Responses to a COVID-19 vaccination intervention: Qualitative analysis of 17K unsolicited SMS replies.

The development of effective interventions for COVID-19 vaccination has proven challenging given the unique and evolving determinants of that behavior. A tailored intervention to drive vaccination uptake through machine learning-enabled personalization of behavior change messages unexpectedly yielded a high volume of real-time short message service (SMS) feedback from recipients. A qualitative analysis of those replies contributes to a better understanding of the barriers to COVID-19 vaccination and demographic variations in determinants, supporting design improvements for vaccination interventions. OBJECTIVE: The purpose of this study was to examine unsolicited replies to a text message intervention for COVID-19 vaccination to understand the types of barriers experienced and any relationships between recipient demographics, intervention content, and reply type. METHOD: We categorized SMS replies into 22 overall themes. Interrater agreement was very good (all κpooled > 0.62). Chi-square analyses were used to understand demographic variations in reply types and which messaging types were most related to reply types. RESULTS: In total, 10,948 people receiving intervention text messages sent 17,090 replies. Most frequent reply types were "already vaccinated" (31.1%), attempts to unsubscribe (25.4%), and "will not get vaccinated" (12.7%). Within "already vaccinated" and "will not get vaccinated" replies, significant differences were observed in the demographics of those replying against expected base rates, all p > .001. Of those stating they would not vaccinate, 34% of the replies involved mis-/disinformation, suggesting that a determinant of vaccination involves nonvalidated COVID-19 beliefs. CONCLUSIONS: Insights from unsolicited replies can enhance our ability to identify appropriate intervention techniques to influence COVID-19 vaccination behaviors. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Effectiveness and cost-effectiveness of text messages with or without endowment incentives for weight management in men with obesity (Game of Stones): study protocol for a randomised controlled trial.

BACKGROUND: Obesity increases the risk of type 2 diabetes, heart disease, stroke, mobility problems and some cancers, and its prevalence is rising. Men engage less than women in existing weight loss interventions. Game of Stones builds on a successful feasibility study and aims to find out if automated text messages with or without endowment incentives are effective and cost-effective for weight loss at 12 months compared to a waiting list comparator arm in men with obesity. METHODS: A 3-arm, parallel group, assessor-blind superiority randomised controlled trial with process evaluation will recruit 585 adult men with body mass index of 30 kg/m2 or more living in and around three UK centres (Belfast, Bristol, Glasgow), purposively targeting disadvantaged areas. Intervention groups: (i) automated, theory-informed text messages daily for 12 months plus endowment incentives linked to verified weight loss targets at 3, 6 and 12 months; (ii) the same text messages and weight loss assessment protocol; (iii) comparator group: 12 month waiting list, then text messages for 3 months. The primary outcome is percentage weight change at 12 months from baseline. Secondary outcomes at 12 months are as follows: quality of life, wellbeing, mental health, weight stigma, behaviours, satisfaction and confidence. Follow-up includes weight at 24 months. A health economic evaluation will measure cost-effectiveness over the trial and over modelled lifetime: including health service resource-use and quality-adjusted life years. The cost-utility analysis will report incremental cost per quality-adjusted life years gained. Participant and service provider perspectives will be explored via telephone interviews, and exploratory mixed methods process evaluation analyses will focus on mental health, multiple long-term conditions, health inequalities and implementation strategies. DISCUSSION: The trial will report whether text messages (with and without cash incentives) can help men to lose weight over 1 year and maintain this for another year compared to a comparator group; the costs and benefits to the health service; and men's experiences of the interventions. Process analyses with public involvement and service commissioner input will ensure that this open-source digital self-care intervention could be sustainable and scalable by a range of NHS or public services. TRIAL REGISTRATION: ISRCTN 91974895 . Registered on 14/04/2021.

Three-Month Symptom Profiles Among Symptomatic Adults With Positive and Negative Severe Acute Respiratory Syndrome Coronavirus 2 Tests: A Prospective Cohort Study From the INSPIRE Group.

