Positive breastfeeding experiences and facilitators in mothers of preterm and low birthweight infants: a meta-ethnographic review

Background Most qualitative research on breastfeeding the preterm or low-birthweight (LBW) infant has focused on negative insights; there are no comprehensive insights into how, when and why mothers experience positive breastfeeding experiences. We aimed to address this knowledge gap by exploring what characterizes and facilitates a positive breastfeeding experience in mothers of preterm and/or LBW infants. Methods A systematic review using meta-ethnographic methods was conducted. Search strategies involved a comprehensive search strategy on six bibliographic databases, citation tracking and reference checking. The analysis involved a reciprocal level of translation and a line of argument synthesis. Results Searches identified 1774 hits and 17 articles from 14 studies were included, representing the views of 697 mothers. A positive breastfeeding experience was identified as being ‘attuned’. Three themes and eight sub-themes were developed to describe what characterizes attuned breastfeeding. ‘Trusting the body and what it can do’, concerned how attuned breastfeeding was facilitated through understanding the bodily responses and capacity and feeling comfortable with holding the infant and to breastfeed. ‘Being emotionally present – in the here and now’ described the importance of feeling relaxed and reassured. ‘Experiencing mutual positive responses’, illuminated how attunement was related to feelings of mutuality - when the mother recognises the infant’s cues, responds to these signals and receives a positive response from the infant. The key factors to facilitate attuned breastfeeding were opportunities for prolonged close physical contact with the infant, positive relationships with and support from staff and peers, and being facilitated to breastfeed when the infant showed feeding cues. Conclusions This study provides new insights into what characterizes a positive breastfeeding experience and how staff can facilitate and enable mothers to achieve attuned breastfeeding. Improvements in units’ design, such as for rooming-in and having prolonged skin-to-skin contact, and care provided by knowledgeable, supportive and encouraging staff and peers, are crucial. The mother’s physical and emotional states and the infant’s behavioural responses and physiological signals should guide the process towards positive breastfeeding practices.

Bona Fide Tumor Suppressor Genes Hypermethylated in Melanoma: A Narrative Review

Loss-of-function events in tumor suppressor genes (TSGs) contribute to the development and progression of cutaneous malignant melanoma (CMM). Epigenetic alterations are the major mechanisms of TSG inactivation, in particular, silencing by promoter CpG-island hypermethylation. TSGs are valuable tools in diagnosis and prognosis and, possibly, in future targeted therapy. The aim of this narrative review is to outline bona fide TSGs affected by promoter CpG-island hypermethylation and their functional role in the progression of CMM. We conducted a systematic literature review to identify studies providing evidence of bona fide TSGs by cell line or animal experiments. We performed a broad first search and a gene-specific second search, supplemented by reference checking. We included studies describing bona fide TSGs in CMM with promoter CpG-island hypermethylation in which inactivating mechanisms were reported. We extracted data about protein role, pathway, experiments conducted to meet the bona fide criteria and hallmarks of cancer acquired by TSG inactivation. A total of 24 studies were included, describing 24 bona fide TSGs silenced by promoter CpG-island hypermethylation in CMM. Their effect on cell proliferation, apoptosis, growth, senescence, angiogenesis, migration, invasion or metastasis is also described. These data give further insight into the role of TSGs in the progression of CMM.

Who is Tweeting? A Scoping Review of Methods to Establish Race and Ethnicity from Twitter Datasets

Background: A growing amount of health research uses social media data. Those critical of social media research often cite that it may be unrepresentative of the population. Identifying the demographics of social media users enables us to measure the representativeness. Extracting race or ethnicity from social media data can be difficult and researchers may choose from a multitude of different approaches. Methods: We present a scoping review to identify the methods used to extract race or ethnicity from Twitter datasets. We searched 16 electronic databases and carried out reference checking in order to identify relevant articles. Sifting of each record was undertaken independently by at least two researchers with any disagreement discussed. The research could be grouped by the methods applied to extract race or ethnicity.Results: From 1093 records we identified 56 that met our inclusion criteria. The majority focus on Twitter users based in the US. A range of types of data were used including Twitter profile -pictures, bios, and/or location, and the content in the tweets themselves. The methods used were wide ranging and included using manual inference, linkage to census data, commercial software, language/dialect recognition and machine learning. Not all studies evaluated their methods. Those that did found accuracy to vary from 45% to 93% with significantly lower accuracy identifying non-white race categories. There may be some ethical questions over some of the methods used, particularly using photos or dialect, as well as questions surrounding accuracy.Conclusion: There is no standard approach or guidelines for extracting race or ethnicity from Twitter or other social media. Social media researchers must use careful interpretation of race or ethnicity and not over-promise what can be achieved, as even manual screening is a subjective, imperfect method. Future research should establish the accuracy of methods to inform evidence-based best practice guidelines for social media researchers, and be guided by concerns of equity and social justice.

