BackgroundMobile application based delivery of psycho-social interventions may help reduce the treatment gap for severe mental illnesses (SMIs) and decrease the burden on caregivers. Apps developed in high income settings show effectiveness, but they suffer from lack of applicability in low resource scenarios due to the difference in technology penetration, affordability, and acceptance.ObjectiveThis study aimed to understand health technology usage, perceived needs, and acceptability of app based interventions in patients with SMIs to improve illness management and reduce caregiver burden.MethodsThe study was conducted in inpatient and outpatient settings of a tertiary care center in North India. A cross-sectional survey assessed smartphone and health app usage. Further, three focus group discussions evaluated the needs and apprehensions in using apps in management of SMIs.ResultsA total of 176 participants including 88 patients and 88 caregivers completed the survey. Smartphone ownership was similar to the national average (30%) in both caregivers (38.6%) and in patients (31.8%). Although subjects regularly used a third party app, health app usage was very low. Cost, unfamiliarity, and language were significant barriers to adoption. The focus group discussions provided insight into the various apprehensions of caregivers in using and in allowing patients to use smartphones and such apps. Caregivers wanted mobile apps for accessing information regarding services and resources available for people with SMI, and they felt such apps can be helpful if they could automate some of their routine caregiving activities. However, the significant difficulty was perceived in regards to the cost of the device, language of the medium, and unfamiliarity in using technology. Apprehensions that SMI patients might misuse technology, or damage the device were also prevalent.ConclusionsThe study systematically looks into the scope, design considerations and limitations of implementing a mobile technology based intervention for low resource settings. With only one-third of the patients and caregivers having access to smartphones and internet, parallel outreach strategies like IVRS should be actively considered while designing interventions. The difficulty of understanding and searching in a non-native language needs to be addressed. Hand holding of caregivers and frequent encouragement from treating doctors might significantly help in technology adoption and in surmounting the apprehensions related to using technology. To make the solution acceptable and useful to the already over-burdened caregivers, developers need to work closely with patients’ family members and follow a ground-up collaborative approach to app development. The scope of delivering mental health services through technology is immense in resource constrained settings like India, provided we, researchers, appreciate and accept the fact that in the varied landscape of a divergent economic, educational, and cultural milieu, a single solution will never suffice for all...

Interactive Voice Response (IVR) platforms have been widely deployed in resource-limited settings. These systems tend to afford asynchronous push interactions, and within the context of health, provide medication reminders, descriptions of symptoms and tips on self-management. Here, we present the development of an IVR system for resource-limited settings that enables real-time, synchronous interaction. Inspired by community radio, and calls for health systems that are truly local, we developed 'Sehat ki Vaani'. Sehat ki Vaani is a real-time IVR platform that enables hosting and participation in radio chat shows on community-led topics. We deployed Sehat ki Vaani with two communities in North India on topics related to the management of Type 2 diabetes and maternal health. Our deployments highlight the potential for synchronous IVR systems to offer community connection and localised sharing of experience, while also highlighting the complexity of producing, hosting and participating in radio shows in real time through IVR. We discuss the relative strengths and weaknesses of synchronous IVR systems, and highlight lessons learnt for interaction design in this area.

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Efficient energy consumption at the building level is vital for sustainability. Providing energy efficient systems and solutions requires an understanding of how energy gets consumed. However, there is a general lack of large-scale open datasets about the energy consumption of buildings, which hinders the research. The recent emergence of smart energy meters makes it possible to collect such data, which can then be used for analysis. In this paper, we release I-BLEND, 52 months of electrical energy dataset at a one-minute sampling rate from commercial and residential buildings of an academic institute campus in an emerging economy, India. Also, we provide occupancy datasets at a 10-minute sampling rate for each of the campus buildings. To the best of our knowledge, this is the first such dataset from India. Public availability of such fine-granular data will allow users to perform different research tasks such as analyzing the impact of weather or occupancy schedule on energy consumption, detecting anomalies, and developing algorithms for predictive maintenance.

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Buildings are one of the largest consumers of electricity. Dominant electricity consumption within the buildings, contributed by plug loads, lighting and air conditioning, can be significantly improved using Occupancy-based Building Management Systems (Ob-BMS). In this paper, we address three critical aspects of Ob-BMS i.e. 1) Modular sensor node design to support diverse deployment scenarios; 2) Building architecture to support and scale fine resolution monitoring; and 3) Detailed analysis of the collected data for smarter actuation. We present key learning across these three aspects evolved over more than one year of design and deployment experiences.The sensor node design evolved over a period of time to address specific deployment requirements. With an opportunity at the host institute where two dorm buildings were getting constructed, we planned for the support infrastructure required for fine resolution monitoring embedded in the design phase and share our preliminary experiences and key learning thereof. Prototype deployment of the sensing system as per the planned support infrastructure was performed at two faculty offices with effective data collection worth 45 days. Collected data is analyzed accounting for efficient switching of appliances, in addition to energy conservation and user comfort as performed in the earlier occupancy based frameworks. Our analysis shows that occupancy prediction using simple heuristic based modeling can achieve similar performance as more complex Hidden Markov Models, thus simplifying the analytic framework.

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Background Structural and cultural barriers limit Indian women’s access to adequate postnatal care and support despite their importance for maternal and neonatal health. Targeted postnatal education and support through a mobile health intervention may improve postnatal recovery, neonatal care practices, nutritional status, knowledge and care seeking, and mental health. Objective We sought to understand the feasibility and acceptability of our first pilot phase, a flexible 6-week postnatal mobile health intervention delivered to 3 groups of women in Punjab, India, and adapt our intervention for our next pilot phase, which will formally assess intervention feasibility, acceptability, and preliminary efficacy. Methods Our intervention prototype was designed to deliver culturally tailored educational programming via a provider-moderated, voice- and text-based group approach to connect new mothers with a social support group of other new mothers, increase their health-related communication with providers, and refer them to care needed. We targeted deployment using feature phones to include participants from diverse socioeconomic groups. We held moderated group calls weekly, disseminated educational audios, and created SMS text messaging groups. We varied content delivery, group discussion participation, and chat moderation. Three groups of postpartum women from Punjab were recruited for the pilot through community health workers. Sociodemographic data were collected at baseline. Intervention feasibility and acceptability were assessed through weekly participant check-ins (N=29), weekly moderator reports, structured end-line in-depth interviews among a subgroup of participants (15/29, 52%), and back-end technology data. Results The participants were aged 24 to 28 years and 1 to 3 months postpartum. Of the 29 participants, 17 (59%) had their own phones. Half of the participants (14/29, 48%) attended ≥3 of the 6 calls; the main barriers were childcare and household responsibilities and network or phone issues. Most participants were very satisfied with the intervention (16/19, 84%) and found the educational content (20/20, 100%) and group discussions (17/20, 85%) very useful. The participants used the SMS text messaging chat, particularly when facilitator-moderated. Sustaining participation and fostering group interactions was limited by technological and sociocultural challenges. Conclusions The intervention was considered generally feasible and acceptable, and protocol adjustments were identified to improve intervention delivery and engagement. To address technological issues, we engaged a cloud-based service provider for group calls and an interactive voice response service provider for educational recordings and developed a smartphone app for the participants. We seek to overcome sociocultural challenges through new strategies for increasing group engagement, including targeting midlevel female community health care providers as moderators. Our second pilot will assess intervention feasibility, acceptability, and preliminary effectiveness at 6 months. Ultimately, we seek to support the health and well-being of postpartum women and their infants in South Asia and beyond through the development of efficient, acceptable, and effective intervention strategies.