BACKGROUND: Long-term symptoms following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are a major concern, yet their prevalence is poorly understood. METHODS: We conducted a prospective cohort study comparing adults with SARS-CoV-2 infection (coronavirus disease-positive [COVID+]) with adults who tested negative (COVID-), enrolled within 28 days of a Food and Drug Administration (FDA)-approved SARS-CoV-2 test result for active symptoms. Sociodemographic characteristics, symptoms of SARS-CoV-2 infection (assessed with the Centers for Disease Control and Prevention [CDC] Person Under Investigation Symptom List), and symptoms of post-infectious syndromes (ie, fatigue, sleep quality, muscle/joint pains, unrefreshing sleep, and dizziness/fainting, assessed with CDC Short Symptom Screener for myalgic encephalomyelitis/chronic fatigue syndrome) were assessed at baseline and 3 months via electronic surveys sent via text or email. RESULTS: Among the first 1000 participants, 722 were COVID+ and 278 were COVID-. Mean age was 41.5 (SD 15.2); 66.3% were female, 13.4% were Black, and 15.3% were Hispanic. At baseline, SARS-CoV-2 symptoms were more common in the COVID+ group than the COVID- group. At 3 months, SARS-CoV-2 symptoms declined in both groups, although were more prevalent in the COVID+ group: upper respiratory symptoms/head/eyes/ears/nose/throat (HEENT; 37.3% vs 20.9%), constitutional (28.8% vs 19.4%), musculoskeletal (19.5% vs 14.7%), pulmonary (17.6% vs 12.2%), cardiovascular (10.0% vs 7.2%), and gastrointestinal (8.7% vs 8.3%); only 50.2% and 73.3% reported no symptoms at all. Symptoms of post-infectious syndromes were similarly prevalent among the COVID+ and COVID- groups at 3 months. CONCLUSIONS: Approximately half of COVID+ participants, as compared with one-quarter of COVID- participants, had at least 1 SARS-CoV-2 symptom at 3 months, highlighting the need for future work to distinguish long COVID. CLINICAL TRIALS REGISTRATION: NCT04610515.

Mobile Phone Data: A Survey of Techniques, Features, and Applications.

Due to the rapid growth in the use of smartphones, the digital traces (e.g., mobile phone data, call detail records) left by the use of these devices have been widely employed to assess and predict human communication behaviors and mobility patterns in various disciplines and domains, such as urban sensing, epidemiology, public transportation, data protection, and criminology. These digital traces provide significant spatiotemporal (geospatial and time-related) data, revealing people's mobility patterns as well as communication (incoming and outgoing calls) data, revealing people's social networks and interactions. Thus, service providers collect smartphone data by recording the details of every user activity or interaction (e.g., making a phone call, sending a text message, or accessing the internet) done using a smartphone and storing these details on their databases. This paper surveys different methods and approaches for assessing and predicting human communication behaviors and mobility patterns from mobile phone data and differentiates them in terms of their strengths and weaknesses. It also gives information about spatial, temporal, and call characteristics that have been extracted from mobile phone data and used to model how people communicate and move. We survey mobile phone data research published between 2013 and 2021 from eight main databases, namely, the ACM Digital Library, IEEE Xplore, MDPI, SAGE, Science Direct, Scopus, SpringerLink, and Web of Science. Based on our inclusion and exclusion criteria, 148 studies were selected.

Chatbots for Smoking Cessation: Scoping Review.

BACKGROUND: Despite significant progress in reducing tobacco use over the past 2 decades, tobacco still kills over 8 million people every year. Digital interventions, such as text messaging, have been found to help people quit smoking. Chatbots, or conversational agents, are new digital tools that mimic instantaneous human conversation and therefore could extend the effectiveness of text messaging. OBJECTIVE: This scoping review aims to assess the extent of research in the chatbot literature for smoking cessation and provide recommendations for future research in this area. METHODS: Relevant studies were identified through searches conducted in Embase, MEDLINE, APA PsycINFO, Google Scholar, and Scopus, as well as additional searches on JMIR, Cochrane Library, Lancet Digital Health, and Digital Medicine. Studies were considered if they were conducted with tobacco smokers, were conducted between 2000 and 2021, were available in English, and included a chatbot intervention. RESULTS: Of 323 studies identified, 10 studies were included in the review (3 framework articles, 1 study protocol, 2 pilot studies, 2 trials, and 2 randomized controlled trials). Most studies noted some benefits related to smoking cessation and participant engagement; however, outcome measures varied considerably. The quality of the studies overall was low, with methodological issues and low follow-up rates. CONCLUSIONS: More research is needed to make a firm conclusion about the efficacy of chatbots for smoking cessation. Researchers need to provide more in-depth descriptions of chatbot functionality, mode of delivery, and theoretical underpinnings. Consistency in language and terminology would also assist in reviews of what approaches work across the field.

