Influences on the Uptake of and Engagement With Health and Well-Being Smartphone Apps: Systematic Review

Background: The public health impact of health and well-being digital interventions is dependent upon sufficient real-world uptake and engagement. Uptake is currently largely dependent on popularity indicators (eg, ranking and user ratings on app stores), which may not correspond with effectiveness, and rapid disengagement is common. Therefore, there is an urgent need to identify factors that influence uptake and engagement with health and well-being apps to inform new approaches that promote the effective use of such tools. Objective: This review aimed to understand what is known about influences on the uptake of and engagement with health and well-being smartphone apps among adults. Methods: We conducted a systematic review of quantitative, qualitative, and mixed methods studies. Studies conducted on adults were included if they focused on health and well-being smartphone apps reporting on uptake and engagement behavior. Studies identified through a systematic search in Medical Literature Analysis and Retrieval System Online, or MEDLARS Online (MEDLINE), EMBASE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsychINFO, Scopus, Cochrane library databases, DataBase systems and Logic Programming (DBLP), and Association for Computing Machinery (ACM) Digital library were screened, with a proportion screened independently by 2 authors. Data synthesis and interpretation were undertaken using a deductive iterative process. External validity checking was undertaken by an independent researcher. A narrative synthesis of the findings was structured around the components of the capability, opportunity, motivation, behavior change model and the theoretical domains framework (TDF). Results: Of the 7640 identified studies, 41 were included in the review. Factors related to uptake (U), engagement (E), or both (B) were identified. Under capability, the main factors identified were app literacy skills (B), app awareness (U), available user guidance (B), health information (E), statistical information on progress (E), well-designed reminders (E), features to reduce cognitive load (E), and self-monitoring features (E). Availability at low cost (U), positive tone, and personalization (E) were identified as physical opportunity factors, whereas recommendations for health and well-being apps (U), embedded health professional support (E), and social networking (E) possibilities were social opportunity factors. Finally, the motivation factors included positive feedback (E), available rewards (E), goal setting (E), and the perceived utility of the app (E). Conclusions: Across a wide range of populations and behaviors, 26 factors relating to capability, opportunity, and motivation appear to influence the uptake of and engagement with health and well-being smartphone apps. Our recommendations may help app developers, health app portal developers, and policy makers in the optimization of health and well-being apps

Thesaurus-assisted search term selection and query expansion: a review of user-centred studies

This paper provides a review of the literature related to the application of domain-specific thesauri in the search and retrieval process. Focusing on studies which adopt a user-centred approach, the review presents a survey of the methodologies and results from empirical studies undertaken on the use of thesauri as sources of term selection for query formulation and expansion during the search process. It summaries the ways in which domain-specific thesauri from different disciplines have been used by various types of users and how these tools aid users in the selection of search terms. The review consists of two main sections covering, firstly studies on thesaurus-aided search term selection and secondly those dealing with query expansion using thesauri. Both sections are illustrated with case studies that have adopted a user-centred approach

