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Background: Internally displaced persons (IDPs) in Nigeria face a high burden of mental health disorders, with limited access to evidence-based, culturally relevant interventions. Life skills education (LSE) is a promising approach to promote mental health and psychosocial well-being in humanitarian settings. This study aims to evaluate the effectiveness and implementation of a culturally adapted LSE program delivered through in-person and mobile platforms among IDPs in Northern Nigeria., Methods: This cluster-randomized hybrid type 2 effectiveness-implementation trial will be conducted in 20 IDP camps or host communities in Maiduguri, Nigeria. Sites will be randomly assigned to receive a 12-week LSE program delivered either through in-person peer support groups or WhatsApp-facilitated mobile groups. The study will recruit 500 participants aged 13 years and older. Intervention effectiveness outcomes include the primary outcome of change in post-traumatic stress disorder (PTSD) symptoms assessed using the PCL-5 scale, and secondary outcomes of depression, anxiety, well-being, and life skills acquisition. Implementation outcomes will be assessed using the Acceptability of Intervention Measure (AIM), Intervention Appropriateness Measure (IAM), and Feasibility of Intervention Measure (FIM). Both sets of outcomes will be compared between the in-person and mobile delivery groups. Quantitative data will be analyzed using mixed-effects linear regression models, while qualitative data will be examined through reflexive thematic analysis. The study will be guided by the Reach-Effectiveness-Adoption-Implementation-Maintenance (RE-AIM) framework., Discussion: The RESETTLE-IDPs study addresses key gaps in the evidence base on mental health interventions for conflict-affected populations. It focuses on underserved IDP populations, evaluates the comparative effectiveness of in-person and mobile-delivered LSE, and incorporates implementation science frameworks to assess contextual factors influencing adoption, fidelity, and sustainability. The study employs a community-based participatory approach to enhance cultural relevance, acceptability, and ownership. Findings will inform the development and scale-up of evidence-based, sustainable mental health interventions for IDPs in Nigeria and other humanitarian contexts., Trial Sponsor: Dalhousie University, 6299 South St, Halifax, NS B3H 4R2, Canada., Trial Registration: ClinicalTrials.gov, NCT06412679  Registered 15 May 2024., (© 2024. The Author(s).)

Background: To evaluate the effects of a web-based, personalized avatar intervention conveying the concept of community immunity (herd immunity) on risk perception (perceptions of the risk of infection spreading (to self, family, community, and vulnerable individuals)) and other cognitive and emotional responses across 4 vaccine-preventable disease contexts: measles, pertussis, influenza, and an unnamed "vaccine-preventable disease.", Methods: Through a robust user-centered design process, we developed a web application, " herdimm ," showing how community immunity works. In our application, people personalize a virtual community by creating avatars (themselves, 2 vulnerable people in their community, and 6 other people around them; e.g., family members or co-workers.) Herdimm integrates these avatars in a 2-minute narrated animation showing visually how infections spread with and without the protection of community immunity. The present study was a 2×4 factorial randomized controlled trial to assess herdimm 's effects. We recruited 3883 adults via Qualtrics living in Canada who could complete an online study in English or French. We pre-registered our study, including depositing our questionnaire and pre-scripted statistical code on Open Science Framework (https://osf.io/hkysb/). The trial ran from March 1 to July 1, 2021. We compared the web application to no intervention (i.e. control) on primary outcome risk perception, divided into objective risk perception (accuracy of risk perception) and subjective risk perception (subjective sense of risk), and on secondary outcomes-emotions (worry, anticipated guilt), knowledge, and vaccination intentions-using analysis of variance for continuous outcomes and logistic regression for dichotomous outcomes. We conducted planned moderation analyses using participants' scores on a validated scale of individualism and collectivism as moderators., Results: Overall, herdimm had desirable effects on all outcomes. People randomized to herdimm were more likely to score high on objective risk perception (58.0%, 95% confidence interval 56.0%-59.9%) compared to those assigned to the control condition (38.2%, 95% confidence interval 35.5%-40.9%). Herdimm increased subjective risk perception from a mean of 5.30 on a scale from 1 to 7 among those assigned to the control to 5.54 among those assigned to herdimm . The application also increased emotions (worry, anticipated guilt) (F(1,3875)=13.13, p<0.001), knowledge (F(1,3875)=36.37, p<0.001) and vaccination intentions (Chi-squared(1)=9.4136, p=0.002). While objective risk perception did not differ by disease (Chi-squared(3)=6.94, p=0.074), other outcomes did (subjective risk perception F(3,3875) = 5.6430, p<0.001; emotions F(3,3875)=78.54, p<0.001; knowledge (F(3,3875)=5.20, p=0.001); vaccination intentions Chi-squared (3)=15.02, p=0.002). Moderation models showed that many findings were moderated by participants' individualism and collectivism scores. Overall, whereas outcomes tended not to vary by individualism and collectivism among participants in the control condition, the positive effects of herdimm were larger among participants with more collectivist orientations and effects were sometimes negative among participants with more individualist orientations., Conclusions: Conveying the concept of community immunity through a web application using personalized avatars increases objective and subjective risk perception and positively influences intentions to receive vaccines, particularly among people who have more collectivist worldviews. Including prosocial messages about the collective benefits of vaccination in public health campaigns may increase positive effects among people who are more collectivist while possibly backfiring among those who are more individualistic., Competing Interests: Conflict of interest None

