1
|
Carpenter SM, Greer ZM, Newman R, Murphy SA, Shetty V, Nahum-Shani I. Developing Message Strategies to Engage Racial and Ethnic Minority Groups in Digital Oral Self-Care Interventions: Participatory Co-Design Approach. JMIR Form Res 2023; 7:e49179. [PMID: 38079204 PMCID: PMC10750234 DOI: 10.2196/49179] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 08/01/2023] [Accepted: 08/25/2023] [Indexed: 12/28/2023] Open
Abstract
BACKGROUND The prevention of oral health diseases is a key public health issue and a major challenge for racial and ethnic minority groups, who often face barriers in accessing dental care. Daily toothbrushing is an important self-care behavior necessary for sustaining good oral health, yet engagement in regular brushing remains a challenge. Identifying strategies to promote engagement in regular oral self-care behaviors among populations at risk of poor oral health is critical. OBJECTIVE The formative research described here focused on creating messages for a digital oral self-care intervention targeting a racially and ethnically diverse population. Theoretically grounded strategies (reciprocity, reciprocity-by-proxy, and curiosity) were used to promote engagement in 3 aspects: oral self-care behaviors, an oral care smartphone app, and digital messages. A web-based participatory co-design approach was used to develop messages that are resource efficient, appealing, and novel; this approach involved dental experts, individuals from the general population, and individuals from the target population-dental patients from predominantly low-income racial and ethnic minority groups. Given that many individuals from racially and ethnically diverse populations face anonymity and confidentiality concerns when participating in research, we used an approach to message development that aimed to mitigate these concerns. METHODS Messages were initially developed with feedback from dental experts and Amazon Mechanical Turk workers. Dental patients were then recruited for 2 facilitator-mediated group webinar sessions held over Zoom (Zoom Video Communications; session 1: n=13; session 2: n=7), in which they provided both quantitative ratings and qualitative feedback on the messages. Participants interacted with the facilitator through Zoom polls and a chat window that was anonymous to other participants. Participants did not directly interact with each other, and the facilitator mediated sessions by verbally asking for message feedback and sharing key suggestions with the group for additional feedback. This approach plausibly enhanced participant anonymity and confidentiality during the sessions. RESULTS Participants rated messages highly in terms of liking (overall rating: mean 2.63, SD 0.58; reciprocity: mean 2.65, SD 0.52; reciprocity-by-proxy: mean 2.58, SD 0.53; curiosity involving interactive oral health questions and answers: mean 2.45, SD 0.69; curiosity involving tailored brushing feedback: mean 2.77, SD 0.48) on a scale ranging from 1 (do not like it) to 3 (like it). Qualitative feedback indicated that the participants preferred messages that were straightforward, enthusiastic, conversational, relatable, and authentic. CONCLUSIONS This formative research has the potential to guide the design of messages for future digital health behavioral interventions targeting individuals from diverse racial and ethnic populations. Insights emphasize the importance of identifying key stimuli and tasks that require engagement, gathering multiple perspectives during message development, and using new approaches for collecting both quantitative and qualitative data while mitigating anonymity and confidentiality concerns.
Collapse
Affiliation(s)
- Stephanie M Carpenter
- College of Health Solutions, Arizona State University, Phoenix, AZ, United States
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, United States
| | - Zara M Greer
- Oral and Maxillofacial Surgery, School of Dentistry, University of California, Los Angeles, Los Angeles, CA, United States
| | - Rebecca Newman
- Oral and Maxillofacial Surgery, School of Dentistry, University of California, Los Angeles, Los Angeles, CA, United States
| | - Susan A Murphy
- Department of Statistics, Harvard University, Cambridge, MA, United States
- Department of Computer Science, Harvard University, Cambridge, MA, United States
| | - Vivek Shetty
- Oral and Maxillofacial Surgery, School of Dentistry, University of California, Los Angeles, Los Angeles, CA, United States
| | - Inbal Nahum-Shani
- Institute for Social Research, University of Michigan, Ann Arbor, MI, United States
| |
Collapse
|
2
|
Mallafré-Larrosa M, Papi G, Trilla A, Ritchie D. Development and Promotion of an mHealth App for Adolescents Based on the European Code Against Cancer: Retrospective Cohort Study. JMIR Cancer 2023; 9:e48040. [PMID: 38015612 DOI: 10.2196/48040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Revised: 09/09/2023] [Accepted: 10/27/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND Mobile health technologies, underpinned by scientific evidence and ethical standards, exhibit considerable promise and potential in actively engaging consumers and patients while also assisting health care providers in delivering cancer prevention and care services. The WASABY mobile app was conceived as an innovative, evidence-based mobile health tool aimed at disseminating age-appropriate messages from the European Code Against Cancer (ECAC) to adolescents across Europe. OBJECTIVE This study aims to assess the outcomes of the design, development, and promotion of the WASABY app through a 3-pronged evaluation framework that encompasses data on social media promotion, app store traffic, and user engagement. METHODS The WASABY app's content, cocreated with cancer-focused civil society organizations across 6 European countries, drew upon scientific evidence from the ECAC. The app's 10 modules were designed using the health belief model and a gamification conceptual framework characterized by spaced repetition learning techniques, refined through 2 rounds of testing. To evaluate the effectiveness of the app, we conducted a retrospective cohort study using the WASABY app's user database registered from February 4 to June 30, 2021, using a 3-pronged assessment framework: social media promotion, app store traffic, and user engagement. Descriptive statistics and association analyses explored the relationship between sociodemographic variables and user performance analytics. RESULTS After extensive promotion on various social media platforms and subsequent traffic to the Apple App and Google Play stores, a sample of 748 users aged between 14 and 19 years was included in the study cohort. The selected sample exhibited a mean age of 16.08 (SD 1.28) years and was characterized by a predominant representation of female users (499/748, 66.7%). Most app users identified themselves as nonsmokers (689/748, 92.1%), reported either no or infrequent alcohol consumption (432/748, 57.8% and 250/748, 33.4%, respectively), and indicated being physically active for 1 to 5 hours per week (505/748, 67.5%). In aggregate, the app's content garnered substantial interest, as evidenced by 40.8% (305/748) of users visiting each of the 10 individual modules. Notably, sex and smoking habits emerged as predictors of app completion rates; specifically, male and smoking users demonstrated a decreased likelihood of successfully completing the app's content (odds ratio 0.878, 95% CI 0.809-0.954 and odds ratio 0.835, 95% CI 0.735-0.949, respectively). CONCLUSIONS The development and promotion of the WASABY app presents a valuable case study, illustrating the effective dissemination of evidence-based recommendations on cancer prevention within the ECAC through an innovative mobile app aimed at European adolescents. The data derived from this study provide insightful findings for the implementation of Europe's Beating Cancer Plan, particularly the creation of the EU Mobile App for Cancer Prevention.
