Science - Springer Nature Singapore, 2020, 5(2024), 5 vom: 23. Apr. |
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| Übergeordnetes Werk: |
volume:5 ; year:2024 ; number:5 ; day:23 ; month:04 |
| Links: |
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| DOI / URN: |
10.1007/s42979-024-02840-2 |
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| Katalog-ID: |
SPR055623921 |
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| 520 | |a Abstract mHealth has been constantly efficiently leveraging healthcare and management-specific tasks since the last decade. The recent accumulation of smartphones, especially the inclusion of APPs is immensely affecting human livelihood in all aspects. This article investigates the impact of smartphone-based APPs, in medicinal knowledge gathering, diagnosis, and search-related activities in mHealth care. 82 APPs were randomly picked and were further given some unique ID (1–82) to make the retrieval, updating, and referencing procedure. The APP selected were further tabulated based on components such as Ownership: Open source/Proprietary; Implementation agency: Private/Government; cost of Service: paid/free; type of user: Naïve/Expert/Moderate/both Moderate and expert; supported platform: Android/iOS/Windows/Android and iOS/Android, iOS and Windows; Expertise, Disease Diagnosis and Information service. Secondly, different categories were formalized such as Stress Management, Baby monitoring (Ehn et al. in JMIR Mhealth Uhealth 6(2):e34, 2018), Post-natal, Cardiac, Search/Online Booking, m-health/Information, Basic Health Management, and Women's Health. 82 APPs selected were thereby placed under the above categories based on their components identified. Thirdly, the APPs were further classified into two categories based on cost of service: Free/Paid. The paid APP was tabulated based on their ID, Name of the APP, and price. The major reason for doing so was to perform the one-sample T-test based on their price as a factor to calculate the mean, Standard deviation, and Standard Error Mean. The results obtained from this study are promising in terms of new information about APP-based deployments per cost, ownership, user, and developing agency. The surveyed APPs are studied per their applicability (segregated into 17 different dominant characters) and 9 specific classes of diseases including stress management, baby monitor, m-Health, post-natal, cardiac, search/online booking, basic health information, women health, and others. Domain-specific percentage-wise comparison is also performed. One sample T-test is performed for analysis of the cost of paid APPs. A few key challenges and future road maps are also prescribed. APP-based health care seems to propagate the agenda of m-Health in a multitude of forms be it medical knowledge gathering, disease diagnosis, or health management. Medical APPs hold the key to changing the current scenario of healthcare into a smart and effective future. | ||
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10.1007/s42979-024-02840-2 doi (DE-627)SPR055623921 (SPR)s42979-024-02840-2-e DE-627 ger DE-627 rakwb eng Chettri, Lekhika verfasserin aut A Perspective Review: State-of-the-Art on m-Health Services 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract mHealth has been constantly efficiently leveraging healthcare and management-specific tasks since the last decade. The recent accumulation of smartphones, especially the inclusion of APPs is immensely affecting human livelihood in all aspects. This article investigates the impact of smartphone-based APPs, in medicinal knowledge gathering, diagnosis, and search-related activities in mHealth care. 82 APPs were randomly picked and were further given some unique ID (1–82) to make the retrieval, updating, and referencing procedure. The APP selected were further tabulated based on components such as Ownership: Open source/Proprietary; Implementation agency: Private/Government; cost of Service: paid/free; type of user: Naïve/Expert/Moderate/both Moderate and expert; supported platform: Android/iOS/Windows/Android and iOS/Android, iOS and Windows; Expertise, Disease Diagnosis and Information service. Secondly, different categories were formalized such as Stress Management, Baby monitoring (Ehn et al. in JMIR Mhealth Uhealth 6(2):e34, 2018), Post-natal, Cardiac, Search/Online Booking, m-health/Information, Basic Health Management, and Women's Health. 82 APPs selected were thereby placed under the above categories based on their components identified. Thirdly, the APPs were further classified into two categories based on cost of service: Free/Paid. The paid APP was tabulated based on their ID, Name of the APP, and price. The major reason for doing so was to perform the one-sample T-test based on their price as a factor to calculate the mean, Standard deviation, and Standard Error Mean. The results obtained from this study are promising in terms of new information about APP-based deployments per cost, ownership, user, and developing agency. The surveyed APPs are studied per their applicability (segregated into 17 different dominant characters) and 9 specific classes of diseases including stress management, baby monitor, m-Health, post-natal, cardiac, search/online booking, basic health information, women health, and others. Domain-specific percentage-wise comparison is also performed. One sample T-test is performed for analysis of the cost of paid APPs. A few key challenges and future road maps are also prescribed. APP-based health care seems to propagate the agenda of m-Health in a multitude of forms be it medical knowledge gathering, disease diagnosis, or health management. Medical APPs hold the key to changing the current scenario of healthcare into a smart and effective future. m-Health (dpeaa)DE-He213 APPs (dpeaa)DE-He213 Pervasive health care (dpeaa)DE-He213 Rai, Rebika verfasserin aut Enthalten in SN Computer Science Springer Nature Singapore, 2020 5(2024), 5 vom: 23. Apr. (DE-627)1668832976 (DE-600)2977367-2 2661-8907 nnns volume:5 year:2024 number:5 day:23 month:04 https://dx.doi.org/10.1007/s42979-024-02840-2 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 5 2024 5 23 04 |