Background: Smartphone-delivered attentional bias modification training (ABMT) intervention has gained popularity as a remote solution for alleviating symptoms of mental health problems. However, the existing literature presents mixed results indicating both significant and insignificant effects of smartphone-delivered interventions., Objective: This systematic review and meta-analysis aims to assess the impact of smartphone-delivered ABMT on attentional bias and symptoms of mental health problems. Specifically, we examined different design approaches and methods of administration, focusing on common mental health issues, such as anxiety and depression, and design elements, including gamification and stimulus types., Methods: Our search spanned from 2014 to 2023 and encompassed 4 major databases: MEDLINE, PsycINFO, PubMed, and Scopus. Study selection, data extraction, and critical appraisal were performed independently by 3 authors using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. When necessary, we pooled the standardized mean difference with a 95% CI. In addition, we conducted sensitivity, subgroup, and meta-regression analyses to explore moderator variables of active and placebo ABMT interventions on reducing symptoms of mental health problems and attentional bias., Results: Our review included 12 papers, involving a total of 24,503 participants, and we were able to conduct a meta-analysis on 20 different study samples from 11 papers. Active ABMT exhibited an effect size (Hedges g) of -0.18 (P=.03) in reducing symptoms of mental health problems, while the overall effect remained significant. Similarly, placebo ABMT showed an effect size of -0.38 (P=.008) in reducing symptoms of mental health problems. In addition, active ABMT (Hedges g -0.17; P=.004) had significant effects on reducing attentional bias, while placebo ABMT did not significantly alter attentional bias (Hedges g -0.04; P=.66)., Conclusions: Our understanding of smartphone-delivered ABMT's potential highlights the value of both active and placebo interventions in mental health care. The insights from the moderator analysis also showed that tailoring smartphone-delivered ABMT interventions to specific threat stimuli and considering exposure duration are crucial for optimizing their efficacy. This research underscores the need for personalized approaches in ABMT to effectively reduce attentional bias and symptoms of mental health problems., Trial Registration: PROSPERO CRD42023460749; https://www.crd.york.ac.uk/prospero/display&#95;record.php?RecordID=460749., (©Bilikis Banire, Matt Orr, Hailey Burns, Youna McGowan, Rita Orji, Sandra Meier. Originally published in JMIR Mental Health (https://mental.jmir.org), 02.09.2024.)

Background: Mental health disorders are the leading cause of health-related problems worldwide. It is projected that mental health disorders will be the leading cause of morbidity among adults as the incidence rates of anxiety and depression grow worldwide. Recently, "extended reality" (XR), a general term covering virtual reality (VR), augmented reality (AR), and mixed reality (MR), is paving the way for the delivery of mental health care., Objective: We aimed to investigate the adoption and implementation of XR technology used in interventions for mental disorders and to provide statistical analyses of the design, usage, and effectiveness of XR technology for mental health interventions with a worldwide demographic focus., Methods: In this paper, we conducted a scoping review of the development and application of XR in the area of mental disorders. We performed a database search to identify relevant studies indexed in Google Scholar, PubMed, and the ACM Digital Library. A search period between August 2016 and December 2023 was defined to select papers related to the usage of VR, AR, and MR in a mental health context. The database search was performed with predefined queries, and a total of 831 papers were identified. Ten papers were identified through professional recommendation. Inclusion and exclusion criteria were designed and applied to ensure that only relevant studies were included in the literature review., Results: We identified a total of 85 studies from 27 countries worldwide that used different types of VR, AR, and MR techniques for managing 14 types of mental disorders. By performing data analysis, we found that most of the studies focused on high-income countries, such as the United States (n=14, 16.47%) and Germany (n=12, 14.12%). None of the studies were for African countries. The majority of papers reported that XR techniques lead to a significant reduction in symptoms of anxiety or depression. The majority of studies were published in 2021 (n=26, 30.59%). This could indicate that mental disorder intervention received higher attention when COVID-19 emerged. Most studies (n=65, 76.47%) focused on a population in the age range of 18-65 years, while few studies (n=2, 3.35%) focused on teenagers (ie, subjects in the age range of 10-19 years). In addition, more studies were conducted experimentally (n=67, 78.82%) rather than by using analytical and modeling approaches (n=8, 9.41%). This shows that there is a rapid development of XR technology for mental health care. Furthermore, these studies showed that XR technology can effectively be used for evaluating mental disorders in a similar or better way that conventional approaches., Conclusions: In this scoping review, we studied the adoption and implementation of XR technology for mental disorder care. Our review shows that XR treatment yields high patient satisfaction, and follow-up assessments show significant improvement with large effect sizes. Moreover, the studies adopted unique designs that were set up to record and analyze the symptoms reported by their participants. This review may aid future research and development of various XR mechanisms for differentiated mental disorder procedures., (©Olatunji Mumini Omisore, Ifeanyi Odenigbo, Joseph Orji, Amelia Itzel Hernandez Beltran, Sandra Meier, Nilufar Baghaei, Rita Orji. Originally published in JMIR Serious Games (https://games.jmir.org), 24.07.2024.)

