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BackgroundThe prevalence of obesity among children remains high. Given obesity's significant lifelong consequences, there is great interest in preventing obesity early in life. There is a need to better understand the relation of common infant feeding styles and practices to obesity in infants using longitudinal study designs. There is also an urgent need to understand the role of caregivers other than mothers in feeding. A better understanding of variation in feeding styles and practices can inform the identification of risk groups and the tailoring of interventions to them.MethodsIn partnership with Early Head Start programs across four counties in southern California, mothers and infants will be enrolled in a two-year longitudinal study collecting survey and anthropometric data. A subsample of mothers and their selected other caregivers will participate in qualitative research involving feeding diaries and dyadic interviews. The results will be used to develop and test an enhanced nutrition education program.DiscussionWe outline a study methodology to examine feeding styles and practices and their association with early childhood obesity risk and enhance an existing intervention to promote healthy infant feeding and growth among children in low-income families.

Vaccination is the primary strategy to prevent COVID-19 illness and hospitalization. However, supplies are scarce and due to the regional mutations of the virus, new vaccines or booster shots will need to be administered potentially regularly. Hence, the prediction of the rate of growth of COVID-19 cases is paramount to ensuring the ample supply of vaccines as well as for local, state, and federal government measures to ensure the availability of hospital beds, supplies, and staff. eVision is an epidemic forecaster aimed at combining Machine Learning (ML) - in the form of a Long Short-Term Memory (LSTM) Recursive Neural Network (RNN) - and search engine statistics, in order to make accurate predictions about the weekly number of cases for highly communicable diseases. By providing eVision with the relative popularity of carefully selected keywords searched via Google along with the number of positive cases reported from the US Centers for Disease Control and Prevention (CDC) and/or the World Health Organization (WHO) the model can make highly accurate predictions about the trend of the outbreak by learning the relationship between the two trends. Thus, in order to predict the trend of the outbreak in a specific region, eVision is provided with a weekly count of the number of COVID-19 cases in a region along with statistics surrounding common symptom search phrases such as “loss of smell” and “loss of taste” that have been searched on Google in that region since the start of the pandemic. eVision has, for instance, been able to achieve an accuracy of %89 for predicting the trend of the COVID-19 outbreak in the United States

The commitment of an organization shows a worker's psychological connection, loyalty, and devotion to their employer. It is the degree to which staff members identify with the organization's objectives, values, and mission and are willing to work diligently for its success. This quantitative research utilized the descriptive, correlational design in assessing the relationship between profile and organizational commitment among nurses in healthcare institutions in the Province of Cotabato. The findings of the study revealed that the majority of the respondents were young adults or belonging to 19 to 35 years old and the majority of them were females and college degree holders. Furthermore, most of the respondents have served their organization for 3 to 6 years already and the majority of the respondents are connected to a private hospital. Continuance commitment was rated as neither low nor high while affective commitment and normative commitment were rated as high. Overall, the organizational commitment of the respondents was high. Age, sex, educational attainment, years of service, and type of hospital did not have a significant relationship with continuance commitment. Age, sex, educational attainment, years of service, and type of hospital did not have a significant relationship with affective commitment. There was a significant relationship between years of experience and normative commitment while age, sex, educational attainment, and the type of hospital showed no significant relationship with normative commitment. Significant relationships were seen between years of experience and overall organizational commitment as well as type of hospital and overall organizational commitment. Meanwhile age, sex, and educational attainment did not have a significant relationship with overall organizational commitment. In conclusion, years of experience and the type of hospital influence organizational commitment. Longer years of experience translate to higher organizational commitment. Private hospitals have been seen to have increased organizational commitment. As an output of the study, an organizational commitment enhancement plan was created. [ABSTRACT FROM AUTHOR]