| spelling |
10.1007/s42979-024-02840-2 doi (DE-627)SPR055623921 (SPR)s42979-024-02840-2-e DE-627 ger DE-627 rakwb eng Chettri, Lekhika verfasserin aut A Perspective Review: State-of-the-Art on m-Health Services 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract mHealth has been constantly efficiently leveraging healthcare and management-specific tasks since the last decade. The recent accumulation of smartphones, especially the inclusion of APPs is immensely affecting human livelihood in all aspects. This article investigates the impact of smartphone-based APPs, in medicinal knowledge gathering, diagnosis, and search-related activities in mHealth care. 82 APPs were randomly picked and were further given some unique ID (1–82) to make the retrieval, updating, and referencing procedure. The APP selected were further tabulated based on components such as Ownership: Open source/Proprietary; Implementation agency: Private/Government; cost of Service: paid/free; type of user: Naïve/Expert/Moderate/both Moderate and expert; supported platform: Android/iOS/Windows/Android and iOS/Android, iOS and Windows; Expertise, Disease Diagnosis and Information service. Secondly, different categories were formalized such as Stress Management, Baby monitoring (Ehn et al. in JMIR Mhealth Uhealth 6(2):e34, 2018), Post-natal, Cardiac, Search/Online Booking, m-health/Information, Basic Health Management, and Women's Health. 82 APPs selected were thereby placed under the above categories based on their components identified. Thirdly, the APPs were further classified into two categories based on cost of service: Free/Paid. The paid APP was tabulated based on their ID, Name of the APP, and price. The major reason for doing so was to perform the one-sample T-test based on their price as a factor to calculate the mean, Standard deviation, and Standard Error Mean. The results obtained from this study are promising in terms of new information about APP-based deployments per cost, ownership, user, and developing agency. The surveyed APPs are studied per their applicability (segregated into 17 different dominant characters) and 9 specific classes of diseases including stress management, baby monitor, m-Health, post-natal, cardiac, search/online booking, basic health information, women health, and others. Domain-specific percentage-wise comparison is also performed. One sample T-test is performed for analysis of the cost of paid APPs. A few key challenges and future road maps are also prescribed. APP-based health care seems to propagate the agenda of m-Health in a multitude of forms be it medical knowledge gathering, disease diagnosis, or health management. Medical APPs hold the key to changing the current scenario of healthcare into a smart and effective future. m-Health (dpeaa)DE-He213 APPs (dpeaa)DE-He213 Pervasive health care (dpeaa)DE-He213 Rai, Rebika verfasserin aut Enthalten in SN Computer Science Springer Nature Singapore, 2020 5(2024), 5 vom: 23. Apr. (DE-627)1668832976 (DE-600)2977367-2 2661-8907 nnns volume:5 year:2024 number:5 day:23 month:04 https://dx.doi.org/10.1007/s42979-024-02840-2 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 5 2024 5 23 04 |
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10.1007/s42979-024-02840-2 doi (DE-627)SPR055623921 (SPR)s42979-024-02840-2-e DE-627 ger DE-627 rakwb eng Chettri, Lekhika verfasserin aut A Perspective Review: State-of-the-Art on m-Health Services 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract mHealth has been constantly efficiently leveraging healthcare and management-specific tasks since the last decade. The recent accumulation of smartphones, especially the inclusion of APPs is immensely affecting human livelihood in all aspects. This article investigates the impact of smartphone-based APPs, in medicinal knowledge gathering, diagnosis, and search-related activities in mHealth care. 82 APPs were randomly picked and were further given some unique ID (1–82) to make the retrieval, updating, and referencing procedure. The APP selected were further tabulated based on components such as Ownership: Open source/Proprietary; Implementation agency: Private/Government; cost of Service: paid/free; type of user: Naïve/Expert/Moderate/both Moderate and expert; supported platform: Android/iOS/Windows/Android and iOS/Android, iOS and Windows; Expertise, Disease Diagnosis and Information service. Secondly, different categories were formalized such as Stress Management, Baby monitoring (Ehn et al. in JMIR Mhealth Uhealth 6(2):e34, 2018), Post-natal, Cardiac, Search/Online Booking, m-health/Information, Basic Health Management, and Women's Health. 