Persuasive technologies, in connection with human factor engineering requirements for healthy workplaces, have played a significant role in ensuring a change in human behavior. Healthy workplaces suggest different best practices applicable to body posture, proximity to the computer system, movement, lighting conditions, computer system layout, and other significant psychological and cognitive aspects. Most importantly, body posture suggests how users should sit or stand in workplaces in line with best and healthy practices. In this study, we developed two study phases (pilot and main) using two deep learning models: convolutional neural networks (CNN) and Yolo-V3. To train the two models, we collected posture datasets from creative common license YouTube videos and Kaggle. We classified the dataset into comfortable and uncomfortable postures. Results show that our YOLO-V3 model outperformed CNN model with a mean average precision of 92%. Based on this finding, we recommend that YOLO-V3 model be integrated in the design of persuasive technologies for a healthy workplace. Additionally, we provide future implications for integrating proximity detection taking into consideration the ideal number of centimeters users should maintain in a healthy workplace., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Ataguba and Orji.)

Androgen deprivation therapy is the cornerstone of systemic management for prostate cancer but is associated with multiple adverse effects that must be considered during treatment. These effects occur because of the profound hypogonadism that is induced from lack of testosterone or due to the medications used in the treatment or in combination with androgen receptor signaling inhibitors. This article critically reviews the associations between androgen deprivation therapy, androgen receptor signaling inhibitors, and cardiovascular complications such as prolonged QT interval, atrial fibrillation, heart failure, atherosclerosis, coronary heart disease, venous thromboembolism, and peripheral arterial occlusive disease. These unfavorable outcomes reinforce the need for regular cardiovascular screening of patients undergoing androgen deprivation for the management of prostate cancer.

African foods have socio-cultural significance that extends through migration, tourism, and marriage. Africans travel and integrate within the continent through intermarriages. There are over a thousand cultural aspects that differ such as language, food, dressing, beliefs and customs. Food is one of the cultural aspects that Africans embrace quickly as they migrate and integrate socio-culturally. We considered the limited representation of African food research in the HCI community and propose to contribute the rich significant food datasets from two African countries: Cameroon and Ghana. List of Cameroonian foods collected are: Ekwang, Eru and Ndole. In addition, the list of Ghanaian foods we collected are: Jollof Rice, Palm-nut Soup and Waakye. Given the cultural diversity and our study's goal for cultural inclusion, we interacted with at least two locals from the selected countries, and they confirmed that these foods were universally recognized within their respective countries. The datasets were collected from YouTube, Facebook, the field (restaurants), Creative Common Attribution Google Images, and other Creative Commons Attribution sources. A total of 204 images of Ekwang, 206 images of Eru and 205 images of Ndole were collected. In addition, we collected a total of 347 images of Jollof Rice, 392 images of Palm-nut Soup and 400 images of Waakye. We present a meta-data description of the data, quality assessments of our dataset and opportunities for the HCI community to explore in the future., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier Inc.)

Sick sinus syndrome (SSS) is a condition of the sinoatrial node that arises from a constellation of aberrant rhythms, resulting in reduced pacemaker activity and impulse transmission. According to the World Health Organization, pulmonary hypertension (PH) is defined by a mean pulmonary arterial pressure of >25 mmHg at rest, measured during right heart catheterization. It can result in right atrial remodeling, which may predispose the patient to sinus node dysfunction. This study sought to estimate the impact of PH on clinical outcomes of hospitalizations with SSS. The U.S. National Inpatient Sample database from 2016-2019 was searched for hospitalized adult patients with SSS as a principal diagnosis with and without PH as a secondary diagnosis using the International Classification of Diseases, Tenth Revision, codes. The primary outcome was inpatient mortality. The secondary outcomes were acute kidney injury (AKI), cardiogenic shock (CS), cardiac arrest, rates of pacemaker insertion, total hospital charges (THCs), and length of stay (LOS). Multivariate regression analysis was used to adjust for confounders. A total of 181,230 patients were admitted for SSS; 8.3% (14,990) had underlying PH. Compared to patients without PH, patients admitted with coexisting PH had a statistically significant increase in mortality (95% confidence interval, 1.21-2.32; P = .002), AKI ( P < .001), CS ( P = .004), THC ( P = .037), and LOS ( P < .001). In conclusion, patients admitted primarily for SSS with coexisting PH had a statistically significant increase in mortality, AKI, CS, THC, and LOS. Additional studies geared at identifying and addressing the underlying etiologies for PH in this population may be beneficial in the management of this patient group., Competing Interests: The authors report no conflicts of interest for the published content. No funding information was provided., (Copyright: © 2023 Innovations in Cardiac Rhythm Management.)

