The importance of need-altruism and kin-altruism to blood donor behaviour for black and white people.

BACKGROUND: Need-altruism (a preference to help people in need) and kin-altruism (a preference to help kin over non-kin) underlie two hypotheses for voluntary blood donation: (i) Need-altruism underlies motivations for volunteer blood donation and (ii) Black people express a stronger preference for kin-altruism, which is a potential barrier to donation. This paper tests these hypotheses and explores how need- and kin-altruism are associated with wider altruistic motivations, barriers, and strategies to encourage donation. METHODS: We assessed need- and kin-altruism, other mechanisms-of-altruism (e.g., reluctant-altruism), barriers, strategies to encourage donation, donor status, and willingness-to-donate across four groups based on ethnicity (Black; White), nationality (British; Nigerian), and country-of-residence: (i) Black-British people (n = 395), and Black-Nigerian people (ii) in the UK (n = 97) or (iii) across the rest of the world (n = 101), and (v) White-British people in the UK (n = 452). We also sampled a Black-Nigerian Expert group (n = 60). RESULTS: Need-altruism was higher in donors and associated with willingness-to-donate in non-donors. Levels of kin-altruism did not differ between Black and White people, but need-altruism was lower in Black-British people. Kin-altruism was associated with a preference for incentives, and need-altruism with a preference for recognition (e.g., a thank you) as well as an increased willingness-to-donate for Black non-donors. Need-altruism underlies a blood-donor-cooperative-phenotype. CONCLUSION: Need-altruism is central to blood donation, in particular recruitment. Lower need-altruism may be a specific barrier for Black-British people. Kin-altruism is important for Black non-donors. The blood donor cooperative phenotype deserves further consideration. Implications for blood services are discussed.

Engagement With a Remote Symptom-Tracking Platform Among Participants With Major Depressive Disorder: Randomized Controlled Trial.

BACKGROUND: Multiparametric remote measurement technologies (RMTs), which comprise smartphones and wearable devices, have the potential to revolutionize understanding of the etiology and trajectory of major depressive disorder (MDD). Engagement with RMTs in MDD research is of the utmost importance for the validity of predictive analytical methods and long-term use and can be conceptualized as both objective engagement (data availability) and subjective engagement (system usability and experiential factors). Positioning the design of user interfaces within the theoretical framework of the Behavior Change Wheel can help maximize effectiveness. In-app components containing information from credible sources, visual feedback, and access to support provide an opportunity to promote engagement with RMTs while minimizing team resources. Randomized controlled trials are the gold standard in quantifying the effects of in-app components on engagement with RMTs in patients with MDD. OBJECTIVE: This study aims to evaluate whether a multiparametric RMT system with theoretically informed notifications, visual progress tracking, and access to research team contact details could promote engagement with remote symptom tracking over and above the system as usual. We hypothesized that participants using the adapted app (intervention group) would have higher engagement in symptom monitoring, as measured by objective and subjective engagement. METHODS: A 2-arm, parallel-group randomized controlled trial (participant-blinded) with 1:1 randomization was conducted with 100 participants with MDD over 12 weeks. Participants in both arms used the RADAR-base system, comprising a smartphone app for weekly symptom assessments and a wearable Fitbit device for continuous passive tracking. Participants in the intervention arm (n=50, 50%) also had access to additional in-app components. The primary outcome was objective engagement, measured as the percentage of weekly questionnaires completed during follow-up. The secondary outcomes measured subjective engagement (system engagement, system usability, and emotional self-awareness). RESULTS: The levels of completion of the Patient Health Questionnaire-8 (PHQ-8) were similar between the control (67/97, 69%) and intervention (66/97, 68%) arms (P value for the difference between the arms=.83, 95% CI -9.32 to 11.65). The intervention group participants reported slightly higher user engagement (1.93, 95% CI -1.91 to 5.78), emotional self-awareness (1.13, 95% CI -2.93 to 5.19), and system usability (2.29, 95% CI -5.93 to 10.52) scores than the control group participants at follow-up; however, all CIs were wide and included 0. Process evaluation suggested that participants saw the in-app components as helpful in increasing task completion. CONCLUSIONS: The adapted system did not increase objective or subjective engagement in remote symptom tracking in our research cohort. This study provides an important foundation for understanding engagement with RMTs for research and the methodologies by which this work can be replicated in both community and clinical settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT04972474; https://clinicaltrials.gov/ct2/show/NCT04972474. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/32653.

