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.

Implementation of virtual reality in healthcare: a scoping review on the implementation process of virtual reality in various healthcare settings.

BACKGROUND: Virtual reality (VR) is increasingly used in healthcare settings as recent technological advancements create possibilities for diagnosis and treatment. VR is a technology that uses a headset to simulate a reality in which the user is immersed in a virtual environment, creating the impression that the user is physically present in this virtual space. Despite the potential added value of virtual reality technology in healthcare, its uptake in clinical practice is still in its infancy and challenges arise in the implementation of VR. Effective implementation could improve the adoption, uptake, and impact of VR. However, these implementation procedures still seem to be understudied in practice. This scoping review aimed to examine the current state of affairs in the implementation of VR technology in healthcare settings and to provide an overview of factors related to the implementation of VR. METHODS: To give an overview of relevant literature, a scoping review was undertaken of articles published up until February 2022, guided by the methodological framework of Arksey and O'Malley (2005). The databases Scopus, PsycINFO, and Web of Science were systematically searched to identify records that highlighted the current state of affairs regarding the implementation of VR in healthcare settings. Information about each study was extracted using a structured data extraction form. RESULTS: Of the 5523 records identified, 29 were included in this study. Most studies focused on barriers and facilitators to implementation, highlighting similar factors related to the behavior of adopters of VR and the practical resources the organization should arrange for. However, few studies focus on systematic implementation and on using a theoretical framework to guide implementation. Despite the recommendation of using a structured, multi-level implementation intervention to support the needs of all involved stakeholders, there was no link between the identified barriers and facilitators, and specific implementation objectives or suitable strategies to overcome these barriers in the included articles. CONCLUSION: To take the implementation of VR in healthcare to the next level, it is important to ensure that implementation is not studied in separate studies focusing on one element, e.g., healthcare provider-related barriers, as is common in current literature. Based on the results of this study, we recommend that the implementation of VR entails the entire process, from identifying barriers to developing and employing a coherent, multi-level implementation intervention with suitable strategies. This implementation process could be supported by implementation frameworks and ideally focus on behavior change of stakeholders such as healthcare providers, patients, and managers. This in turn might result in increased uptake and use of VR technologies that are of added value for healthcare practice.

A Mobile Self-control Training App to Improve Self-control and Physical Activity in People With Severe Mental Illness: Protocol for 2 Single-Case Experimental Designs.

BACKGROUND: Lack of physical activity is a common issue with detrimental consequences for the health of people with severe mental illness (SMI). Existing physical activity interventions show suboptimal effects as they require substantial cognitive skills, including goal setting and writing, whereas cognitive deficits are common in this population. To bolster the effectiveness of physical activity interventions, self-control training (SCT), in which users practice the ability to override unwanted thoughts and behaviors, can be used in addition. Recent research has demonstrated the initial effectiveness of a mobile SCT app, but this has not been studied in psychiatric clinical practice. OBJECTIVE: This study aims to evaluate to what extent adding a mobile SCT app designed for and with people with SMI to a mobile lifestyle intervention aimed at increasing physical activity increases physical activity and self-control levels. METHODS: A mixed methods approach incorporating 2 single-case experimental designs (SCEDs) and qualitative interviews was used to evaluate and optimize SCT. Overall, 12 participants with SMI will be recruited from 2 organizations offering outpatient and inpatient care to people with SMI. Each experiment will include 6 patients. SCED I is a concurrent multiple-baseline design across participants that explores initial effectiveness and optimal intervention duration. Using accelerometry and experience sampling questionnaires, participants' physical activity and self-control will be monitored for ≥5 days from baseline, followed by the sequential introduction of Google Fit, the physical activity intervention, for 7 days and the addition of SCIPP: Self-Control Intervention App for 28 days. SCED II is an introduction/withdrawal design in which optimized SCT will be introduced and withdrawn to validate the findings from SCED I. In both experiments, the daily average of total activity counts per hour and the state level of self-control will serve as the primary and secondary outcome measures. Data will be analyzed using visual analysis and piecewise linear regression models. RESULTS: The study was designated as not subject to the Dutch Medical Research Involving Human Subjects Act by the Medical Research Ethical Committee Oost-Nederland and approved by the Ethics Committee/domain Humanities and Social Sciences of the Faculty of Behavioural, Management, and Social Sciences at the University of Twente. Participant recruitment started in January 2022, and we expect to publish the results in early 2023. CONCLUSIONS: The mobile SCT app is expected to be feasible and effective. It is self-paced and scalable and can increase patient motivation, making it a suitable intervention for people with SMI. SCED is a relatively novel yet promising method for gaining insights into whether and how mobile apps work that can handle heterogeneous samples and makes it possible to involve a diverse population with SMI without having to include a large number of participants. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/37727.

