Online Journal of Public Health Informatics 

About: Online Journal of Public Health Informatics is an academic journal published by University of Illinois at Chicago. The journal publishes majorly in the area(s): Public health & Population. It has an ISSN identifier of 1947-2579. It is also open access. Over the lifetime, 1095 publications have been published receiving 5233 citations. The journal is also known as: OJPHI & Online J Public Health Inform.

Mobile medical and health apps: state of the art, concerns, regulatory control and certification

Abstract: This paper examines the state of the art in mobile clinical and health-related apps. A 2012 estimate puts the number of health-related apps at no fewer than 40,000, as healthcare professionals and consumers continue to express concerns about the quality of many apps, calling for some form of app regulatory control or certification to be put in place. We describe the range of apps on offer as of 2013, and then present a brief survey of evaluation studies of medical and health-related apps that have been conducted to date, covering a range of clinical disciplines and topics. Our survey includes studies that highlighted risks, negative issues and worrying deficiencies in existing apps. We discuss the concept of ‘apps as a medical device’ and the relevant regulatory controls that apply in USA and Europe, offering examples of apps that have been formally approved using these mechanisms. We describe the online Health Apps Library run by the National Health Service in England and the calls for a vetted medical and health app store. We discuss the ingredients for successful apps beyond the rather narrow definition of ‘apps as a medical device’. These ingredients cover app content quality, usability, the need to match apps to consumers’ general and health literacy levels, device connectivity standards (for apps that connect to glucometers, blood pressure monitors, etc.), as well as app security and user privacy. ‘Happtique Health App Certification Program’ (HACP), a voluntary app certification scheme, successfully captures most of these desiderata, but is solely focused on apps targeting the US market. HACP, while very welcome, is in ways reminiscent of the early days of the Web, when many “similar” quality benchmarking tools and codes of conduct for information publishers were proposed to appraise and rate online medical and health information. It is probably impossible to rate and police every app on offer today, much like in those early days of the Web, when people quickly realised the same regarding informational Web pages. The best first line of defence was, is, and will always be to educate consumers regarding the potentially harmful content of (some) apps.

Towards an Effective Health Interventions Design: An Extension of the Health Belief Model

Abstract: Introduction: The recent years have witnessed a continuous increase in lifestyle related health challenges around the world. As a result, researchers and health practitioners have focused on promoting healthy behavior using various behavior change interventions. The designs of most of these interventions are informed by health behavior models and theories adapted from various disciplines. Several health behavior theories have been used to inform health intervention designs, such as the Theory of Planned Behavior, the Transtheoretical Mode, and the Health Belief Model (HBM). However, the Health Belief Model (HBM), developed in the 1950s to investigate why people fail to undertake preventive health measures, remains one of the most widely employed theories of health behavior. However, the effectiveness of this model is limited. The first limitation is the low predictive capacity (R2 < 0.21 on average) of existing HBM’s variables coupled with the small effect size of individual variables. The second is lack of clear rules of combination and relationship between the individual variables. In this paper, we propose a solution that aims at addressing these limitations as follows: (1) we extended the Health Belief Model by introducing four new variables: Self-identity, Perceived Importance, Consideration of Future Consequences, and Concern for Appearance as possible determinants of healthy behavior. (2) We exhaustively explored the relationships/interactions between the HBM variables and their effect size. (3) We tested the validity of both our proposed extended model and the original HBM on healthy eating behavior. Finally, we compared the predictive capacity of the original HBM model and our extended model. Methods: To achieve the objective of this paper, we conducted a quantitative study of 576 participants’ eating behavior. Data for this study were collected over a period of one year (from August 2011 to August 2012). The questionnaire consisted of validated scales assessing the HBM determinants – perceived benefit, barrier, susceptibility, severity, cue to action, and self-efficacy – using 7-point Likert scale. We also assessed other health determinants such as consideration of future consequences, self-identity, Concern for appearance and perceived importance. To analyses our data, we employed factor analysis and Partial Least Square Structural Equation Model (PLS-SEM) to exhaustively explore the interaction/relationship between the determinants and healthy eating behavior. We tested for the validity of both our proposed extended model and the original HBM on healthy eating behavior. Finally, we compared the predictive capacity of the original HBM model and our extended model and investigated possible mediating effects. Results: The results show that the three newly added determinants are better predictors of healthy behavior. Our extended HBM model lead to approximately 78% increase (from 40 to 71%) in predictive capacity compared to the old model. This shows the suitability of our extended HBM for use in predicting healthy behavior and in informing health intervention design. The results from examining possible relationships between the determinants in our model lead to an interesting discovery of some mediating relationships between the HBM’s determinants, therefore, shedding light on some possible combinations of determinants that could be employed by intervention designers to increase the effectiveness of their design. Conclusion: Consideration of future consequences, self-identity, concern for appearance, perceived importance, self-efficacy, perceived susceptibility are significant determinants of healthy eating behavior that can be manipulated by healthy eating intervention design. Most importantly, the result from our model established the existence of some mediating relationships among the determinants. The knowledge of both the direct and indirect relationships sheds some light on the possible combination rules

