Human Subjects Protection and Technology in Prevention Science: Selected Opportunities and Challenges

Commentary on "Protecting User Privacy and Rights in Academic Data-Sharing Partnerships: Principles From a Pilot Program at Crisis Text Line"

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Gone Too Soon: priorities for action to prevent premature mortality associated with mental illness and mental distress

Globally, too many people die prematurely from suicide and the physical comorbidities associated with mental illness and mental distress. The purpose of this Review is to mobilise the translation of evidence into prioritised actions that reduce this inequity. The mental health research charity, MQ Mental Health Research, convened an international panel that used roadmapping methods and review evidence to identify key factors, mechanisms, and solutions for premature mortality across the social-ecological system. We identified 12 key overarching risk factors and mechanisms, with more commonalities than differences across the suicide and physical comorbidities domains. We also identified 18 actionable solutions across three organising principles: the integration of mental and physical health care; the prioritisation of prevention while strengthening treatment; and the optimisation of intervention synergies across social-ecological levels and the intervention cycle. These solutions included accessible, integrated high-quality primary care; early life, workplace, and community-based interventions co-designed by the people they should serve; decriminalisation of suicide and restriction of access to lethal means; stigma reduction; reduction of income, gender, and racial inequality; and increased investment. The time to act is now, to rebuild health-care systems, leverage changes in funding landscapes, and address the effects of stigma, discrimination, marginalisation, gender violence, and victimisation.

The Paradox of Suicide Prevention

The recognition that we cannot use risk stratification (high, medium, low) to predict suicide or to allocate resources has led to a paradigm shift in suicide prevention efforts. There are challenges in adapting to these new paradigms, including reluctance of clinicians and services to move away from traditional risk categorisations; and conversely, the risk of a pendulum swing in which the focus of care swings from one approach to determining service priority and focus (e.g., diagnosis, formulation, risk and clinical care) to a new focus (e.g., suicide specific and non-clinical care), potentially supplanting the previous approach. This paper argues that the Prevention Paradox provides a useful mental model to support a shift in paradigm, whilst maintaining a balanced approach that incorporates new paradigms within the effective aspects of existing ones. The Prevention Paradox highlights the seemingly paradoxical situation where the greatest burden of disease or death is caused by those at low to moderate risk due their larger numbers. Current planning frameworks and resources do not support successful or sustainable adoption of these new approaches, leading to missed opportunities to prevent suicidal behaviours in healthcare. Adopting systems approaches to suicide prevention, such as the Zero Suicide Framework, implemented in a large mental health service in Australia and presented in this paper as a case study, can support a balanced approach of population- and individual-based suicide prevention efforts. Results demonstrate significant reductions in re-presentations with suicide attempts for consumers receiving this model of care; however, the increasing numbers of placements compromise the capacity of clinical teams to complete all components of standardised pathway of care. This highlights the need for review of resource planning frameworks and ongoing evaluations of the critical aspects of the interventions.

Conducting Digital Intervention Research among Immigrant Survivors of Intimate Partner Violence: Methodological, Safety and Ethnical Considerations

Intimate partner violence, described as a global pandemic by the United Nations, has been found to disproportionately affect immigrant women. Many immigrant survivors of IPV are unable or unwilling to attend in-person services due to barriers related to immigration status, transportation, and social isolation. By providing remote support to women in abusive relationships, digital interventions can help address these barriers and ensure their health and safety. Research on safe and ethical approaches to digital service delivery for immigrant IPV survivors is a necessary first step to meeting these women's needs for remote support. The purpose of this qualitative study was to explore considerations and challenges of conducting digital intervention research (online, phone and text) with diverse groups of immigrant women. Data was collected via 5 focus groups and 46 in-depth interviews with immigrant survivors of IPV from different countries of origin. In addition, data was collected via key informant interviews with 17 service providers. Participants shared safety, ethical and methodological challenges to accessing interventions, such as their abusive partner being at home or lack of safe access to technology. Further, participants shared strategies for safe data collection, such as scheduling a contact time when participants are afforded privacy and deleting evidence of the intervention to retain personal safety. The findings will be informative for researchers conducting digital intervention studies or practitioners engaging in remote intervention approaches with marginalized populations such as immigrant women at high risk of violence.