82 APPs selected were thereby placed under the above categories based on their components identified. Thirdly, the APPs were further classified into two categories based on cost of service: Free/Paid. The paid APP was tabulated based on their ID, Name of the APP, and price. The major reason for doing so was to perform the one-sample T-test based on their price as a factor to calculate the mean, Standard deviation, and Standard Error Mean. The results obtained from this study are promising in terms of new information about APP-based deployments per cost, ownership, user, and developing agency. The surveyed APPs are studied per their applicability (segregated into 17 different dominant characters) and 9 specific classes of diseases including stress management, baby monitor, m-Health, post-natal, cardiac, search/online booking, basic health information, women health, and others. Domain-specific percentage-wise comparison is also performed. One sample T-test is performed for analysis of the cost of paid APPs. A few key challenges and future road maps are also prescribed. APP-based health care seems to propagate the agenda of m-Health in a multitude of forms be it medical knowledge gathering, disease diagnosis, or health management. Medical APPs hold the key to changing the current scenario of healthcare into a smart and effective future. m-Health (dpeaa)DE-He213 APPs (dpeaa)DE-He213 Pervasive health care (dpeaa)DE-He213 Rai, Rebika verfasserin aut Enthalten in SN Computer Science Springer Nature Singapore, 2020 5(2024), 5 vom: 23. Apr. (DE-627)1668832976 (DE-600)2977367-2 2661-8907 nnns volume:5 year:2024 number:5 day:23 month:04 https://dx.doi.org/10.1007/s42979-024-02840-2 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 5 2024 5 23 04 |
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10.1007/s42979-024-02840-2 doi (DE-627)SPR055623921 (SPR)s42979-024-02840-2-e DE-627 ger DE-627 rakwb eng Chettri, Lekhika verfasserin aut A Perspective Review: State-of-the-Art on m-Health Services 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract mHealth has been constantly efficiently leveraging healthcare and management-specific tasks since the last decade. The recent accumulation of smartphones, especially the inclusion of APPs is immensely affecting human livelihood in all aspects. This article investigates the impact of smartphone-based APPs, in medicinal knowledge gathering, diagnosis, and search-related activities in mHealth care. 82 APPs were randomly picked and were further given some unique ID (1–82) to make the retrieval, updating, and referencing procedure. The APP selected were further tabulated based on components such as Ownership: Open source/Proprietary; Implementation agency: Private/Government; cost of Service: paid/free; type of user: Naïve/Expert/Moderate/both Moderate and expert; supported platform: Android/iOS/Windows/Android and iOS/Android, iOS and Windows; Expertise, Disease Diagnosis and Information service. Secondly, different categories were formalized such as Stress Management, Baby monitoring (Ehn et al. in JMIR Mhealth Uhealth 6(2):e34, 2018), Post-natal, Cardiac, Search/Online Booking, m-health/Information, Basic Health Management, and Women's Health. 82 APPs selected were thereby placed under the above categories based on their components identified. Thirdly, the APPs were further classified into two categories based on cost of service: Free/Paid. The paid APP was tabulated based on their ID, Name of the APP, and price. The major reason for doing so was to perform the one-sample T-test based on their price as a factor to calculate the mean, Standard deviation, and Standard Error Mean. The results obtained from this study are promising in terms of new information about APP-based deployments per cost, ownership, user, and developing agency. The surveyed APPs are studied per their applicability (segregated into 17 different dominant characters) and 9 specific classes of diseases including stress management, baby monitor, m-Health, post-natal, cardiac, search/online booking, basic health information, women health, and others. Domain-specific percentage-wise comparison is also performed. One sample T-test is performed for analysis of the cost of paid APPs. A few key challenges and future road maps are also prescribed. APP-based health care seems to propagate the agenda of m-Health in a multitude of forms be it medical knowledge gathering, disease diagnosis, or health management. Medical APPs hold the key to changing the current scenario of healthcare into a smart and effective future. m-Health (dpeaa)DE-He213 APPs (dpeaa)DE-He213 Pervasive health care (dpeaa)DE-He213 Rai, Rebika verfasserin aut Enthalten in SN Computer Science Springer Nature Singapore, 2020 5(2024), 5 vom: 23. Apr. 