The Role of Compassionate Technology in Blended and Digital Mental Health Interventions: Systematic Scoping Review.

BACKGROUND: An essential value in mental health care is compassion: awareness of suffering, tolerating difficult feelings in the face of suffering, and acting or being motivated to alleviate suffering. Currently, technologies for mental health care are on the rise and could offer several advantages, such as more options for self-management by clients and more accessible and economically viable care. However, digital mental health interventions (DMHIs) have not been widely implemented in daily practice. Developing and evaluating DMHIs around important mental health care values, such as compassion, could be key for a better integration of technology in the mental health care context. OBJECTIVE: This systematic scoping review explored the literature for previous instances where technology for mental health care has been linked to compassion or empathy to investigate how DMHIs can support compassion in mental health care. METHODS: Searches were conducted in the PsycINFO, PubMed, Scopus, and Web of Science databases, and screening by 2 reviewers resulted in 33 included articles. From these articles, we extracted the following data: technology types, goals, target groups, and roles of the technologies in the intervention; study designs; outcome measures; and the extent to which the technologies met a 5-step proposed definition of compassion. RESULTS: We found 3 main ways in which technology can contribute to compassion in mental health care: by showing compassion to people, by enhancing self-compassion in people, or by facilitating compassion between people. However, none of the included technologies met all 5 elements of compassion nor were they evaluated in terms of compassion. CONCLUSIONS: We discuss the potential of compassionate technology, its challenges, and the need to evaluate technology for mental health care on compassion. Our findings could contribute to the development of compassionate technology, in which elements of compassion are explicitly embedded in its design, use, and evaluation.

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.

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.

A self-control training app to increase self-control and reduce aggression - A full factorial design.

BACKGROUND: Research has shown that self-control training (SCT) is an effective intervention to increase self-control and behaviour driven by self-control, such as reactive aggression. We developed an app that offers SCT by asking users to use their non-dominant hand for daily tasks, and aimed to examine whether participants that received SCT via app or e-mail, and received either one daily task or five tasks at once, improved more in self-control and decreased in aggression compared to each other and a control group. METHODS: The design of this study was based on a pilot study in which a first version of the SCT app was developed and tested with students via a pretest-posttest design. Based on the outcomes of the pilot study, a 2 × 2 full factorial design (N = 204) with control group (n = 69) was used, with delivery via e-mail versus app and receiving one daily task versus five at once as factors. During four measuring points, self-control was assessed via the Brief Self-Control Scale (BSCS) and the Go/No-Go task, aggression was assessed using the Brief Aggression Questionnaire (BAQ). In the final questionnaire, open-ended questions were asked to gain insight into the app's points of improvement. Quantitative data were analysed using repeated measures linear mixed models, qualitative data were analysed via inductive coding. RESULTS: While no interaction effects were found, analyses showed that only the BSCS-scores of participants that used the app significantly improved over time (F[3, 196.315] = 4.090, p = .008), no improvements were observed in the e-mail and control condition. No meaningful differences in aggression, the Go/No-Go task, and between the one- and five-task conditions and control groups were found. Qualitative data showed that while the opinions on SCT-tasks differed, participants were overall satisfied with the intervention, but wanted more reminders. CONCLUSIONS: The results of this study showed that an SCT app has the potential to bolster self-control. No convincing effects on aggression were found in this student sample, which might be explained by the relatively low levels of aggression in this target group. Consequently, the app should also be investigated in populations with aggression regulation problems. Future research might also focus on the use of SCT to improve other types of behaviour driven by self-control, such as physical activity or smoking. Finally, a more personalized version of the app, in which users can select the number and types of SCT-tasks, should be developed and evaluated.

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.

Psychometric Evaluation of the TWente Engagement with Ehealth Technologies Scale (TWEETS): Evaluation Study.