Centering Lived Experience in Developing Digital Interventions for Suicide and Self-injurious Behaviors: User-Centered Design Approach

BACKGROUND

The prevalence of self-injurious thoughts and behaviors (SITB) signals a growing public health crisis. Despite a recognized need for improved and scalable interventions, the field of SITB intervention faces several challenges: existing interventions are often time and resource intensive, most individuals with SITB do not seek formal mental health care, and efficacious treatments are characterized by small effects. Combined, these challenges indicate a need for improved SITB interventions for individuals in formal treatment and those who are not treatment engaged but are at high risk of worsening mental health and future suicide attempts.

OBJECTIVE

We present a methodological approach and set of techniques that may address these challenges by centering the lived experience of individuals with SITB in the process of developing needed services: user-centered design (UCD).

METHODS

We highlight the value of UCD in the context of digital interventions for SITB by describing the UCD approach and explicating how it can be leveraged to include lived experience throughout the development and evaluation process. We provide a detailed case example highlighting 3 phases of the early development process that can be used to design an intervention that is engaging and meets end-user needs. In addition, we point to novel applications of UCD to complement new directions in SITB research.

RESULTS

In this paper, we offer a 2-pronged approach to meet these challenges. First, in terms of addressing access to effective interventions, digital interventions hold promise to extend the reach of evidence-based treatments outside of brick-and-mortar health care settings. Second, to address challenges related to treatment targets and engagement, we propose involving individuals with lived experience in the design and research process.

CONCLUSIONS

UCD offers a well-developed and systematic process to center the unique needs, preferences, and perceived barriers of individuals with lived SITB experience in the development and evaluation of digital interventions.

Determining the Intellectual Structure and Academic Trends of Smart Home Health Care Research: Coword and Topic Analyses

Background

With the rapid development of information and communication technologies, smart homes are being investigated as effective solutions for home health care. The increasing academic attention on smart home health care has primarily been on the development and application of smart home technologies. However, comprehensive studies examining the general landscape of diverse research areas for smart home health care are still lacking.

Objective

This study aims to determine the intellectual structure of smart home health care in a time series by conducting a coword analysis and topic analysis. Specifically, it investigates (1) the intellectual basis of smart home health care through overall academic status, (2) the intellectual foci through influential keywords and their evolutions, and (3) intellectual trends through primary topics and their evolutions.

Methods

Analyses were conducted in 5 steps: (1) data retrieval from article databases (Web of Science, Scopus, and PubMed) and the initial dataset preparation of 6080 abstracts from the year 2000 to the first half of 2019; (2) data preprocessing and refinement extraction of 25,563 words; (3) a descriptive analysis of the overall academic status and period division (ie, 4 stages of 3-year blocks); (4) coword analysis based on word co-occurrence networks for the intellectual foci; and (5) topic analysis for the intellectual trends based on latent Dirichlet allocation (LDA) topic modeling, word-topic networks, and researcher workshops.

Results

First, regarding the intellectual basis of smart home health care, recent academic interest and predominant journals and research domains were verified. Second, to determine the intellectual foci, primary keywords were identified and classified according to the degree of their centrality values. Third, 5 themes pertaining to the topic evolution emerged: (1) the diversification of smart home health care research topics; (2) the shift from technology-oriented research to technological convergence research; (3) the expansion of application areas and system functionality of smart home health care; (4) the increased focus on system usability, such as service design and experiences; and (5) the recent adaptation of the latest technologies in health care. Based on these findings, the pattern of technology diffusion in smart home health care research was determined as the adaptation of technologies, the proliferation of application areas, and an extension into system design and service experiences.

Conclusions

The research findings provide academic and practical value in 3 aspects. First, they promote a comprehensive understanding of the smart home health care domain by identifying its multifaceted intellectual structure in a time series. Second, they can help clinicians discern the development and dispersion level of their respective disciplines. Third, the pattern of technology diffusion in smart home health care could help scholars comprehend current and future research trends and identify research opportunities based on upcoming research waves of newly adapted technologies in smart home health care.

Longform recordings of everyday life: Ethics for best practices

Recent advances in large-scale data storage and processing offer unprecedented opportunities for behavioral scientists to collect and analyze naturalistic data, including from underrepresented groups. Audio data, particularly real-world audio recordings, are of particular interest to behavioral scientists because they provide high-fidelity access to subtle aspects of daily life and social interactions. However, these methodological advances pose novel risks to research participants and communities. In this article, we outline the benefits and challenges associated with collecting, analyzing, and sharing multi-hour audio recording data. Guided by the principles of autonomy, privacy, beneficence, and justice, we propose a set of ethical guidelines for the use of longform audio recordings in behavioral research. This article is also accompanied by an Open Science Framework Ethics Repository that includes informed consent resources such as frequent participant concerns and sample consent forms.