User review analysis of dating apps based on text mining.

With the continuous development of information technology, more and more people have become to use online dating apps, and the trend has been exacerbated by the COVID-19 pandemic in these years. However, there is a phenomenon that most of user reviews of mainstream dating apps are negative. To study this phenomenon, we have used topic model to mine negative reviews of mainstream dating apps, and constructed a two-stage machine learning model using data dimensionality reduction and text classification to classify user reviews of dating apps. The research results show that: firstly, the reasons for the current negative reviews of dating apps are mainly concentrated in the charging mechanism, fake accounts, subscription and advertising push mechanism and matching mechanism in the apps, proposed corresponding improvement suggestions are proposed by us; secondly, using principal component analysis to reduce the dimensionality of the text vector, and then using XGBoost model to learn the low-dimensional data after oversampling, a better classification accuracy of user reviews can be obtained. We hope These findings can help dating apps operators to improve services and achieve sustainable business operations of their apps.

Comparative effectiveness of two versions of a caring contacts intervention in healthcare providers, staff, and patients for reducing loneliness and mental distress: A randomized controlled trial.

BACKGROUND: Caring Contacts can effectively reduce suicide ideation, attempts, and death. In published clinical trials, Caring Contacts were sent by someone who knew the recipient. At scale, Caring Contacts programs rarely introduce the recipient and sender. It is not known whether receiving Caring Contacts from someone unknown is as effective as messages from someone the recipient has met. METHODS: Pragmatic randomized controlled trial comparing Caring Contacts with (CC+) versus without an introductory phone call (CC). Recruitment occurred January-July 2021, with outcomes assessed at 6 months. Participants were primary care patients or healthcare providers/staff reporting adverse mental health outcomes on a qualifying survey. Participants were sent 11 standardized caring text messages over 6 months; when participants replied, they received personalized unscripted responses. CC+ calls were semi-structured. The primary outcome was loneliness (NIH Toolkit). RESULTS: Participants included 331 patients (mean [SD] age: 45.5 [16.4], 78.9 % female) and 335 healthcare providers/staff (mean [SD] age: 40.9 [11.8], 86.6 % female). There were no significant differences in loneliness at 6 months by treatment arm in either stratum. In patients, mean (SD) loneliness was 61.9 (10.7) in CC, and 60.8 (10.3) in CC+, adjusted mean difference of -1.0 (95 % CI: -3.0, 1.0); p-value = 0.31. In providers/staff, mean (SD) loneliness was 61.2 (11) in CC, and 61.3 (11.1) in CC+, adjusted mean difference of 0.2 (95 % CI: -1.8, 2.2); p-value = 0.83. LIMITATIONS: Study population was 93 % white which may limit generalizability. CONCLUSIONS: Including an initial phone call added operational complexity without significantly improving the effectiveness of a Caring Contacts program.

Dissemination and Implementation of a Text Messaging Campaign to Improve Health Disparities among Im/Migrant Workers.

