IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i7p1197-d219630.html
   My bibliography  Save this article

Considerations for Designing Context-Aware Mobile Apps for Mental Health Interventions

Author

Listed:
  • Ignacio Miralles

    (Geospatial Technologies Research Group (GEOTEC), Universitat Jaume I, Av. Vicente Sos Baynat s/n, 12071 Castellón de la Plana, Spain
    These authors contributed equally to this work.)

  • Carlos Granell

    (Geospatial Technologies Research Group (GEOTEC), Universitat Jaume I, Av. Vicente Sos Baynat s/n, 12071 Castellón de la Plana, Spain
    These authors contributed equally to this work.)

Abstract

This work identifies major areas of knowledge and proposes a set of relevant dimensions by area that must be taken into account in the design and delivery of context-aware mobile applications for mental health interventions. We argue that much of the related research has focused only on a few dimensions, paying little or no attention to others and, most importantly, to potential relationships between them. Our belief is that the improvement of the effectiveness of mobile interventions to support mental health necessarily implies that developers and therapists comprehensively consider the interaction between the proposed dimensions. Taking as a starting point the three areas of knowledge (Technology, Context, and Mental Health), we re-examine each area to identify relevant dimensions, discuss the relationships between them and finally draw a series of considerations. The resulting considerations can help therapists and developers to devise, design, and generate custom mobile applications in a way that increases the motivation and engagement of patients and, therefore, the effectiveness of psychological treatments.