Ethical Challenges in Promoting the Implementation of Preventive Interventions: Report of the SPR Task Force

Prevention science researchers and practitioners are increasingly engaged in a wide range of activities and roles to promote evidence-based prevention practices in the community. Ethical concerns invariably arise in these activities and roles that may not be explicitly addressed by university or professional guidelines for ethical conduct. In 2015, the Society for Prevention Research (SPR) Board of Directors commissioned Irwin Sandler and Tom Dishion to organize a series of roundtables and establish a task force to identify salient ethical issues encountered by prevention scientists and community-based practitioners as they collaborate to implement evidence-based prevention practices. This article documents the process and findings of the SPR Ethics Task Force and aims to inform continued efforts to articulate ethical practice. Specifically, the SPR membership and task force identified prevention activities that commonly stemmed from implementation and scale-up efforts. This article presents examples that illustrate typical ethical dilemmas. We present principles and concepts that can be used to frame the discussion of ethical concerns that may be encountered in implementation and scale-up efforts. We summarize value statements that stemmed from our discussion. We also conclude that the field of prevention science in general would benefit from standards and guidelines to promote ethical behavior and social justice in the process of implementing evidence-based prevention practices in community settings. It is our hope that this article serves as an educational resource for students, investigators, and Human Subjects Review Board members regarding some of the complexity of issues of fairness, equality, diversity, and personal rights for implementation of preventive interventions.

Short-term prediction of suicidal thoughts and behaviors in adolescents: Can recent developments in technology and computational science provide a breakthrough?

BACKGROUND

Suicide is one of the leading causes of death among adolescents, and developing effective methods to improve short-term prediction of suicidal thoughts and behaviors (STBs) is critical. Currently, the most robust predictors of STBs are demographic or clinical indicators that have relatively weak predictive value. However, there is an emerging literature on short-term prediction of suicide risk that has identified a number of promising candidates, including (but not limited to) rapid escalation of: (a) emotional distress, (b) social dysfunction (e.g., bullying, rejection), and (c) sleep disturbance. However, these prior studies are limited in two critical ways. First, they rely almost entirely on self-report. Second, most studies have not focused on assessment of these risk factors using intensive longitudinal assessment techniques that are able to capture the dynamics of changes in risk states at the individual level.

METHOD

In this paper we explore how to capitalize on recent developments in real-time monitoring methods and computational analysis in order to address these fundamental problems.

RESULTS

We now have the capacity to use: (a) smartphone, wearable computing, and smart home technology to conduct intensive longitudinal assessments monitoring of putative risk factors with minimal participant burden and (b) modern computational techniques to develop predictive algorithms for STBs. Current research and theory on short-term risk processes for STBs, combined with the emergent capabilities of new technologies, suggest that this is an important research agenda for the future.

LIMITATIONS

Although these approaches have enormous potential to create new knowledge, the current empirical literature is limited. Moreover, passive monitoring of risk for STBs raises complex ethical issues that will need to be resolved before large scale clinical applications are feasible.

CONCLUSIONS

Smartphone, wearable, and smart home technology may provide one point of access that might facilitate both early identification and intervention implementation, and thus, represents a key area for future STB research.

An Ecological Approach to Smart Homes for Health Care Services: Conceptual Framework of a Smart Servicescape Wheel

Background

Smart homes are considered effective solutions for home health care for the elderly, as smart home technologies can reduce care costs and improve elderly residents’ independence. To develop a greater understanding of smart homes for health care services (SHHSs), this study accentuated the necessity of ecological approaches with an emphasis on environmental constraints. This study was based on 2 rationales: (1) users are inclined to perceive the service quality and service experience from environments (ie, servicescape) owing to the intangibility of health care and the pervasiveness of smart home technologies, and (2) both service domains are complex adaptive systems in which diversified and undefined service experiences—not only a few intended service flows—can be generated by complex combinations of servicescape elements.

Objective

This study proposed the conceptual framework of a Smart Servicescape Wheel (SSW) as an ecological approach delineating the extensive spectrum of environmental constraints in SHHSs.

