A systematic literature review on mHealth related research during the COVID-19 outbreak

Alam, Mohammad Zahedul; Proteek, S.M.; Hoque, Md Imranul

doi:10.1108/he-08-2022-0067

Cited by 12 publications

(6 citation statements)

References 26 publications

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“…The ever-increasing prevalence of mental health disorders is subsequently resulting in an ever-increasing burden on mental health services globally (WHO, 2022b; Bower et al , 2023). Due to need outweighing capacity, and spurred on in light of the COVID-19 pandemic, a plethora of digital interventional resources have been designed, and implemented, to alleviate the burden upon mental health services and increase access to support for those in need (Adans-Dester et al , 2020; Cao et al , 2022; Alam et al , 2023; Lu et al , 2023). A variety of interventions have proven efficacious, such as mHealth apps (Kruse et al , 2022; Denecke et al , 2022; Dufoe, 2023), online support groups (Bauman and Rivers, 2023; Sharma et al , 2023), symptom checkers (Wallace et al , 2022; Pairon et al , 2023) and online talking therapies (Khan et al , 2022) to name but a few.…”

Section: Introductionmentioning

confidence: 99%

Digital altruism: the motivators for, effects of and support received when moderating mental health online

Rathbone,

Clarry,

Prescott

et al. 2024

MHDT

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Purpose The ever increasing prevalence of mental health disorders is subsequently resulting in an ever increasing burden on mental health services globally. Due to need outweighing capacity, many turn to, or are signposted to, online resources. Online mental health chatrooms are chat-based services that users can frequent to discuss their mental health, often with individuals experiencing similar issues. Most of these are moderated by volunteers. The purpose of this study was to explore the motivations for moderating, the positive and negative effects of the role and to identifying current and required pathways of support. Design/methodology/approach This study used an online questionnaire design, disseminated via the online mental health community, 18percent. An open ended interview schedule was disseminated to eight volunteer moderators. Qualitative data was analysed using NVivo software and reflexive thematic analysis. Findings Moderators were motivated to engage in this role due to past experiences and to help others. The positive effects of moderating were engaging in digital altruism and improving one’s personal mental health. The negative effects were personal triggers and role specific issues such as harassment and being unable to help people in crisis situations. For further support, moderators would benefit from refresher training sessions and further professional training in which they can proactively help when a user is experiencing suicidal ideation/behaviours. Originality/value The research highlighted the motivations for, positive and negative effects of and the current and further pathways of support required by volunteer moderators and proffers recommendations within the discussion.

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Section: Introductionmentioning

confidence: 99%

Digital altruism: the motivators for, effects of and support received when moderating mental health online

Rathbone,

Clarry,

Prescott

et al. 2024

MHDT

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“…More hospitals are looking at the advantages of mobile health (mHealth) due to rising healthcare expenses and the desire for better care at home. They are seeking better communication between doctors and patients, especially those in more remote locations, as well as better utilisation of medical facilities like wireless data transmission, short message service and ease of connection with regular healthcare providers (Alam et al, 2023). Better communication enhances services that prevent patients from contracting serious forms of disease.…”

Section: Introductionmentioning

confidence: 99%

Analysis of barriers of mHealth adoption in the context of sustainable operational practices in health care supply chains