BACKGROUND: Engagement emerges as a predictor for the effectiveness of digital health interventions. However, a shared understanding of engagement is missing. Therefore, a new scale has been developed that proposes a clear definition and creates a tool to measure it. The TWente Engagement with Ehealth Technologies Scale (TWEETS) is based on a systematic review and interviews with engaged health app users. It defines engagement as a combination of behavior, cognition, and affect. OBJECTIVE: This paper aims to evaluate the psychometric properties of the TWEETS. In addition, a comparison is made with the experiential part of the Digital Behavior Change Intervention Engagement Scale (DBCI-ES-Ex), a scale that showed some issues in previous psychometric analyses. METHODS: In this study, 288 participants were asked to use any step counter app on their smartphones for 2 weeks. They completed online questionnaires at 4 time points: T0=baseline, T1=after 1 day, T2=1 week, and T3=2 weeks. At T0, demographics and personality (conscientiousness and intellect/imagination) were assessed; at T1-T3, engagement, involvement, enjoyment, subjective usage, and perceived behavior change were included as measures that are theoretically related to our definition of engagement. Analyses focused on internal consistency, reliability, and the convergent, divergent, and predictive validity of both engagement scales. Convergent validity was assessed by correlating the engagement scales with involvement, enjoyment, and subjective usage; divergent validity was assessed by correlating the engagement scales with personality; and predictive validity was assessed by regression analyses using engagement to predict perceived behavior change at later time points. RESULTS: The Cronbach alpha values of the TWEETS were .86, .86, and .87 on T1, T2, and T3, respectively. Exploratory factor analyses indicated that a 1-factor structure best fits the data. The TWEETS is moderately to strongly correlated with involvement and enjoyment (theoretically related to cognitive and affective engagement, respectively; P<.001). Correlations between the TWEETS and frequency of use were nonsignificant or small, and differences between adherers and nonadherers on the TWEETS were significant (P<.001). Correlations between personality and the TWEETS were nonsignificant. The TWEETS at T1 was predictive of perceived behavior change at T3, with an explained variance of 16%. The psychometric properties of the TWEETS and the DBCI-ES-Ex seemed comparable in some aspects (eg, internal consistency), and in other aspects, the TWEETS seemed somewhat superior (divergent and predictive validity). CONCLUSIONS: The TWEETS performs quite well as an engagement measure with high internal consistency, reasonable test-retest reliability and convergent validity, good divergent validity, and reasonable predictive validity. As the psychometric quality of a scale is a reflection of how closely a scale matches the conceptualization of a concept, this paper is also an attempt to conceptualize and define engagement as a unique concept, providing a first step toward an acceptable standard of defining and measuring engagement.

Evaluation of the Perceived Persuasiveness Questionnaire: User-Centered Card-Sort Study.

BACKGROUND: eHealth technologies aim to change users' health-related behavior. Persuasive design and system features can make an eHealth technology more motivating, engaging, or supportive to its users. The Persuasive Systems Design (PSD) model incorporates software features that have the possibility to increase the persuasiveness of technologies. However, the effects of specific PSD software features on the effectiveness of an intervention are still largely unknown. The Perceived Persuasiveness Questionnaire (PPQ) was developed to gain insight into the working mechanisms of persuasive technologies. Although the PPQ seems to be a suitable method for measuring subjective persuasiveness, it needs to be further evaluated to determine how suitable it is for measuring perceived persuasiveness among the public. OBJECTIVE: This study aims to evaluate the face and construct validity of the PPQ, identify points of improvement, and provide suggestions for further development of the PPQ. METHODS: A web-based closed-ended card-sort study was performed wherein participants grouped existing PPQ items under existing PPQ constructs. Participants were invited via a Massive Open Online Course on eHealth. A total of 398 people (average age 44.15 years, SD 15.17; 251/398, 63.1% women) completed the card sort. Face validity was evaluated by determining the item-level agreement of the original PPQ constructs. Construct validity was evaluated by determining the construct in which each item was placed most often, regardless of the original placement and how often 2 items were (regardless of the constructs) paired together and what interitem correlations were according to a cluster analysis. RESULTS: Four PPQ constructs obtained relatively high face validity scores: perceived social support, use continuance, perceived credibility, and perceived effort. Item-level agreement on the other constructs was relatively low. Item-level agreement for almost all constructs, except perceived effort and perceived effectiveness, would increase if items would be grouped differently. Finally, a cluster analysis of the PPQ indicated that the strengths of the newly identified 9 clusters varied strongly. Unchanged strong clusters were only found for perceived credibility support, perceived social support, and use continuance. The placement of the other items was much more spread out over the other constructs, suggesting an overlap between them. CONCLUSIONS: The findings of this study provide a solid starting point toward a redesigned PPQ that is a true asset to the field of persuasiveness research. To achieve this, we advocate that the redesigned PPQ should adhere more closely to what persuasiveness is according to the PSD model and to the mental models of potential end users of technology. The revised PPQ should, for example, enquire if the user thinks anything is done to provide task support but not how this is done exactly.

