Accessible and reliable neurometric testing in humans using a smartphone platform

Tests of human brain circuit function typically require fixed equipment in lab environments. We have developed a smartphone-based platform for neurometric testing. This platform, which uses AI models like computer vision, is optimized for at-home use and produces reproducible, robust results on a battery of tests, including eyeblink conditioning, prepulse inhibition of acoustic startle response, and startle habituation. This approach provides a scalable, universal resource for quantitative assays of central nervous system function.</p

“We have been working overnight without sleeping”: traditional birth attendants’ practices and perceptions of post-partum care services in rural Tanzania

Background: In many low-income countries, formal post-partum care utilization is much lower than that of skilled delivery and antenatal care. While Traditional Birth Attendants (TBAs) might play a role in post-partum care, research exploring their attitudes and practices during this period is scarce. Therefore, the aim of this study was to explore TBAs’ practices and perceptions in post-partum care in rural Tanzania. Methods: Qualitative in-depth interview data were collected from eight untrained and three trained TBAs. Additionally, five multiparous women who were clients of untrained TBAs were also interviewed. Interviews were conducted in February 2013. Data were digitally recorded and transcribed verbatim. Qualitative content analysis was used to analyze data. Results: Our study found that TBAs take care of women during post-partum with rituals appreciated by women. They report lacking formal post-partum care training, which makes them ill-equipped to detect and handle post-partum complications. Despite their lack of preparation, they try to provide care for some post-partum complications which could put the health of the woman at risk. TBAs perceive that utilization of hospital-based post-partum services among women was only important for the baby and for managing complications which they cannot handle. They are poorly linked with the health system. Conclusions: This study found that the TBAs conducted close follow-ups and some of their practices were appreciated by women. However, the fact that they were trying to manage certain post-partum complications can put women at risk. These findings point out the need to enhance the communication between TBAs and the formal health system and to increase the quality of the TBA services, especially in terms of prompt referral, through provision of training, mentoring, monitoring and supervision of the TBA servic

Beyond the ‘Migrant Network’? Exploring assistance received in the migration of brazilians to Portugal and the Netherlands

This paper explores the tenability of three important critiques to the ‘migrant network’ approach in migration studies: (1) the narrow focus on kin and community members, which connect prospective migrants in origin countries with immigrants in the destination areas, failing to take due account of sources of assistance beyond the ‘migrant network’ like institutional or online sources; (2) that it is misleading to assume a general pattern in the role of migrant networks in migration, regardless of contexts of arrival or departure, including the scale and history of migration or the immigration regime; and (3) that ‘migrant networks’ are not equally relevant to all migrants, and that important differences may exist between labour migrants and other types of migrants like family migrants or students. Drawing on survey data on the migration of Brazilians to Portugal and the Netherlands we find support for these critiques but also reaffirm the relevance of ‘migrant networks’.info:eu-repo/semantics/publishedVersio

S-D logic-informed customer engagement: Integrative framework, revised fundamental propositions, and application to CRM

Advance online in 2016</p

Impact of Birth Preparedness and Complication Readiness Interventions on Birth with a Skilled Attendant: A Systematic Review.

Background: Increased preparedness for birth and complications is an essential part of antenatal care and has the potential to increase birth with a skilled attendant. We conducted a systematic review of studies to assess the effect of birth preparedness and complication readiness interventions on increasing birth with a skilled attendant. Methods: PubMed, Embase, CINAHL and grey literature were searched for studies from 2000 to 2012 using a broad range of search terms. Studies were included with diverse designs and intervention strategies that contained an element of birth preparedness and complication readiness. Data extracted included population, setting, study design, outcomes, intervention description, type of intervention strategy and funding sources. Quality of the studies was assessed. The studies varied in BP/CR interventions, design, use of control groups, data collection methods, and outcome measures. We therefore deemed meta-analysis was not appropriate and conducted a narrative synthesis of the findings. Results: Thirty-three references encompassing 20 different intervention programmes were included, of which one programmatic element was birth preparedness and complication readiness. Implementation strategies were diverse and included facility-, community-, or home-based services. Thirteen studies resulted in an increase in birth with a skilled attendant or facility birth. The majority of authors reported an increase in knowledge on birth preparedness and complication readiness. Conclusions: Birth Preparedness and Complication Readiness interventions can increase knowledge of preparations for birth and complications; however this does not always correspond to an increase in the use of a skilled attendant at birth

Transatlantic transferability of a new reinforcement learning model for optimizing haemodynamic treatment for critically ill patients with sepsis

© 2020Introduction: In recent years, reinforcement learning (RL) has gained traction in the healthcare domain. In particular, RL methods have been explored for haemodynamic optimization of septic patients in the Intensive Care Unit. Most hospitals however, lack the data and expertise for model development, necessitating transfer of models developed using external datasets. This approach assumes model generalizability across different patient populations, the validity of which has not previously been tested. In addition, there is limited knowledge on safety and reliability. These challenges need to be addressed to further facilitate implementation of RL models in clinical practice. Method: We developed and validated a new reinforcement learning model for hemodynamic optimization in sepsis on the MIMIC intensive care database from the USA using a dueling double deep Q network. We then transferred this model to the European AmsterdamUMCdb intensive care database. T-Distributed Stochastic Neighbor Embedding and Sequential Organ Failure Assessment scores were used to explore the differences between the patient populations. We apply off-policy policy evaluation methods to quantify model performance. In addition, we introduce and apply a novel deep policy inspection to analyse how the optimal policy relates to the different phases of sepsis and sepsis treatment to provide interpretable insight in order to assess model safety and reliability. Results: The off-policy evaluation revealed that the optimal policy outperformed the physician policy on both datasets despite marked differences between the two patient populations and physician's policies. Our novel deep policy inspection method showed insightful results and unveiled that the model could initiate therapy adequately and adjust therapy intensity to illness severity and disease progression which indicated safe and reliable model behaviour. Compared to current physician behavior, the developed policy prefers a more liberal use of vasopressors with a more restrained use of fluid therapy in line with previous work. Conclusion: We created a reinforcement learning model for optimal bedside hemodynamic management and demonstrated model transferability between populations from the USA and Europe for the first time. We proposed new methods for deep policy inspection integrating expert domain knowledge. This is expected to facilitate progression to bedside clinical decision support for the treatment of critically ill patients

Gamification via mobile applications: A longitudinal examination of its impact on attitudinal loyalty and behavior toward a core service

Organizations increasingly use gamification to engage with, and influence, consumers’ attitudes and behaviors. In this article, we present findings from a longitudinal, mixed‐method research design that (1) examined the extent to which game design elements created by a third‐party app lead to increased attitudinal loyalty toward core service providers and (2) sought to explain the underlying processes that invoke attitudinal change. Behavioral data collected from app users indicated that knowledge‐focused affordances positively influenced consumer loyalty and explained 11.3% of the variance in attitudinal change. Follow‐up interviews revealed that Rewards, Competition, Sense of Achievement, and Gaining Knowledge were representative of consumers’ motives for using the app, and Engagement and Identity explained how using the gamified application influenced users’ attitudinal loyalty toward the core service. Overall, we contribute to knowledge about how gamified affordances can be used to add value to consumer experiences, both in relation to the gamified consumption experiences, and the focal brand that is serviced by a third‐party app