Technical Aspects of Developing Chatbots for Medical Applications: Scoping Review

Background Chatbots are applications that can conduct natural language conversations with users. In the medical field, chatbots have been developed and used to serve different purposes. They provide patients with timely information that can be critical in some scenarios, such as access to mental health resources. Since the development of the first chatbot, ELIZA, in the late 1960s, much effort has followed to produce chatbots for various health purposes developed in different ways. Objective This study aimed to explore the technical aspects and development methodologies associated with chatbots used in the medical field to explain the best methods of development and support chatbot development researchers on their future work. Methods We searched for relevant articles in 8 literature databases (IEEE, ACM, Springer, ScienceDirect, Embase, MEDLINE, PsycINFO, and Google Scholar). We also performed forward and backward reference checking of the selected articles. Study selection was performed by one reviewer, and 50% of the selected studies were randomly checked by a second reviewer. A narrative approach was used for result synthesis. Chatbots were classified based on the different technical aspects of their development. The main chatbot components were identified in addition to the different techniques for implementing each module. Results The original search returned 2481 publications, of which we identified 45 studies that matched our inclusion and exclusion criteria. The most common language of communication between users and chatbots was English (n=23). We identified 4 main modules: text understanding module, dialog management module, database layer, and text generation module. The most common technique for developing text understanding and dialogue management is the pattern matching method (n=18 and n=25, respectively). The most common text generation is fixed output (n=36). Very few studies relied on generating original output. Most studies kept a medical knowledge base to be used by the chatbot for different purposes throughout the conversations. A few studies kept conversation scripts and collected user data and previous conversations. Conclusions Many chatbots have been developed for medical use, at an increasing rate. There is a recent, apparent shift in adopting machine learning–based approaches for developing chatbot systems. Further research can be conducted to link clinical outcomes to different chatbot development techniques and technical characteristics.

The Use of Information Communication and Technology (ICT) to Enable Transparency, Accountability, and Participation in Indonesia

This research aims at understanding how ICT as panopticon vision enable transparency, accountability, and Participation in Indonesia. The betterment of these three aspects is believed to be beneficial for the government in fighting corruption. In the transparency aspect, this research has eight indicators which are constructed from studies by Bhatmagar, Davies & Fumega, Park & Florida, Grimmelikhuijsen, Keuffer & Mabillard: (1) the availability of laws and regulations, (2) the availability of government budget allocations and spending, (3) the availability of performance reports, (4) open government processes, (5) identification of elected officials and civil servants under investigation for corruption and fraudulent activities, (6) disclosure of assets and investments of public officials, (7) provision of e-procurement, and (8) using file formats. In the accountability aspect, four indicators from studies of Lee & Kwak and Davies & Fumega are used. They are (1) the availability of social media presence, (2) using mainstream social media for interactive, on-going conversations, storytelling, and communications, (3) the availability of a platform for questions and answers, and (4) the availability of information about feedback from the public. Finally, for the aspect of Participation, three indicators by Lee & Kwak are employed. Those are (1) voting and polling for a decision-making process or a public organization assessment, (2) feedback and ideation platform, and (3) crowdsourcing to report corruption or grievances. This research uses a qualitative research approach. It is benefiting from the use of secondary data as a form of the big data source. Hence, this research is an initial attempt to exploit the availability of big data as a valid data source. To ensure the secondary data sources’ validity, the researchers employed a triangulation process of backgrounds and reference checking. The data analysis in this research is based on 2 ICT based initiatives; Government websites and apps. It is evident from this research finding that, first, there are 35 ICT based initiatives, 31 websites, and four apps. From these numbers, there are only18 websites and four apps that are available. Second, in general, those websites and apps do enable transparency, accountability, and Participation. Another important highlight of the finding is that three unidentified websites and ten websites are unsuccessful in promoting those three aspects. However, most of the websites and apps had turned out a success. In the meanwhile, ICT as panopticon vision also results in new corruption opportunities. This study highlights three examples of new corruption opportunities. It is recommended that Indonesia continue to work on those ten unavailable websites and, more importantly, be cautious and aware of the new corruption modes. Only by doing those, the role of ICT to fight corruption can be more strengthened.