Persuasive technologies are designed to change human behavior or attitude using various persuasive strategies. Recent years have witnessed increasing evidence of the need to personalize and adapt persuasive interventions to various users and contextual factors because a persuasive strategy that works for one individual may rather demotivate others. As a result, several research studies have been conducted to investigate how to effectively personalize persuasive technologies. As research in this direction is gaining increasing attention, it becomes essential to conduct a systematic review to provide an overview of the current trends, challenges, approaches used for developing personalized persuasive technologies, and opportunities for future research in the area. To fill this need, we investigate approaches to personalize persuasive interventions by understanding user-related factors considered when personalizing persuasive technologies. Particularly, we conducted a systematic review of 72 research published in the last ten years in personalized and adaptive persuasive systems. The reviewed papers were evaluated based on different aspects, including metadata (e.g., year of publication and venue), technology, personalization dimension, personalization approaches, target outcome, individual differences, theories and scales, and evaluation approaches. Our results show (1) increased attention toward personalizing persuasive interventions, (2) personality trait is the most popular dimension of individual differences considered by existing research when tailoring their persuasive and behavior change systems, (3) students are among the most commonly targeted audience, and (4) education, health, and physical activity are the most considered domains in the surveyed papers. Based on our results, the paper provides insights and prospective future research directions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Alslaity, Chan and Orji.)

Smartphone use provides a significant amount of screen-time for youth, and there have been growing concerns regarding its impact on their mental health. While time spent in a passive manner on the device is frequently considered deleterious, more active engagement with the phone might be protective for mental health. Recent developments in mobile sensing technology provide a unique opportunity to examine behaviour in a naturalistic manner. The present study sought to investigate, in a sample of 451 individuals (mean age 20.97 years old, 83% female), whether the amount of time spent on the device, an indicator of passive smartphone use, would be associated with worse mental health in youth and whether an active form of smartphone use, namely frequent checking of the device, would be associated with better outcomes. The findings highlight that overall time spent on the smartphone was associated with more pronounced internalizing and externalizing symptoms in youth, while the number of unlocks was associated with fewer internalizing symptoms. For externalizing symptoms, there was also a significant interaction between the two types of smartphone use observed. Using objective measures, our results suggest interventions targeting passive smartphone use may contribute to improving the mental health of youth., Competing Interests: Declaration of Competing Interest All authors have no conflicts of interest to declare., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Multiple waves of COVID-19 have significantly impacted the emotional well-being of all, but many were subject to additional risks associated with forced regulations. The objective of this research was to assess the immediate emotional impact, expressed by Canadian Twitter users, and to estimate the linear relationship, with the vicissitudes of COVID caseloads, using ARIMA time-series regression. We developed two Artificial Intelligence-based algorithms to extract tweets using 18 semantic terms related to social confinement and locked down and then geocoded them to tag Canadian provinces. Tweets (n = 64,732) were classified as positive, negative, and neutral sentiments using a word-based Emotion Lexicon. Our results indicated: that Tweeters were expressing a higher daily percentage of negative sentiments representing, negative anticipation (30.1%), fear (28.1%), and anger (25.3%), than positive sentiments comprising positive anticipation (43.7%), trust (41.4%), and joy (14.9%), and neutral sentiments with mostly no emotions, when hash-tagged social confinement and locked down. In most provinces, negative sentiments took on average two to three days after caseloads increase to emerge, whereas positive sentiments took a slightly longer period of six to seven days to submerge. As daily caseloads increase, negative sentiment percentage increases in Manitoba (by 68% for 100 caseloads increase) and Atlantic Canada (by 89% with 100 caseloads increase) in wave 1(with 30% variations explained), while other provinces showed resilience. The opposite was noted in the positive sentiments. The daily percentage of emotional expression variations explained by daily caseloads in wave one were 30% for negative, 42% for neutral, and 2.1% for positive indicating that the emotional impact is multifactorial. These provincial-level impact differences with varying latency periods should be considered when planning geographically targeted, time-sensitive, confinement-related psychological health promotion efforts. Artificial Intelligence-based Geo-coded sentiment analysis of Twitter data opens possibilities for targeted rapid emotion sentiment detection opportunities., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2023.)