The use of short message service (SMS) text messaging technology has grown in popularity over the last twenty years, but there is limited data on the design and feasibility of campaigns to reduce work-related injury, particularly among rural workers, non-native English speakers, and illiterate or low-literacy populations. Although there is a critical need for tech equity or 'TechQuity' interventions that reduce injury and enhance the wellbeing of under-reached communities, the barriers and benefits to implementation must be empirically and systematically examined. Thus, our team used D&I science to design and implement an 18-week texting campaign for under-reached workers with a higher-than-average risk of fatal and non-fatal injury. The experimental project was conducted with English-, Spanish-, and Vietnamese-speaking commercial fishermen in the Gulf of Mexico to test the design and feasibility, and messaging focused on preventing injury from slips, trips, and falls, as well as hurricane preparedness. The ubiquity of mobile devices and the previous success of texting campaigns made this a promising approach for enhancing health and preventing injury among an under-reached population. However, the perceived benefits were not without their barriers. The lessons learned included the difficulty of navigating federal regulations regarding limits for special characters, enrolling migratory participants, and navigating areas with limited cellular service or populations with limited accessibility to technology. We conclude with short- and long-term suggestions for future technology interventions for under-reached worker populations, including ethical and policy regulations.

Smokers' user experience of smoking cessation apps: A systematic review.

OBJECTIVES: To explore how smokers view common functions and characteristics of smoking cessation apps. DESIGN: Systematic review. SEARCH SOURCES: CINAHL PLUS, MEDLINE, PsycINFO, EMBASE, IEEE Xplore, ACM Digital Library, and Google Scholar. REVIEW METHODS: Seven digital databases were searched separately using relevant search terms. Search results were uploaded to Covidence. Inclusion and exclusion criteria were identified with the expert team in advance. Titles, abstracts, and full texts were screened by two reviewers independently. Any disagreements were discussed in research meetings. Pertinent data were extracted and analysed using qualitative content analysis. Findings were presented in a narrative approach. RESULTS: 28 studies were included in this review. The overarching themes were app functionality and app characteristics. Under app "functionality", six subthemes emerged: 1) education; 2) tracking; 3) social support; 4) compensation; 5) distraction, and 6) reminding. Under "app characteristics", five subthemes emerged: 1) simplification, 2) personalisation, 3) diverse content forms, 4) interactivity, and 5) privacy and security. CONCLUSION: Understanding user needs and expectations is crucial for developing a programme theory for smoking cessation app interventions. Relevant needs identified in this review should be linked to broader theories of smoking cessation and app-based intervention.

Five-Year Community Surveillance Study for Acute Respiratory Infections Using Text Messaging: Findings From the MoSAIC Study.

BACKGROUND: Acute respiratory infections (ARI) are the most common infectious diseases globally. Community surveillance may provide a more comprehensive picture of disease burden than medically attended illness alone. METHODS: In this longitudinal study conducted from 2012 to 2017 in the Washington Heights/Inwood area of New York City, we enrolled 405 households with 1915 individuals. Households were sent research text messages twice weekly inquiring about ARI symptoms. Research staff confirmed symptoms by follow-up call. If ≥2 criteria for ARI were met (fever/feverish, cough, congestion, pharyngitis, myalgias), staff obtained a mid-turbinate nasal swab in participants' homes. Swabs were tested using the FilmArray reverse transcription polymerase chain reaction (RT-PCR) respiratory panel. RESULTS: Among participants, 43.9% were children, and 12.8% had a chronic respiratory condition. During the 5 years, 114 724 text messages were sent; the average response rate was 78.8% ± 6.8%. Swabs were collected for 91.4% (2756/3016) of confirmed ARI; 58.7% had a pathogen detected. Rhino/enteroviruses (51.9%), human coronaviruses (13.9%), and influenza (13.2%) were most commonly detected. The overall incidence was 0.62 ARI/person-year, highest (1.73) in <2 year-olds and lowest (0.46) in 18-49 year-olds. Approximately one-fourth of those with ARI sought healthcare; percents differed by pathogen, demographic factors, and presence of a chronic respiratory condition. CONCLUSIONS: Text messaging is a novel method for community-based surveillance that could be used both seasonally as well as during outbreaks, epidemics and pandemics. The importance of community surveillance to accurately estimate disease burden is underscored by the findings of low rates of care-seeking that varied by demographic factors and pathogens.

Digital approaches to continuing care.