Swain

Muduli

Luthra³

2023

IJIEOM

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PurposeThe goal of this research is to analyse the obstacles to the implementation of mobile health (mHealth) in India and to gain an understanding of the contextual inter-relationships that exist amongst those obstacles.Design/methodology/approachPotential barriers and their interrelationships in their respective contexts have been uncovered. Using MICMAC analysis, the categorization of these barriers was done based on their degree of reliance and driving power (DP). Furthermore, an interpretive structural modeling (ISM) framework for the barriers to mHealth activities in India has been proposed.FindingsThe study explores a total of 15 factors that reduce the efficiency of mHealth adoption in India. The findings of the Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) investigation show that the economic situation of the government, concerns regarding the safety of intellectual technologies and privacy issues are the primary obstacles because of the significant driving power they have in mHealth applications.Practical implicationsPromoters of mHealth practices may be able to make better plans if they understand the social barriers and how they affect each other; this leads to easier adoption of these practices. The findings of this study might be helpful for governments of developing nations to produce standards relating to the deployment of mHealth; this will increase the efficiency with which it is adopted.Originality/valueAt this time, there is no comprehensive analysis of the factors that influence the adoption of mobile health care with social cognitive theory in developing nations like India. In addition, there is a lack of research in investigating how each of these elements affects the success of mHealth activities and how the others interact with them. Because developed nations learnt the value of mHealth practices during the recent pandemic, this study, by investigating the obstacles to the adoption of mHealth and their inter-relationships, makes an important addition to both theory and practice.

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“…A systematic review has shown that mHealth has been successfully deployed to promote health services during the COVID-19 pandemic ( 4 ). Another systematic review identified mHealth as a very suitable alternative to patient-physician contacts during the COVID-19 pandemic ( 31 ).…”

Section: Introductionmentioning

confidence: 99%

The intention to use mHealth applications among Dutch older adults prior and during the COVID pandemic

Elburg

Klundert

Nieboer

et al. 2023

Front. Public Health

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BackgroundMobile health (mHealth) applications are widely valued for their potential to increase self-management among older adults and reduce their healthcare demands. However, the intention to use mHealth of Dutch older adults before the COVID-19 pandemic was modest. Healthcare access was considerably reduced during the pandemic and mHealth services substituted for in person health services. As older adults utilize health services more frequently and have been particularly vulnerable to the pandemic, they can be viewed to have especially benefitted from the transition toward mHealth services. Furthermore, one might expect their intention to use these services and reap the potential benefits has increased, especially during the pandemic.ObjectiveThe aim of this study was to examine whether the intention of Dutch older adults to use medical applications increased during the COVID pandemic and how the explanatory power of the extended Technology Acceptance Model (TAM) developed for this purpose was affected by the onset of the pandemic.MethodsWe conducted a cross-sectional survey using two samples collected before (n = 315) and after (n = 501) the onset of the pandemic. Data was collected using questionnaires which were distributed digitally and on paper, by convenience sampling and snowballing. Participants were 65 years or older, lived independently or in a senior living facility, without cognitive impairment. A controlled analysis was performed to test for significant differences in the intention to use mHealth. The before and after differences in extended TAM variables and their relationship with intention to use (ITU) were analyzed using controlled (multivariate) logistic and linear regression models. These models were also used to explore whether the onset of the pandemic had an effect on ITU not captured by the extended TAM model.ResultsWhile the two samples differed in ITU (p = 0.017; uncontrolled) there was no statistically significant difference in ITU in the controlled logistic regression analysis (p = 0.107). The scores of the extended TAM variables explaining intention to use were all significantly higher, except for Subjective norm and Feelings of Anxiety. The relationships of these variables with intention to use before and after the onset of the pandemic were similar, except for Social relationships which lost its significance. We found no indications of effects of the pandemic on intention to use not captured by our instrument.ConclusionThe intention to use mHealth applications of Dutch older adults has not changed since the onset of the pandemic. The extended TAM model has robustly explained intention to use, with only minor differences after the first months of the pandemic. Interventions targeting facilitation and support are likely to promote the uptake of mHealth. Follow-up studies are needed to investigate whether the pandemic has had long term effects on the ITU of the older adult.

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A systematic literature review on mHealth related research during the COVID-19 outbreak

Cited by 12 publications

References 26 publications

Digital altruism: the motivators for, effects of and support received when moderating mental health online

Digital altruism: the motivators for, effects of and support received when moderating mental health online

Analysis of barriers of mHealth adoption in the context of sustainable operational practices in health care supply chains

The intention to use mHealth applications among Dutch older adults prior and during the COVID pandemic

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