Background: Primary, basic, secondary, and high school teachers are constantly faced with increased work stressors that can result in psychological health challenges such as burnout, anxiety, and depression, and in some cases, physical health problems. It is presently unknown what the mental health literacy levels are or the prevalence and correlates of psychological issues among teachers in Zambia. It is also unknown if an email mental messaging program (Wellness4Teachers) would effectively reduce burnout and associated psychological problems and improve mental health literacy among teachers., Objective: The primary objectives of this study are to determine if daily supportive email messages plus weekly mental health literacy information delivered via email can help improve mental health literacy and reduce the prevalence of moderate to high stress symptoms, burnout, moderate to high anxiety symptoms, moderate to high depression symptoms, and low resilience among school teachers in Zambia. The secondary objectives of this study are to evaluate the baseline prevalence and correlates of moderate to high stress, burnout, moderate to high anxiety, moderate to high depression, and low resilience among school teachers in Zambia., Methods: This is a quantitative longitudinal and cross-sessional study. Data will be collected at the baseline (the onset of the program), 6 weeks, 3 months, 6 months (the program midpoint), and 12 months (the end point) using web-based surveys. Individual teachers will subscribe by accepting an invitation to do so from the Lusaka Apex Medical University organizational account on the ResilienceNHope web-based application. Data will be analyzed using SPSS version 25 with descriptive and inferential statistics. Outcome measures will be evaluated using standardized rating scales., Results: The Wellness4Teachers email program is expected to improve the participating teachers' mental health literacy and well-being. It is anticipated that the prevalence of stress, burnout, anxiety, depression, and low resilience among teachers in Zambia will be similar to those reported in other jurisdictions. In addition, it is expected that demographic, socioeconomic, and organizational factors, class size, and grade teaching will be associated with burnout and other psychological disorders among teachers, as indicated in the literature. Results are expected 2 years after the program's launch., Conclusions: The Wellness4Teachers email program will provide essential insight into the prevalence and correlates of psychological problems among teachers in Zambia and the program's impact on subscribers' mental health literacy and well-being. The outcome of this study will help inform policy and decision-making regarding psychological interventions for teachers in Zambia., International Registered Report Identifier (irrid): PRR1-10.2196/44370., (©Belinda Agyapong, Charles Chishimba, Yifeng Wei, Raquel da Luz Dias, Ejemai Eboreime, Eleanor Msidi, Syed Sibte Raza Abidi, Maryn Mutaka-Loongo, James Mwansa, Rita Orji, John Mathias Zulu, Vincent Israel Opoku Agyapong. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 06.03.2023.)

Drugs have the potential of causing adverse reactions or side effects and prior knowledge of these reactions can help prevent hospitalizations and premature deaths. Public databases of common adverse drug reactions (ADRs) depend on individual reports from drug manufacturers and health professionals. However, this passive approach to ADR surveillance has been shown to suffer from severe under-reporting. Social media, such as online health forums where patients across the globe willingly share their drug intake experience, is a viable and rich source for detecting unreported ADRs. In this paper, we design an ADR Detection Framework (ADF) using Natural Language Processing techniques to identify ADRs in drug reviews mined from social media. We demonstrate the applicability of ADF in the domain of Diabetes by identifying ADRs associated with diabetes drugs using data extracted from three online patient-based health forums: askapatient.com , webmd.com , and iodine.com . Next, we analyze and visualize the ADRs identified and present valuable insights including prevalent and less prevalent ADRs, age and gender differences in ADRs detected, as well as the previously unknown ADRs detected by our framework. Our work could promote active (real-time) ADR surveillance and also advance pharmacovigilance research.

Over the years, there has been a global increase in the use of technology to deliver interventions for health and wellness, such as improving people's mental health and resilience. An example of such technology is the Q-Life app which aims to improve people's resilience to stress and adverse life events through various coping mechanisms, including journaling. Using a combination of sentiment analysis and thematic analysis methods, this paper presents the results of analyzing 6023 journal entries from 755 users. We uncover both positive and negative factors that are associated with resilience. First, we apply two lexicon-based and eight machine learning (ML) techniques to classify journal entries into positive or negative sentiment polarity, and then compare the performance of these classifiers to determine the best performing classifier overall. Our results show that Support Vector Machine (SVM) is the best classifier overall, outperforming other ML classifiers and lexicon-based classifiers with a high F1-score of 89.7%. Second, we conduct thematic analysis of negative and positive journal entries to identify themes representing factors associated with resilience either negatively or positively, and to determine various coping mechanisms. Our findings reveal 14 negative themes such as stress, worry, loneliness, lack of motivation, sickness, relationship issues, as well as depression and anxiety. Also, 13 positive themes emerged including self-efficacy, gratitude, socialization, progression, relaxation, and physical activity. Seven (7) coping mechanisms are also identified including time management, quality sleep, and mindfulness. Finally, we reflect on our findings and suggest technological interventions that address the negative factors to promote resilience.