PURPOSE OF REVIEW: To provide an update of studies on the effectiveness of digital and telephonic approaches to providing remote continuing care for substance use disorders. RECENT FINDINGS: Effective continuing care can be provided via smartphone apps, text messaging, interactive voice response, and structured telephone counseling. The remote continuing care interventions with the strongest evidence of efficacy are the Addiction Comprehensive Health Enhancement Support System app and Telephone Monitoring and Counseling. Positive effects for these intervention on drinking outcomes in patients with alcohol use disorders were replicated in a recent randomized controlled study. SUMMARY: Continuing care is widely believed to be an important component of treatment for substance use disorders, especially for sustaining positive outcomes. However, many individuals do not attend clinic-based continuing care, due to a variety of reasons, including competing work and family responsibilities, disabilities, transportation challenges, and recently the COVID-19 pandemic. Remote continuing care, provided via smartphone apps, text messaging, and various telephonic approaches, has been shown to be effective, and could be used to provide continuing care to patients who would otherwise not receive it. Further work is needed to determine how to effectively combine more traditional continuing care with newer digitized and telephonic approaches.

Nudging attitudes toward IT innovations by information provision that serves as a reminder of familial support.

There is concern among the general public that information technology (IT) innovations may make existing jobs redundant. This may be perceived to pose a greater problem to future generations because new technologies, not limited to IT innovations, will be sophisticated in the future. Our previous work revealed that messages reminding people of familial support as a nudge can moderate risk-averse attitudes toward risks that are perceived to threaten future generations, which could be effective for other kinds of risks. Therefore, we conducted a randomized controlled trial to examine the message effects for information provision on IT innovations. The study was conducted via an online questionnaire survey in January 2020, before the COVID-19 pandemic, and more than 3,200 samples were collected from respondents aged 20 years or older living in Japan. The treatment groups received basic information supplemented with additional text or additional text and an illustration that highlighted IT innovations as support from previous generations. The control group received only the basic textual information. The effects of the intervention were evaluated by comparing changes in average subjective assessment of IT in the treatment groups with those in the control group. The intervention effect was statistically significant, and the sense of familial support after receiving the intervention messages was significantly increased in the treatment group that viewed the illustration compared with the control group. Additionally, we discuss how each component of the HEXACO personality traits influences responses to the intervention messages. Through a series of surveys, we demonstrated the potential of our framework for a wide variety of applications involving information provision perceived to involve future generations.

Smoking cessation interventions for US adults with disabilities: protocol for a systematic review.

INTRODUCTION: People with disabilities have a higher prevalence of cigarette smoking than people without disabilities. However, little information exists on smoking cessation interventions tailored to address the unique needs of people with disabilities. This paper describes a systematic review protocol to identify and evaluate tobacco smoking cessation interventions designed to improve outcomes for people with disabilities. METHODS AND ANALYSIS: We will conduct a systematic review of the literature using the procedures outlined by Cochrane. We will search four electronic databases (CINAHL Plus (EBSCO), Embase (Ovid), Medline (Ovid) and PsycINFO (Ovid)) with no date restriction to identify tobacco cessation interventions tailored to meet the needs of people with disabilities. We will extract data and assess risk of bias using the RoB2 and ROBINS-I for included studies using Covidence systematic review software. Quantitative and qualitative syntheses will summarise key study characteristics and outcomes with text, tables and forest plots; a meta-analysis will be conducted, if appropriate. ETHICS AND DISSEMINATION: Ethical approval is not required as there are no primary data associated with the study. Data will be disseminated through a peer-reviewed articles and conference presentations. PROSPERO REGISTRATION NUMBER: CRD42022337434.

Reduction of No-Show Rate for New Patients in a Pediatric Neurology Clinic.

BACKGROUND: The rate of patients not keeping their appointments at our children's hospital outpatient pediatric neurology clinic (no-shows) was high. We conducted a quality improvement project to reduce no-show rates and improve operational efficiency. Specifically, we aimed to decrease the new patient no-show mean rate from 7% to 4% at the main campus and from 17% to 12% at the south campus. METHODS: After reviewing the previous literature on this topic and institutional data, we used the simplified failure mode and effects analysis (sFMEA) to identify the key drivers. Of the patients at the main campus who failed to keep their appointment, 84% had not confirmed their appointment. Errors in inpatient/family contact information, limited use of the electronic patient portal, and miscommunication were other key drivers identified. Three Plan-Do-Study-Act (PDSA) cycles were completed over seven months. The key interventions we implemented were bidirectional text triage, telephone reminders, and promoting the use of the electronic patient portal. A run chart was used to assess the results of these interventions. RESULTS: A statistically significant shift was noted in the run chart for the median rate of no-shows, which declined from 7% to 4% at the main campus and 17% to 10% at the south campus. CONCLUSION: We were able to successfully reduce no-shows among new patients in the neurology clinic. The limitations of our study include unknown external factors, the potential impact of COVID-19, and the brief length of the study.

