Integrating People, Context, and Technology in the Implementation of a Web-Based Intervention in Forensic Mental Health Care: Mixed-Methods Study

Challenges and opportunities in mobile e-coaching

Background

Mobile e-health technologies have proven to provide tailored assessment, intervention, and coaching capabilities for various usage scenarios. Thanks to their spread and adoption, smartphones are one of the most important carriers for such applications.

Problem

However, the process of design, realization, evaluation, and implementation of these e-health solutions is wicked and challenging, requiring multiple stakeholders and expertise.

Method

Here, we present a tailorable intervention and interaction e-health solution that allows rapid prototyping, development, and evaluation of e-health interventions at scale. This platform allows researchers and clinicians to develop ecological momentary assessment, just-in-time adaptive interventions, ecological momentary intervention, cohort studies, and e-coaching and personalized interventions quickly, with no-code, and in a scalable way.

Result

The Twente Intervention and Interaction Instrument (TIIM) has been used by over 320 researchers in the last decade. We present the ecosystem and synthesize the main scientific output from clinical and research studies in different fields.

Discussion

The importance of mobile e-coaching for prediction, management, and prevention of adverse health outcomes is increasing. A profound e-health development strategyand strategic, technical, and operational investments are needed to prototype, develop, implement, and evaluate e-health solutions. TIIM ecosystem has proven to support these processes. This paper ends with the main research opportunities in mobile coaching, including intervention mechanisms, fine-grained monitoring, and inclusion of objective biomarker data.

Exploring the added value of virtual reality biofeedback game DEEP in forensic psychiatric inpatient care-A qualitative study

Background

Low motivation and suboptimal cognitive skills are common among forensic psychiatric patients. By focusing on doing and experiencing, innovative technologies could offer an alternative to existing treatment for this patient group. One promising technology is DEEP, a VR biofeedback game that teaches diaphragmatic breathing, which has shown its potential in reducing stress in other populations. This exploratory study aimed at identifying if, how and for whom DEEP can be of added value in forensic mental healthcare.

Methods

This study used a qualitative approach. Six focus groups with 24 healthcare providers and 13 semi-structured interviews with forensic psychiatric inpatients were conducted in two Dutch forensic mental healthcare organizations. All healthcare providers and patients experienced DEEP before participating. The data were coded inductively, using the method of constant comparison.

Results

The data revealed six themes with accompanying (sub)codes, including (1) the possible advantages and (2) disadvantages of DEEP, (3) patient characteristics that could make DEEP more or (4) less suitable and beneficial, (5) ways DEEP could be used in current treatment, and (6) conditions that need to be met to successfully implement DEEP in forensic mental healthcare. The results showed that DEEP can offer novel ways to support forensic psychiatric patients in coping with negative emotions by practicing diaphragmatic breathing. Its appealing design might be suitable to motivate a broad range of forensic psychiatric patient groups. However, DEEP cannot be personalized, which might decrease engagement and uptake of DEEP long-term. Regarding its place in current care, DEEP could be structurally integrated in existing treatment programs or used ad hoc when the need arises. Finally, this study showed that both healthcare providers and patients would need practical support and information to use DEEP.

Conclusion

With its experience-based and gamified design, DEEP could be useful for forensic mental healthcare. It is recommended that patients and healthcare providers are included in the evaluation and implementation from the start. Besides, a multilevel approach should be used for formulating implementation strategies. If implemented well, DEEP can offer new ways to provide forensic psychiatric patients with coping strategies to better control their anger.

The effectiveness of blended versus regular Forensic Outpatient Systemic Therapy in the treatment of juvenile antisocial behavior: a study protocol of a randomized controlled trial

BACKGROUND

Antisocial behavior during adolescence can have long-lasting negative effects and leads to high societal costs. Forensic Outpatient Systemic Therapy (Forensische Ambulante Systeem Therapie; FAST) is a promising treatment for juveniles aged 12-21 showing severe antisocial behavior. The intensity, content and duration of FAST can be adjusted to the needs of the juvenile and their caregiver(s), which is considered crucial for effective treatment. Next to the regular version of FAST (FASTr), a blended version (FASTb) in which face-to-face contacts are replaced by minimally 50% online contacts over the duration of intervention was developed during the Covid-19 pandemic. The current study will investigate whether FASTb is equally effective as FASTr, and through which mechanisms of change, for whom, and under which conditions FASTr and FASTb work.