Stress is one of the significant triggers of several physiological and psychological illnesses. Mobile health apps have been used to deliver various stress management interventions and coping strategies over the years. However, little work exists on persuasive strategies employed in stress management apps to promote behavior change. To address this gap, we review 150 stress management apps on both Google Play and Apple's App Store in three stages. First, we deconstruct and compare the persuasive/behavior change strategies operationalized in the apps using the Persuasive Systems Design (PSD) framework and Cialdini's Principles of Persuasion. Our results show that the most frequently employed strategies are personalization , followed by self-monitoring , and trustworthiness , while social support strategies such as competition, cooperation and social comparison are the least employed. Second, we compare our findings within the stress management domain with those from other mental health domains to uncover further insights. Finally, we reflect on our findings and offer eight design recommendations to improve the effectiveness of stress management apps and foster future research., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Alhasani, Mulchandani, Oyebode, Baghaei and Orji.)

The COVID-19 pandemic has affected people's lives in many ways. Social media data can reveal public perceptions and experience with respect to the pandemic, and also reveal factors that hamper or support efforts to curb global spread of the disease. In this paper, we analyzed COVID-19-related comments collected from six social media platforms using natural language processing (NLP) techniques. We identified relevant opinionated keyphrases and their respective sentiment polarity (negative or positive) from over 1 million randomly selected comments, and then categorized them into broader themes using thematic analysis. Our results uncover 34 negative themes out of which 17 are economic, socio-political, educational, and political issues. Twenty (20) positive themes were also identified. We discuss the negative issues and suggest interventions to tackle them based on the positive themes and research evidence., Competing Interests: Conflict of InterestThe authors declare no competing interests., (© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022.)

Persuasive gamified systems for health are interventions that promote behaviour change using various persuasive strategies. While research has shown that these strategies are effective at motivating behaviour change, there is little knowledge on whether and how the effectiveness of these strategies vary across multiple domains for people of distinct personality traits. To bridge this gap, we conducted a quantitative study with 568 participants to investigate (a) whether the effectiveness of the persuasive strategies implemented vary within each domain (b) whether the effectiveness of various strategies vary across two distinct domains, (c) how people belonging to different personality traits respond to these strategies, and (d) if people high in a personality trait would be influenced by a persuasive strategy within one domain and not in the other. Our results show that there are significant differences in the effectiveness of various strategies across domains and that people's personality plays a significant role in the perceived persuasiveness of different strategies both within and across distinct domains. The Reward strategy (which involves incentivizing users for achieving specific milestones towards the desired behaviour) and the Competition strategy (which involves allowing users to compete with each other to perform the desired behaviour) were effective for promoting healthy eating but not for smoking cessation for people high in Conscientiousness . We provide design suggestions for developing persuasive gamified interventions for health targeting distinct domains and tailored to individuals depending on their personalities., Competing Interests: Conflict of interestOn behalf of all authors, the corresponding author states that there is no conflict of interest., (© The Author(s), under exclusive licence to Springer Nature B.V. 2022.)

With the proliferation of ubiquitous computing and mobile technologies, mobile apps are tailored to support users to perform target behaviors in various domains, including a sustainable future. This article provides a systematic evaluation of mobile apps for sustainable waste management to deconstruct and compare the persuasive strategies employed and their implementations. Specifically, it targeted apps that support various sustainable waste management activities such as personal tracking, recycling, conference management, data collection, food waste management, do-it-yourself (DIY) projects, games, etc. The authors who are persuasive technology researchers retrieved a total of 244 apps from App Store and Google Play, out of which 148 apps were evaluated. Two researchers independently analyzed and coded the apps and a third researcher was involved to resolve any disagreement. They coded the apps based on the persuasive strategies of the persuasive system design framework. Overall, the findings uncover that out of the 148 sustainable waste management apps evaluated, primary task support was the most employed category by 89% (n = 131) apps, followed by system credibility support implemented by 76% (n = 112) apps. The dialogue support was implemented by 71% (n = 105) apps and social support was the least utilized strategy by 34% (n = 51) apps. Specifically, Reduction (n = 97), personalization (n = 90), real-world feel (n = 83), surface credibility (n = 83), reminder (n = 73), and self-monitoring (n = 50) were the most commonly employed persuasive strategies. The findings established that there is a significant association between the number of persuasive strategies employed and the apps' effectiveness as indicated by user ratings of the apps. How the apps are implemented differs depending on the kind of sustainable waste management activities it was developed for. Based on the findings, this paper offers design implications for personalizing sustainable waste management apps to improve their persuasiveness and effectiveness., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Nkwo, Suruliraj and Orji.)

