Mobile Applications for Caregivers of Individuals with Chronic Conditions and/or Diseases: Quantitative Content Analysis

Lorca-Cabrera, Jael; Martí-Arques, Rut; Albacar-Riobóo, Núria; Raigal-Aran, Laia; Roldán‐Merino, Juan; Ferré‐Grau, Carmen

doi:10.1016/j.ijmedinf.2020.104310

Cited by 25 publications

(14 citation statements)

References 24 publications

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“…Lastly, our findings highlight the potential that mHealth tools have for reducing chronic disease disparities in disease management and outcomes beyond the COVID-19 pandemic. Although there has been a proliferation of mHealth tools for people with chronic health conditions, the acceptability and long-term use of mHealth tools have varied considerably across people with different chronic conditions [101,102]. Variability in mHealth tool use across people with chronic health conditions may be related to the quality of both the content and functionality of mHealth tools, as well as user-related preferences [103][104][105][106][107].…”

Section: Principal Resultsmentioning

confidence: 99%

Attitudes Toward Using COVID-19 mHealth Tools Among Adults With Chronic Health Conditions: Secondary Data Analysis of the COVID-19 Impact Survey (Preprint)

Camacho-Rivera¹,

Islam²,

Rivera³

et al. 2020

Preprint

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BACKGROUND Adults with chronic conditions are disproportionately burdened by COVID-19 morbidity and mortality. Although COVID-19 mobile health (mHealth) apps have emerged, research on attitudes toward using COVID-19 mHealth tools among those with chronic conditions is scarce. OBJECTIVE This study aimed to examine attitudes toward COVID-19, identify determinants of COVID-19 mHealth tool use across demographic and health-related characteristics, and evaluate associations between chronic health conditions and attitudes toward using COVID-19 mHealth tools (eg, mHealth or web-based methods for tracking COVID-19 exposures, symptoms, and recommendations). METHODS We used nationally representative data from the COVID-19 Impact Survey collected from April to June 2020 (n=10,760). Primary exposure was a history of chronic conditions, which were defined as self-reported diagnoses of cardiometabolic, respiratory, immune-related, and mental health conditions and overweight/obesity. Primary outcomes were attitudes toward COVID-19 mHealth tools, including the likelihood of using (1) a mobile phone app to track COVID-19 symptoms and receive recommendations; (2) a website to track COVID-19 symptoms, track location, and receive recommendations; and (3) an app using location data to track potential COVID-19 exposure. Outcome response options for COVID-19 mHealth tool use were extremely/very likely, moderately likely, or not too likely/not likely at all. Multinomial logistic regression was used to compare the likelihood of COVID-19 mHealth tool use between people with different chronic health conditions, with not too likely/not likely at all responses used as the reference category for each outcome. We evaluated the determinants of each COVID-19 mHealth intervention using Poisson regression. RESULTS Of the 10,760 respondents, 21.8% of respondents were extremely/very likely to use a mobile phone app or a website to track their COVID-19 symptoms and receive recommendations. Additionally, 24.1% of respondents were extremely/very likely to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19. After adjusting for age, race/ethnicity, sex, socioeconomic status, and residence, adults with mental health conditions were the most likely to report being extremely/very or moderately likely to use each mHealth intervention compared to those without such conditions. Adults with respiratory-related chronic diseases were extremely/very (conditional odds ratio 1.16, 95% CI 1.00-1.35) and moderately likely (conditional odds ratio 1.23, 95% CI 1.04-1.45) to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19. CONCLUSIONS Our study demonstrates that attitudes toward using COVID-19 mHealth tools vary widely across modalities (eg, web-based method vs app) and chronic health conditions. These findings may inform the adoption of long-term engagement with COVID-19 apps, which is crucial for determining their potential in reducing disparities in COVID-19 morbidity and mortality among individuals with chronic health conditions.

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Section: Principal Resultsmentioning

confidence: 99%

Attitudes Toward Using COVID-19 mHealth Tools Among Adults With Chronic Health Conditions: Secondary Data Analysis of the COVID-19 Impact Survey (Preprint)

Camacho-Rivera¹,

Islam²,

Rivera³

et al. 2020

Preprint

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“…While this study is not the first to examine the available health app-landscape, there exist only a limited amount of literature describing systematic searches of MHapps (e.g., [ 61 , 62 , 63 , 64 ]) and the empirical evidence base surrounding them. Other reviews of MHapps were focused on other country contexts (e.g., China [ 65 ], Arabic speakers [ 66 ]), as well as different, more general, or more specific disease areas or patient populations (e.g., chronic conditions in general [ 67 , 68 ], peripartum mood disorders [ 69 ], eating disorders [ 70 ], older adults [ 71 ], attention-deficit hyperactivity disorder [ 72 ]).…”

Section: Discussionmentioning

confidence: 99%

Mobile Applications in Mood Disorders and Mental Health: Systematic Search in Apple App Store and Google Play Store and Review of the Literature