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10.1007/s42979-024-02840-2 doi (DE-627)SPR055623921 (SPR)s42979-024-02840-2-e DE-627 ger DE-627 rakwb eng Chettri, Lekhika verfasserin aut A Perspective Review: State-of-the-Art on m-Health Services 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract mHealth has been constantly efficiently leveraging healthcare and management-specific tasks since the last decade. The recent accumulation of smartphones, especially the inclusion of APPs is immensely affecting human livelihood in all aspects. This article investigates the impact of smartphone-based APPs, in medicinal knowledge gathering, diagnosis, and search-related activities in mHealth care. 82 APPs were randomly picked and were further given some unique ID (1–82) to make the retrieval, updating, and referencing procedure. The APP selected were further tabulated based on components such as Ownership: Open source/Proprietary; Implementation agency: Private/Government; cost of Service: paid/free; type of user: Naïve/Expert/Moderate/both Moderate and expert; supported platform: Android/iOS/Windows/Android and iOS/Android, iOS and Windows; Expertise, Disease Diagnosis and Information service. Secondly, different categories were formalized such as Stress Management, Baby monitoring (Ehn et al. in JMIR Mhealth Uhealth 6(2):e34, 2018), Post-natal, Cardiac, Search/Online Booking, m-health/Information, Basic Health Management, and Women's Health. 82 APPs selected were thereby placed under the above categories based on their components identified. Thirdly, the APPs were further classified into two categories based on cost of service: Free/Paid. The paid APP was tabulated based on their ID, Name of the APP, and price. The major reason for doing so was to perform the one-sample T-test based on their price as a factor to calculate the mean, Standard deviation, and Standard Error Mean. The results obtained from this study are promising in terms of new information about APP-based deployments per cost, ownership, user, and developing agency. The surveyed APPs are studied per their applicability (segregated into 17 different dominant characters) and 9 specific classes of diseases including stress management, baby monitor, m-Health, post-natal, cardiac, search/online booking, basic health information, women health, and others. Domain-specific percentage-wise comparison is also performed. One sample T-test is performed for analysis of the cost of paid APPs. A few key challenges and future road maps are also prescribed. APP-based health care seems to propagate the agenda of m-Health in a multitude of forms be it medical knowledge gathering, disease diagnosis, or health management. Medical APPs hold the key to changing the current scenario of healthcare into a smart and effective future. m-Health (dpeaa)DE-He213 APPs (dpeaa)DE-He213 Pervasive health care (dpeaa)DE-He213 Rai, Rebika verfasserin aut Enthalten in SN Computer Science Springer Nature Singapore, 2020 5(2024), 5 vom: 23. Apr. (DE-627)1668832976 (DE-600)2977367-2 2661-8907 nnns volume:5 year:2024 number:5 day:23 month:04 https://dx.doi.org/10.1007/s42979-024-02840-2 X:SPRINGER Resolving-System lizenzpflichtig Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 5 2024 5 23 04 |
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A Perspective Review: State-of-the-Art on m-Health Services |
| abstract |
Abstract mHealth has been constantly efficiently leveraging healthcare and management-specific tasks since the last decade. The recent accumulation of smartphones, especially the inclusion of APPs is immensely affecting human livelihood in all aspects. This article investigates the impact of smartphone-based APPs, in medicinal knowledge gathering, diagnosis, and search-related activities in mHealth care. 82 APPs were randomly picked and were further given some unique ID (1–82) to make the retrieval, updating, and referencing procedure. The APP selected were further tabulated based on components such as Ownership: Open source/Proprietary; Implementation agency: Private/Government; cost of Service: paid/free; type of user: Naïve/Expert/Moderate/both Moderate and expert; supported platform: Android/iOS/Windows/Android and iOS/Android, iOS and Windows; Expertise, Disease Diagnosis and Information service. Secondly, different categories were formalized such as Stress Management, Baby monitoring (Ehn et al. in JMIR Mhealth Uhealth 6(2):e34, 2018), Post-natal, Cardiac, Search/Online Booking, m-health/Information, Basic Health Management, and Women's Health. 82 APPs selected were thereby placed under the above categories based on their components identified. Thirdly, the APPs were further classified into two categories based on cost of service: Free/Paid. The paid APP was tabulated based on their ID, Name of the APP, and price. The major reason for doing so was to perform the one-sample T-test based on their price as a factor to calculate the mean, Standard deviation, and Standard Error Mean. The results obtained from this study are promising in terms of new information about APP-based deployments per cost, ownership, user, and developing agency. The surveyed APPs are studied per their applicability (segregated into 17 different dominant characters) and 9 specific classes of diseases including stress management, baby monitor, m-Health, post-natal, cardiac, search/online booking, basic health information, women health, and others. Domain-specific percentage-wise comparison is also performed. One sample T-test is performed for analysis of the cost of paid APPs. A few key challenges and future road maps are also prescribed. APP-based health care seems to propagate the agenda of m-Health in a multitude of forms be it medical knowledge gathering, disease diagnosis, or health management. Medical APPs hold the key to changing the current scenario of healthcare into a smart and effective future. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstractGer |
