Social Media for the Dissemination of Cochrane Child Health Evidence: Evaluation Study

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Abstract

Background

Health care providers value ready access to reliable synthesized information to support point-of-care decision making. Web-based communities, facilitated by the adoption of social media tools such as Facebook, Twitter, and YouTube, are increasingly being used for knowledge dissemination, bridging the gap between knowledge generation and synthesis and knowledge implementation.

Objective

Our objective was to implement and evaluate a structured social media strategy, using multiple platforms, to disseminate Cochrane Child Health evidence to health care providers caring for children.

Methods

Our social media strategy had three components: daily “tweets” using the Cochrane Child Health Twitter account, weekly WordPress blog posts, and a monthly journal club on Twitter (“tweet chat”). Each tweet, blog, and journal club shared Cochrane evidence on a child health topic. We evaluated the strategy through (1) Twitter and blog site analytics, (2) traceable link (Bitly) statistics, (3) Altmetric.com scores for promoted evidence, and (4) participant feedback. We also tracked the resources required to write the blog, tweet content, and manage the strategy.

Results

The 22-week social media strategy ran between November 2014 and April 2015. We created 25 blog posts, sent 585 tweets, and hosted 3 tweet chats. Monthly blog visits and views and Twitter account followers increased over time. During the study period, the blog received 2555 visitors and 3967 page views from a geographically diverse audience of health care providers, academics, and health care organizations. In total, 183 traceable Bitly links received 3463 clicks, and the Twitter account gained 469 new followers. The most visited and viewed blog posts included gastrointestinal topics (lactose avoidance), research on respiratory conditions (honey for cough and treatments for asthma), and maternal newborn care (skin-to-skin contact). On Twitter, popular topics were related to public health (vaccination) and pain management. We collected Altmetric.com scores for 61 studies promoted during the study period and recorded an average increase of 11 points. Research staff (n=3) contributed approximately 433 hours to promotion activities and planning (6.5 hours each per week) to implement the social media strategy, and study investigators reviewed all content (blog posts and tweets).

Conclusions

This study provides empirical evidence on the use of a coordinated social media strategy for the dissemination of evidence to professionals providing health services to children and youth. The results and lessons learned from our study provide guidance for future knowledge dissemination activities using social media tools.

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Most cited references 22

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Interventions for preventing obesity in children.

Elizabeth Waters, Andrea M de Silva-Sanigorski, Belinda Hall … (2011)

