Family Context, Parenting and Child Development: An Epigenetic Approach

Barreto-Zarza, Florencia; Arranz-Freijo, Enrique B.

doi:10.3390/socsci11030113

Cited by 6 publications

(4 citation statements)

References 56 publications

(82 reference statements)

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“…Taking a look at the academic articles that relate to this parameter, we were able to find a number of topics that describe various dimensions of this parameter. The topics and dimensions include psychological [67][68][69], social [70], cognitive [71], physical and mental health development [72][73][74], family engagement [75][76][77], behaviour change [78,79], and education [70,[80][81][82]. Figure 10 shows the inter-topic distance map, where twelve groups of parameters are identified (see Section 3.9).…”

Section: Nurturing Childrenmentioning

confidence: 99%

Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery Using BERT Modelling

et al. 2022

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Homes are the building block of cities and societies and therefore smart homes are critical to establishing smart living and are expected to play a key role in enabling smart, sustainable cities and societies. The current literature on smart homes has mainly focused on developing smart functions for homes such as security and ambiance management. Homes are composed of families and are inherently complex phenomena underlined by humans and their relationships with each other, subject to individual, intragroup, intergroup, and intercommunity goals. There is a clear need to understand, define, consolidate existing research, and actualize the overarching roles of smart homes, and the roles of smart homes that will serve the needs of future smart cities and societies. This paper introduces our data-driven parameter discovery methodology and uses it to provide, for the first time, an extensive, fairly comprehensive, analysis of the families and homes landscape seen through the eyes of academics and the public, using over a hundred thousand research papers and nearly a million tweets. We developed a methodology using deep learning, natural language processing (NLP), and big data analytics methods (BERT and other machine learning methods) and applied it to automatically discover parameters that capture a comprehensive knowledge and design space of smart families and homes comprising social, political, economic, environmental, and other dimensions. The 66 discovered parameters and the knowledge space comprising 100 s of dimensions are explained by reviewing and referencing over 300 articles from the academic literature and tweets. The knowledge and parameters discovered in this paper can be used to develop a holistic understanding of matters related to families and homes facilitating the development of better, community-specific policies, technologies, solutions, and industries for families and homes, leading to strengthening families and homes, and in turn, empowering sustainable societies across the globe.

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Section: Nurturing Childrenmentioning

confidence: 99%

Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery Using BERT Modelling

et al. 2022

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“…Taking a look at the academic articles that relate to this parameter, we were able to find a number of topics that describe various dimensions of this parameter. The topics and dimensions include psychological [65]- [67], social [68], cognitive [69], physical and mental health development [70]- [72], family engagement [73]- [75], behaviour change [76], [77], and education [68], [78]- [80].…”

Section: Nurturing Childrenmentioning

confidence: 99%

“…Children's psychological development --including their cognitive, intellectual, social, and emotional capabilities --is affected by many factors related to their families and homes. Arranz-Freijo and Barreto-Zarza [65] advocated the use of an epigenetic approach to better understand the effects of family structure and parenting quality on the psychological development of children. Solsona et al [81] noticed the concept of family has grown to be broader and more complex.…”

Section: Nurturing Childrenmentioning

confidence: 99%

Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery using BERT Modelling

Alqahtani¹,

Janbi²,

Sharaf³

et al. 2022

Preprint

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Technological advancements and innovations have profoundly changed the lives of people giving rise to smart environments, cities, and societies. As homes are the building block of cities and societies, smart homes are critical to establishing smart living and are expected to play a key role in enabling smart cities and societies. The current academic literature and commercial advancements on smart homes have mainly focused on developing and providing smart functions for homes to provide security management and facilitate the residents in their various activities such as ambiance management. Homes are much more than physical structures, buildings, appliances, operational machines, and systems. Homes are composed of families and are inherently complex phenomena underlined by humans and their relationships with each other, subject to individual, intragroup, intergroup, and intercommunity goals. There is a clear need to understand, define, consolidate existing research, and actualize the overarching roles of smart homes, the roles of smart homes that would serve the needs of future smart cities and societies. This paper introduces our data-driven parameter discovery methodology and uses it to provide, for the first time, an extensive, rather fairly comprehensive, analysis of the families and homes landscape seen through the eyes of academics and the public using over a hundred thousand research papers and nearly a million tweets. We develop a methodology using deep learning, natural language processing (NLP), and big data analytics methods and apply it to automatically discover parameters that capture a comprehensive knowledge and design space of smart families and homes comprising social, political, economic, environmental, and other dimensions. The 66 discovered parameters and the knowledge space comprising 100s of dimensions are explained by reviewing and referencing over 300 articles from the academic literature and tweets. The knowledge and parameters discovered in this paper can be used to develop a holistic understanding of matters related to families and homes facilitating the development of better, community-specific, policies, technologies, solutions, and industries for families and homes, leading to strengthening families and homes, and in turn, empowering sustainable societies across the globe.

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“…Parenting is in uenced by perceptions and beliefs about parenting itself [24,26] and the level of parental stress [27,28]. Both factors seem to be involved in the family stress model, which shows that more stressed parents have greater di culties in providing good-quality cognitive and socioemotional scaffolding [29] and, subsequently, promoting cognition [28].…”

Section: Introductionmentioning

confidence: 99%

Socioeconomic position, family context, and child cognitive development

González,

Popovic,

Rebagliato

et al. 2023

Preprint

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Background Socioeconomic position (SEP) may have different effects on cognitive development and family context could play a role in this association. This work aimed to analyse the role of socioeconomic positions, measured via various indicators collected longitudinally, in cognitive development at 7–11 years of age, evaluating the role of family context as a potential mediator. Method The study sample included 394 and 382 children from the INMA Gipuzkoa and Valencia cohorts, respectively. SEP indicators were assessed during pregnancy (family social class, parental education, employment, and disposable income) and at 7 (Gipuzkoa) and 11 (Valencia) years of age (At Risk of Poverty or Social Exclusion (AROPE)). Family context and cognitive development were measured with the Haezi-Etxadi Family Assessment Scale 7–11 (HEFAS 7–11) and Raven’s Coloured Progressive Matrices (Raven’s CPM), respectively. Linear regression models were developed to assess the relationships between a) SEP-family context, b) SEP-cognitive development, and c) family context-cognitive development, adjusting for a priori-selected confounders. Simple and multiple mediation analyses were performed to explore the role of family context in the SEP-cognitive development relationship. Results Lower SEP was related with a lower cognitive score, this association being particularly robust for family social class. SEP indicators were related to subscales of family context, in particular those regarding cognitive stimulation, parental stress, and parenting. A relationship was also found between these three subscales and child cognitive development, mediating the effect of family social class on child cognition by 5.2, 5.5, and 10.8%, respectively, and 12.0% jointly. Conclusions Both family SEP and context contribute to a child’s cognitive development. Equalising policies and positive parenting programmes could contribute to improving cognitive development in children.

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Family Context, Parenting and Child Development: An Epigenetic Approach

Cited by 6 publications

References 56 publications

Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery Using BERT Modelling

Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery Using BERT Modelling

Smart Homes and Families to Enable Sustainable Societies: A Data-Driven Approach for Multi-Perspective Parameter Discovery using BERT Modelling

Socioeconomic position, family context, and child cognitive development

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