Understanding the Subjective Experience of Long-term Remote Measurement Technology Use for Symptom Tracking in People With Depression: Multisite Longitudinal Qualitative Analysis.

BACKGROUND: Remote measurement technologies (RMTs) have the potential to revolutionize major depressive disorder (MDD) disease management by offering the ability to assess, monitor, and predict symptom changes. However, the promise of RMT data depends heavily on sustained user engagement over extended periods. In this paper, we report a longitudinal qualitative study of the subjective experience of people with MDD engaging with RMTs to provide insight into system usability and user experience and to provide the basis for future promotion of RMT use in research and clinical practice. OBJECTIVE: We aimed to understand the subjective experience of long-term engagement with RMTs using qualitative data collected in a longitudinal study of RMTs for monitoring MDD. The objectives were to explore the key themes associated with long-term RMT use and to identify recommendations for future system engagement. METHODS: In this multisite, longitudinal qualitative research study, 124 semistructured interviews were conducted with 99 participants across the United Kingdom, Spain, and the Netherlands at 3-month, 12-month, and 24-month time points during a study exploring RMT use (the Remote Assessment of Disease and Relapse-Major Depressive Disorder study). Data were analyzed using thematic analysis, and interviews were audio recorded, transcribed, and coded in the native language, with the resulting quotes translated into English. RESULTS: There were 5 main themes regarding the subjective experience of long-term RMT use: research-related factors, the utility of RMTs for self-management, technology-related factors, clinical factors, and system amendments and additions. CONCLUSIONS: The subjective experience of long-term RMT use can be considered from 2 main perspectives: experiential factors (how participants construct their experience of engaging with RMTs) and system-related factors (direct engagement with the technologies). A set of recommendations based on these strands are proposed for both future research and the real-world implementation of RMTs into clinical practice. Future exploration of experiential engagement with RMTs will be key to the successful use of RMTs in clinical care.

Experiences of health tracking in mobile apps for multiple sclerosis: A qualitative content analysis of user reviews.

BACKGROUND: Mobile health applications (apps) are promising condition self-management tools for people living with multiple sclerosis (MS). However, most existing apps do not include health tracking features. This gap has been raised as a priority research topic, but the development of new self-management apps will require designers to understand the context and needs of those living with MS. Our aim was to conduct a content analysis of publicly available user reviews of existing MS self-management apps to understand desired features and guide the design of future apps. METHODS: We systematically reviewed MS self-management apps which were publicly available in English on the Google Play and iOS app stores. We then conducted sentiment and content analysis of recent user reviews which referenced health tracking and data visualization to understand self-reported experiences and feedback. RESULTS: Searches identified 75 unique apps, of which six met eligibility criteria and had reviews. One hundred and thirty-seven user reviews of these apps were eligible, though most were associated with a single app (n=108). Overall, ratings and sentiment scores skewed highly positive (Median [IQR]: Ratings - 5 [4-5], Sentiment scores - 0.70 [0.44-0.86]), though scores of individual apps varied. Content analysis revealed five themes: reasons for app usage, simple user experience, customization and flexibility, feature requests, and technical issues. Reviewers suggested that app customization, interconnectivity, and consolidated access to desired features should be considered in the design of future apps. User ratings weakly correlated with review sentiment scores (ρ = 0.27 [0.11-0.42]). CONCLUSIONS: Self-tracking options in MS apps are currently limited, though the apps that offer these functions are considered useful by individuals with MS. Additional qualitative research is required to understand how specific app features and opportunities for personalization should be incorporated into new self-management tools for this population.

Health Tracking via Mobile Apps for Depression Self-management: Qualitative Content Analysis of User Reviews.