Eis¹,

Solà-Morales²,

Duarte-Díaz

et al. 2022

IJERPH

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Objectives: The main objective of this work was to explore and characterize the current landscape of mobile applications available to treat mood disorders such as depression, bipolar disorder, and dysthymia. Methods: We developed a tool that makes both the Apple App Store and the Google Play Store searchable using keywords and that facilitates the extraction of basic app information of the search results. All app results were filtered using various inclusion and exclusion criteria. We characterized all resultant applications according to their technical details. Furthermore, we searched for scientific publications on each app’s website and PubMed, to understand whether any of the apps were supported by any type of scientific evidence on their acceptability, validation, use, effectiveness, etc. Results: Thirty apps were identified that fit the inclusion and exclusion criteria. The literature search yielded 27 publications related to the apps. However, these did not exclusively concern mood disorders. 6 were randomized studies and the rest included a protocol, pilot-, feasibility, case-, or qualitative studies, among others. The majority of studies were conducted on relatively small scales and 9 of the 27 studies did not explicitly study the effects of mobile application use on mental wellbeing. Conclusion: While there exists a wealth of mobile applications aimed at the treatment of mental health disorders, including mood disorders, this study showed that only a handful of these are backed by robust scientific evidence. This result uncovers a need for further clinically oriented and systematic validation and testing of such apps.

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“…As MindfulGarden is a novel device, there are not many studies in the literature to compare the findings with, still, based on its mechanism of action, it might be categorized as an 'individualized sensory stimulation' device. Other devices and approaches in the sensory stimulation category used with PwD include Snoezelen which is based on the 'Model of Imbalance in Sensoristasis' (MIS) (Sánchez, et al, 2013;Lorusso & Bosch, 2018;Maseda et al, 2018;Prins, et al, 2020;) and Project Soothe (with the online gallery added to an app-called CogniCare) (Wilson, et al, 2018;Lorca-Cabrera et al, 2020). Using the MIS model, Kovach (2000) postulates that agitated behaviours may be initiated or escalated when there is an imbalance between sensory-stimulating and sensory-calming activity -a state commonly occurring in institutionalized PwD.…”

Section: Discussionmentioning

confidence: 99%

Feasibility study of a digital screen-based calming device (MindfulGarden) for bathing-related agitation among LTC residents with dementia

Gutman¹,

Karbakhsh²,

Vashisht³

et al. 2021

Gerontechnology

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Background: Behavioural and psychological symptoms of dementia (BPSD) are common and disturbing and can deter or disrupt the care process. Bathing is associated with the highest frequency of BPSD, triggering a fear response in dementia patients. As part of a larger feasibility/pilot study, this investigation explored whether exposure to MindfulGarden (MG), a digital screen-based calming device, can minimize BPSD during bathing -an activity well-documented to be problematic for both residents and staff. Objective: To determine outcome trends of exposure to MG on number and type of BPSD exhibited by residents with dementia during bathing and on staff time to undress, shower and re-dress them. Method: 8 long-term care home residents (5F, 3M) mean age 86.00±8.16, diagnosed with dementia and reported by care staff as exhibiting BPSD were observed while being showered in their en-suite bathroom. On Days 1 and 2 staff followed the usual bathing procedure; on Day 3 exposure to MG was added. A 26-item checklist developed in a previous study, based on the Cohen-Mansfield Agitation Inventory and the work of Gutman, Mac-Fadgen and Killam, was used to record type and frequency of BPSD, time of staff entry and exit from the resident's room was recorded, and on Day 3 staff rated MG exposure as having a positive, neutral or negative effect. Results: Days 1 -2 yielded highly similar results -an average of 4 BPSD per resident and an average bathing time of 13-14 minutes, with the most common BPSD on both days being physical resistance, verbal resistance, screaming, complaining, and strange noises. Subsequent to exposure to MG (Day 3) trends were observed towards reduction in number of BPSD and bathing duration. Conclusion: MG shows some promise in calming residents, reducing resistance to care, and allowing bathing to proceed more quickly.

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Mobile Applications for Caregivers of Individuals with Chronic Conditions and/or Diseases: Quantitative Content Analysis

Cited by 25 publications

References 24 publications

Attitudes Toward Using COVID-19 mHealth Tools Among Adults With Chronic Health Conditions: Secondary Data Analysis of the COVID-19 Impact Survey (Preprint)

Attitudes Toward Using COVID-19 mHealth Tools Among Adults With Chronic Health Conditions: Secondary Data Analysis of the COVID-19 Impact Survey (Preprint)

Mobile Applications in Mood Disorders and Mental Health: Systematic Search in Apple App Store and Google Play Store and Review of the Literature

Feasibility study of a digital screen-based calming device (MindfulGarden) for bathing-related agitation among LTC residents with dementia

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