METHODS

A randomized controlled trial (RCT) will be carried out. Participants (N = 200) will be randomly assigned to FASTb (n = 100) or FASTr (n = 100). Data collection will consist of self-report questionnaires and case file analysis, and include a pre-test at the start of the intervention, a post-test immediately after the intervention, and a six month follow-up. Mechanisms of change will be investigated using monthly questionnaires of key variables during treatment. Official recidivism data will be collected at two-year follow-up.

DISCUSSION

This study aims to improve the effectiveness and quality of forensic mental health care for juveniles with antisocial behavior by studying the effectiveness of blended care, which has not been studied before in treatment of externalizing behavior. If found to be at least as effective as face-to-face treatment, blended treatment can help meet the urgent need for more flexible and efficient interventions in this field. In addition, the proposed study aims to unravel what works for whom, knowledge urgently needed in mental health care for juveniles with severe antisocial behavior.

TRIAL REGISTRATION

This trial was registered at ClinicalTrials.gov on 07/11/2022, registration number NCT05606978.

How Reflective Automated e-Coaching Can Help Employees Improve Their Capacity for Resilience: Mixed Methods Study

BACKGROUND

An eHealth tool that coaches employees through the process of reflection has the potential to support employees with moderate levels of stress to increase their capacity for resilience. Most eHealth tools that include self-tracking summarize the collected data for the users. However, users need to gain a deeper understanding of the data and decide upon the next step to take through self-reflection.

OBJECTIVE

In this study, we aimed to examine the perceived effectiveness of the guidance offered by an automated e-Coach during employees' self-reflection process in gaining insights into their situation and on their perceived stress and resilience capacities and the usefulness of the design elements of the e-Coach during this process.

METHODS

Of the 28 participants, 14 (50%) completed the 6-week BringBalance program that allowed participants to perform reflection via four phases: identification, strategy generation, experimentation, and evaluation. Data collection consisted of log data, ecological momentary assessment (EMA) questionnaires for reflection provided by the e-Coach, in-depth interviews, and a pre- and posttest survey (including the Brief Resilience Scale and the Perceived Stress Scale). The posttest survey also asked about the utility of the elements of the e-Coach for reflection. A mixed methods approach was followed.

RESULTS

Pre- and posttest scores on perceived stress and resilience were not much different among completers (no statistical test performed). The automated e-Coach did enable users to gain an understanding of factors that influenced their stress levels and capacity for resilience (identification phase) and to learn the principles of useful strategies to improve their capacity for resilience (strategy generation phase). Design elements of the e-Coach reduced the reflection process into smaller steps to re-evaluate situations and helped them to observe a trend (identification phase). However, users experienced difficulties integrating the chosen strategies into their daily life (experimentation phase). Moreover, the identified events related to stress and resilience were too specific through the guidance offered by the e-Coach (identification phase), and the events did not recur, which consequently left users unable to sufficiently practice (strategy generation phase), experiment (experimentation phase), and evaluate (evaluation phase) the techniques during meaningful events.

CONCLUSIONS

Participants were able to perform self-reflection under the guidance of the automated e-Coach, which often led toward gaining new insights. To improve the reflection process, more guidance should be offered by the e-Coach that would aid employees to identify events that recur in daily life. Future research could study the effects of the suggested improvements on the quality of reflection via an automated e-Coach.

The development of a smartphone app to enhance post-traumatic stress disorder treatment in high-risk workers

Objective

Post-traumatic stress disorder (PTSD) is highly prevalent in certain populations. However, evidence indicates that many individuals do not respond to treatment. Digital supports hold promise for increasing service provision and engagement but there is a lack of evidence on blended care options and still less research guiding the development of such tools. This study details the development and overarching framework used to build a smartphone app to support PTSD treatment.

Methods

The app was developed in line with the Integrate, Design, Assess, and Share (IDEAS) framework for the development of digital health interventions and involved clinicians (n=3), frontline worker clients (n=5) and trauma-exposed frontline workers (n=19). Integrated iterative rounds of testing were conducted via in-depth interviews, surveys, prototype testing and workshops, alongside app and content development.

Results

Clinicians and frontline workers both expressed a clear preference for the app to augment but not replace face-to-face therapy, with the aim of increasing between-session support, and facilitating homework completion. Content was adapted for app delivery from manualised therapy (trauma-focused cognitive behavioural therapy (CBT). Prototype versions of the app were well received, with both clinicians and clients reporting the app was easy to use, understandable, appropriate and highly recommendable. System Usability Scale (SUS) scores were on average in the excellent range (82/100).

Conclusions

This is one of the first studies to document the development of a blended care app designed specifically to augment clinical care for PTSD, and the first within a frontline worker population. Through a systematic framework with active end user consultation, a highly usable app was built to undergo subsequent evaluation.