Collapse
Affiliation(s)
- Meritxell Mallafré-Larrosa
- Association of European Cancer Leagues, Brussels, Belgium
- Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - Ginevra Papi
- Association of European Cancer Leagues, Brussels, Belgium
| | - Antoni Trilla
- Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - David Ritchie
- Association of European Cancer Leagues, Brussels, Belgium
| |
Collapse
|
3
|
Ghantasala RP, Albers N, Penfornis KM, van Vliet MHM, Brinkman WP. Feasibility of generating structured motivational messages for tailored physical activity coaching. Front Digit Health 2023; 5:1215187. [PMID: 37771819 PMCID: PMC10523307 DOI: 10.3389/fdgth.2023.1215187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 08/25/2023] [Indexed: 09/30/2023] Open
Abstract
Tailored motivational messages are helpful to motivate people in eHealth applications for increasing physical activity, but it is not sufficiently clear how such messages can be effectively generated in advance. We, therefore, put forward a theory-driven approach to generating tailored motivational messages for eHealth applications for behavior change, and we examine its feasibility by assessing how motivating the resulting messages are perceived. For this, we designed motivational messages with a specific structure that was based on an adaptation of an existing ontology for tailoring motivational messages in the context of physical activity. To obtain tailored messages, experts in health psychology and coaching successfully wrote messages with this structure for personas in scenarios that differed with regard to the persona's mood, self-efficacy, and progress. Based on an experiment in which 60 participants each rated the perceived motivational impact of six generic and six tailored messages based on scenarios, we found credible support for our hypothesis that messages tailored to mood, self-efficacy, and progress are perceived as more motivating. A thematic analysis of people's free-text responses about what they found motivating and demotivating about motivational messages further supports the use of tailored messages, as well as messages that are encouraging and empathetic, give feedback about people's progress, and mention the benefits of physical activity. To aid future work on motivational messages, we make our motivational messages and corresponding scenarios publicly available.
Collapse
Affiliation(s)
- Ramya P. Ghantasala
- Department of Intelligent Systems, Delft University of Technology, Delft, Netherlands
| | - Nele Albers
- Department of Intelligent Systems, Delft University of Technology, Delft, Netherlands
| | - Kristell M. Penfornis
- Unit Health Medical and Neuropsychology, Institute of Psychology, Leiden University, Leiden, Netherlands
- Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands
| | - Milon H. M. van Vliet
- Public Health and Primary Care, Leiden University Medical Center, Leiden, Netherlands
- National eHealth Living Lab, Leiden University Medical Center, Leiden, Netherlands
| | - Willem-Paul Brinkman
- Department of Intelligent Systems, Delft University of Technology, Delft, Netherlands
| |
Collapse
|
4
|
Cai Y, Yu F, Kumar M, Gladney R, Mostafa J. Health Recommender Systems Development, Usage, and Evaluation from 2010 to 2022: A Scoping Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:15115. [PMID: 36429832 PMCID: PMC9690602 DOI: 10.3390/ijerph192215115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 11/10/2022] [Accepted: 11/13/2022] [Indexed: 06/16/2023]
Abstract
A health recommender system (HRS) provides a user with personalized medical information based on the user's health profile. This scoping review aims to identify and summarize the HRS development in the most recent decade by focusing on five key aspects: health domain, user, recommended item, recommendation technology, and system evaluation. We searched PubMed, ACM Digital Library, IEEE Xplore, Web of Science, and Scopus databases for English literature published between 2010 and 2022. Our study selection and data extraction followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. The following are the primary results: sixty-three studies met the eligibility criteria and were included in the data analysis. These studies involved twenty-four health domains, with both patients and the general public as target users and ten major recommended items. The most adopted algorithm of recommendation technologies was the knowledge-based approach. In addition, fifty-nine studies reported system evaluations, in which two types of evaluation methods and three categories of metrics were applied. However, despite existing research progress on HRSs, the health domains, recommended items, and sample size of system evaluation have been limited. In the future, HRS research shall focus on dynamic user modelling, utilizing open-source knowledge bases, and evaluating the efficacy of HRSs using a large sample size. In conclusion, this study summarized the research activities and evidence pertinent to HRSs in the most recent ten years and identified gaps in the existing research landscape. Further work shall address the gaps and continue improving the performance of HRSs to empower users in terms of healthcare decision making and self-management.
Collapse
Affiliation(s)
- Yao Cai
- School of Information and Library Science, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China
| | - Fei Yu
- School of Information and Library Science, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Health Informatics Program, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Manish Kumar
- Public Health Leadership Program, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Roderick Gladney
- Carolina Health Informatics Program, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Javed Mostafa
- School of Information and Library Science, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Health Informatics Program, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| |
Collapse
|
5
|
Escrivá-Martínez T, Vara MD, Czeraniuk N, Denis M, Núñez-Benjumea FJ, Fernández-Luque L, Jiménez-Díaz A, Traver V, Llull JJ, Martínez-Millana A, Garcés-Ferrer J, Miragall M, Herrero R, Enríquez A, Schaefer V, Cervera-Torres S, Villasanti C, Cabral CV, Fernández I, Baños RM. mHealth intervention to improve quality of life in patients with chronic diseases during the COVID-19 crisis in Paraguay: A study protocol for a randomized controlled trial. PLoS One 2022; 17:e0273290. [PMID: 36346807 PMCID: PMC9642890 DOI: 10.1371/journal.pone.0273290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 07/26/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Patients with chronic disease represent an at-risk group in the face of the COVID-19 crisis as they need to regularly monitor their lifestyle and emotional management. Coping with the illness becomes a challenge due to supply problems and lack of access to health care facilities. It is expected these limitations, along with lockdown and social distancing measures, have affected the routine disease management of these patients, being more pronounced in low- and middle-income countries with a flawed health care system. OBJECTIVES The purpose of this study is to describe a protocol for a randomized controlled trial to test the efficacy of the Adhera® MejoraCare Digital Program, an mHealth intervention aimed at improving the quality of life of patients with chronic diseases during the COVID-19 outbreak in Paraguay. METHOD A two-arm randomized controlled trial will be carried out, with repeated measures (baseline, 1-month, 3-month, 6-month, and 12-month) under two conditions: Adhera® MejoraCare Digital Program or waiting list. The primary outcome is a change in the quality of life on the EuroQol 5-Dimensions 3-Levels Questionnaire (EQ-5D-3L). Other secondary outcomes, as the effect on anxiety and health empowerment, will be considered. All participants must be 18 years of age or older and meet the criteria for chronic disease. A total of 96 participants will be recruited (48 per arm). CONCLUSIONS It is expected that the Adhera® MejoraCare Digital Program will show significant improvements in quality of life and emotional distress compared to the waiting list condition. Additionally, it is hypothesized that this intervention will be positively evaluated by the participants in terms of usability and satisfaction. The findings will provide new insights into the viability and efficacy of mHealth solutions for chronic disease management in developing countries and in times of pandemic. TRIAL REGISTRATION ClinicalTrials.gov NCT04659746.