Prevention of childhood obesity is an international public health priority given the significant impact of obesity on acute and chronic diseases, general health, development and well-being. The international evidence base for strategies that governments, communities and families can implement to prevent obesity, and promote health, has been accumulating but remains unclear. This review primarily aims to update the previous Cochrane review of childhood obesity prevention research and determine the effectiveness of evaluated interventions intended to prevent obesity in children, assessed by change in Body Mass Index (BMI). Secondary aims were to examine the characteristics of the programs and strategies to answer the questions "What works for whom, why and for what cost?" The searches were re-run in CENTRAL, MEDLINE, EMBASE, PsychINFO and CINAHL in March 2010 and searched relevant websites. Non-English language papers were included and experts were contacted. The review includes data from childhood obesity prevention studies that used a controlled study design (with or without randomisation). Studies were included if they evaluated interventions, policies or programs in place for twelve weeks or more. If studies were randomised at a cluster level, 6 clusters were required. Two review authors independently extracted data and assessed the risk of bias of included studies. Data was extracted on intervention implementation, cost, equity and outcomes. Outcome measures were grouped according to whether they measured adiposity, physical activity (PA)-related behaviours or diet-related behaviours. Adverse outcomes were recorded. A meta-analysis was conducted using available BMI or standardised BMI (zBMI) score data with subgroup analysis by age group (0-5, 6-12, 13-18 years, corresponding to stages of developmental and childhood settings). This review includes 55 studies (an additional 36 studies found for this update). The majority of studies targeted children aged 6-12 years. The meta-analysis included 37 studies of 27,946 children and demonstrated that programmes were effective at reducing adiposity, although not all individual interventions were effective, and there was a high level of observed heterogeneity (I(2)=82%). Overall, children in the intervention group had a standardised mean difference in adiposity (measured as BMI or zBMI) of -0.15kg/m(2) (95% confidence interval (CI): -0.21 to -0.09). Intervention effects by age subgroups were -0.26kg/m(2) (95% CI:-0.53 to 0.00) (0-5 years), -0.15kg/m(2) (95% CI -0.23 to -0.08) (6-12 years), and -0.09kg/m(2) (95% CI -0.20 to 0.03) (13-18 years). Heterogeneity was apparent in all three age groups and could not explained by randomisation status or the type, duration or setting of the intervention. Only eight studies reported on adverse effects and no evidence of adverse outcomes such as unhealthy dieting practices, increased prevalence of underweight or body image sensitivities was found. Interventions did not appear to increase health inequalities although this was examined in fewer studies. We found strong evidence to support beneficial effects of child obesity prevention programmes on BMI, particularly for programmes targeted to children aged six to 12 years. However, given the unexplained heterogeneity and the likelihood of small study bias, these findings must be interpreted cautiously. A broad range of programme components were used in these studies and whilst it is not possible to distinguish which of these components contributed most to the beneficial effects observed, our synthesis indicates the following to be promising policies and strategies:· school curriculum that includes healthy eating, physical activity and body image· increased sessions for physical activity and the development of fundamental movement skills throughout the school week· improvements in nutritional quality of the food supply in schools· environments and cultural practices that support children eating healthier foods and being active throughout each day· support for teachers and other staff to implement health promotion strategies and activities (e.g. professional development, capacity building activities)· parent support and home activities that encourage children to be more active, eat more nutritious foods and spend less time in screen based activitiesHowever, study and evaluation designs need to be strengthened, and reporting extended to capture process and implementation factors, outcomes in relation to measures of equity, longer term outcomes, potential harms and costs.Childhood obesity prevention research must now move towards identifying how effective intervention components can be embedded within health, education and care systems and achieve long term sustainable impacts.

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How Health Care Professionals Use Social Media to Create Virtual Communities: An Integrative Review

Kaye Rolls, Margaret Hansen, Debra Jackson … (2016)

Background Prevailing health care structures and cultures restrict intraprofessional communication, inhibiting knowledge dissemination and impacting the translation of research into practice. Virtual communities may facilitate professional networking and knowledge sharing in and between health care disciplines. Objectives This study aimed to review the literature on the use of social media by health care professionals in developing virtual communities that facilitate professional networking, knowledge sharing, and evidence-informed practice. Methods An integrative literature review was conducted to identify research published between 1990 and 2015. Search strategies sourced electronic databases (PubMed, CINAHL), snowball references, and tables of contents of 3 journals. Papers that evaluated social media use by health care professionals (unless within an education framework) using any research design (except for research protocols or narrative reviews) were included. Standardized data extraction and quality assessment tools were used. Results Overall, 72 studies were included: 44 qualitative (including 2 ethnographies, 26 qualitative descriptive, and 1 Q-sort) and 20 mixed-methods studies, and 8 literature reviews. The most common methods of data collection were Web-based observation (n=39), surveys (n=23), interviews (n=11), focus groups (n=2), and diaries (n=1). Study quality was mixed. Social media studied included Listservs (n=22), Twitter (n=18), general social media (n=17), discussion forums (n=7), Web 2.0 (n=3), virtual community of practice (n=3), wiki (n=1), and Facebook (n=1). A range of health care professionals were sampled in the studies, including physicians (n=24), nurses (n=15), allied health professionals (n=14), followed by health care professionals in general (n=8), a multidisciplinary clinical specialty area (n=9), and midwives (n=2). Of 36 virtual communities, 31 were monodiscipline for a discrete clinical specialty. Population uptake by the target group ranged from 1.6% to 29% (n=4). Evaluation using related theories of “planned behavior” and the “technology acceptance model” (n=3) suggests that social media use is mediated by an individual’s positive attitude toward and accessibility of the media, which is reinforced by credible peers. The most common reason to establish a virtual community was to create a forum where relevant specialty knowledge could be shared and professional issues discussed (n=17). Most members demonstrated low posting behaviors but more frequent reading or accessing behaviors. The most common Web-based activity was request for and supply of specialty-specific clinical information. This knowledge sharing is facilitated by a Web-based culture of collectivism, reciprocity, and a respectful noncompetitive environment. Findings suggest that health care professionals view virtual communities as valuable knowledge portals for sourcing clinically relevant and quality information that enables them to make more informed practice decisions. Conclusions There is emerging evidence that health care professionals use social media to develop virtual communities to share domain knowledge. These virtual communities, however, currently reflect tribal behaviors of clinicians that may continue to limit knowledge sharing. Further research is required to evaluate the effects of social media on knowledge distribution in clinical practice and importantly whether patient outcomes are significantly improved.