Suggested Citation

  • Ignacio Miralles & Carlos Granell, 2019. "Considerations for Designing Context-Aware Mobile Apps for Mental Health Interventions," IJERPH, MDPI, vol. 16(7), pages 1-21, April.
  • Handle: RePEc:gam:jijerp:v:16:y:2019:i:7:p:1197-:d:219630
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/7/1197/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/16/7/1197/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    2. Nathan Wilkinson & Rebecca P. Ang & Dion H. Goh, 2008. "Online Video Game Therapy for Mental Health Concerns: A Review," International Journal of Social Psychiatry, , vol. 54(4), pages 370-382, July.
    3. Ruoyu Wang & Desheng Xue & Ye Liu & Penghua Liu & Hongsheng Chen, 2018. "The Relationship between Air Pollution and Depression in China: Is Neighbourhood Social Capital Protective?," IJERPH, MDPI, vol. 15(6), pages 1-13, June.
    4. Jing Ma & Chunjiang Li & Mei-Po Kwan & Yanwei Chai, 2018. "A Multilevel Analysis of Perceived Noise Pollution, Geographic Contexts and Mental Health in Beijing," IJERPH, MDPI, vol. 15(7), pages 1-18, July.
    5. Giulia Melis & Elena Gelormino & Giulia Marra & Elisa Ferracin & Giuseppe Costa, 2015. "The Effects of the Urban Built Environment on Mental Health: A Cohort Study in a Large Northern Italian City," IJERPH, MDPI, vol. 12(11), pages 1-18, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zihan Kan & Mei-Po Kwan & Mee Kam Ng & Hendrik Tieben, 2022. "The Impacts of Housing Characteristics and Built-Environment Features on Mental Health," IJERPH, MDPI, vol. 19(9), pages 1-19, April.
    2. Rongrong Zhang & Song Liu & Ming Li & Xiong He & Chunshan Zhou, 2021. "The Effect of High-Density Built Environments on Elderly Individuals’ Physical Health: A Cross-Sectional Study in Guangzhou, China," IJERPH, MDPI, vol. 18(19), pages 1-22, September.
    3. Sun, Bindong & Liu, Jiahang & Yin, Chun & Cao, Jason, 2022. "Residential and workplace neighborhood environments and life satisfaction: Exploring chain-mediation effects of activity and place satisfaction," Journal of Transport Geography, Elsevier, vol. 104(C).
    4. Abu Yousuf Md Abdullah & Jane Law & Zahid A. Butt & Christopher M. Perlman, 2021. "Understanding the Differential Impact of Vegetation Measures on Modeling the Association between Vegetation and Psychotic and Non-Psychotic Disorders in Toronto, Canada," IJERPH, MDPI, vol. 18(9), pages 1-25, April.
    5. Yinhua Tao & Jie Yang & Yanwei Chai, 2019. "The Anatomy of Health-Supportive Neighborhoods: A Multilevel Analysis of Built Environment, Perceived Disorder, Social Interaction and Mental Health in Beijing," IJERPH, MDPI, vol. 17(1), pages 1-19, December.
    6. Mehzabin Tuli, Farzana & Mitra, Suman & Crews, Mariah B., 2021. "Factors influencing the usage of shared E-scooters in Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 164-185.
    7. John Stanley & Janet Stanley, 2023. "Improving Appraisal Methodology for Land Use Transport Measures to Reduce Risk of Social Exclusion," Sustainability, MDPI, vol. 15(15), pages 1-18, August.
    8. Marie Geraldine Herrmann-Lunecke & Cristhian Figueroa-Martínez & Francisca Parra Huerta & Rodrigo Mora, 2022. "The Disabling City: Older Persons Walking in Central Neighbourhoods of Santiago de Chile," Sustainability, MDPI, vol. 14(17), pages 1-19, September.
    9. Li, Jingjing & Kim, Changjoo & Sang, Sunhee, 2018. "Exploring impacts of land use characteristics in residential neighborhood and activity space on non-work travel behaviors," Journal of Transport Geography, Elsevier, vol. 70(C), pages 141-147.
    10. Ding, Chuan & Wang, Donggen & Liu, Chao & Zhang, Yi & Yang, Jiawen, 2017. "Exploring the influence of built environment on travel mode choice considering the mediating effects of car ownership and travel distance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 65-80.
    11. Hyun Jin Lee & Dong Kun Lee, 2019. "Do Sociodemographic Factors and Urban Green Space Affect Mental Health Outcomes Among the Urban Elderly Population?," IJERPH, MDPI, vol. 16(5), pages 1-13, March.
    12. Van Acker, Veronique & Ho, Loan & Stevens, Larissa & Mulley, Corinne, 2020. "Quantifying the effects of childhood and previous residential experiences on the use of public transport," Journal of Transport Geography, Elsevier, vol. 86(C).
    13. Ding, Yu & Lu, Huapu, 2016. "Activity participation as a mediating variable to analyze the effect of land use on travel behavior: A structural equation modeling approach," Journal of Transport Geography, Elsevier, vol. 52(C), pages 23-28.
    14. Singleton, Patrick A. & Park, Keunhyun & Lee, Doo Hong, 2021. "Varying influences of the built environment on daily and hourly pedestrian crossing volumes at signalized intersections estimated from traffic signal controller event data," Journal of Transport Geography, Elsevier, vol. 93(C).
    15. Toşa, Cristian & Sato, Hitomi & Morikawa, Takayuki & Miwa, Tomio, 2018. "Commuting behavior in emerging urban areas: Findings of a revealed-preferences and stated-intentions survey in Cluj-Napoca, Romania," Journal of Transport Geography, Elsevier, vol. 68(C), pages 78-93.
    16. Liu, Yan & Wang, Siqin & Xie, Bin, 2019. "Evaluating the effects of public transport fare policy change together with built and non-built environment features on ridership: The case in South East Queensland, Australia," Transport Policy, Elsevier, vol. 76(C), pages 78-89.
    17. Regine Gerike & Caroline Koszowski & Bettina Schröter & Ralph Buehler & Paul Schepers & Johannes Weber & Rico Wittwer & Peter Jones, 2021. "Built Environment Determinants of Pedestrian Activities and Their Consideration in Urban Street Design," Sustainability, MDPI, vol. 13(16), pages 1-21, August.
    18. Chetan Doddamani & M. Manoj, 2023. "Analysis of the influences of built environment measures on household car and motorcycle ownership decisions in Hubli-Dharwad cities," Transportation, Springer, vol. 50(1), pages 205-243, February.
    19. Pan Zhang & Zhiguo Wang, 2019. "PM 2.5 Concentrations and Subjective Well-Being: Longitudinal Evidence from Aggregated Panel Data from Chinese Provinces," IJERPH, MDPI, vol. 16(7), pages 1-13, March.
    20. Jie Gao & Dick Ettema & Marco Helbich & Carlijn B. M. Kamphuis, 2019. "Travel mode attitudes, urban context, and demographics: do they interact differently for bicycle commuting and cycling for other purposes?," Transportation, Springer, vol. 46(6), pages 2441-2463, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:16:y:2019:i:7:p:1197-:d:219630. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.