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

BACKGROUND: While eMental health interventions can have many potential benefits for mental health care, implementation outcomes are often disappointing. In order to improve these outcomes, there is a need for a better understanding of complex, dynamic interactions between a broad range of implementation-related factors. These interactions and processes should be studied holistically, paying attention to factors related to context, technology, and people. OBJECTIVE: The main objective of this mixed-method study was to holistically evaluate the implementation strategies and outcomes of an eMental health intervention in an organization for forensic mental health care. METHODS: First, desk research was performed on 18 documents on the implementation process. Second, the intervention's use by 721 patients and 172 therapists was analyzed via log data. Third, semistructured interviews were conducted with all 18 therapists of one outpatient clinic to identify broad factors that influence implementation outcomes. The interviews were analyzed via a combination of deductive analysis using the nonadoption, abandonment, scale-up, spread, and sustainability framework and inductive, open coding. RESULTS: The timeline generated via desk research showed that implementation strategies focused on technical skills training of therapists. Log data analyses demonstrated that 1019 modules were started, and 18.65% (721/3865) of patients of the forensic hospital started at least one module. Of these patients, 18.0% (130/721) completed at least one module. Of the therapists using the module, 54.1% (93/172 sent at least one feedback message to a patient. The median number of feedback messages sent per therapist was 1, with a minimum of 0 and a maximum of 460. Interviews showed that therapists did not always introduce the intervention to patients and using the intervention was not part of their daily routine. Also, therapists indicated patients often did not have the required conscientiousness and literacy levels. Furthermore, they had mixed opinions about the design of the intervention. Important organization-related factors were the need for more support and better integration in organizational structures. Finally, therapists stated that despite its current low use, the intervention had the potential to improve the quality of treatment. CONCLUSIONS: Synthesis of different types of data showed that implementation outcomes were mostly disappointing. Implementation strategies focused on technical training of therapists, while little attention was paid to changes in the organization, design of the technology, and patient awareness. A more holistic approach toward implementation strategies-with more attention to the organization, patients, technology, and training therapists-might have resulted in better implementation outcomes. Overall, adaptivity appears to be an important concept in eHealth implementation: a technology should be easily adaptable to an individual patient, therapists should be trained to deal flexibly with an eMental health intervention in their treatment, and organizations should adapt their implementation strategies and structures to embed a new eHealth intervention.

The Importance of Systematically Reporting and Reflecting on eHealth Development: Participatory Development Process of a Virtual Reality Application for Forensic Mental Health Care.