Systematic review assessing the evidence for the use of stem cells in fracture healing

Aims Bone demonstrates good healing capacity, with a variety of strategies being utilized to enhance this healing. One potential strategy that has been suggested is the use of stem cells to accelerate healing. Methods The following databases were searched: MEDLINE, CENTRAL, EMBASE, Cochrane Database of Systematic Reviews, WHO-ICTRP, ClinicalTrials.gov, as well as reference checking of included studies. The inclusion criteria for the study were: population (any adults who have sustained a fracture, not including those with pre-existing bone defects); intervention (use of stem cells from any source in the fracture site by any mechanism); and control (fracture healing without the use of stem cells). Studies without a comparator were also included. The outcome was any reported outcomes. The study design was randomized controlled trials, non-randomized or observational studies, and case series. Results In all, 94 eligible studies were identified. The clinical and methodological aspects of the studies were too heterogeneous for a meta-analysis to be undertaken. A narrative synthesis examined study characteristics, stem cell methods (source, aspiration, concentration, and application) and outcomes. Conclusion Insufficient high-quality evidence is available to determine the efficacy of stem cells for fracture healing. The studies were heterogeneous in population, methods, and outcomes. Work to address these issues and establish standards for future research should be undertaken. Cite this article: Bone Joint Open 2020;1-10:628–638.

Effect of subsidies on healthful consumption: a protocol for a systematic review update

IntroductionThe prevalence of diet-related non-communicable diseases (NCDs) are rapidly increasing in most parts of the world. In order to ameliorate the related public health burden, evidence-informed policies to improve diet need to be implemented. Financial subsidies that promote healthful consumption patterns have the potential to reduce NCD risk and may also reduce inequality if targeted at those of low socio-economic position. This protocol is for an updated systematic review of such evidence.Methods and analysisA systematic search strategy will be used to identify publications on fiscal intervention studies indexed in Embase, CINAHL, Web of Science, EconLit and PubMed in between January 2013 to February 2019. Two reviewers will independently sift identified citations using prespecified inclusion and exclusion criteria to inform full-text review. The outcomes of interest are: consumption patterns (% change in targeted items and in overall dietary patterns), purchasing patterns (% change) or body mass index. Pretested data capture forms will be used for double data extraction. Any inconsistencies in citation sifting or data extraction will be resolved by a third investigator and study authors will be contacted if needed. Systematic searches will be supplemented by reference checking of key articles. Study quality will be assessed and a narrative summary of findings will be produced. Meta-analyses and exploration of heterogeneity will be completed if appropriate.Ethics and disseminationThe review aims to strengthen findings of the primary studies it incorporates. It will synthesise existing published aggregated patient data and only present further aggregate data. Given this, no concerns are held relating to confidentiality and informed consent due to re-use of patient data.If publications or data with ethical concerns are identified, they will be excluded from the review.Results of the systematic review will be published in full and authors will engage directly with research audiences and key stakeholders to share findings.PROSPERO registration numberCRD42019125013

Working with families: A systematic scoping review of family-centred care in universal, community-based maternal, child, and family health services

Children’s long- and short-term health and developmental outcomes can be improved when families are engaged and supported, and inform care planning. Family-centred care (FCC) underpins policy directions for universal, community-based, child and family health services in the early years, although its implementation in this context is poorly understood. This systematic scoping review of the current literature aimed to improve understanding of FCC implementation in maternal, child, and family health universal services. Key databases and grey literature were searched using descriptors of maternal, child, and family health population and context, and FCC concept. Reference checking identified further literature for analysis. Thirteen included papers reported on nine studies from Australia, New Zealand, and the United Kingdom. Limited participant representation of fathers and diverse community members was evident. Deductive thematic analysis identified four areas of FCC demonstrated in this literature: respectful relationships, effective communication to foster shared understanding, flexible and contextualized care, and support for autonomy and agency. The literature demonstrated the interplay between organizational, professional, and recipient factors and their impact on the implementation of FCC. For successful FCC implementation, all these elements should be considered.