Factors Associated With Intention and Use of e-Mental Health by Mental Health Counselors in General Practices: Web-Based Survey

BACKGROUND

Mental health care counselors have a high intention to use e-mental health (EMH), whereas actual use is limited. Facilitating future use requires insight into underlying factors as well as eligibility criteria that mental health care counselors use in their decision to apply EMH.

OBJECTIVE

The aim of this study was to unfold the intention and underlying reasons for mental health counselors to use EMH and to unveil the criteria they use to estimate patient eligibility for EMH. The theoretical framework was based on the reasoned action approach model, the Unified Theory of Acceptance and Use of Technology, and the Measurement Instrument for Determinants of Innovation model.

METHODS

To empirically validate our theoretical model, a web-based survey was conducted among mental health care counselors (n=132). To unveil the eligibility criteria, participants were asked to rank their reasons for considering EMH suitable or unsuitable for a patient.

RESULTS

The mean intention to use EMH was positive (mean 4.04, SD 0.64). The mean use of EMH before the COVID-19 pandemic was 38% (mean 0.38, SD 0.22), and it was 49% (mean 0.49, SD 0.25) during the pandemic. In total, 57% of the patient population was considered eligible for EMH. Usefulness and benefits (β=.440; P<.001), Task perception (β=.306; P=.001), and Accessibility (β=.140; P=.02) explained the intention to use EMH (F_3,131=54.151; P<.001; R²=0.559). In turn, intention explained patient eligibility (F_1,130=34.716; P<.001; R²=0.211), whereas intention and patient eligibility explained EMH use (F_2,129=41.047; P<.001; R²=0.389). Patient eligibility partially mediated the relationship between intention to use EMH and EMH use, with a larger direct effect (c'=0.116; P<.001) than indirect effect (c=0.065, 95% CI 0.035-0.099; P<.001). Mental health counselors assessed patients' eligibility for EMH mainly through the availability of computers and the internet and patient motivation.

CONCLUSIONS

To stimulate the use of EMH, intention and patient eligibility need to be influenced. Intention, in turn, can be enhanced by addressing the perceived usefulness and benefits of EMH, perceived accessibility, and task perception. Access to a computer and patients' motivation to use EMH are important in facilitating patient eligibility. To cause an impact with EMH in general practice, mental health counselors need to be convinced of the benefits of EMH and transfer this enthusiasm to the patient. It is recommended to involve mental health counselors in the development of EMH to increase the (perceived) added value and use.

Methods for Human-Centered eHealth Development: Narrative Scoping Review

Background

Thorough holistic development of eHealth can contribute to a good fit among the technology, its users, and the context. However, despite the availability of frameworks, not much is known about specific research activities for different aims, phases, and settings. This results in researchers having to reinvent the wheel. Consequently, there is a need to synthesize existing knowledge on research activities for participatory eHealth development processes.

Objective

The 3 main goals of this review are to create an overview of the development strategies used in studies based on the CeHRes (Center for eHealth Research) Roadmap, create an overview of the goals for which these methods can be used, and provide insight into the lessons learned about these methods.

Methods

We included eHealth development studies that were based on the phases and/or principles of the CeHRes Roadmap. This framework was selected because of its focus on participatory, iterative eHealth design in context and to limit the scope of this review. Data were extracted about the type of strategy used, rationale for using the strategy, research questions, and reported information on lessons learned. The most frequently mentioned lessons learned were summarized using a narrative, inductive approach.

Results

In the included 160 papers, a distinction was made between overarching development methods (n=10) and products (n=7). Methods are used to gather new data, whereas products can be used to synthesize previously collected data and support the collection of new data. The identified methods were focus groups, interviews, questionnaires, usability tests, literature studies, desk research, log data analyses, card sorting, Delphi studies, and experience sampling. The identified products were prototypes, requirements, stakeholder maps, values, behavior change strategies, personas, and business models. Examples of how these methods and products were applied in the development process and information about lessons learned were provided.

Conclusions

This study shows that there is a plethora of methods and products that can be used at different points in the development process and in different settings. To do justice to the complexity of eHealth development, it seems that multiple strategies should be combined. In addition, we found no evidence for an optimal single step-by-step approach to develop eHealth. Rather, researchers need to select the most suitable research methods for their research objectives, the context in which data are collected, and the characteristics of the participants. This study serves as a first step toward creating a toolkit to support researchers in applying the CeHRes Roadmap to practice. In this way, they can shape the most suitable and efficient eHealth development process.