BACKGROUND: The use of electronic health (eHealth) technologies in practice often is lower than expected, mostly because there is no optimal fit among a technology, the characteristics of prospective users, and their context. To improve this fit, a thorough systematic development process is recommended. However, more knowledge about suitable development methods is necessary to create a tool kit that guides researchers in choosing development methods that are appropriate for their context and users. In addition, there is a need for reflection on the existing frameworks for eHealth development to be able to constantly improve them. OBJECTIVE: The two main objectives of this case study were to present and reflect on the (1) methods used in the development process of a virtual reality application for forensic mental health care and (2) development model that was used: the CeHRes Roadmap (the Centre for eHealth Research Roadmap). METHODS: In the development process, multiple methods were used to operationalize the first 2 phases of the CeHRes Roadmap: the contextual inquiry and value specification. To summarize the most relevant information for the goals of this study, the following information was extracted per method: (1) research goal, (2) explanation of the method used, (3) main results, (4) main conclusions, and (5) lessons learned about the method. RESULTS: Information on 10 methods used is presented in a structured manner. These 10 methods were stakeholder identification, project team composition, focus groups, literature study, semistructured interviews, idea generation with scenarios, Web-based questionnaire, value specification, idea generation with prototyping, and a second round of interviews. The lessons learned showed that although each method added new insights to the development process, not every method appeared to be the most appropriate for each research goal. CONCLUSIONS: Reflection on the methods used pointed out that brief methods with concrete examples or scenarios fit the forensic psychiatric patients the best, among other things, because of difficulties with abstract reasoning and low motivation to invest much time in participating in research. Formulating clear research questions based on a model's underlying principles and composing a multidisciplinary project team with prospective end users appeared to be important in this study. The research questions supported the project team in keeping the complex development processes structured and prevented tunnel vision. With regard to the CeHRes Roadmap, continuous stakeholder involvement and formative evaluations were evaluated as strong points. A suggestion to further improve the Roadmap is to explicitly integrate the use of domain-specific theories and models. To create a tool kit with a broad range of methods for eHealth development and further improve development models, studies that report and reflect on development processes in a consistent and structured manner are needed.

Identifying the Added Value of Virtual Reality for Treatment in Forensic Mental Health: A Scenario-Based, Qualitative Approach.

Background: Although literature and practice underline the potential of virtual reality (VR) for forensic mental healthcare, studies that explore why and in what way VR can be of added value for treatment of forensic psychiatric patients is lacking. Goals: This study aimed to identify (1) points of improvements in existing forensic mental health treatment of in- and outpatients, (2) possible ways of using VR that can improve current treatment, and (3) positive and negative aspects of the use of VR for the current treatment according to patients and therapists. Methods: Two scenario-based methods were used. First, semi-structured interviews were conducted with eight therapists and three patients to elicit scenarios from them. Based on these results, six scenarios about possibilities for using VR in treatment were created and presented to 89 therapists and 19 patients in an online questionnaire. The qualitative data from both methods were coded independently by two researchers, using the method of constant comparison. Results: In the interviews, six main codes with accompanying sub codes emerged. Ideas for improvement of treatment were grouped around the unique characteristics of the forensic setting, characteristics of the complex patient population, and characteristics of the type of treatment. For possibilities of VR, main codes were skills training with interaction, observation of situations or stimuli without interaction, and creating insight for others into the patient. The questionnaire resulted in a broad range of insights into potential positive and negative aspects of VR related to the current treatment, the patient, the content of a VR application, and practical matters. Conclusion: VR offers a broad range of possibilities for forensic mental health. Examples are offering training of behavioral and cognitive skills in a realistic context to bridge the gap between a therapy room and the real world, increasing treatment motivation, being able to adapt a VR application to individual patients, and providing therapists with new insights into a patient. These findings can be used to ground the development of new VR applications. Nevertheless, we should remain critical of when in the treatment process and for whom VR could be of added value.

eHealth in Treatment of Offenders in Forensic Mental Health: A Review of the Current State.

BACKGROUND: Treatment of offenders in forensic mental health is complex. Often, these in- or outpatients have low treatment motivation, suffer from multiple disorders, and have poor literacy skills. eHealth may be able to improve treatment outcomes because of its potential to increase motivation and engagement, and it can overcome the predominant one-size-fits-all approach by being tailored to individual patients. OBJECTIVE: To examine its potential, this systematic review studies the way that eHealth has been used and studied in forensic mental health and identifies accompanying advantages and disadvantages for both patients and treatment, including effectiveness. METHODS: A systematic search in Scopus, PsycINFO, and Web of Science was performed up until December 2017. Studies were included if they focused on technological interventions to improve the treatment of forensic psychiatric patients. RESULTS: The search resulted in 50 studies in which eHealth was used for treatment purposes. Multiple types of studies and technologies were identified, such as virtual reality, web-based interventions, and videoconferencing. The results confirmed the benefits of technology, for example, the acquisition of unique information about offenders, effectiveness, and tailoring to specific characteristics, but indicated that these are not fully taken advantage of. DISCUSSION: To overcome the barriers and obtain the benefits, eHealth has to have a good fit with patients and the forensic psychiatric context. It has to be seamlessly integrated in existing care and should not be added as an isolated element. To bridge the gap between the current situation and eHealth's potential, further research on development, implementation, and evaluation should be conducted.