Health Misinformation in Search and Social Media

People increasingly rely on the Internet in order to search for and share health-related information. Indeed, searching for and sharing information about medical treatments are among the most frequent uses of online data. While this is a convenient and fast method to collect information, online sources may contain incorrect information that has the potential to cause harm, especially if people believe what they read without further research or professional medical advice. The goal of this thesis is to address the misinformation problem in two of the most commonly used online services: search engines and social media platforms. We examined how people use these platforms to search for and share health information. To achieve this, we designed controlled laboratory user studies and employed large-scale social media data analysis tools. The solutions proposed in this thesis can be used to build systems that better support people's health-related decisions. The techniques described in this thesis addressed online searching and social media sharing in the following manner. First, with respect to search engines, we aimed to determine the extent to which people can be influenced by search engine results when trying to learn about the efficacy of various medical treatments. We conducted a controlled laboratory study wherein we biased the search results towards either correct or incorrect information. We then asked participants to determine the efficacy of different medical treatments. Results showed that people were significantly influenced both positively and negatively by search results bias. More importantly, when the subjects were exposed to incorrect information, they made more incorrect decisions than when they had no interaction with the search results. Following from this work, we extended the study to gain insights into strategies people use during this decision-making process, via the think-aloud method. We found that, even with verbalization, people were strongly influenced by the search results bias. We also noted that people paid attention to what the majority states, authoritativeness, and content quality when evaluating online content. Understanding the effects of cognitive biases that can arise during online search is a complex undertaking because of the presence of unconscious biases (such as the search results ranking) that the think-aloud method fails to show. Moving to social media, we first proposed a solution to detect and track misinformation in social media. Using Zika as a case study, we developed a tool for tracking misinformation on Twitter. We collected 13 million tweets regarding the Zika outbreak and tracked rumors outlined by the World Health Organization and the Snopes fact-checking website. We incorporated health professionals, crowdsourcing, and machine learning to capture health-related rumors as well as clarification communications. In this way, we illustrated insights that the proposed tools provide into potentially harmful information on social media, allowing public health researchers and practitioners to respond with targeted and timely action. From identifying rumor-bearing tweets, we examined individuals on social media who are posting questionable health-related information, in particular those promoting cancer treatments that have been shown to be ineffective. Specifically, we studied 4,212 Twitter users who have posted about one of 139 ineffective ``treatments'' and compared them to a baseline of users generally interested in cancer. Considering features that capture user attributes, writing style, and sentiment, we built a classifier that is able to identify users prone to propagating such misinformation. This classifier achieved an accuracy of over 90%, providing a potential tool for public health officials to identify such individuals for preventive intervention

Design and pilot testing of a dietary assessment methodology for children at school

Nutrition's impact on an individual's health and sustainable consumption of food are issues that have long been on both the public and political agenda but are often viewed as two separate debates. This is surprising since many innovation projects in food service systems are concerned with both healthy eating and sustainable consumption (organic food). The relationship between them forms the background in this study. Evidence has shown that caterers serving organic food tend to also serve healthier meals than their non-organic counterparts but, so far, no studies have been carried out in school food environments. The aim of this report was to investigate and develop appropriate methods for studying the link between healthy eating practices and organic food procurement policies using Danish public elementary schools as a setting. Based on relevant scientific literature, the Danish Dietary Recommendations, and inspired by other successful studies, a self-administered questionnaire investigating children‟s eating habits was designed. After testing by an Expert Evaluation Panel and Think Aloud Interviews adjustments were integrated. Conclusion: If special attention is given to literacy skills and cognitive development, children in Danish 6th grade classes can be used as respondents in studies of the relation between food procurement policies and eating practice

Factors that influence public engagement with eHealth: a literature review

Purpose: Public engagement with eHealth is generally viewed as beneficial. However, despite the potential benefits, public engagement with eHealth services remains variable. This article explores reasons for this variability through a review of published international literature. Methods: A focused search, conducted in January 2009, of three bibliographic databases, MEDLINE, CINAHL and EMBASE, returned 2622 unique abstracts. Results: Fifty articles met the inclusion criteria for the review. Four main types of eHealth service were identified: health information on the Internet; custom-made online health information; online support; and telehealth. Public engagement with these services appears to depend on a number of factors: characteristics of users; technological issues; characteristics of eHealth services; social aspects of use; and eHealth services in use. Conclusions: Recommendations for policy makers, developers, users and health professionals, include: targeting efforts towards those underserved by eHealth; improving access; tailoring services to meet the needs of a broader range of users; exploiting opportunities for social computing; and clarifying of the role of health professionals in endorsement, promotion and facilitation

Combining multivariate statistics and the think-aloud protocol to assess Human-Computer Interaction barriers in symptom checkers