BACKGROUND: Tracking and visualizing health data using mobile apps can be an effective self-management strategy for mental health conditions. However, little evidence is available to guide the design of mental health-tracking mechanisms. OBJECTIVE: The aim of this study was to analyze the content of user reviews of depression self-management apps to guide the design of data tracking and visualization mechanisms for future apps. METHODS: We systematically reviewed depression self-management apps on Google Play and iOS App stores. English-language reviews of eligible apps published between January 1, 2018, and December 31, 2021, were extracted from the app stores. Reviews that referenced health tracking and data visualization were included in sentiment and qualitative framework analyses. RESULTS: The search identified 130 unique apps, 26 (20%) of which were eligible for inclusion. We included 783 reviews in the framework analysis, revealing 3 themes. Impact of app-based mental health tracking described how apps increased reviewers' self-awareness and ultimately enabled condition self-management. The theme designing impactful mental health-tracking apps described reviewers' feedback and requests for app features during data reporting, review, and visualization. It also described the desire for customization and contexts that moderated reviewer preference. Finally, implementing impactful mental health-tracking apps described considerations for integrating apps into a larger health ecosystem, as well as the influence of paywalls and technical issues on mental health tracking. CONCLUSIONS: App-based mental health tracking supports depression self-management when features align with users' individual needs and goals. Heterogeneous needs and preferences raise the need for flexibility in app design, posing challenges for app developers. Further research should prioritize the features based on their importance and impact on users.

Trust and distrust: Identifying recruitment targets for ethnic minority blood donors.

BACKGROUND: We explore the role of trust, distrust, and the prevailing socio-political context to better understand why people from ethnic minority communities are less likely to be blood donors compared to people from White communities. Recruiting more ethnic minority donors will enhance representativeness, reduce inequality, and help meet the clinical need to increase the proportion of blood with Ro Kell antigen to treat Sickle Cell Disease (SCD). STUDY DESIGN AND METHODS: A 2 (donor-status: current donor; non-donors) by 4 (ethnicity: People from Asian, Black, Mixed and White ethnic backgrounds) quasi-experiment (N = 981) was conducted to examine perceptions of trust/distrust and their influence on willingness to donate blood, within the socio-political context of the Windrush scandal and Brexit. RESULTS: We identified five domains of trust ('National Health Service [NHS] and staff,' 'NHS Blood and Transplant,' 'outgroups,' 'individuals' and 'politics'), and a single domain of conditional distrust domain. Trust across all the domains was lower, and 'conditional distrust' higher for ethnic minorities. Trust in 'individuals' and 'NHSBT' predicted willingness to donate in non-donors from ethnic minorities and White non-donors, respectively. Concerns about the Windrush scandal were related to lower political trust. Viewing Brexit as 'positive for the UK' was related to lower trust across domains and reduced willingness to donate in White non-donors through its influence on reduced trust in NHSBT. CONCLUSION: Distinct domains of trust and distrust are identified, and targeting 'trust in others' through conditional cooperation is recommended as a strategy to increase donor numbers from ethnic minority communities.

Key Drivers and Facilitators of the Choice to Use mHealth Technology in People With Neurological Conditions: Observational Study.

BACKGROUND: There is increasing interest in the potential uses of mobile health (mHealth) technologies, such as wearable biosensors, as supplements for the care of people with neurological conditions. However, adherence is low, especially over long periods. If people are to benefit from these resources, we need a better long-term understanding of what influences patient engagement. Previous research suggests that engagement is moderated by several barriers and facilitators, but their relative importance is unknown. OBJECTIVE: To determine preferences and the relative importance of user-generated factors influencing engagement with mHealth technologies for 2 common neurological conditions with a relapsing-remitting course: multiple sclerosis (MS) and epilepsy. METHODS: In a discrete choice experiment, people with a diagnosis of MS (n=141) or epilepsy (n=175) were asked to select their preferred technology from a series of 8 vignettes with 4 characteristics: privacy, clinical support, established benefit, and device accuracy; each of these characteristics was greater or lower in each vignette. These characteristics had previously been emphasized by people with MS and or epilepsy as influencing engagement with technology. Mixed multinomial logistic regression models were used to establish which characteristics were most likely to affect engagement. Subgroup analyses explored the effects of demographic factors (such as age, gender, and education), acceptance of and familiarity with mobile technology, neurological diagnosis (MS or epilepsy), and symptoms that could influence motivation (such as depression). RESULTS: Analysis of the responses to the discrete choice experiment validated previous qualitative findings that a higher level of privacy, greater clinical support, increased perceived benefit, and better device accuracy are important to people with a neurological condition. Accuracy was perceived as the most important factor, followed by privacy. Clinical support was the least valued of the attributes. People were prepared to trade a modest amount of accuracy to achieve an improvement in privacy, but less likely to make this compromise for other factors. The type of neurological condition (epilepsy or MS) did not influence these preferences, nor did the age, gender, or mental health status of the participants. Those who were less accepting of technology were the most concerned about privacy and those with a lower level of education were prepared to trade accuracy for more clinical support. CONCLUSIONS: For people with neurological conditions such as epilepsy and MS, accuracy (ie, the ability to detect symptoms) is of the greatest interest. However, there are individual differences, and people who are less accepting of technology may need far greater reassurance about data privacy. People with lower levels of education value greater clinician involvement. These patient preferences should be considered when designing mHealth technologies.