Clinician Perspectives on Barriers and Facilitators to Implementing e-Health Technology in Substance Use Disorder (SUD) Treatment Facilities

Background:

Substance use disorders (SUDs) in the United States cause many preventable deaths each year. Finding effective ways to manage SUDs is vital to improving outcomes for individuals seeking treatment. This has increased interest in using e-health technologies in behavioral healthcare settings. This research is part of a larger study evaluating the efficacy of the NIATx coaching intervention for implementing RISE Iowa, an e-health patient recovery app, in SUD treatment organizations and seeks to examine clinician perspectives of the barriers and facilitators to its implementation.

Method:

Semi-structured qualitative interviews were conducted with 13 clinicians from 9 different intervention sites involved in the study.

Results:

Major barriers to implementing e-health technology include inability to access the technology, lack of time for both patients and clinicians, and a perceived lack of patient motivation to make changes. Facilitators to implementation include collaboration with other staff using e-health technology and integrating technology use into typical workflows.

Conclusions:

Implementation of e-health technology in SUD treatment will require integrating the technology into clinical workflows and improving patient access to the technology.

Implementation of Unobtrusive Sensing Systems for Older Adult Care: Scoping Review

Background

The continuous growth of the older adult population will have implications for the organization of health and social care. Potentially, in-home monitoring unobtrusive sensing systems (USSs) can be used to support formal or informal caregivers of older adults, as they can monitor deviant physical and physiological behavior changes. Most existing USSs are not specific to older adult care. Hence, to facilitate the implementation of existing USSs in older adult care, it is important to know which USSs would be more suitable for older adults.

Objective

This scoping review aims to examine the literature to identify current USSs for monitoring human activities and behaviors and assess their implementation readiness for older adult care.

Methods

We conducted a structured search in the Scopus, Web of Science, and ACM Digital Library databases. Predefined inclusion criteria included studies on unobtrusive sensor-based technology; experimental in nature; aimed at monitoring human social, emotional, physical, and physiological behavior; having the potential to be scalable in in-home care; and having at least 5 adults as participants. Using these criteria, we screened studies by title, abstract, and full text. A deductive thematic analysis based on the Proctor implementation framework along with an additional outcome of external validity was applied to the included studies to identify the factors contributing to successful implementation. Finally, the identified factors were used to report the implementation readiness of the included studies for older adult care.

Results

In this review, 52 studies were included. Deductive analysis using the implementation framework by Proctor resulted in six factors that can contribute to the successful implementation of USSs in older adult care: study settings, age of participants, activities monitored, sensor setup, sensing technology used, and usefulness of USSs. These factors were associated with the implementation outcomes as follows: study settings and age of participants contributed to external validity, sensor setup contributed to acceptability, usefulness of USSs contributed to adoption, activities monitored contributed to appropriateness, and sensing technology used contributed to implementation cost. Furthermore, the implementation assessment of the included 52 studies showed that none of the studies addressed all the identified factors. This assessment was useful in highlighting studies that have addressed multiple factors; thus, these studies represent a step ahead in the implementation process.

Conclusions

This review is the first to scope state-of-the-art USSs suitable for older adult care. Although the included 52 USS studies fulfilled the basic criteria to be suitable for older adult care, systems leveraging radio frequency technology in a no-contact sensor setup for monitoring life risk or health wellness activities are more suitable for older adult care. Finally, this review has extended the discussion about unobtrusiveness as a property of systems that cannot be measured in binary because it varies greatly with user perception and context.

A Perspective on the Integration of eHealth in Treatment of Offenders: Combining Technology and the Risk-Need-Responsivity Model

While there are multiple ways in which eHealth interventions such as online modules, apps and virtual reality can improve forensic psychiatry, uptake in practice is low. To overcome this problem, better integration of eHealth in treatment is necessary. In this perspective paper, we describe how the possibilities of eHealth can be connected to the risk-need-responsivity (RNR) model. To account for the risk-principle, stand-alone eHealth interventions might be used to offer more intensive treatment to high-risk offenders. The need-principle can be addressed by connecting novel experience-based interventions such as VR and apps to stable and acute dynamic risk factors. Finally, using and combining personalized interventions is in line with the responsivity-principle. Based on research inside and outside of forensic psychiatry, we conclude that there are many possibilities for eHealth to improve treatment-not just based on RNR, but also on other models. However, there is a pressing need for more development, implementation and evaluation research.

