58 research outputs found

    Women who experience feelings of aversion while breastfeeding: A meta-ethnographic review.

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    PROBLEM:Limited literature is available about women who wish to breastfeed but experience unexpected feelings of aversion in reaction to their infant suckling at the breast while breastfeeding. BACKGROUND:Breastfeeding benefits mothers, infants and society yet breastfeeding rates continue to fall below recommendations in part due to inadequate tailored support after hospital discharge. Influences on breastfeeding are complex and include many physiological, psychosocial and cultural factors. AIM:To better understand the experience of women who have feelings of aversion during breastfeeding by synthesising the existing literature. METHODS:MEDLINE, CINAHL, PsycINFO, Maternity and Infant Care databases were searched for relevant literature published between 2000 to 2019. Using Covidence software, five qualitative research studies were identified. Studies were then analysed using meta-ethnographic qualitative synthesis. FINDINGS:Feelings of aversion during breastfeeding were described as visceral and overwhelming; leading to feelings of shame and inadequacy. This synthesis identified five findings; a central conceptual category of "it's such a strong feeling of get away from me" with four key metaphors translated from this central conceptual category: "I do it because I feel it is best for my baby", "I can't control those feelings", "I should be able to breastfeed my son and enjoy it", and "I'm glad I did it". This phenomenon may negatively affect a women's sense of self and impact on the mother-infant relationship. CONCLUSION:Some women who want to breastfeed can experience feelings of aversion while breastfeeding. The feelings of 'aversion' while breastfeeding can inhibit women from achieving their personal breastfeeding goals

    Guilt, shame, and postpartum infant feeding outcomes: A systematic review

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    Abstract Negative maternal affect (e.g., depression and anxiety) has been associated with shorter breastfeeding duration and poorer breastfeeding intention, initiation, and exclusivity. Other affective states, including guilt and shame, have been linked with formula feeding practice, though existing literature has yet to be synthesised. A narrative synthesis of quantitative data and a framework synthesis of qualitative and quantitative data were conducted to explore guilt and/or shame in relation to infant feeding outcomes. Searches were conducted on the DISCOVER database between December 2017 and March 2018. The search strategy was rerun in February 2020, together yielding 467 studies. The study selection process identified 20 articles, published between 1997 and 2017. Quantitative results demonstrated formula feeders experienced guilt more commonly than breastfeeding mothers. Formula feeders experienced external guilt most commonly associated with healthcare professionals, whereas breastfeeding mothers experienced guilt most commonly associated with peers and family. No quantitative literature examined shame in relation to infant feeding outcomes, warranting future research. The framework synthesis generated four distinct themes which explored guilt and/or shame in relation to infant feeding outcomes: ‘underprepared and ineffectively supported’, ‘morality and perceived judgement’ (breastfeeding), ‘frustration with infant feeding care’ and ‘failures, fears and forbidden practice’ (formula feeding). Both guilt and shame were associated with self‐perception as a bad mother and poorer maternal mental health. Guilt and shame experiences were qualitatively different in terms of sources and outcomes, dependent on infant feeding method. Suggestions for tailored care to minimise guilt and shame, while supporting breastfeeding, are provided

    Analog design of a new neural network for optical character recognition

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    The DSFPN, a new neural network for optical character recognition

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    Analog design of a competitive middle layer for a new neural network for optical character recognition

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    The DSFPN: A New Neural Network and Circuit Simulation for Optical Character Recognition

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    Analog design of a new neural network for optical character recognition

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