The use of M-Health interventions for gestational diabetes mellitus: A descriptive literature review

Zahmatkeshan, Maryam; Yazdani, Azita; Karbasi, Zahra; Afifian, Mahboubeh; Seraji, Maryam; Gholampour, Yousef

doi:10.22541/au.159000286.68663909

Cited by 4 publications

(2 citation statements)

References 21 publications

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“…The first important step in planning and designing intervention is problem identification (24). In determining the problem, the problem should be identified correctly, because improper identification of problem can lead to the presentation of wrong solutions (25,26). According to the research, it can be claimed that the present study is the first of its kind and so far, no research has been done on the prioritization of constructs of cognitive-social theory that affect the obesity prevention behaviors in 4-6 years of children.…”

Section: Introductionmentioning

confidence: 88%

Prioritizing factors affecting obesity prevention behaviors in 4-6 years old children from mothers' perspective (based on social-cognitive theory)

Seraji¹,

Zahmatkeshan²,

Abadi³

et al. 2021

PJMHS

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Introduction: The development of effective prevention and intervention programs in preschool period is an essential step in the fight against the obesity epidemic throughout life. The aim of this study was to prioritize the factors affecting the obesity prevention behaviors in 4-6 years old children from the perspective of mothers based on social-cognitive theory. Materials and Methods: This cross-sectional and analytical study was conducted on 240 children aged 4-6 years in Behbahan city, Iran in 2016. The random multi-stage sampling method was used in this study. Data collection tools included a demographic information questionnaire and a questionnaire based on cognitive-social theory (constructs of environment, outcome expectation, emotional coping, self-control and self-efficacy), which its validity and reliability have been evaluated and confirmed (α> 0.7). The questionnaire which was based on cognitive-social theory included 4 obesity prevention behaviors in children (physical activity, consumption of fruits and vegetables, consumption of sugar-free drinks and screen), which were completed by the mothers of these children. SPSS-23 software and Friedman’s test were used to analyze the data. Results: The results of this study suggest that from the mothers' point of view, the constructs of cognitive-social theory affecting obesity prevention behaviors in 4-6 years old children do not have the same priority (p <0.01). Also, considering the mean ratings obtained in this study, the outcome expectation construct in all 4 behaviors of obesity prevention are of primary importance. The average ranking of the outcome expectation construct was 4.38, 4.39, 4.25 and 4.49 in the behaviors of physical activity, consumption of fruits and vegetables, consumption of sugar-free drinks, and the screen, respectively. Conclusion: In designing maternal-centered educational interventions that prevent obesity in 4-6 years old children, the construct of outcome expectation should be given the highest priority. Keywords: Obesity, Pediatric, Lifestyle, Behavior, Health Priorities, Health Planning

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Section: Introductionmentioning

confidence: 88%

Prioritizing factors affecting obesity prevention behaviors in 4-6 years old children from mothers' perspective (based on social-cognitive theory)

Seraji¹,

Zahmatkeshan²,

Abadi³

et al. 2021

PJMHS

Self Cite

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“…Disease registration systems provide an important tool for public health surveillance (8). Electronic record of patient health information, while providing a dynamic and flexible structure for reporting (9,10), Allows the discovery of hidden knowledge from stored data. With the expansion of electronic data registration in the health care, there is a large and complex amount of data that cannot be analyzed by traditional methods.…”

Section: Introductionmentioning

confidence: 99%

Data Mining Approach to Analyze COVID-19 Clinical Dataset

Yazdani¹,

Ravangard²,

Sharifian³

2021

PJMHS

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The new coronavirus has been spreading since the beginning of 2020 and many efforts have been made to develop vaccines to help patients recover. It is now clear that the world needs a rapid solution to curb the spread of COVID-19 worldwide with non-clinical approaches such as data mining, enhanced intelligence, and other artificial intelligence techniques. These approaches can be effective in reducing the burden on the health care system to provide the best possible way to diagnose and predict the COVID-19 epidemic. In this study, data mining models for early detection of Covid-19 in patients were developed using the epidemiological dataset of patients and individuals suspected of having Covid-19 in Iran. C4.5, support vector machine, Naive Bayes, logistic regression, Random Forest, and k-nearest neighbor algorithm were used directly on the dataset using Rapid miner to develop the models. By receiving clinical signs, this model diagnosis the risk of contracting the COVID-19 virus. Examination of the models in this study has shown that the support vector machine with 93.41% accuracy is more efficient in the diagnosis of patients with COVID-19 pandemic, which is the best model among other developed models. Keywords: COVID-19, Data mining, Machine Learning, Artificial Intelligence, Classification

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Evaluarea impactului platformei digitale de sănătate Cordia® asupra îngrijirii materne în zonele defavorizate: un studiu-pilot

Solanki,

Pradhan,

Singh

et al. 2024

Ginecologia.ro

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The use of M-Health interventions for gestational diabetes mellitus: A descriptive literature review

Cited by 4 publications

References 21 publications

Prioritizing factors affecting obesity prevention behaviors in 4-6 years old children from mothers' perspective (based on social-cognitive theory)

Prioritizing factors affecting obesity prevention behaviors in 4-6 years old children from mothers' perspective (based on social-cognitive theory)

Data Mining Approach to Analyze COVID-19 Clinical Dataset

Evaluarea impactului platformei digitale de sănătate Cordia® asupra îngrijirii materne în zonele defavorizate: un studiu-pilot

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