schema: An open-source, distributed mobile platform for deploying mHealth research tools and interventions

Background: Mobile applications for health, also known as \u27mHealth apps\u27, have experienced increasing popularity over the past ten years. However, most publicly available mHealth apps are not clinically validated, and many do not utilise evidence-based strategies. Health researchers wishing to develop and evaluate mHealth apps may be impeded by cost and technical skillset barriers. As traditionally lab-based methods are translated onto mobile platforms, robust and accessible tools are needed to enable the development of quality, evidence-based programs by clinical experts. Results: This paper introduces schema, an open-source, distributed, app-based platform for researchers to deploy behavior monitoring and health interventions onto mobile devices. The architecture and design features of the platform are discussed, including flexible scheduling, randomisation, a wide variety of survey and media elements, and distributed storage of data. The platform supports a range of research designs, including cross-sectional surveys, ecological momentary assessment, randomised controlled trials, and micro-randomised just-in-time adaptive interventions. Use cases for both researchers and participants are considered to demonstrate the flexibility and usefulness of the platform for mHealth research. Conclusions: The paper concludes by considering the strengths and limitations of the platform, and a call for support from the research community in areas of technical development and evaluation. To get started with schema, please visit the GitHub repository: Https://github.com/schema-app/schema

Peer support of fathers on Reddit: Quantifying the stressors, behaviors, and drivers

This paper aimed to delineate the behavioralpatterns of fathers in seeking and providing peer support on the popular social media site Redditusing a sample of 2,393users. First, fathers’ support-seeking posts were characterized, finding that fathers self-disclosed a range of individual, familial, and societal stressors,including topics sensitive to traditional male gender roles. Second, peers’ commentswere differentiatedby support type, withdifferences observed in thebehaviors, emotions, andlanguage that peers use when providing advice, confirmation and encouragement.Third, the relationship between types of fatherhood stressors and their associated peer commentswas mapped.While fathers seeking support forindividual stressors received fewer comments, the support provided utilizedmore action-oriented language. Finally, a statistical model was developed to examine the factors that drive peer support on the fatherhood forums, which are observed to influence the qualityof peers’ comments and peers’ commenting behaviors. Combined, the findings provide a comprehensive understanding of the peer support environment for fathers on social media like Reddit, strengthening the research literature that is limited to qualitative evidence to date. The results have important implications for formal support services targeting fathers,both online and offlin

schema: an open-source, distributed mobile platform for deploying mHealth research tools and interventions

Background: Mobile applications for health, also known as ‘mHealth apps’, have experienced increasing popularity over the past ten years. However, most publicly available mHealth apps are not clinically validated, and many do not utilise evidence-based strategies. Health researchers wishing to develop and evaluate mHealth apps may be impeded by cost and technical skillset barriers. As traditionally lab-based methods are translated onto mobile platforms, robust and accessible tools are needed to enable the development of quality, evidence-based programs by clinical experts. Results: This paper introduces schema, an open-source, distributed, app-based platform for researchers to deploy behavior monitoring and health interventions onto mobile devices. The architecture and design features of the platform are discussed, including flexible scheduling, randomisation, a wide variety of survey and media elements, and distributed storage of data. The platform supports a range of research designs, including cross-sectional surveys, ecological momentary assessment, randomised controlled trials, and micro-randomised just-in-time adaptive interventions. Use cases for both researchers and participants are considered to demonstrate the flexibility and usefulness of the platform for mHealth research. Conclusions: The paper concludes by considering the strengths and limitations of the platform, and a call for support from the research community in areas of technical development and evaluation. To get started with schema, please visit the GitHub repository: https://github.com/schema-app/schema

Social media markers to identify fathers at risk of postpartum depression : a machine learning approach

Postpartum depression (PPD) is a significant mental health issue in mothers and fathers alike; yet at-risk fathers often come to the attention of health care professionals late due to low awareness of symptoms and reluctance to seek help. This study aimed to examine whether passive social media markers are effective for identifying fathers at risk of PPD. We collected 67,796 Reddit posts from 365 fathers, spanning a 6-month period around the birth of their child. A list of "at-risk"words was developed in collaboration with a perinatal mental health expert. PPD was assessed by evaluating the change in fathers' use of words indicating depressive symptomatology after childbirth. Predictive models were developed as a series of support vector machine classifiers using behavior, emotion, linguistic style, and discussion topics as features. The performance of these classifiers indicates that fathers at risk of PPD can be predicted from their prepartum data alone. Overall, the best performing model used discussion topic features only with a recall score of 0.82. These findings could assist in the development of support and intervention tools for fathers during the prepartum period, with specific applicability to personalized and preventative support tools for at-risk fathers. © Copyright 2020, Mary Ann Liebert, Inc., publishers 2020