Identifying Persuasive Design Principles and Behavior Change Techniques Supporting End User Values and Needs in eHealth Interventions for Long-Term Weight Loss Maintenance: Qualitative Study

BACKGROUND

An increasing number of eHealth interventions aim to support healthy behaviors that facilitate weight loss. However, there is limited evidence of the effectiveness of the interventions and little focus on weight loss maintenance. Knowledge about end user values and needs is essential to create meaningful and effective eHealth interventions, and to identify persuasive system design (PSD) principles and behavior change techniques (BCTs) that may contribute to the behavior change required for successful long-term weight loss maintenance.

OBJECTIVE

This study aimed to provide insight into the design of eHealth interventions supporting behavior change for long-term weight maintenance. The study sought to identify the values and needs of people with obesity aiming to maintain weight after weight loss, and to identify PSD principles, BCTs, and design requirements that potentially enable an eHealth intervention to meet end user values and needs.

METHODS

This study presents the concept of integrating PSD principles and BCTs into the design process of eHealth interventions to meet user values and needs. In this study, individual interviews and focus groups were conducted with people with obesity (n=23) and other key stakeholders (n=27) to explore end user values and needs related to weight loss maintenance. Design thinking methods were applied during the focus group sessions to identify design elements and to explore how eHealth solutions can support the needs to achieve sustainable weight loss maintenance. The PSD model and behavior change taxonomy by Michie were used to identify PSD principles and BCT clusters to meet end user values and needs.

RESULTS

A total of 8 key end user values were identified, reflecting user needs for weight loss maintenance support: self-management, personalized care, autonomy, feel supported, positive self-image, motivation, happiness, and health. Goals and planning, feedback and monitoring, repetition and substitution, shaping knowledge, social support, identity, and self-belief were some of the BCT clusters identified to address these concepts, together with PSD principles such as personalization, tailoring, self-monitoring, praise, and suggestions.

CONCLUSIONS

The process of translating end user values and needs into design elements or features of eHealth technologies is an important part of the design process. To our knowledge, this is the first study to explore how PSD principles and BCTs can be integrated when designing eHealth self-management interventions for long-term weight loss maintenance. End users and other key stakeholders highlighted important factors to be considered in the design of eHealth interventions supporting sustained behavior change. The PSD principles and BCTs identified provide insights and suggestions about design elements and features to include for supporting weight loss maintenance. The findings indicate that a combination of BCTs and PSD principles may be needed in evidence-based eHealth interventions to stimulate motivation and adherence to support healthy behaviors and sustained weight loss maintenance.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04537988; https://clinicaltrials.gov/ct2/show/NCT04537988.

Shaping Blended Care: Adapting an Instrument to Support Therapists in Using eMental Health

BACKGROUND

Although eMental health interventions, especially when delivered in a blended way, have great potential to improve the quality and efficiency of mental health care, their use in practice lags behind expectations. The Fit for Blended Care (FfBC) instrument was developed to support therapists and clients in shaping blended care in a way that optimally fits their needs. However, this existing version cannot be directly applied to specific branches of mental health care as it is too broad and generic.

OBJECTIVE

The goal of this study is to adapt the existing FfBC instrument to fit a specific, complex setting-forensic mental health care-by means of participatory development with therapists.

METHODS

The participatory process was divided into 4 phases and was executed by a project team consisting of 1 manager, 3-5 therapists, and 1 researcher. In phase 1, general requirements for the adaptation of the existing instrument were discussed in 2 focus groups with the project team. In phase 2, patient-related factors that influence the use of an existing web-based intervention were elicited through semistructured interviews with all 18 therapists working at an outpatient clinic. In phase 3, multiple focus groups with the project teams were held to create the first version of the adapted FfBC instrument. In phase 4, a digital prototype of the instrument was used with 8 patients, and the experiences of the 4 therapists were discussed in a focus group.

RESULTS

In phase 1, it became clear that the therapists' main requirement was to develop a much shorter instrument with a few items, in which the content was specifically tailored to the characteristics of forensic psychiatric outpatients. The interviews showed a broad range of patient-related factors, of which 5 were used in the instrument: motivation for blended treatment; writing about thoughts, feelings, and behavior; conscientiousness; psychosocial problems; and social support. In addition, a part of the instrument was focused on the practical necessary preconditions that patients should fill by themselves before the treatment was developed. The use of the web-based prototype of the instrument in treatment resulted in overall positive experiences with the content; however, therapists indicated that the items should be formulated in a more patient-centered way to encourage their involvement in discussing the factors.

CONCLUSIONS

The participatory, iterative process of this study resulted in an adapted version of the FfBC instrument that fits the specific forensic context and supports shared decision making. In general, the adaptiveness of the instrument is important: its content and implementation should fit the type of care, the organization, and eHealth intervention. To adapt the instrument to other contexts, the guidelines described in this paper can be followed.