Effective uses of social media in public health and medicine: a systematic review of systematic reviews

Abstract: Introduction: Research examining the effective uses of social media (SM) in public health and medicine, especially in the form of systematic r e views (SRs), has grown considerably in the past decade To our knowledge, no comprehensive synthesis of this literature has been conducted to date Aims and methods : To conduct a systematic review of systematic reviews of the benefits and harms (“effects”) of SM tools and platforms (such as Twitter and Facebook) in public health and medicine To perform a synthesis of this literature and create a ‘living systematic review’ Results: Forty-two (42) high-quality SRs were examined Overall, evidence of SM’s effectiveness in public health and medicine was judged to be minimal However, qualitative benefits for patients are seen in improved psychosocial support and psychological functioning Health professionals benefited from better peer-to-peer communication and lifelong learning Harms on all groups include the impact of SM on mental health, privacy, confidentiality and information reliability Conclusions: A range of negatives and positives of SM in public health and medicine are seen in the SR literature but definitive conclusions cannot be made at this time Clearly better research designs are needed to measure the effectiveness of social technologies For ongoing updates, see the wiki “Effective uses of social media in health: a living systematic review of systematic reviews” http://hlwikislaisubcca/indexphp/Effective_uses_of_social_media_in_healthcare:_a_living_systematic_review_of_reviews

Google Scholar is not enough to be used alone for systematic reviews.

Abstract: Background Google Scholar (GS) has been noted for its ability to search broadly for important references in the literature. Gehanno et al. recently examined GS in their study: ‘Is Google scholar enough to be used alone for systematic reviews?’ In this paper, we revisit this important question, and some of Gehanno et al.’s other findings in evaluating the academic search engine. Methods The authors searched for a recent systematic review (SR) of comparable size to run search tests similar to those in Gehanno et al. We selected Chou et al. (2013) contacting the authors for a list of publications they found in their SR on social media in health. We queried GS for each of those 506 titles (in quotes ""), one by one. When GS failed to retrieve a paper, or produced too many results, we used the allintitle: command to find papers with the same title. Results Google Scholar produced records for ~95% of the papers cited by Chou et al. (n=476/506). A few of the 30 papers that were not in GS were later retrieved via PubMed and even regular Google Search. But due to its different structure, we could not run searches in GS that were originally performed by Chou et al. in PubMed, Web of Science, Scopus and PsycINFO®. Identifying 506 papers in GS was an inefficient process, especially for papers using similar search terms. Conclusions Has Google Scholar improved enough to be used alone in searching for systematic reviews? No. GS’ constantly-changing content, algorithms and database structure make it a poor choice for systematic reviews. Looking for papers when you know their titles is a far different issue from discovering them initially. Further research is needed to determine when and how (and for what purposes) GS can be used alone. Google should provide details about GS’ database coverage and improve its interface (e.g., with semantic search filters, stored searching, etc.) . Perhaps then it will be an appropriate choice for systematic reviews.

Health Information Seeking and Social Media Use on the Internet among People with Diabetes.

Abstract: Objective: To understand the online health information-seeking behaviors of people with diabetes, determine whether they utilize online social media, and to see if they would be willing to use these sites to discuss health information. Design and sample: 57 participants were recruited from the South-Eastern US between June and October 2009 and asked to take an online survey. Participants were asked demographic data, information about their diabetes, and Internet and online social networking use. Results: The majority of participants utilize popular online social networking sites and many would be willing to discuss health information online. Conclusions: Popular online social networks and online social media have the potential to serve as important platforms for nursing and public health interventions. In particular, these venues may serve as appropriate tools to reach minority populations and people in rural areas. Further research is needed to understand how we can use these Internet sites to reach people directly where they are and for delivering diabetes education and support.