Methods and applications of social media monitoring of mental health during disasters : scoping review

Background: With the increasing frequency and magnitude of disasters internationally, there is growing research and clinical interest in the application of social media sites for disaster mental health surveillance. However, important questions remain regarding the extent to which unstructured social media data can be harnessed for clinically meaningful decision-making. Objective: This comprehensive scoping review synthesizes interdisciplinary literature with a particular focus on research methods and applications. Methods: A total of 6 health and computer science databases were searched for studies published before April 20, 2021, resulting in the identification of 47 studies. Included studies were published in peer-reviewed outlets and examined mental health during disasters or crises by using social media data. Results: Applications across 31 mental health issues were identified, which were grouped into the following three broader themes: estimating mental health burden, planning or evaluating interventions and policies, and knowledge discovery. Mental health assessments were completed by primarily using lexical dictionaries and human annotations. The analyses included a range of supervised and unsupervised machine learning, statistical modeling, and qualitative techniques. The overall reporting quality was poor, with key details such as the total number of users and data features often not being reported. Further, biases in sample selection and related limitations in generalizability were often overlooked. Conclusions: The application of social media monitoring has considerable potential for measuring mental health impacts on populations during disasters. Studies have primarily conceptualized mental health in broad terms, such as distress or negative affect, but greater focus is required on validating mental health assessments. There was little evidence for the clinical integration of social media-based disaster mental health monitoring, such as combining surveillance with social media-based interventions or developing and testing real-world disaster management tools. To address issues with study quality, a structured set of reporting guidelines is recommended to improve the methodological quality, replicability, and clinical relevance of future research on the social media monitoring of mental health during disasters. © 2022 Samantha J Teague, Adrian B R Shatte, Emmelyn Weller, Matthew Fuller-Tyszkiewicz, Delyse M Hutchinson

Methods and Applications of Social Media Monitoring of Mental Health During Disasters: Scoping Review

Background: With the increasing frequency and magnitude of disasters internationally, there is growing research and clinical interest in the application of social media sites for disaster mental health surveillance. However, important questions remain regarding the extent to which unstructured social media data can be harnessed for clinically meaningful decision-making. Objective: This comprehensive scoping review synthesizes interdisciplinary literature with a particular focus on research methods and applications. Methods: A total of 6 health and computer science databases were searched for studies published before April 20, 2021, resulting in the identification of 47 studies. Included studies were published in peer-reviewed outlets and examined mental health during disasters or crises by using social media data. Results: Applications across 31 mental health issues were identified, which were grouped into the following three broader themes: estimating mental health burden, planning or evaluating interventions and policies, and knowledge discovery. Mental health assessments were completed by primarily using lexical dictionaries and human annotations. The analyses included a range of supervised and unsupervised machine learning, statistical modeling, and qualitative techniques. The overall reporting quality was poor, with key details such as the total number of users and data features often not being reported. Further, biases in sample selection and related limitations in generalizability were often overlooked. Conclusions: The application of social media monitoring has considerable potential for measuring mental health impacts on populations during disasters. Studies have primarily conceptualized mental health in broad terms, such as distress or negative affect, but greater focus is required on validating mental health assessments. There was little evidence for the clinical integration of social media-based disaster mental health monitoring, such as combining surveillance with social media-based interventions or developing and testing real-world disaster management tools. To address issues with study quality, a structured set of reporting guidelines is recommended to improve the methodological quality, replicability, and clinical relevance of future research on the social media monitoring of mental health during disasters

“You are not alone”: A big data and qualitative analysis of men's unintended fatherhood

Background: Becoming a father is a profound change in a man's life that is not always planned or wanted. Little is known about the subjective experiences of men who become fathers unintentionally or reluctantly. The aim of this research was to explore how men who did not intend to have children discuss their feelings about becoming a father in an online, anonymous environment. We sought insights into emotional responses, appraisals of family functioning, and relationships with infants. Method: Data were collected from two Reddit forums for new and expectant fathers, r/Daddit and r/Predaddit. Approximately 2600 posts and 21,000 comments were extracted from the period between January 2019 and March 2020. We employed a two-stage methodology, blending big data techniques and qualitative analyses. Stage One included extraction and data preparation for topic modelling Stage Two was an adapted approach to thematic qualitative analysis. Results: Topic modelling revealed 49 topics of which 6 were relevant thematically to unintended fatherhood. Men's communication in these were then classified within three domains: 1) Men's Concerns included their mental health, problems bonding with baby, their relationships with family and partner, and finances; 2) Men's Affective Experiences existed on a spectrum of complex emotions including regret, resignation, ambivalence, acceptance, and excitement; and 3) the Purpose of Communication included asking for and offering advice, normalisation, and perspective. Conclusions: Online forums like Reddit provide a unique opportunity for fathers who did not intend to have children to normalize their experience by expressing concerns and emotions in a pseudonymous environment. This study highlights the supportive environment that online discussions offer to fathers, and particularly unexpected fathers who may face stigma or barriers in other settings