Factors Influencing Increased Use of Technology to Communicate With Others During the COVID-19 Pandemic: Cross-sectional Web-Based Survey Study.

BACKGROUND: Communication via technology is regarded as an effective way of maintaining social connection and helping individuals to cope with the psychological impact of social distancing measures during a pandemic. However, there is little information about which factors have influenced increased use of technology to communicate with others during lockdowns and whether this has changed over time. OBJECTIVE: The aim of this study is to explore which psychosocial factors (eg, mental health and employment) and pandemic-related factors (eg, shielding and time) influenced an increase in communication via technology during the first lockdown in the United Kingdom. METHODS: A cross-sectional, web-based survey was conducted between April and July 2020, examining thoughts, feelings, and behaviors associated with the pandemic, including communicating more using technology (eg, via messaging, phone, or video). We collected sociodemographic information, employment status, mental health service user status, and depression symptoms. We used hierarchical logistic regression to test which factors were associated with communicating more using technology during the lockdown. RESULTS: Participants (N=1464) were on average 41.07 (SD 14.61) years old, and mostly women (n=1141; 77.9%), White (n=1265; 86.4%), and employed (n=1030; 70.4%). Participants reported a mild level of depression (mean 9.43, SD 7.02), and were communicating more using technology (n=1164; 79.5%). The hierarchical regression indicated that people who were employed and experiencing lower levels of depression were more likely to report increased communication using technology during a lockdown period of the COVID-19 pandemic, and over time, men communicated more using technology. Increased use of technology to communicate was related to greater communication and the inability to see others due to the social distancing measures enacted during the lockdown. It was not related to a general increase in technology use during the lockdown. CONCLUSIONS: Although most participants reported increased use of technology to communicate during a lockdown period of the COVID-19 pandemic, this was more apparent in the employed and those experiencing low levels of depression. Moving forward, we should continue to monitor groups who may have been excluded from the benefits of support and communication using technology.

Exploring the Effects of In-App Components on Engagement With a Symptom-Tracking Platform Among Participants With Major Depressive Disorder (RADAR-Engage): Protocol for a 2-Armed Randomized Controlled Trial.

BACKGROUND: Multi-parametric remote measurement technologies (RMTs) comprise smartphone apps and wearable devices for both active and passive symptom tracking. They hold potential for understanding current depression status and predicting future depression status. However, the promise of using RMTs for relapse prediction is heavily dependent on user engagement, which is defined as both a behavioral and experiential construct. A better understanding of how to promote engagement in RMT research through various in-app components will aid in providing scalable solutions for future remote research, higher quality results, and applications for implementation in clinical practice. OBJECTIVE: The aim of this study is to provide the rationale and protocol for a 2-armed randomized controlled trial to investigate the effect of insightful notifications, progress visualization, and researcher contact details on behavioral and experiential engagement with a multi-parametric mobile health data collection platform, Remote Assessment of Disease and Relapse (RADAR)-base. METHODS: We aim to recruit 140 participants upon completion of their participation in the RADAR Major Depressive Disorder study in the London site. Data will be collected using 3 weekly tasks through an active smartphone app, a passive (background) data collection app, and a Fitbit device. Participants will be randomly allocated at a 1:1 ratio to receive either an adapted version of the active app that incorporates insightful notifications, progress visualization, and access to researcher contact details or the active app as usual. Statistical tests will be used to assess the hypotheses that participants using the adapted app will complete a higher percentage of weekly tasks (behavioral engagement: primary outcome) and score higher on self-awareness measures (experiential engagement). RESULTS: Recruitment commenced in April 2021. Data collection was completed in September 2021. The results of this study will be communicated via publication in 2022. CONCLUSIONS: This study aims to understand how best to promote engagement with RMTs in depression research. The findings will help determine the most effective techniques for implementation in both future rounds of the RADAR Major Depressive Disorder study and, in the long term, clinical practice. TRIAL REGISTRATION: ClinicalTrials.gov NCT04972474; http://clinicaltrials.gov/ct2/show/NCT04972474. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/32653.