[EN] Symptom checkers are software tools that allow users to submit a set of symptoms and receive advice related to them in the form of a diagnosis list, health information or triage. The heterogeneity of their potential users and the number of different components in their user interfaces can make testing with end-users unaffordable. We designed and executed a two-phase method to test the respiratory diseases module of the symptom checker Erdusyk. Phase I consisted of an online test with a large sample of users (n = 53). In Phase I, users evaluated the system remotely and completed a questionnaire based on the Technology Acceptance Model. Principal Component Analysis was used to correlate each section of the interface with the questionnaire responses, thus identifying which areas of the user interface presented significant contributions to the technology acceptance. In the second phase, the think-aloud procedure was executed with a small number of samples (n = 15), focusing on the areas with significant contributions to analyze the reasons for such contributions. Our method was used effectively to optimize the testing of symptom checker user interfaces. The method allowed kept the cost of testing at reasonable levels by restricting the use of the think-aloud procedure while still assuring a high amount of coverage. The main barriers detected in Erdusyk were related to problems understanding time repetition patterns, the selection of levels in scales to record intensities, navigation, the quantification of some symptom attributes, and the characteristics of the symptoms. (C) 2017 Elsevier Inc. All rights reserved.This work was supported by Helse Nord [grant HST1121-13], the Faculty of Health Sciences from UIT The Arctic University of Norway [researcher code 1108], and The Research Council of Norway [grant 248150/O70]. We thank Professor Emeritus Rafael Romero-Villafranca for reviewing the statistical analysis of this paper.Marco-Ruiz, L.; Bones, E.; De La Asuncion, E.; Gabarron, E.; Aviles-Solis, JC.; Lee, E.; Traver Salcedo, V.... (2017). Combining multivariate statistics and the think-aloud protocol to assess Human-Computer Interaction barriers in symptom checkers. Journal of Biomedical Informatics. 74:104-122. https://doi.org/10.1016/j.jbi.2017.09.002S1041227

Effects of user expectations on website information comprehension and satisfaction, The

2014 Summer.Includes bibliographical references.The purpose of this qualitative study was to examine the role of users' expectations of a website information search in determining their comprehension of the information on a website and their satisfaction with the website. Interviews to determine their satisfaction with the website and think-aloud sessions were employed to gather data from participants, and open coding was used to analyze responses. The findings of this study support the previous literature on scripts with respect to the usability of the Veterans Affairs website. The study found that scripts are present before users search for information on a website. Those scripts provide users with a strategy to find needed information efficiently, but when a website fails to conform to a user's script, users experience a more difficult search and lower satisfaction with the website. More research into the particular scripts that inform users website searching strategies will help to encourage better communication on websites. Adhering to the Plain Writing Act (2010) will improve communication on the Veterans Affairs website

The GUIDES checklist: development of a tool to improve the successful use of guideline-based computerised clinical decision support

Background: Computerised decision support (CDS) based on trustworthy clinical guidelines is a key component of a learning healthcare system. Research shows that the effectiveness of CDS is mixed. Multifaceted context, system, recommendation and implementation factors may potentially affect the success of CDS interventions. This paper describes the development of a checklist that is intended to support professionals to implement CDS successfully. Methods: We developed the checklist through an iterative process that involved a systematic review of evidence and frameworks, a synthesis of the success factors identified in the review, feedback from an international expert panel that evaluated the checklist in relation to a list of desirable framework attributes, consultations with patients and healthcare consumers and pilot testing of the checklist. Results: We screened 5347 papers and selected 71 papers with relevant information on success factors for guideline-based CDS. From the selected papers, we developed a 16-factor checklist that is divided in four domains, i.e. the CDS context, content, system and implementation domains. The panel of experts evaluated the checklist positively as an instrument that could support people implementing guideline-based CDS across a wide range of settings globally. Patients and healthcare consumers identified guideline-based CDS as an important quality improvement intervention and perceived the GUIDES checklist as a suitable and useful strategy. Conclusions: The GUIDES checklist can support professionals in considering the factors that affect the success of CDS interventions. It may facilitate a deeper and more accurate understanding of the factors shaping CDS effectiveness. Relying on a structured approach may prevent that important factors are missed