Cost analysis of COVID-19 test result notification using an automated messaging system compared to a staff caller practice in Alberta.

SETTING: In Alberta, polymerase chain reaction (PCR) COVID-19 tests were an important step in detecting and isolating contagious individuals throughout the pandemic. Initially, a staff member provided results to all PCR COVID-19 test clients by phone. As the number of tests increased, new approaches were essential for timely result notification. INTERVENTION: An innovative automated IT system was introduced during the pandemic to reduce workloads and support timely result notification. At the time of the COVID-19 test booking and again following swabbing, clients had an option to consent to receive their test results via an automated text or voice message. Prior to implementation, a privacy impact assessment was approved, a pilot was undertaken, and changes to lab information systems were made. OUTCOMES: Health administration data were used in a cost analysis to compare the unique costs associated with the novel automated IT practice (e.g., administration, integration, messages, staffing costs) and a hypothetical staff caller practice (e.g., administration, staffing costs) for negative test results. The costs of sharing 2,161,605 negative test results in 2021 were assessed. The automated IT practice demonstrated a cost savings of $6,272,495 over the staff caller practice. A follow-up analysis determined the cost savings threshold of 46,463 negative tests to break even. IMPLICATIONS: Using an automated IT practice for consenting clients can be a cost-effective approach to reach clients in a timely manner during a pandemic or other instances warranting direct notification. This approach is being explored for test result notification of other communicable diseases in other contexts.

RéSUMé: LIEU: En Alberta, les tests de réaction de polymérisation en chaîne (PCR) pour la COVID-19 ont représenté une étape importante dans la détection et l'isolement des personnes contagieuses tout au long de la pandémie. Au début, un membre du personnel communiquait par téléphone les résultats de tous les tests PCR de la COVID-19 aux usagers et usagères. Avec l'augmentation du nombre de tests, il a absolument fallu trouver de nouvelles façons de communiquer les résultats rapidement. INTERVENTION: Un système de TI automatisé novateur a été introduit durant la pandémie pour alléger la charge de travail et favoriser la communication rapide des résultats des tests. Au moment de la réservation d'un test de dépistage de la COVID-19 et après l'écouvillonnage, les usagers et usagères pouvaient consentir à recevoir leurs résultats via un message texte automatisé ou un message vocal. Avant la mise en œuvre, une évaluation des facteurs relatifs à la vie privée a été approuvée, un projet pilote a été mené, et des changements ont été apportés aux systèmes d'information des laboratoires. RéSULTATS: Les données administratives sanitaires ont servi à effectuer une analyse des coûts visant à comparer les coûts spécifiquement associés à la nouvelle pratique de TI automatisée (p. ex. frais d'administration, d'intégration, de messages, de personnel) et ceux d'une hypothétique pratique d'appel par un membre du personnel (p. ex. frais d'administration, de personnel) pour les tests négatifs. Les coûts de communication des résultats de 2 161 605 tests négatifs en 2021 ont été évalués. La pratique de TI automatisée a représenté des économies de 6 272 495 $ par rapport à la pratique d'appel par un membre du personnel. Selon une analyse de suivi, le seuil de rentabilité était atteint après 46 463 tests négatifs. CONSéQUENCES: L'utilisation d'une pratique de TI automatisée pour les usagers et usagères ayant consenti à cette option peut être une méthode efficace par rapport au coût pour joindre rapidement les usagères et usagers lors d'une pandémie ou dans d'autres cas où une notification directe est justifiée. Cette méthode est explorée pour la communication des résultats de tests d'autres maladies transmissibles dans d'autres contextes.