Collapse
Affiliation(s)
- Tamara Escrivá-Martínez
- Polibienestar Research Institute, University of Valencia, Valencia, Spain
- CIBER-Obn Physiopathology of Obesity and Nutrition, Instituto de Salud Carlos III, Madrid, Spain
| | - Mª Dolores Vara
- Polibienestar Research Institute, University of Valencia, Valencia, Spain
- CIBER-Obn Physiopathology of Obesity and Nutrition, Instituto de Salud Carlos III, Madrid, Spain
| | - Nadia Czeraniuk
- Centro de Investigación y Documentación, Universidad Autónoma de Encarnación, Encarnación, Paraguay
| | - Matías Denis
- Centro de Investigación y Documentación, Universidad Autónoma de Encarnación, Encarnación, Paraguay
| | | | | | - Alba Jiménez-Díaz
- Department of Personality, Evaluation and Psychological Treatment, Faculty of Psychology, University of Valencia, Valencia, Spain
| | - Vicente Traver
- ITACA Institute, Polytechnic University of Valencia, Valencia, Spain
| | - Juan José Llull
- ITACA Institute, Polytechnic University of Valencia, Valencia, Spain
| | | | | | - Marta Miragall
- CIBER-Obn Physiopathology of Obesity and Nutrition, Instituto de Salud Carlos III, Madrid, Spain
- Adhera Health, Inc, Palo Alto, CA, United States of America
| | - Rocío Herrero
- CIBER-Obn Physiopathology of Obesity and Nutrition, Instituto de Salud Carlos III, Madrid, Spain
- Department of Psychology and Sociology, Faculty of Social and Human Sciences, University of Zaragoza, Teruel, Spain
| | - Analía Enríquez
- Centro de Investigación y Documentación, Universidad Autónoma de Encarnación, Encarnación, Paraguay
| | - Verena Schaefer
- Instituto Superior de Educación Divina Esperanza, Encarnación, Paraguay
| | | | - Cecilia Villasanti
- Centro de Investigación y Documentación, Universidad Autónoma de Encarnación, Encarnación, Paraguay
| | | | - Irene Fernández
- Department of Methodology for the Behavioral Sciences, Faculty of Psychology, University of Valencia, Valencia, Spain
| | - Rosa Mª Baños
- Polibienestar Research Institute, University of Valencia, Valencia, Spain
- CIBER-Obn Physiopathology of Obesity and Nutrition, Instituto de Salud Carlos III, Madrid, Spain
- Department of Personality, Evaluation and Psychological Treatment, Faculty of Psychology, University of Valencia, Valencia, Spain
| |
Collapse
|
6
|
Oguntoye AO, Eades NT, Aldossary D, Kuenzli G, Gehling G, Ezenwa MO, Johnson-Mallard V, Yao Y, Gallo AM, Wilkie DJ. Tailored Parenting Plans of Young Adults With Sickle Cell Disease or Sickle Cell Trait. Comput Inform Nurs 2022; 40:633-640. [PMID: 35930415 PMCID: PMC9464668 DOI: 10.1097/cin.0000000000000933] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Our study purpose was to evaluate the variation and accuracy of tailored parenting plans individually generated as a supplement to reproductive health education on the genetic inheritance of sickle cell disease or sickle cell trait. We present a secondary data analysis of experimental group data from a randomized controlled trial. Participants completed the valid and reliable Internet-based Sickle Cell Reproductive Health Knowledge Parenting Intent Questionnaire. We created a computerized algorithm that used participants' responses to generate tailored parenting plans based on their parenting preferences and partner's sickle cell status. Thirty-one different parenting plans were generated to meet the variety in the participants' preferences. The most frequently generated plan was for participants with sickle cell disease who had a partner with hemoglobin AA, who wanted to be a parent, was not likely to be pregnant, and wanted their child to be sickle cell disease free. More than half of the participants required alteration in their reproductive behavior to achieve their parenting goals. Findings provide insight into the variety and accuracy of computer algorithm-generated parenting plans, which could further guide refinement of the algorithm to produce patient-centered, tailored parenting plans supplemental to Internet-based genetic inheritance education.
Collapse
Affiliation(s)
- Anne O Oguntoye
- Author Affiliations: College of Nursing, University of Florida (Drs Oguntoye, Eades, Ezenwa, Johnson-Mallard, Yao, and Wilkie; Mrs Aldossary, Ms Kuenzli, and Mrs Gehling), Gainesville; and College of Nursing, University of Illinois at Chicago (Dr Gallo)
| | | | | | | | | | | | | | | | | | | |
Collapse
|
7
|
Magee MR, Gholamrezaei A, McNeilage AG, Sim A, Dwyer L, Ferreira ML, Darnall BD, Glare P, Ashton-James CE. A DIGITAL VIDEO AND TEXT MESSAGING INTERVENTION TO SUPPORT PEOPLE WITH CHRONIC PAIN DURING OPIOID TAPERING: CONTENT DEVELOPMENT USING CO-DESIGN (Preprint). JMIR Form Res 2022; 6:e40507. [DOI: 10.2196/40507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 09/05/2022] [Accepted: 09/06/2022] [Indexed: 11/13/2022] Open
|
8
|
Applying Collective Intelligence in Health Recommender Systems for Smoking Cessation: A Comparison Trial. ELECTRONICS 2022. [DOI: 10.3390/electronics11081219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Background: Health recommender systems (HRSs) are intelligent systems that can be used to tailor digital health interventions. We compared two HRSs to assess their impact providing smoking cessation support messages. Methods: Smokers who downloaded a mobile app to support smoking abstinence were randomly assigned to two interventions. They received personalized, ratable motivational messages on the app. The first intervention had a knowledge-based HRS (n = 181): it selected random messages from a subset matching the users’ demographics and smoking habits. The second intervention had a hybrid HRS using collective intelligence (n = 190): it selected messages applying the knowledge-based filter first, and then chose the ones with higher ratings provided by other similar users in the system. Both interventions were compared on: (a) message appreciation, (b) engagement with the system, and (c) one’s own self-reported smoking cessation status, as indicated by the last seven-day point prevalence report in different time intervals during a period of six months. Results: Both interventions had similar message appreciation, number of rated messages, and abstinence results. The knowledge-based HRS achieved a significantly higher number of active days, number of abstinence reports, and better abstinence results. The hybrid algorithm led to more quitting attempts in participants who completed their user profiles.
Collapse
|
9
|
Rodriguez DV, Lawrence K, Luu S, Yu JL, Feldthouse DM, Gonzalez J, Mann D. Development of a computer-aided text message platform for user engagement with a digital Diabetes Prevention Program: a case study. J Am Med Inform Assoc 2021; 29:155-162. [PMID: 34664647 PMCID: PMC8714274 DOI: 10.1093/jamia/ocab206] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 09/03/2021] [Accepted: 09/09/2021] [Indexed: 11/12/2022] Open
Abstract
Digital Diabetes Prevention Programs (dDPP) are novel mHealth applications that leverage digital features such as tracking and messaging to support behavior change for diabetes prevention. Despite their clinical effectiveness, long-term engagement to these programs remains a challenge, creating barriers to adherence and meaningful health outcomes. We partnered with a dDPP vendor to develop a personalized automatic message system (PAMS) to promote user engagement to the dDPP platform by sending messages on behalf of their primary care provider. PAMS innovates by integrating into clinical workflows. User-centered design (UCD) methodologies in the form of iterative cycles of focus groups, user interviews, design workshops, and other core UCD activities were utilized to defined PAMS requirements. PAMS uses computational tools to deliver theory-based, automated, tailored messages, and content to support patient use of dDPP. In this article, we discuss the design and development of our system, including key requirements and features, the technical architecture and build, and preliminary user testing.