Background: Internalizing disorders are the most common psychiatric problems observed among youth in Canada. Sadly, youth with internalizing disorders often avoid seeking clinical help and rarely receive adequate treatment. Current methods of assessing internalizing disorders usually rely on subjective symptom ratings, but internalizing symptoms are frequently underreported, which creates a barrier to the accurate assessment of these symptoms in youth. Therefore, novel assessment tools that use objective data need to be developed to meet the highest standards of reliability, feasibility, scalability, and affordability. Mobile sensing technologies, which unobtrusively record aspects of youth behaviors in their daily lives with the potential to make inferences about their mental health states, offer a possible method of addressing this assessment barrier., Objective: This study aims to explore whether passively collected smartphone sensor data can be used to predict internalizing symptoms among youth in Canada., Methods: In this study, the youth participants (N=122) completed self-report assessments of symptoms of anxiety, depression, and attention-deficit hyperactivity disorder. Next, the participants installed an app, which passively collected data about their mobility, screen time, sleep, and social interactions over 2 weeks. Then, we tested whether these passive sensor data could be used to predict internalizing symptoms among these youth participants., Results: More severe depressive symptoms correlated with more time spent stationary (r=0.293; P=.003), less mobility (r=0.271; P=.006), higher light intensity during the night (r=0.227; P=.02), and fewer outgoing calls (r=-0.244; P=.03). In contrast, more severe anxiety symptoms correlated with less time spent stationary (r=-0.249; P=.01) and greater mobility (r=0.234; P=.02). In addition, youths with higher anxiety scores spent more time on the screen (r=0.203; P=.049). Finally, adding passively collected smartphone sensor data to the prediction models of internalizing symptoms significantly improved their fit., Conclusions: Passively collected smartphone sensor data provide a useful way to monitor internalizing symptoms among youth. Although the results replicated findings from adult populations, to ensure clinical utility, they still need to be replicated in larger samples of youth. The work also highlights intervention opportunities via mobile technology to reduce the burden of internalizing symptoms early on., (©Lucy MacLeod, Banuchitra Suruliraj, Dominik Gall, Kitti Bessenyei, Sara Hamm, Isaac Romkey, Alexa Bagnell, Manuel Mattheisen, Viswanath Muthukumaraswamy, Rita Orji, Sandra Meier. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 26.10.2021.)

Background: During the COVID-19 pandemic, people had to adapt their daily life routines to the currently implemented public health measures, which is likely to have resulted in a lack of in-person social interactions, physical activity, or sleep. Such changes can have a significant impact on mental health. Mobile sensing apps can passively record the daily life routines of people, thus making them aware of maladaptive behavioral adjustments to the pandemic., Objective: This study aimed to explore the views of people on mobile sensing apps that passively record behaviors and their potential to increase awareness and helpfulness for self-managing mental health during the pandemic., Methods: We conducted an anonymous web-based survey including people with and those without mental disorders, asking them to rate the helpfulness of mobile sensing apps for the self-management of mental health during the COVID-19 pandemic. The survey was conducted in May 2020., Results: The majority of participants, particularly those with a mental disorder (n=106/148, 72%), perceived mobile sensing apps as very or extremely helpful for managing their mental health by becoming aware of maladaptive behaviors. The perceived helpfulness of mobile sensing apps was also higher among people who experienced a stronger health impact of the COVID-19 pandemic (β=.24; 95% CI 0.16-0.33; P<.001), had a better understanding of technology (β=.17; 95% CI 0.08-0.25; P<.001), and had a higher education (β=.1; 95% CI 0.02-0.19; P=.02)., Conclusions: Our findings highlight the potential of mobile sensing apps to assist in mental health care during the pandemic., (©Banuchitra Suruliraj, Kitti Bessenyei, Alexa Bagnell, Patrick McGrath, Lori Wozney, Rita Orji, Sandra Meier. Originally published in JMIR Formative Research (https://formative.jmir.org), 26.04.2021.)

Background: The COVID-19 pandemic has caused a global health crisis that affects many aspects of human lives. In the absence of vaccines and antivirals, several behavioral change and policy initiatives such as physical distancing have been implemented to control the spread of COVID-19. Social media data can reveal public perceptions toward how governments and health agencies worldwide are handling the pandemic, and the impact of the disease on people regardless of their geographic locations in line with various factors that hinder or facilitate the efforts to control the spread of the pandemic globally., Objective: This paper aims to investigate the impact of the COVID-19 pandemic on people worldwide using social media data., Methods: We applied natural language processing (NLP) and thematic analysis to understand public opinions, experiences, and issues with respect to the COVID-19 pandemic using social media data. First, we collected over 47 million COVID-19-related comments from Twitter, Facebook, YouTube, and three online discussion forums. Second, we performed data preprocessing, which involved applying NLP techniques to clean and prepare the data for automated key phrase extraction. Third, we applied the NLP approach to extract meaningful key phrases from over 1 million randomly selected comments and computed sentiment score for each key phrase and assigned sentiment polarity (ie, positive, negative, or neutral) based on the score using a lexicon-based technique. Fourth, we grouped related negative and positive key phrases into categories or broad themes., Results: A total of 34 negative themes emerged, out of which 15 were health-related issues, psychosocial issues, and social issues related to the COVID-19 pandemic from the public perspective. Some of the health-related issues were increased mortality, health concerns, struggling health systems, and fitness issues; while some of the psychosocial issues were frustrations due to life disruptions, panic shopping, and expression of fear. Social issues were harassment, domestic violence, and wrong societal attitude. In addition, 20 positive themes emerged from our results. Some of the positive themes were public awareness, encouragement, gratitude, cleaner environment, online learning, charity, spiritual support, and innovative research., Conclusions: We uncovered various negative and positive themes representing public perceptions toward the COVID-19 pandemic and recommended interventions that can help address the health, psychosocial, and social issues based on the positive themes and other research evidence. These interventions will help governments, health professionals and agencies, institutions, and individuals in their efforts to curb the spread of COVID-19 and minimize its impact, and in reacting to any future pandemics., (©Oladapo Oyebode, Chinenye Ndulue, Ashfaq Adib, Dinesh Mulchandani, Banuchitra Suruliraj, Fidelia Anulika Orji, Christine T Chambers, Sandra Meier, Rita Orji. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 06.04.2021.)