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How Web 2.0 is changing medicine.

Dean Giustini (2006)

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Author and article information

Contributors

Michele P Dyson:

Alberta Research Centre for Health EvidenceUniversity of Alberta4-474 Edmonton Clinic Health Academy, 11405-87 Avenue NWEdmonton, AB, T6G 1C9Canada1 780 492 12411 780 248 5627mdyson@ualberta.ca

ORCID: http://orcid.org/0000-0003-4856-2283

Journal

Journal ID (nlm-ta): J Med Internet Res

Journal ID (iso-abbrev): J. Med. Internet Res

Journal ID (publisher-id): JMIR

Title: Journal of Medical Internet Research

Publisher: JMIR Publications (Toronto, Canada )

ISSN (Print): 1439-4456

ISSN (Electronic): 1438-8871

Publication date Collection: September 2017

Publication date (Electronic): 01 September 2017

Volume: 19

Issue: 9

Electronic Location Identifier: e308

Affiliations

[1] ¹ Alberta Research Centre for Health Evidence University of Alberta Edmonton, AB Canada

[2] ² Department of Pediatrics University of Alberta Edmonton, AB Canada

[3] ³ Cochrane Child Health University of Alberta Edmonton, AB Canada

[4] ⁴ Faculty of Medicine Universidade de Lisboa Lisbon Portugal

[5] ⁵ Cochrane Portugal Universidade de Lisboa Lisbon Portugal

Author notes

Corresponding Author: Michele P Dyson mdyson@ 123456ualberta.ca

Author information

Michele P Dyson http://orcid.org/0000-0003-4856-2283

Amanda S Newton http://orcid.org/0000-0003-3020-674X

Kassi Shave http://orcid.org/0000-0002-3986-5322

Robin M Featherstone http://orcid.org/0000-0003-2517-2258

Denise Thomson http://orcid.org/0000-0002-4972-5331

Aireen Wingert http://orcid.org/0000-0002-8024-5221

Ricardo M Fernandes http://orcid.org/0000-0002-7253-6475

Lisa Hartling http://orcid.org/0000-0001-8341-3991

Article

Publisher ID: v19i9e308

DOI: 10.2196/jmir.7819

PMC ID: 5600964

PubMed ID: 28864427

SO-VID: e21e4006-e915-4f19-b775-129cd6e074bc

Copyright © ©Michele P Dyson, Amanda S Newton, Kassi Shave, Robin M Featherstone, Denise Thomson, Aireen Wingert, Ricardo M Fernandes, Lisa Hartling. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 01.09.2017.

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

History

Date received : 3 April 2017

Date revision requested : 18 May 2017

Date revision received : 23 June 2017

Date accepted : 10 July 2017

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