Collapse
Affiliation(s)
- Danissa V Rodriguez
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Katharine Lawrence
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Son Luu
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Jonathan L Yu
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Dawn M Feldthouse
- Medical Center Information Technology, NYU Langone Health, New York, New York, USA
| | - Javier Gonzalez
- Medical Center Information Technology, NYU Langone Health, New York, New York, USA
| | - Devin Mann
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
- Medical Center Information Technology, NYU Langone Health, New York, New York, USA
| |
Collapse
|
10
|
Viana JN, Edney S, Gondalia S, Mauch C, Sellak H, O'Callaghan N, Ryan JC. Trends and gaps in precision health research: a scoping review. BMJ Open 2021; 11:e056938. [PMID: 34697128 PMCID: PMC8547511 DOI: 10.1136/bmjopen-2021-056938] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 10/08/2021] [Indexed: 11/09/2022] Open
Abstract
OBJECTIVE To determine progress and gaps in global precision health research, examining whether precision health studies integrate multiple types of information for health promotion or restoration. DESIGN Scoping review. DATA SOURCES Searches in Medline (OVID), PsycINFO (OVID), Embase, Scopus, Web of Science and grey literature (Google Scholar) were carried out in June 2020. ELIGIBILITY CRITERIA Studies should describe original precision health research; involve human participants, datasets or samples; and collect health-related information. Reviews, editorial articles, conference abstracts or posters, dissertations and articles not published in English were excluded. DATA EXTRACTION AND SYNTHESIS The following data were extracted in independent duplicate: author details, study objectives, technology developed, study design, health conditions addressed, precision health focus, data collected for personalisation, participant characteristics and sentence defining 'precision health'. Quantitative and qualitative data were summarised narratively in text and presented in tables and graphs. RESULTS After screening 8053 articles, 225 studies were reviewed. Almost half (105/225, 46.7%) of the studies focused on developing an intervention, primarily digital health promotion tools (80/225, 35.6%). Only 28.9% (65/225) of the studies used at least four types of participant data for tailoring, with personalisation usually based on behavioural (108/225, 48%), sociodemographic (100/225, 44.4%) and/or clinical (98/225, 43.6%) information. Participant median age was 48 years old (IQR 28-61), and the top three health conditions addressed were metabolic disorders (35/225, 15.6%), cardiovascular disease (29/225, 12.9%) and cancer (26/225, 11.6%). Only 68% of the studies (153/225) reported participants' gender, 38.7% (87/225) provided participants' race/ethnicity, and 20.4% (46/225) included people from socioeconomically disadvantaged backgrounds. More than 57% of the articles (130/225) have authors from only one discipline. CONCLUSIONS Although there is a growing number of precision health studies that test or develop interventions, there is a significant gap in the integration of multiple data types, systematic intervention assessment using randomised controlled trials and reporting of participant gender and ethnicity. Greater interdisciplinary collaboration is needed to gather multiple data types; collectively analyse big and complex data; and provide interventions that restore, maintain and/or promote good health for all, from birth to old age.
Collapse
Affiliation(s)
- John Noel Viana
- Responsible Innovation Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Queensland, Australia
- Australian National Centre for the Public Awareness of Science, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Sarah Edney
- Physical Activity and Nutrition Determinants in Asia (PANDA) programme, Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Shakuntla Gondalia
- Precision Health Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
- Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
| | - Chelsea Mauch
- Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
| | - Hamza Sellak
- Precision Health Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
- Data61, Commonwealth Scientific and Industrial Research Organisation, Melbourne, Victoria, Australia
| | - Nathan O'Callaghan
- Precision Health Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
| | - Jillian C Ryan
- Precision Health Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
- Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia
| |
Collapse
|
11
|
Borchers P, Piller S, Böhme M, Voigt K, Bergmann A. Need-based care of multi-morbid patients - supporting general practitioners with algorithm-generated recommendations of healthcare services (telemedicine-project ATMoSPHÄRE). BMC FAMILY PRACTICE 2021; 22:198. [PMID: 34625053 PMCID: PMC8499564 DOI: 10.1186/s12875-021-01537-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 09/07/2021] [Indexed: 11/23/2022]
Abstract
Background The patient-oriented and need-based care of multi-morbid patients with healthcare services and assistive products can be a highly complex task for the general practitioners (GPs). An algorithm-based digital recommendation system (DRS) for healthcare services was developed within the context of the telemedicine research project ATMoSPHÄRE. The plausibility of the DRS was tested and the results used to examine if, and to what degree, the DRS provides useful assistance to GPs. Methods The plausibility of the recommendations of the DRS were tested with the Delphi procedure (n = 8) and Interviews (n = 4) in collaboration with the GPs. They proposed services and assistive products they considered appropriate for two multi-morbid patients. Furthermore, GPs had to report whether, and to what degree they deemed the algorithm-generated recommendations appropriate. Significant quantitative differences between the GPs’, and the algorithm-generated, recommendations were evaluated with paired-samples-Wilcoxon-test. Results The first Delphi round revealed a high variability regarding the amount and character of services recommended by the physicians (1 to 10 recommendations, mean = 5.6, sd = 2.8). These professional recommendations converged after consideration of the algorithm-generated recommendations. The number of algorithm-generated recommendations which were judged as appropriate ranged between 7 and 17 of a total of 20 (mean = 11.9, sd = 2.5). The interviews revealed that the additional algorithm-generated recommendations which were judged appropriate contained mainly social care services. Conlusion The DRS provides GPs with additional appropriate recommendations for the need-based care of patients, which may not have been previously considered. It can therefore be assessed as a helpful complement in the primary care of multi-morbid patients. Supplementary Information The online version contains supplementary material available at 10.1186/s12875-021-01537-2.
Collapse
Affiliation(s)
- Peggy Borchers
- Department of General Practice, Medical Clinic III, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, 01307, Dresden, Germany.
| | | | - Mandy Böhme
- Department of General Practice, Medical Clinic III, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, 01307, Dresden, Germany
| | - Karen Voigt
- Department of General Practice, Medical Clinic III, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, 01307, Dresden, Germany
| | - Antje Bergmann
- Department of General Practice, Medical Clinic III, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, 01307, Dresden, Germany
| |
Collapse
|
12
|
Chen J, Houston TK, Faro JM, Nagawa CS, Orvek EA, Blok AC, Allison JJ, Person SD, Smith BM, Sadasivam RS. Evaluating the use of a recommender system for selecting optimal messages for smoking cessation: patterns and effects of user-system engagement. BMC Public Health 2021; 21:1749. [PMID: 34563161 PMCID: PMC8465689 DOI: 10.1186/s12889-021-11803-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 09/13/2021] [Indexed: 11/28/2022] Open
Abstract
Background Motivational messaging is a frequently used digital intervention to promote positive health behavior changes, including smoking cessation. Typically, motivational messaging systems have not actively sought feedback on each message, preventing a closer examination of the user-system engagement. This study assessed the granular user-system engagement around a recommender system (a new system that actively sought user feedback on each message to improve message selection) for promoting smoking cessation and the impact of engagement on cessation outcome. Methods We prospectively followed a cohort of current smokers enrolled to use the recommender system for 6 months. The system sent participants motivational messages to support smoking cessation every 3 days and used machine learning to incorporate user feedback (i.e., user’s rating on the perceived influence of each message, collected on a 5-point Likert scale with 1 indicating strong disagreement and 5 indicating strong agreement on perceiving the influence on quitting smoking) to improve the selection of the following message. We assessed user-system engagement by various metrics, including user response rate (i.e., the percent of times a user rated the messages) and the perceived influence of messages. We compared retention rates across different levels of user-system engagement and assessed the association between engagement and the 7-day point prevalence abstinence (missing outcome = smoking) by using multiple logistic regression. Results We analyzed data from 731 participants (13% Black; 73% women). The user response rate was 0.24 (SD = 0.34) and user-perceived influence was 3.76 (SD = 0.84). The retention rate positively increased with the user response rate (trend test P < 0.001). Compared with non-response, six-month cessation increased with the levels of response rates: low response rate (odds ratio [OR] = 1.86, 95% confidence interval [CI]: 1.07–3.23), moderate response rate (OR = 2.30, 95% CI: 1.36–3.88), high response rate (OR = 2.69, 95% CI: 1.58–4.58). The association between perceived message influence and the outcome showed a similar pattern. Conclusions High user-system engagement was positively associated with both high retention rate and smoking cessation, suggesting that investigation of methods to increase engagement may be crucial to increase the impact of the recommender system for smoking cessation. Trial registration Registration Identifier: NCT03224520. Registration date: July 21, 2017. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-021-11803-8.