Background: Recent advances in mobile technology have created opportunities to develop mobile apps to aid and assist people in achieving various health and wellness goals. Mental health apps hold significant potential to assist people affected by various mental health issues at any time they may need it, considering the ubiquitous nature of mobile phones. However, there is a need for research to explore and understand end users' perceptions, needs, and concerns with respect to such technologies., Objective: The aim of this paper is to explore the opinions, perceptions, preferences, and experiences of people who have experienced some form of mental health issues based on self-diagnosis to inform the design of a next-generation mental health app that would be substantially more engaging and effective than the currently available apps to improve mental health and well-being., Methods: We conducted six focus group sessions with people who had experienced mental health issues based on self-diagnosis (average age 26.7 years, SD 23.63; 16/32, 50% male; 16/32, 50% female). We asked participants about their experiences with mental health issues and their viewpoints regarding two existing mental health apps (the Happify app and the Self-Help Anxiety Management app). Finally, participants were engaged in a design session where they each sketched a design for their ideal mental health and well-being mobile app., Results: Our findings revealed that participants used strategies to deal with their mental health issues: doing something to distract themselves from their current negative mood, using relaxation exercises and methods to relieve symptoms, interacting with others to share their issues, looking for an external source to solve their problems, and motivating themselves by repeating motivational sentences to support themselves or by following inspirational people. Moreover, regarding the design of mental health apps, participants identified that general design characteristics; personalization of the app, including tracking and feedback, live support, and social community; and providing motivational content and relaxation exercises are the most important features that users want in a mental health app. In contrast, games, relaxation audio, the Google map function, personal assistance to provide suggestions, goal setting, and privacy preservation were surprisingly the least requested features., Conclusions: Understanding end users' needs and concerns about mental health apps will inform the future design of mental health apps that are useful to and used by many people., (©Felwah Alqahtani, Andrea Winn, Rita Orji. Originally published in JMIR Formative Research (http://formative.jmir.org), 26.02.2021.)

Background: Gamification and persuasive games are effective tools to motivate behavior change, particularly to promote daily physical activities. On the one hand, studies have suggested that a one-size-fits-all approach does not work well for persuasive game design. On the other hand, player modeling and recommender systems are increasingly used for personalizing content. However, there are few existing studies on how to build comprehensive player models for personalizing gamified systems, recommending daily physical activities, or the long-term effectiveness of such gamified exercise-promoting systems., Objective: This paper aims to introduce a gamified, 24/7 fitness assistant system that provides personalized recommendations and generates gamified content targeted at individual users to bridge the aforementioned gaps. This research aims to investigate how to design gamified physical activity interventions to achieve long-term engagement., Methods: We proposed a comprehensive model for gamified fitness recommender systems that uses detailed and dynamic player modeling and wearable-based tracking to provide personalized game features and activity recommendations. Data were collected from 40 participants (23 men and 17 women) who participated in a long-term investigation on the effectiveness of our recommender system that gradually establishes and updates an individual player model (for each unique user) over a period of 60 days., Results: Our results showed the feasibility and effectiveness of the proposed system, particularly for generating personalized exercise recommendations using player modeling. There was a statistically significant difference among the 3 groups (full, personalized, and gamified) for overall motivation (F 3,36 =22.49; P<.001), satisfaction (F 3,36 =22.12; P<.001), and preference (F 3,36 =15.0; P<.001), suggesting that both gamification and personalization have positive effects on the levels of motivation, satisfaction, and preference. Furthermore, qualitative results revealed that a customized storyline was the most requested feature, followed by a multiplayer mode, more quality recommendations, a feature for setting and tracking fitness goals, and more location-based features., Conclusions: On the basis of these results and drawing from the gamer modeling literature, we conclude that personalizing recommendations using player modeling and gamification can improve participants' engagement and motivation toward fitness activities over time., (©Zhao Zhao, Ali Arya, Rita Orji, Gerry Chan. Originally published in JMIR Serious Games (http://games.jmir.org), 17.11.2020.)