Methods

The SSW framework was established based on a literature review.

Results

Generally divided by perceptible and imperceptible servicescapes, the SSW consists of the perceptible Physical scape (ie, hardware components, environmental cues, and human states) and Social scape (ie, service relationships and social relationships) as well as the imperceptible Datascape (ie, computing intelligence, databases, and communication networks). Following the ecological approach, each category of the SSW is subdivided and defined at the level of components or functions.

Conclusions

The SSW’s strengths lie in the various application opportunities for SHHSs. In terms of service planning and development, the SSW can be utilized to (1) establish the requirements for SHHS development, (2) associate with work domain analysis by defining component layers, and (3) understand the real contexts of SHHSs for the enhanced prediction of diverse service experiences. Regarding service management, it can be applied to develop measurement items for the operation and evaluation of SHHSs.

Protecting User Privacy and Rights in Academic Data-Sharing Partnerships: Principles From a Pilot Program at Crisis Text Line

Data sharing between technology companies and academic health researchers has multiple health care, scientific, social, and business benefits. Many companies remain wary about such sharing because of unaddressed concerns about ethics, data security, logistics, and public relations. Without guidance on these issues, few companies are willing to take on the potential work and risks involved in noncommercial data sharing, and the scientific and societal potential of their data goes unrealized. In this paper, we describe the 18-month long pilot of a data-sharing program led by Crisis Text Line (CTL), a not-for-profit technology company that provides a free 24/7 text line for people in crisis. The primary goal of the data-sharing pilot was to design, develop, and implement a rigorous framework of principles and protocols for the safe and ethical sharing of user data. CTL used a stakeholder-based policy process to develop a feasible and ethical data-sharing program. The process comprised forming a data ethics committee; identifying policy challenges and solutions; announcing the program and generating interest; and revising the policy and launching the program. Once the pilot was complete, CTL examined how well the program ran and compared it with other potential program models before putting in place the program that was most suitable for its organizational needs. By drawing on CTL's experiences, we have created a 3-step set of guidelines for other organizations that wish to develop their own data-sharing program with academic researchers. The guidelines explain how to (1) determine the value and suitability of the data and organization for creating a data-sharing program; (2) decide on an appropriate data sharing and collaboration model; and (3) develop protocols and technical solutions for safe and ethical data sharing and the best organizational structure for implementing the program. An internal evaluation determined that the pilot satisfied CTL's goals of sharing scientific data and protecting client confidentiality. The policy development process also yielded key principles and protocols regarding the ethical challenges involved in data sharing that can be applied by other organizations. Finally, CTL's internal review of the pilot program developed a number of alternative models for sharing data that will suit a range of organizations with different priorities and capabilities. In implementing and studying this pilot program, CTL aimed both to optimize its own future data-sharing programs and to inform similar decisions made by others. Open data programs are both important and feasible to establish. With careful planning and appropriate resources, data sharing between big data companies and academic researchers can advance their shared mission to benefit society and improve lives.

Extending the Passive-Sensing Toolbox: Using Smart-Home Technology in Psychological Science

New smart-home devices provide the opportunity to advance psychological science and theory through novel research opportunities in home environments. These technologies extend the in vivo research and intervention capabilities afforded by other assessment techniques such as Ecological Momentary Assessment methods as well as mobile and wearable devices. Smart-home devices contain a multitude of sensors capable of continuously and unobtrusively collecting multimodal data within home contexts. These devices have some complementary strengths and limitations compared with other assessment methods. This article (a) briefly reviews data collection methods in home environments, (b) discusses the unique advantages of smart-home devices, (c) describes the extant smart-home literature, (d) explores how these devices may advance evaluation and refinement of psychological theories, (e) describes examples of psychological processes that are potential targets for smart-home assessment and intervention, (f) considers methodological challenges and barriers, (g) discusses ethical considerations, and (h) concludes with a discussion of future directions for research and the merging of passive-sensing technologies with active self-report methods. This article aims to highlight the potential utility of smart-home devices within psychological research to evaluate psychological theories related to behavior within the home context.