Collapse
Affiliation(s)
- Jinying Chen
- Division of Health Informatics and Implementation Science, Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, 368 Plantation Street, Worcester, MA, 01605, USA.
| | - Thomas K Houston
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jamie M Faro
- Division of Health Informatics and Implementation Science, Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, 368 Plantation Street, Worcester, MA, 01605, USA
| | - Catherine S Nagawa
- Division of Health Informatics and Implementation Science, Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, 368 Plantation Street, Worcester, MA, 01605, USA
| | - Elizabeth A Orvek
- Division of Health Informatics and Implementation Science, Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, 368 Plantation Street, Worcester, MA, 01605, USA
| | - Amanda C Blok
- VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, United States Department of Veterans Affairs, Ann Arbor, MI, USA.,Department of Systems, Populations and Leadership, School of Nursing, University of Michigan, Ann Arbor, MI, USA
| | - Jeroan J Allison
- Division of Health Informatics and Implementation Science, Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, 368 Plantation Street, Worcester, MA, 01605, USA
| | - Sharina D Person
- Division of Biostatistics and Health Services Research, Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Bridget M Smith
- Center of Innovation for Complex Chronic Healthcare, Spinal Cord Injury Quality Enhancement Research Initiative, Hines VA Medical Center, Chicago, IL, USA.,Department of Pediatrics, Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Rajani S Sadasivam
- Division of Health Informatics and Implementation Science, Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, 368 Plantation Street, Worcester, MA, 01605, USA
| |
Collapse
|
13
|
Ning X, Fan Z, Burgun E, Ren Z, Schleyer T. Improving information retrieval from electronic health records using dynamic and multi-collaborative filtering. PLoS One 2021; 16:e0255467. [PMID: 34351962 PMCID: PMC8341500 DOI: 10.1371/journal.pone.0255467] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Accepted: 07/16/2021] [Indexed: 12/02/2022] Open
Abstract
Due to the rapid growth of information available about individual patients, most physicians suffer from information overload and inefficiencies when they review patient information in health information technology systems. In this paper, we present a novel hybrid dynamic and multi-collaborative filtering method to improve information retrieval from electronic health records. This method recommends relevant information from electronic health records to physicians during patient visits. It models information search dynamics using a Markov model. It also leverages the key idea of collaborative filtering, originating from Recommender Systems, for prioritizing information based on various similarities among physicians, patients and information items. We tested this new method using electronic health record data from the Indiana Network for Patient Care, a large, inter-organizational clinical data repository maintained by the Indiana Health Information Exchange. Our experimental results demonstrated that, for top-5 recommendations, our method was able to correctly predict the information in which physicians were interested in 46.7% of all test cases. For top-1 recommendations, the corresponding figure was 24.7%. In addition, the new method was 22.3% better than the conventional Markov model for top-1 recommendations.
Collapse
Affiliation(s)
- Xia Ning
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH, United States of America
- Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, United States of America
- Translational Data Analytics Institute, The Ohio State University, Columbus, OH, United States of America
| | - Ziwei Fan
- Department of Computer Science, University of Illinois at Chicago, Chicago, IL, United States of America
| | - Evan Burgun
- Defense Finance and Accounting Service, Indianapolis, IN, United States of America
| | - Zhiyun Ren
- Hyperscience, New York, NY, United States of America
| | - Titus Schleyer
- Regenstrief Institute, Indianapolis, IN, United States of America
- Indiana University School of Medicine, Indianapolis, IN, United States of America
| |
Collapse
|
14
|
van Keulen HM, van Breukelen G, de Vries H, Brug J, Mesters I. A randomized controlled trial comparing community lifestyle interventions to improve adherence to diet and physical activity recommendations: the VitalUM study. Eur J Epidemiol 2021; 36:345-360. [PMID: 33377998 PMCID: PMC8032577 DOI: 10.1007/s10654-020-00708-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 12/08/2020] [Indexed: 11/27/2022]
Abstract
Worldwide, adherence to national guidelines for physical activity (PA), and fruit and vegetable consumption is recommended to promote health and reduce the risk for (chronic) disease. This study reports on the effectiveness of various social-cognitive interventions to improve adherence to guidelines and the revealed adherence predictors. Participants (n = 1,629), aged 45-70 years, randomly selected and recruited in 2005-2006 from 23 Dutch general practices, were randomized (centralized stratified allocation) to four groups to receive a 12-month lifestyle intervention targeting guideline adherence for PA and fruit and vegetable consumption. Study groups received either four computer-tailored print communication (TPC) letters (n = 405), four telephone motivational interviewing (TMI) sessions (n = 407), a combined intervention (two TPC letters and two TMI sessions, n = 408), or no intervention (control group, n = 409). After the baseline assessment, all parties were aware of the treatment groups. Outcomes were measured with self-report postal questionnaires at baseline, 25, 47 and 73 weeks. For PA, all three interventions were associated with better guideline adherence than no intervention. Odds ratios for TPC, TMI and the combined intervention were 1.82 (95% CI 1.31; 2.54), 1.57 (95% CI 1.13; 2.18), and 2.08 (95% CI 1.50; 2.88), respectively. No pedometer effects were found. For fruit and vegetable consumption, TPC seemed superior to those in the other groups. Odd ratio for fruit and vegetable consumption were 1.78 (95% CI 1.32; 2.41) and 1.73 (95% CI 1.28; 2.33), respectively. For each behaviour, adherence was predicted by self-efficacy expectations, habit strength and stages of change, whereas sex, awareness and the number of action plans predicted guideline adherence for fruit and vegetable intake. The season predicted the guideline adherence for PA and fruit consumption. The odds ratios revealed were equivalent to modest effects sizes, although they were larger than those reported in systematic reviews. This study indicated that less resource intensive interventions might have the potential for a large public health impact when widely implemented. The strengths of this study were the participation of lower educated adults and evaluation of maintenance effects. (Trial NL1035, 2007-09-06).
Collapse
Affiliation(s)
- Hilde Marijke van Keulen
- Department of Health Promotion, Maastricht University, Maastricht, The Netherlands
- CAPHRI Care and Public Health Research Institute, PO Box 616, 6200 MD, Maastricht, The Netherlands
- Department of Child Health, Now Employed by TNO, PO Box 3005, 2301 DA, Leiden, The Netherlands
| | - Gerard van Breukelen
- Department of Methodology and Statistics, Maastricht University, Maastricht, The Netherlands
- CAPHRI Care and Public Health Research Institute, PO Box 616, 6200 MD, Maastricht, The Netherlands
| | - Hein de Vries
- Department of Health Promotion, Maastricht University, Maastricht, The Netherlands
- CAPHRI Care and Public Health Research Institute, PO Box 616, 6200 MD, Maastricht, The Netherlands
| | - Johannes Brug
- Department of Epidemiology and Biostatistics, National Institute for Public Health and the Environment (RIVM), Utrecht RIVM and VU Medical Center, Amsterdam, The Netherlands
| | - Ilse Mesters
- Department of Epidemiology, Maastricht University, Maastricht, The Netherlands.