Database combinations to retrieve systematic reviews in Overviews of reviews: A methodological study

Background: When conducting an Overviews of Reviews on health-related topics, it is unclear which combination of bibliographic databases authors should use for searching for SRs. Our goal was to determine which databases included the most systematic reviews and identify an optimal database combination for searching systematic reviews. Methods: A set of 86 Overviews of Reviews with 1219 included systematic reviews was extracted from a previous study. Inclusion of the systematic reviews was assessed in MEDLINE, CINAHL, Embase, Epistemonikos, PsycINFO, and TRIP. The mean inclusion rate (% of included systematic reviews) and corresponding 95% confidence interval were calculated for each database individually, as well as for combinations of MEDLINE with each other database and reference checking. Results: Inclusion of systematic reviews was higher in MEDLINE than in any other single database (mean inclusion rate 89.7%; 95% confidence interval [89.0–90.3%]). Combined with reference checking, this value increased to 93.7% [93.2–94.2%]. The best combination of two databases plus reference checking consisted of MEDLINE and Epistemonikos (99.2% [99.0–99.3%]). Stratification by Health Technology Assessment reports (97.7% [96.5–98.9%]) vs. Cochrane Overviews (100.0%) vs. non-Cochrane Overviews (99.3% [99.1–99.4%]) showed that inclusion was only slightly lower for Health Technology Assessment reports. However, MEDLINE, Epistemonikos, and reference checking remained the best combination. Among the 10/1219 systematic reviews not identified by this combination, five were published as websites rather than journals, two were included in CINAHL and Embase, and one was included in the database ERIC.Conclusions: MEDLINE and Epistemonikos, complemented by reference checking of included studies, is the best database combination to identify systematic reviews on health-related topics.

Technical Aspects of Developing Chatbots for Medical Applications: Scoping Review (Preprint)

BACKGROUND Chatbots are applications that can conduct natural language conversations with users. In the medical field, chatbots have been developed and used to serve different purposes. They provide patients with timely information that can be critical in some scenarios, such as access to mental health resources. Since the development of the first chatbot, ELIZA, in the late 1960s, much effort has followed to produce chatbots for various health purposes developed in different ways. OBJECTIVE This study aimed to explore the technical aspects and development methodologies associated with chatbots used in the medical field to explain the best methods of development and support chatbot development researchers on their future work. METHODS We searched for relevant articles in 8 literature databases (IEEE, ACM, Springer, ScienceDirect, Embase, MEDLINE, PsycINFO, and Google Scholar). We also performed forward and backward reference checking of the selected articles. Study selection was performed by one reviewer, and 50% of the selected studies were randomly checked by a second reviewer. A narrative approach was used for result synthesis. Chatbots were classified based on the different technical aspects of their development. The main chatbot components were identified in addition to the different techniques for implementing each module. RESULTS The original search returned 2481 publications, of which we identified 45 studies that matched our inclusion and exclusion criteria. The most common language of communication between users and chatbots was English (n=23). We identified 4 main modules: text understanding module, dialog management module, database layer, and text generation module. The most common technique for developing text understanding and dialogue management is the pattern matching method (n=18 and n=25, respectively). The most common text generation is fixed output (n=36). Very few studies relied on generating original output. Most studies kept a medical knowledge base to be used by the chatbot for different purposes throughout the conversations. A few studies kept conversation scripts and collected user data and previous conversations. CONCLUSIONS Many chatbots have been developed for medical use, at an increasing rate. There is a recent, apparent shift in adopting machine learning–based approaches for developing chatbot systems. Further research can be conducted to link clinical outcomes to different chatbot development techniques and technical characteristics.