Improving research methods for the study of geography and mental health: Utilization of social networking data and the ESRI GeoEvent Processor

The purpose of this article is to review the literature on geography and mental health, report on a case example using new methods for studying this topic, and provide recommendations for future research. Over 25 years ago, Holley (1988) conducted a review of the literature on geography and mental health and astutely stated, ‘… it is surprising that geographic study designs … have not received greater attention as an important and viable method of assessing population mental health’ (p. 535). In 1997, Parr echoed a similar statement, indicating that little has been researched on this topic and suggested this area be termed ‘geography of mental health’. Decades later, these statements still hold true – researchers have given little attention to the intersection of geography and mental health. Yet, there is great potential for this research to expand in a way that may be of great benefit to those studying mental health as well as the many suffering with mental health problems. In this aricle, a case example is provided to demonstrate the possibilities of utilizing current technologies, Twitter and the ESRI GeoEvent Processor, to expand the methods for research on this topic.

Recruiting to preclinical Alzheimer's disease clinical trials through registries

Participant registries are repositories of individuals who have expressed willingness to learn about studies for which they may be eligible. Registries are increasingly being used to improve recruitment to preclinical Alzheimer's disease (AD) clinical trials, which require large screening efforts to identify adequate numbers of participants who meet enrollment criteria. Recruiting to preclinical AD trials from registries is made more efficient through registry collection of data that permits exclusion of those who will not be eligible and identifies individuals most likely to qualify for trials. Such data could include self-reported disease family history or other risk factors but could also include cognitive, genetic, or biomarker testing outcomes. Few data are available to guide investigators overseeing registries and important ethical questions are likely to arise related to their conduct, especially in registries collecting AD risk information. This article outlines three areas of consideration for registry investigators: informed consent, disclosure, and sponsorship.

Navigating Ethics in the Digital Age: Introducing Connected and Open Research Ethics (CORE), a Tool for Researchers and Institutional Review Boards

Research studies that leverage emerging technologies, such as passive sensing devices and mobile apps, have demonstrated encouraging potential with respect to favorably influencing the human condition. As a result, the nascent fields of mHealth and digital medicine have gained traction over the past decade as demonstrated in the United States by increased federal funding for research that cuts across a broad spectrum of health conditions. The existence of mHealth and digital medicine also introduced new ethical and regulatory challenges that both institutional review boards (IRBs) and researchers are struggling to navigate. In response, the Connected and Open Research Ethics (CORE) initiative was launched. The CORE initiative has employed a participatory research approach, whereby researchers and IRB affiliates are involved in identifying the priorities and functionality of a shared resource. The overarching goal of CORE is to develop dynamic and relevant ethical practices to guide mHealth and digital medicine research. In this Viewpoint paper, we describe the CORE initiative and call for readers to join the CORE Network and contribute to the bigger conversation on ethics in the digital age.

Automatic classification of communication logs into implementation stages via text analysis

BACKGROUND

To improve the quality, quantity, and speed of implementation, careful monitoring of the implementation process is required. However, some health organizations have such limited capacity to collect, organize, and synthesize information relevant to its decision to implement an evidence-based program, the preparation steps necessary for successful program adoption, the fidelity of program delivery, and the sustainment of this program over time. When a large health system implements an evidence-based program across multiple sites, a trained intermediary or broker may provide such monitoring and feedback, but this task is labor intensive and not easily scaled up for large numbers of sites. We present a novel approach to producing an automated system of monitoring implementation stage entrances and exits based on a computational analysis of communication log notes generated by implementation brokers. Potentially discriminating keywords are identified using the definitions of the stages and experts' coding of a portion of the log notes. A machine learning algorithm produces a decision rule to classify remaining, unclassified log notes.

RESULTS

We applied this procedure to log notes in the implementation trial of multidimensional treatment foster care in the California 40-county implementation trial (CAL-40) project, using the stages of implementation completion (SIC) measure. We found that a semi-supervised non-negative matrix factorization method accurately identified most stage transitions. Another computational model was built for determining the start and the end of each stage.

CONCLUSIONS

This automated system demonstrated feasibility in this proof of concept challenge. We provide suggestions on how such a system can be used to improve the speed, quality, quantity, and sustainment of implementation. The innovative methods presented here are not intended to replace the expertise and judgement of an expert rater already in place. Rather, these can be used when human monitoring and feedback is too expensive to use or maintain. These methods rely on digitized text that already exists or can be collected with minimal to no intrusiveness and can signal when additional attention or remediation is required during implementation. Thus, resources can be allocated according to need rather than universally applied, or worse, not applied at all due to their cost.