- CAPHRI Care and Public Health Research Institute, PO Box 616, 6200 MD, Maastricht, The Netherlands.
| |
Collapse
|
15
|
Gimpel H, Manner-Romberg T, Schmied F, Winkler TJ. Understanding the evaluation of mHealth app features based on a cross-country Kano analysis. ELECTRONIC MARKETS 2021; 31:765-794. [PMID: 35602116 PMCID: PMC7987738 DOI: 10.1007/s12525-020-00455-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 12/11/2020] [Indexed: 05/05/2023]
Abstract
While mobile health (mHealth) apps play an increasingly important role in digitalized health care, little is known regarding the effects of specific mHealth app features on user satisfaction across different healthcare system contexts. Using personal health record (PHR) apps as an example, this study identifies how potential users in Germany and Denmark evaluate a set of 26 app features, and whether evaluation differences can be explained by the differences in four pertinent user characteristics, namely privacy concerns, mHealth literacy, mHealth self-efficacy, and adult playfulness. Based on survey data from both countries, we employed the Kano method to evaluate PHR features and applied a quartile-based sample-split approach to understand the underlying relationships between user characteristics and their perceptions of features. Our results not only reveal significant differences in 14 of the features between Germans and Danes, they also demonstrate which of the user characteristics best explain each of these differences. Our two key contributions are, first, to explain the evaluation of specific PHR app features on user satisfaction in two different healthcare contexts and, second, to demonstrate how to extend the Kano method in terms of explaining subgroup differences through user characteristic antecedents. The implications for app providers and policymakers are discussed.
Collapse
Affiliation(s)
- Henner Gimpel
- University of Hohenheim, Schloss Hohenheim 1, 70599 Stuttgart, Germany
- FIM Research Center, University of Augsburg, Universitaetsstr. 12, 86159 Augsburg, Germany
- Project Group Business & Information Systems Engineering, Fraunhofer FIT, Universitaetsstr. 12, 86159 Augsburg, Germany
| | - Tobias Manner-Romberg
- FIM Research Center, University of Augsburg, Universitaetsstr. 12, 86159 Augsburg, Germany
| | - Fabian Schmied
- FIM Research Center, University of Augsburg, Universitaetsstr. 12, 86159 Augsburg, Germany
- Project Group Business & Information Systems Engineering, Fraunhofer FIT, Universitaetsstr. 12, 86159 Augsburg, Germany
| | - Till J. Winkler
- University of Hagen, Universitaetsstr. 47, 58097 Hagen, Germany
- Copenhagen Business School, Howitzvej 60, 2000 Frederiksberg, Denmark
| |
Collapse
|
16
|
Illustration of tailored digital health and potential new avenues. Digit Health 2021. [DOI: 10.1016/b978-0-12-820077-3.00009-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
|
17
|
Aalipour E, Ghazisaeedi M, Sedighi Moghadam MR, Shahmoradi L, Mousavi B, Beigy H. A minimum data set of user profile or electronic health record for chemical warfare victims' recommender system. J Family Med Prim Care 2020; 9:2995-3004. [PMID: 32984162 PMCID: PMC7491823 DOI: 10.4103/jfmpc.jfmpc_261_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2020] [Revised: 03/13/2020] [Accepted: 04/07/2020] [Indexed: 11/19/2022] Open
Abstract
Background: There are many people who are suffering from a variety of physical and mental illnesses due to the chemical attacks. There are various technologies such as recommender systems that can identify the main concerns related to health and make efforts to address them. To design and develop a recommender system, preparation of data source of this system should be considered. The aim of this study was to determine the minimum data set for user profile or user's electronic health record in chemical warfare victims’ recommender system. Methods: This applied descriptive, cross-sectional study which was conducted in 2017. A questionnaire was developed by the authors from the data elements that were collected using the data extraction form from the studied sources. Content validity of the questionnaire was confirmed by using the experts. Test–retest method was used to determine the reliability of the questionnaire. The reliability of the questionnaire with Cronbach's alpha coefficient was confirmed as 84%. The questionnaire were submitted for related experts based on Delphi method by email or in person. Data resulting from the Delphi technique with descriptive statistics methods in SPSS software were analyzed. Results: Forty-seven nonclinical data elements and 181 clinical data elements were classified. Conclusion: Determining minimum data set of user profile or electronic health record in the recommender system for chemical warfare victims helps the health authorities to implement the recommender system which demonstrates chemical warfare victims’ needs.
Collapse
Affiliation(s)
- Elham Aalipour
- Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.,Department of Health Information Technology, School of Allied Medical Sciences, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Marjan Ghazisaeedi
- Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.,Evidence Based Medicine Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Leila Shahmoradi
- Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.,Halal Research Center of IRI, FDA, Tehran, Iran
| | - Batool Mousavi
- Janbazan Medical and Engineering Research Center, Tehran, Iran
| | - Hamid Beigy
- Department of Computer Engineering, Sharif University of Technology, Tehran, Iran
| |
Collapse
|
18
|
Carrasco-Hernandez L, Jódar-Sánchez F, Núñez-Benjumea F, Moreno Conde J, Mesa González M, Civit-Balcells A, Hors-Fraile S, Parra-Calderón CL, Bamidis PD, Ortega-Ruiz F. A Mobile Health Solution Complementing Psychopharmacology-Supported Smoking Cessation: Randomized Controlled Trial. JMIR Mhealth Uhealth 2020; 8:e17530. [PMID: 32338624 PMCID: PMC7215523 DOI: 10.2196/17530] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 03/03/2020] [Accepted: 03/21/2020] [Indexed: 12/20/2022] Open
Abstract
Background Smoking cessation is a persistent leading public health challenge. Mobile health (mHealth) solutions are emerging to improve smoking cessation treatments. Previous approaches have proposed supporting cessation with tailored motivational messages. Some managed to provide short-term improvements in smoking cessation. Yet, these approaches were either static in terms of personalization or human-based nonscalable solutions. Additionally, long-term effects were neither presented nor assessed in combination with existing psychopharmacological therapies. Objective This study aimed to analyze the long-term efficacy of a mobile app supporting psychopharmacological therapy for smoking cessation and complementarily assess the involved innovative technology. Methods A 12-month, randomized, open-label, parallel-group trial comparing smoking cessation rates was performed at Virgen del Rocío University Hospital in Seville (Spain). Smokers were randomly allocated to a control group (CG) receiving usual care (psychopharmacological treatment, n=120) or an intervention group (IG) receiving psychopharmacological treatment and using a mobile app providing artificial intelligence–generated and tailored smoking cessation support messages (n=120). The secondary objectives were to analyze health-related quality of life and monitor healthy lifestyle and physical exercise habits. Safety was assessed according to the presence of adverse events related to the pharmacological therapy. Per-protocol and intention-to-treat analyses were performed. Incomplete data and multinomial regression analyses were performed to assess the variables influencing participant cessation probability. The technical solution was assessed according to the precision of the tailored motivational smoking cessation messages and user engagement. Cessation and no cessation subgroups were compared using t tests. A voluntary satisfaction questionnaire was administered at the end of the intervention to all participants who completed the trial. Results In the IG, abstinence was 2.75 times higher (adjusted OR 3.45, P=.01) in the per-protocol analysis and 2.15 times higher (adjusted OR 3.13, P=.002) in the intention-to-treat analysis. Lost data analysis and multinomial logistic models showed different patterns in participants who dropped out. Regarding safety, 14 of 120 (11.7%) IG participants and 13 of 120 (10.8%) CG participants had 19 and 23 adverse events, respectively (P=.84). None of the clinical secondary objective measures showed relevant differences between the groups. The system was able to learn and tailor messages for improved effectiveness in supporting smoking cessation but was unable to reduce the time between a message being sent and opened. In either case, there was no relevant difference between the cessation and no cessation subgroups. However, a significant difference was found in system engagement at 6 months (P=.04) but not in all subsequent months. High system appreciation was reported at the end of the study. Conclusions The proposed mHealth solution complementing psychopharmacological therapy showed greater efficacy for achieving 1-year tobacco abstinence as compared with psychopharmacological therapy alone. It provides a basis for artificial intelligence–based future approaches. Trial Registration ClinicalTrials.gov NCT03553173; https://clinicaltrials.gov/ct2/show/NCT03553173 International Registered Report Identifier (IRRID) RR2-10.2196/12464
