Spanish version of the mHealth app usability questionnaire (MAUQ) and adaptation to breastfeeding support apps.

INTRODUCTION: Mobile applications (apps) are increasingly used during pregnancy, postpartum and lactation. To ensure the utility and usability of breastfeeding support apps, they need to be evaluated using a reliable scale specific to mHealth apps and breastfeeding users. OBJECTIVE: To translate the original the mHealth App Usability Questionnaire (MAUQ) questionnaire into Spanish and to adapt it to breastfeeding support apps environment. MATERIALS AND METHODS: The questionnaire was translated by one high English proficiency translator and was back translated. The items of the questionnaire were modified for Spanish readers and for breastfeeding users. The modified questionnaire was assessed for content validity with a panel of 5 experts and 12 users and the modified kappa statistic was used to determine the interrater agreement among the raters. The reliability of the questionnaire was assessed in a mobile application for breastfeeding support (LactApp) by 202 users. The structure of the questionnaire was validated using exploratory factor analysis. RESULTS: All items of the questionnaire were relevant, clear or comprehensible with content validity index values higher than 0.79. The modified kappa agreement for each item of the modified MAUQ (m-MAUQ) proved an excellent agreement (κ = 0.9-1.0). Factor analysis of the m-MAUQ showed four subscales. The internal consistency of the complete questionnaire was high (Cronbach α = 0.89). CONCLUSIONS: The Spanish and modified MAUQ demonstrated high reliability and validity and it might be used to evaluate the usability, utility and acceptability of mHealth apps aiming to support lactating women.

Impact of COVID-19 Pandemic in Breastfeeding Consultations on LactApp, an m-Health Solution for Breastfeeding Support.

Introduction: Breastfeeding is an unquestionable right of mothers and their children; however, it is not a one-woman job. For breastfeeding to succeed, women must have access to appropriate support and guidance. The COVID-19 pandemic and subsequent restriction measures and lockdown to reduce community spread of the disease have negatively impacted breastfeeding support from health services and thus, in mothers' breastfeeding experiences. Objective: The present study aims at evaluating the impact of the COVID-19 pandemic on breastfeeding consultations in LactApp (a mobile application [app] for m-Health focused on breastfeeding support, www.lactapp.com) during the COVID-19 pandemic. Materials and Methods: We conducted an observational, descriptive, and retrospective study with LactApp data recorded between July 2018 and March 2021, including 9,151,456 queries classified in 48 topics among 137,327 active users. We used the Interrupted time series model to evaluate the increase of the number of queries consulted and active users due to the COVID-19 pandemic. Wilcoxon test was used to study the increase of certain topics due to the COVID-19 pandemic. Results: LactApp active users increased by 12,092 users (p < 0.001) during the COVID-19 outbreak and confinement and queries consulted in LactApp also significantly increased by 10,899 queries per month after the pandemic outbreak. The breastfeeding topics that significantly increased are those related to growth spurts, breastfeeding stages, breastfeeding technique, breast pain and mastitis, problems with infants not gaining weight correctly, hypogalactia, increased milk demand, and relactation. These findings are important to understand the potential of online tools when face-to-face professional support is unavailable. Conclusions: Critical issues in breastfeeding establishment were highly consulted and significantly increased in the app during the pandemic. We believe that LactApp was a useful tool for breastfeeding support when women could not obtain appropriate support elsewhere. LactApp might be considered a powerful tool to identify critical issues of breastfeeding and trends in an automatized manner.

Situated Agents and Humans in Social Interaction for Elderly Healthcare: From Coaalas to AVICENA.

Assistive Technologies (AT) are an application area where several Artificial Intelligence techniques and tools have been successfully applied to support elderly or impeded people on their daily activities. However, approaches to AT tend to center in the user-tool interaction, neglecting the user's connection with its social environment (such as caretakers, relatives and health professionals) and the possibility to monitor undesired behaviour providing both adaptation to a dynamic environment and early response to potentially dangerous situations. In previous work we have presented COAALAS, an intelligent social and norm-aware device for elderly people that is able to autonomously organize, reorganize and interact with the different actors involved in elderly-care, either human actors or other devices. In this paper we put our work into context, by first examining what are the desirable properties of such a system, analysing the state-of-the-art on the relevant topics, and verifying the validity of our proposal in a larger context that we call AVICENA. AVICENA's aim is develop a semi-autonomous (collaborative) tool to promote monitored, intensive, extended and personalized therapeutic regime adherence at home based on adaptation techniques.