Keeping well in a COVID-19 crisis: a qualitative study formulating the perspectives of mental health service users and carers.

BACKGROUND: People with existing mental health conditions may be particularly vulnerable to the psychological effect of the COVID-19 pandemic. But their positive and negative appraisals, and coping behaviour could prevent or ameliorate future problems. OBJECTIVE: To explore the emotional experiences, thought processes and coping behaviours of people with existing mental health problems and carers living through the pandemic. METHODS: UK participants who identified as a mental health service user (N18), a carer (N5) or both (N8) participated in 30-minute semi-structured remote interviews (31 March 2020 to 9 April 2020). The interviews investigated the effects of social distancing and self-isolation on mental health and the ways in which people were coping. Data were analysed using a framework analysis. Three service user researchers charted data into a framework matrix (consisting of three broad categories: "emotional responses", "thoughts" and "behaviours") and then used an inductive process to capture other contextual themes. RESULTS: Common emotional responses were fear, sadness and anger but despite negative emotions and uncertainty appraisals, participants described efforts to cope and maintain their mental wellbeing. This emphasised an increased reliance on technology, which enabled social contact and occupational or leisure activities. Participants also spoke about the importance of continued and adapted mental health service provision, and the advantages and disadvantages associated with changes in their living environment, life schedule and social interactions. CONCLUSION: This study builds on a growing number of qualitative accounts of how mental health service users and carers experienced and coped with extreme social distancing measures early in the COVID-19 pandemic. Rather than a state of helplessness this study contains a clear message of resourcefulness and resilience in the context of fear and uncertainty.

Calbindin Deficits May Underlie Dissociable Effects of 5-HT6 and mGlu7 Antagonists on Glutamate and Cognition in a Dual-Hit Neurodevelopmental Model for Schizophrenia.

Despite several compounds entering clinical trials for the negative and cognitive symptoms of schizophrenia, few have progressed beyond phase III. This is partly attributed to a need for improved preclinical models, to understand disease and enable predictive evaluation of novel therapeutics. To this end, one recent approach incorporates "dual-hit" neurodevelopmental insults like neonatal phencyclidine plus isolation rearing (PCP-Iso). Glutamatergic dysfunction contributes to schizophrenia pathophysiology and may represent a treatment target, so we used enzyme-based microsensors to evaluate basal- and drug-evoked glutamate release in hippocampal slices from rats that received neonatal PCP and/or isolation rearing. 5-HT6 antagonist-evoked glutamate release (thought to be mediated indirectly via GABAergic disinhibition) was reduced in PCP-Iso, as were cognitive effects of a 5-HT6 antagonist in a hippocampal glutamate-dependent novel object discrimination task. Yet mGlu7 antagonist-evoked glutamatergic and cognitive responses were spared. Immunohistochemical analyses suggest these findings (which mirror the apparent lack of clinical response to 5-HT6 antagonists in schizophrenia) are not due to reduced hippocampal 5-HT input in PCP-Iso, but may be explained by reduced calbindin expression. This calcium-binding protein is present in a subset of GABAergic interneurons receiving preferential 5-HT innervation and expressing 5-HT6 receptors. Its loss (in schizophrenia and PCP-Iso) would be expected to reduce interneuron firing and potentially prevent further 5-HT6 antagonist-mediated disinhibition, without impacting on responses of VIP-expressing interneurons to mGlu7 antagonism. This research highlights the importance of improved understanding for selection of appropriate preclinical models, especially where disease neurobiology impacts on cells mediating the effects of potential therapeutics.