Collapse
Affiliation(s)
- Laura Carrasco-Hernandez
- Smoking Cessation Unit, Medical-Surgical Unit of Respiratory Diseases, Virgen del Rocío University Hospital, Seville, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Carlos III Institute of Health, Madrid, Spain
| | - Francisco Jódar-Sánchez
- Research and Innovation Group in Biomedical Informatics, Biomedical Engineering and Health Economy, Institute of Biomedicine of Seville, Virgen del Rocío University Hospital, Spanish National Research Council, University of Seville, Seville, Spain
| | - Francisco Núñez-Benjumea
- Research and Innovation Group in Biomedical Informatics, Biomedical Engineering and Health Economy, Institute of Biomedicine of Seville, Virgen del Rocío University Hospital, Spanish National Research Council, University of Seville, Seville, Spain
| | - Jesús Moreno Conde
- Research and Innovation Group in Biomedical Informatics, Biomedical Engineering and Health Economy, Institute of Biomedicine of Seville, Virgen del Rocío University Hospital, Spanish National Research Council, University of Seville, Seville, Spain
| | - Marco Mesa González
- Smoking Cessation Unit, Medical-Surgical Unit of Respiratory Diseases, Virgen del Rocío University Hospital, Seville, Spain
| | - Antón Civit-Balcells
- Department of Architecture and Computer Technology, School of Computer Engineering, Universidad de Sevilla, Seville, Spain
| | | | - Carlos Luis Parra-Calderón
- Research and Innovation Group in Biomedical Informatics, Biomedical Engineering and Health Economy, Institute of Biomedicine of Seville, Virgen del Rocío University Hospital, Spanish National Research Council, University of Seville, Seville, Spain
| | - Panagiotis D Bamidis
- Medical Physics Laboratory, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Francisco Ortega-Ruiz
- Smoking Cessation Unit, Medical-Surgical Unit of Respiratory Diseases, Virgen del Rocío University Hospital, Seville, Spain
| |
Collapse
|
19
|
Sittig S, Wang J, Iyengar S, Myneni S, Franklin A. Incorporating Behavioral Trigger Messages Into a Mobile Health App for Chronic Disease Management: Randomized Clinical Feasibility Trial in Diabetes. JMIR Mhealth Uhealth 2020; 8:e15927. [PMID: 32175908 PMCID: PMC7105932 DOI: 10.2196/15927] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 11/13/2019] [Accepted: 02/10/2020] [Indexed: 12/23/2022] Open
Abstract
Background Although there is a rise in the use of mobile health (mHealth) tools to support chronic disease management, evidence derived from theory-driven design is lacking. Objective The objective of this study was to determine the impact of an mHealth app that incorporated theory-driven trigger messages. These messages took different forms following the Fogg behavior model (FBM) and targeted self-efficacy, knowledge, and self-care. We assess the feasibility of our app in modifying these behaviors in a pilot study involving individuals with diabetes. Methods The pilot randomized unblinded study comprised two cohorts recruited as employees from within a health care system. In total, 20 patients with type 2 diabetes were recruited for the study and a within-subjects design was utilized. Each participant interacted with an app called capABILITY. capABILITY and its affiliated trigger (text) messages integrate components from social cognitive theory (SCT), FBM, and persuasive technology into the interactive health communications framework. In this within-subjects design, participants interacted with the capABILITY app and received (or did not receive) text messages in alternative blocks. The capABILITY app alone was the control condition along with trigger messages including spark and facilitator messages. A repeated-measures analysis of variance (ANOVA) was used to compare adherence with behavioral measures and engagement with the mobile app across conditions. A paired sample t test was utilized on each health outcome to determine changes related to capABILITY intervention, as well as participants’ classified usage of capABILITY. Results Pre- and postintervention results indicated statistical significance on 3 of the 7 health survey measures (general diet: P=.03; exercise: P=.005; and blood glucose: P=.02). When only analyzing the high and midusers (n=14) of capABILITY, we found a statistically significant difference in both self-efficacy (P=.008) and exercise (P=.01). Although the ANOVA did not reveal any statistically significant differences across groups, there is a trend among spark conditions to respond more quickly (ie, shorter log-in lag) following the receipt of the message. Conclusions Our theory-driven mHealth app appears to be a feasible means of improving self-efficacy and health-related behaviors. Although our sample size is too small to draw conclusions about the differential impact of specific forms of trigger messages, our findings suggest that spark triggers may have the ability to cue engagement in mobile tools. This was demonstrated with the increased use of capABILITY at the beginning and conclusion of the study depending on spark timing. Our results suggest that theory-driven personalization of mobile tools is a viable form of intervention. Trial Registration ClinicalTrials.gov NCT04132089; http://clinicaltrials.gov/ct2/show/NCT004122089
Collapse
Affiliation(s)
- Scott Sittig
- School of Computing, University of South Alabama, Mobile, AL, United States
| | - Jing Wang
- School of Nursing, University of Texas Health Science Center at San Antonio, San Antonio, TX, United States
| | - Sriram Iyengar
- College of Medicine Phoenix, The University of Arizona, Phoenix, AZ, United States
| | - Sahiti Myneni
- School of Biomedical Informatics, University of Texas Health Science Center Houston, Houston, TX, United States
| | - Amy Franklin
- School of Biomedical Informatics, University of Texas Health Science Center Houston, Houston, TX, United States
| |
Collapse
|
20
|
Taj F, Klein MCA, van Halteren A. Digital Health Behavior Change Technology: Bibliometric and Scoping Review of Two Decades of Research. JMIR Mhealth Uhealth 2019; 7:e13311. [PMID: 31833836 PMCID: PMC6935048 DOI: 10.2196/13311] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Revised: 07/20/2019] [Accepted: 09/26/2019] [Indexed: 12/17/2022] Open
Abstract
Background Research on digital technology to change health behavior has increased enormously in recent decades. Due to the interdisciplinary nature of this topic, knowledge and technologies from different research areas are required. Up to now, it is not clear how the knowledge from those fields is combined in actual applications. A comprehensive analysis that systematically maps and explores the use of knowledge within this emerging interdisciplinary field is required. Objective This study aims to provide an overview of the research area around the design and development of digital technologies for health behavior change and to explore trends and patterns. Methods A bibliometric analysis is used to provide an overview of the field, and a scoping review is presented to identify the trends and possible gaps. The study is based on the publications related to persuasive technologies and health behavior change in the last 18 years, as indexed by the Web of Science and Scopus (317 and 314 articles, respectively). In the first part, regional and time-based publishing trends; research fields and keyword co-occurrence networks; influential journals; and collaboration network between influential authors, countries, and institutions are examined. In the second part, the behavioral domains, technological means and theoretical foundations are investigated via a scoping review. Results The literature reviewed shows a clear and emerging trend after 2001 in technology-based behavior change, which grew exponentially after the introduction of the smartphone around 2009. Authors from the United States, Europe, and Australia have the highest number of publications in the field. The three most active research areas are computer science, public and occupational health, and psychology. The keyword “mhealth” was the dominant term and predominantly used together with the term “physical activity” and “ehealth”. A total of three strong clusters of coauthors have been found. Nearly half of the total reported papers were published in three journals. The United States, the United Kingdom, and the Netherlands have the highest degree of author collaboration and a strong institutional network. Mobile phones were most often used as a technology platform, regardless of the targeted behavioral domain. Physical activity and healthy eating were the most frequently targeted behavioral domains. Most articles did not report about the behavior change techniques that were applied. Among the reported behavior change techniques, goal setting and self-management were the most frequently reported. Conclusions Closer cooperation and interaction between behavioral sciences and technological areas is needed, so that theoretical knowledge and new technological advancements are better connected in actual applications. Eventually, this could result in a larger societal impact, an increase of the effectiveness of digital technologies for health behavioral change, and more insight in the relationship between behavioral change strategies and persuasive technologies' effectiveness.