Dietary Intervention on Overweight and Obesity after Confinement by COVID-19.

BACKGROUND: Obesity has become a public health problem in our society and is associated with many diseases, including type 2 diabetes mellitus, cardiovascular diseases, dyslipidemia, respiratory diseases, and cancer. Several studies relate weight loss in obese patients to improved anthropometric measurements and cardiometabolic risk. The objective of our study was to evaluate anthropometric changes, analytical parameters, insulin resistance, fatty liver, and metabolic scales, after a personalized weight loss program, through dietary advice to increase adherence to the Mediterranean diet and a motivational booster via mobile SMS messaging. METHODS: Intervention study on a sample of 1964 workers, in which different anthropometric parameters were evaluated before and after dietary intervention: the metabolic score of insulin resistance; non-alcoholic fatty liver disease using different scales; metabolic syndrome; atherogenic dyslipidemia; and the cardiometabolic index. A descriptive analysis of the categorical variables was performed, by calculating the frequency and distribution of the responses for each one. For quantitative variables, the mean and standard deviation were calculated, since they followed a normal distribution. Bivariate association analysis was performed by applying the chi-squared test (corrected by Fisher's exact statistic when conditions required it) and Student's t-test for independent samples (for comparison of means). RESULTS: The population subjected to the Mediterranean diet improved in all the variables evaluated at 12 months of follow-up and compliance with the diet. CONCLUSIONS: Dietary advice on a Mediterranean diet and its reinforcement with reminder messages through the use of mobile phones may be useful to improve the parameters evaluated in this study and reduce the cardiometabolic risk of patients.

Integrating third-party apps with electronic health records to support COVID-19 response.

OBJECTIVES: To (1) track the integration of telehealth- and COVID-19-related apps with electronic health records (EHRs) over time, (2) identify the primary functionality of apps designed to support the COVID-19 response, and (3) examine whether apps available prior to the pandemic added new telehealth- or COVID-19-related functionalities during the pandemic. STUDY DESIGN: Data were collected from public EHR app galleries on a monthly basis from December 31, 2019, through June 1, 2021. METHODS: Apps were identified as relating to COVID-19 or telehealth using text analysis of the app marketing materials. Descriptive analyses were conducted to characterize telehealth- and COVID-19-related apps discovered through the app galleries, identify their primary functionality, and examine whether any apps added new telehealth- or COVID-19-related functionalities during the pandemic. RESULTS: The number of COVID-19-related apps increased from 0 in March 2020 to 19 a month later and continued to grow to 62 as of June 2021. The number of telehealth-related apps more than doubled from prepandemic levels (n = 41) to a total of 87 apps by June 2021. These apps were 2 times more likely to contain specialized capabilities used to support COVID-19 response efforts, such as secure messaging, vaccine administration, and laboratory testing, compared with all apps listed in the EHR app galleries. CONCLUSIONS: These findings demonstrate the potential of integrating third-party apps into EHRs to expand the range of tools that health care providers can use to diagnose, treat, and communicate with patients.

Tailored text message and web intervention for smoking cessation in U.S. socioeconomically-disadvantaged young adults: A randomized controlled trial.

The prevalence of cigarette smoking in young adults is higher among those with socioeconomic disadvantage than those without. Low treatment-seeking among young adult smokers is compounded by few efficacious smoking cessation interventions for this group, particularly socioeconomically-disadvantaged young adults (SDYA) who smoke cigarettes. The goal of this study was to test a tailored smoking-cessation intervention for SDYA. 343 SDYA aged 18-30 living in the U.S. (85% female) who smoke cigarettes with access to a smartphone and interest in quitting smoking in the next six months were recruited online in Spring 2020 and randomized to referral to online quit resources (usual care control; n = 171) or a 12-week tailored text message smoking-cessation program with a companion web-based intervention (n = 172). Intent to treat analyses examined associations between study condition, self-reported 30-day point prevalence abstinence (PPA), and confidence to quit smoking at 12 weeks, controlling for potential confounders. Intervention group participants had greater self-reported 30-day PPA at 12-weeks than controls (adjusted relative risk 3.93, 95% CI 2.14-7.24). Among those who continued smoking, the intervention increased confidence to quit (0.81 points, 95% confidence interval 0.08-1.53). Weekly engagement in the intervention predicted greater cessation. A tailored text message intervention for SDYA increased smoking abstinence and confidence to quit at the end-of-treatment. Findings may have been influenced by recruitment at the start of the COVID pandemic but suggest that text messaging is an acceptable and efficacious cessation strategy for SDYA smokers. Future studies should examine the impact on longer-term smoking-cessation and importance of intervention tailoring for SDYA.