Strengthening Peer Mentoring Relationships for New Mothers: A Qualitative Analysis

(1) Background: The transition to motherhood can be challenging, especially for first-time mothers, and can accompany maternal distress. Social support—such as that offered by peers— can be important in assisting mothers to manage such distress. Although primiparous mothers often seek out and value peer support programs, few researchers have investigated factors that may influence the strength of relationships in non-professional maternal peer support programs. Insight into these factors can be key to enhancing the success of future peer support interventions. (2) Methods: Reflexive thematic analysis was applied to data gathered from 36 semi-structured interviews conducted with 14 primiparous mothers and 17 peer mentors in a peer support program. (3) Results: Four themes related to successful mentorship were identified: expectations of peer relationship, independence of peer mentor, contact, and similarities. (4) Conclusions: For primiparous mothers who are developing their support network, these factors appear important for promoting close and effective peer support relationships. Interventions that harness the dynamics between these factors may contribute to more successful peer support relationships and mental health outcomes for participants

Associations between maternal psychological distress and mother-infant bonding: a systematic review and meta-analysis

Purpose: Maternal psychological distress and mother-infant bonding problems each predict poorer offspring outcomes. They are also related to each other, yet the extensive literature reporting their association has not been meta-analysed. Methods: We searched MEDLINE, PsycINFO, CINAHL, Embase, ProQuest DTG, and OATD for English-language peer-reviewed and grey literature reporting an association between mother-infant bonding, and multiple indicators of maternal psychological distress. Results: We included 133 studies representing 118 samples; 99 samples (110,968 mothers) were eligible for meta-analysis. Results showed concurrent associations across a range of timepoints during the first year postpartum, between bonding problems and depression (r = .27 [95% CI 0.20, 0.35] to r = .47 [95% CI 0.41, 0.53]), anxiety (r = .27 [95% CI 0.24, 0.31] to r = .39 [95% CI 0.15, 0.59]), and stress (r = .46 [95% CI 0.40, 0.52]). Associations between antenatal distress and subsequent postpartum bonding problems were mostly weaker and with wider confidence intervals: depression (r = .20 [95% CI 0.14, 0.50] to r = .25 [95% CI 0.64, 0.85]), anxiety (r = .16 [95% CI 0.10, 0.22]), and stress (r = .15 [95% CI − 0.67, 0.80]). Pre-conception depression and anxiety were associated with postpartum bonding problems (r = − 0.17 [95% CI − 0.22, − 0.11]). Conclusion: Maternal psychological distress is associated with postpartum mother-infant bonding problems. Co-occurrence of psychological distress and bonding problems is common, but should not be assumed. There may be benefit in augmenting existing perinatal screening programs with well-validated mother-infant bonding measures

Prevalence and clinical characteristics of non-malignant CT detected incidental findings in the SUMMIT lung cancer screening cohort

BACKGROUND: Pulmonary and extrapulmonary incidental findings are frequently identified on CT scans performed for lung cancer screening. Uncertainty regarding their clinical significance and how and when such findings should be reported back to clinicians and participants persists. We examined the prevalence of non-malignant incidental findings within a lung cancer screening cohort and investigated the morbidity and relevant risk factors associated with incidental findings. We quantified the primary and secondary care referrals generated by our protocol. METHODS: The SUMMIT study (NCT03934866) is a prospective observational cohort study to examine the performance of delivering a low-dose CT (LDCT) screening service to a high-risk population. Spirometry, blood pressure, height/weight and respiratory history were assessed as part of a Lung Health Check. Individuals at high risk of lung cancer were offered an LDCT and returned for two further annual visits. This analysis is a prospective evaluation of the standardised reporting and management protocol for incidental findings developed for the study on the baseline LDCT. RESULTS: In 11 115 participants included in this analysis, the most common incidental findings were coronary artery calcification (64.2%) and emphysema (33.4%). From our protocolised management approach, the number of participants requiring review for clinically relevant findings in primary care was 1 in 20, and the number potentially requiring review in secondary care was 1 in 25. CONCLUSIONS: Incidental findings are common in lung cancer screening and can be associated with reported symptoms and comorbidities. A standardised reporting protocol allows systematic assessment and standardises onward management