Collapse
Affiliation(s)
- Fawad Taj
- Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | | | - Aart van Halteren
- Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Philips Research, Eindhoven, Netherlands
| |
Collapse
|
21
|
Jódar-Sánchez F, Carrasco Hernández L, Núñez-Benjumea FJ, Mesa González MA, Moreno Conde J, Parra Calderón CL, Fernandez-Luque L, Hors-Fraile S, Civit A, Bamidis P, Ortega-Ruiz F. Using the Social-Local-Mobile App for Smoking Cessation in the SmokeFreeBrain Project: Protocol for a Randomized Controlled Trial. JMIR Res Protoc 2018; 7:e12464. [PMID: 30522992 PMCID: PMC6302230 DOI: 10.2196/12464] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Revised: 11/19/2018] [Accepted: 11/20/2018] [Indexed: 01/12/2023] Open
Abstract
Background Smoking is considered the main cause of preventable illness and early deaths worldwide. The treatment usually prescribed to people who wish to quit smoking is a multidisciplinary intervention, combining both psychological advice and pharmacological therapy, since the application of both strategies significantly increases the chance of success in a quit attempt. Objective We present a study protocol of a 12-month randomized open-label parallel-group trial whose primary objective is to analyze the efficacy and efficiency of usual psychopharmacological therapy plus the Social-Local-Mobile app (intervention group) applied to the smoking cessation process compared with usual psychopharmacological therapy alone (control group). Methods The target population consists of adult smokers (both male and female) attending the Smoking Cessation Unit at Virgen del Rocío University Hospital, Seville, Spain. Social-Local-Mobile is an innovative intervention based on mobile technologies and their capacity to trigger behavioral changes. The app is a complement to pharmacological therapies to quit smoking by providing personalized motivational messages, physical activity monitoring, lifestyle advice, and distractions (minigames) to help overcome cravings. Usual pharmacological therapy consists of bupropion (Zyntabac 150 mg) or varenicline (Champix 0.5 mg or 1 mg). The main outcomes will be (1) the smoking abstinence rate at 1 year measured by means of exhaled carbon monoxide and urinary cotinine tests, and (2) the result of the cost-effectiveness analysis, which will be expressed in terms of an incremental cost-effectiveness ratio. Secondary outcome measures will be (1) analysis of the safety of pharmacological therapy, (2) analysis of the health-related quality of life of patients, and (3) monitoring of healthy lifestyle and physical exercise habits. Results Of 548 patients identified using the hospital’s electronic records system, we excluded 308 patients: 188 declined to participate and 120 did not meet the inclusion criteria. A total of 240 patients were enrolled: the control group (n=120) will receive usual psychopharmacological therapy, while the intervention group (n=120) will receive usual psychopharmacological therapy plus the So-Lo-Mo app. The project was approved for funding in June 2015. Enrollment started in October 2016 and was completed in October 2017. Data gathering was completed in November 2018, and data analysis is under way. The first results are expected to be submitted for publication in early 2019. Conclusions Social networks and mobile technologies influence our daily lives and, therefore, may influence our smoking habits as well. As part of the SmokeFreeBrain H2020 European Commission project, this study aims at elucidating the potential role of these technologies when used as an extra aid to quit smoking. Trial Registration ClinicalTrials.gov NCT03553173; https://clinicaltrials.gov/ct2/show/record/NCT03553173 (Archived by WebCite at http://www.webcitation.org/74DuHypOW). International Registered Report Identifier (IRRID) PRR1-10.2196/12464
Collapse
Affiliation(s)
- Francisco Jódar-Sánchez
- Research and Innovation Group in Biomedical Informatics, Biomedical Engineering and Health Economy, Institute of Biomedicine of Seville, Virgen del Rocío University Hospital / Spanish National Research Council / University of Seville, Seville, Spain
| | - Laura Carrasco Hernández
- Smoking Cessation Unit, Medical-Surgical Unit of Respiratory Diseases, Virgen del Rocío University Hospital, Sevilla, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Carlos III Institute of Health, Madrid, Spain
| | - Francisco J Núñez-Benjumea
- Research and Innovation Group in Biomedical Informatics, Biomedical Engineering and Health Economy, Institute of Biomedicine of Seville, Virgen del Rocío University Hospital / Spanish National Research Council / University of Seville, Seville, Spain
| | - Marco Antonio Mesa González
- Smoking Cessation Unit, Medical-Surgical Unit of Respiratory Diseases, Virgen del Rocío University Hospital, Sevilla, Spain
| | - Jesús Moreno Conde
- Research and Innovation Group in Biomedical Informatics, Biomedical Engineering and Health Economy, Institute of Biomedicine of Seville, Virgen del Rocío University Hospital / Spanish National Research Council / University of Seville, Seville, Spain
| | - Carlos Luis Parra Calderón
- Research and Innovation Group in Biomedical Informatics, Biomedical Engineering and Health Economy, Institute of Biomedicine of Seville, Virgen del Rocío University Hospital / Spanish National Research Council / University of Seville, Seville, Spain
| | | | - Santiago Hors-Fraile
- Department of Architecture and Computer Technology, School of Computer Engineering, University of Seville, Sevilla, Spain.,Department of Health Promotion, School for Public Health and Primary Care, Maastricht University, Maastricht, Netherlands
| | - Anton Civit
- Department of Architecture and Computer Technology, School of Computer Engineering, University of Seville, Sevilla, Spain
| | - Panagiotis Bamidis
- Medical Physics Laboratory, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Francisco Ortega-Ruiz
- Smoking Cessation Unit, Medical-Surgical Unit of Respiratory Diseases, Virgen del Rocío University Hospital, Sevilla, Spain
| |
Collapse
|