Abstract mHealth has been constantly efficiently leveraging healthcare and management-specific tasks since the last decade. The recent accumulation of smartphones, especially the inclusion of APPs is immensely affecting human livelihood in all aspects. This article investigates the impact of smartphone-based APPs, in medicinal knowledge gathering, diagnosis, and search-related activities in mHealth care. 82 APPs were randomly picked and were further given some unique ID (1–82) to make the retrieval, updating, and referencing procedure. The APP selected were further tabulated based on components such as Ownership: Open source/Proprietary; Implementation agency: Private/Government; cost of Service: paid/free; type of user: Naïve/Expert/Moderate/both Moderate and expert; supported platform: Android/iOS/Windows/Android and iOS/Android, iOS and Windows; Expertise, Disease Diagnosis and Information service. Secondly, different categories were formalized such as Stress Management, Baby monitoring (Ehn et al. in JMIR Mhealth Uhealth 6(2):e34, 2018), Post-natal, Cardiac, Search/Online Booking, m-health/Information, Basic Health Management, and Women's Health. 82 APPs selected were thereby placed under the above categories based on their components identified. Thirdly, the APPs were further classified into two categories based on cost of service: Free/Paid. The paid APP was tabulated based on their ID, Name of the APP, and price. The major reason for doing so was to perform the one-sample T-test based on their price as a factor to calculate the mean, Standard deviation, and Standard Error Mean. The results obtained from this study are promising in terms of new information about APP-based deployments per cost, ownership, user, and developing agency. The surveyed APPs are studied per their applicability (segregated into 17 different dominant characters) and 9 specific classes of diseases including stress management, baby monitor, m-Health, post-natal, cardiac, search/online booking, basic health information, women health, and others. Domain-specific percentage-wise comparison is also performed. One sample T-test is performed for analysis of the cost of paid APPs. A few key challenges and future road maps are also prescribed. APP-based health care seems to propagate the agenda of m-Health in a multitude of forms be it medical knowledge gathering, disease diagnosis, or health management. Medical APPs hold the key to changing the current scenario of healthcare into a smart and effective future. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract mHealth has been constantly efficiently leveraging healthcare and management-specific tasks since the last decade. The recent accumulation of smartphones, especially the inclusion of APPs is immensely affecting human livelihood in all aspects. This article investigates the impact of smartphone-based APPs, in medicinal knowledge gathering, diagnosis, and search-related activities in mHealth care. 82 APPs were randomly picked and were further given some unique ID (1–82) to make the retrieval, updating, and referencing procedure. The APP selected were further tabulated based on components such as Ownership: Open source/Proprietary; Implementation agency: Private/Government; cost of Service: paid/free; type of user: Naïve/Expert/Moderate/both Moderate and expert; supported platform: Android/iOS/Windows/Android and iOS/Android, iOS and Windows; Expertise, Disease Diagnosis and Information service. Secondly, different categories were formalized such as Stress Management, Baby monitoring (Ehn et al. in JMIR Mhealth Uhealth 6(2):e34, 2018), Post-natal, Cardiac, Search/Online Booking, m-health/Information, Basic Health Management, and Women's Health. 82 APPs selected were thereby placed under the above categories based on their components identified. Thirdly, the APPs were further classified into two categories based on cost of service: Free/Paid. The paid APP was tabulated based on their ID, Name of the APP, and price. The major reason for doing so was to perform the one-sample T-test based on their price as a factor to calculate the mean, Standard deviation, and Standard Error Mean. The results obtained from this study are promising in terms of new information about APP-based deployments per cost, ownership, user, and developing agency. The surveyed APPs are studied per their applicability (segregated into 17 different dominant characters) and 9 specific classes of diseases including stress management, baby monitor, m-Health, post-natal, cardiac, search/online booking, basic health information, women health, and others. Domain-specific percentage-wise comparison is also performed. One sample T-test is performed for analysis of the cost of paid APPs. A few key challenges and future road maps are also prescribed. APP-based health care seems to propagate the agenda of m-Health in a multitude of forms be it medical knowledge gathering, disease diagnosis, or health management. Medical APPs hold the key to changing the current scenario of healthcare into a smart and effective future. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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A Perspective Review: State-of-the-Art on m-Health Services |
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Rai, Rebika |
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|
| score |
7.399534 |