Lung Support Service: Implementation of a Nationwide Text Message Support Program for People with Chronic Respiratory Disease during the COVID-19 Pandemic.

BACKGROUND: COVID-19 pandemic lockdowns led to the closure of most in-person pulmonary rehabilitation programs in Australia. Text message programs are effective for delivering health support to aid the self-management of people with chronic diseases. This study aimed to evaluate the implementation of a six-month pre-post text message support program (Texting for Wellness: Lung Support Service), and the enablers and barriers to its adoption and implementation. METHODS: This mixed-methods pre-post study used the Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) framework to evaluate the Texting for Wellness: Lung Support Service, which is an automated six-month text message support program that included evidence-based lifestyle, disease-self management and COVID-19-related information. Reach was measured by the proportion of participant enrolments and demographic characteristics. Adoption enablers and barriers were measured using text message response data and a user feedback survey (five-point Likert scale questions and free-text responses). Implementation was evaluated to determine fidelity including text message delivery data, opt-outs, and intervention costs to promote and deliver the program. RESULTS: In total, 707/1940 (36.4%) participants enrolled and provided e-consent, with a mean age (±standard deviation) of 67.9 (±9.2) years old (range: 23-87 years). Of participants who provided feedback, (326/707) most 'agreed' or 'strongly agreed' that the text messages were easy to understand (98.5%), helpful them to feel supported (92.3%) and helped them to manage their health (88.0%). Factors influencing engagement included a feeling of support and reducing loneliness, and its usefulness for health self-management. Messages were delivered as planned (93.7% successfully delivered) with minimal participant dropouts (92.2% retention rate) and low cost ($AUD24.48/participant for six months). A total of 2263 text message replies were received from 496 unique participants. There were no reported adverse events. CONCLUSION: Texting for Wellness: Lung Support Service was implemented quickly, had a broad reach, with high retention and acceptability among participants. The program was low cost and required minimal staff oversight, which may facilitate future implementation. Further research is needed to evaluate the efficacy of text messaging for the improvement of lung health outcomes and strategies for long-term pulmonary rehabilitation program maintenance.

A thematic analysis-based model for identifying the impacts of natural crises on a supply chain for service integrity: a text analysis approach.

Numerous studies have been conducted to identify the effects of natural crises on supply chain performance. Conventional analysis methods are based on either manual filter methods or data-driven methods. The manual filter methods suffer from validation problems due to sampling limitations, and data-driven methods suffer from the nature of crisis data which are vague and complex. This study aims to present an intelligent analysis model to automatically identify the effects of natural crises such as the COVID-19 pandemic on the supply chain through metadata generated on social media. This paper presents a thematic analysis framework to extract knowledge under user steering. This framework uses a text-mining approach, including co-occurrence term analysis and knowledge map construction. As a case study to approve our proposed model, we retrieved, cleaned, and analyzed 1024 online textual reports on supply chain crises published during the COVID-19 pandemic in 2019-2021. We conducted a thematic analysis of the collected data and achieved a knowledge map on the impact of the COVID-19 crisis on the supply chain. The resultant knowledge map consists of five main areas (and related sub-areas), including (1) food retail, (2) food services, (3) manufacturing, (4) consumers, and (5) logistics. We checked and validated the analytical results with some field experts. This experiment achieved 53 crisis knowledge propositions classified from 25,272 sentences with 631,799 terms and 31,864 unique terms using just three user-system interaction steps, which shows the model's high performance. The results lead us to conclude that the proposed model could be used effectively and efficiently as a decision support system, especially for crises in the supply chain analysis.