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BackgroundCollege students are at elevated risk for developing mental health problems and face specific barriers around accessing evidence-based treatment. Web-based interventions that focus on mental health promotion and strengthening resilience represent one possible solution. Providing support to users has shown to reduce dropout in these interventions. Further research is needed to assess the efficacy and acceptability of these interventions and explore the viability of automating support. ObjectiveThis study investigated the feasibility of a new web-based resilience program based on positive psychology, provided with human or automated support, in a sample of college students. MethodsA 3-armed closed pilot randomized controlled trial design was used. Participants were randomized to the intervention with human support (n=29), intervention with automated support (n=26), or waiting list (n=28) group. Primary outcomes were resilience and well-being, respectively measured by the Connor–Davidson Resilience Scale and Pemberton Happiness Index. Secondary outcomes included measures of depression and anxiety, self-esteem, and stress. Outcomes were self-assessed through online questionnaires. Intention-to-treat and per-protocol analyses were conducted. ResultsAll participants demonstrated significant improvements in resilience and related outcomes, including an unexpected improvement in the waiting list group. Within- and between-group effect sizes ranged from small to moderate and within-group effects were typically larger for the human than automated support group. A total of 36 participants began the program and completed 46.46% of it on average. Participants were generally satisfied with the program and found it easy to use. ConclusionsFindings support the feasibility of the intervention. Preliminary evidence for the equal benefit of human and automated support needs to be supported by further research with a larger sample. Results of this study will inform the development of a full-scale trial, from which stronger conclusions may be drawn. Trial RegistrationInternational Standard Randomized Controlled Trial Number (ISRCTN) 11866034; http://www.isrctn.com/ISRCTN11866034 International Registered Report Identifier (IRRID)RR2-10.1016/j.invent.2019.100254

BackgroundPoor self-management of symptoms and psychological distress leads to worse outcomes and excess health service use in cardiovascular disease (CVD). Online-delivered therapy is effective, but generic interventions lack relevance for people with specific long-term conditions, such as cardiovascular disease. ObjectiveTo develop a comprehensive online CVD-specific intervention to improve both self-management and well-being, and to test acceptability and feasibility. MethodsInformed by the Medical Research Council (MRC) guidance for the development of complex interventions, we adapted an existing evidence-based generic intervention for depression and anxiety for people with CVD. Content was informed by a literature review of existing resources and trial evidence, and the findings of a focus group study. Think-aloud usability testing was conducted to identify improvements to design and content. Acceptability and feasibility were tested in a cross-sectional study. ResultsFocus group participants (n=10) agreed that no existing resource met all their needs. Improvements such as "collapse and expand" features were added based on findings that participants’ information needs varied, and specific information, such as detecting heart attacks and when to seek help, was added. Think-aloud testing (n=2) led to changes in font size and design changes around navigation. All participants of the cross-sectional study (10/10, 100%) were able to access and use the intervention. Reported satisfaction was good, although the intervention was perceived to lack relevance for people without comorbid psychological distress. ConclusionsWe have developed an evidence-based, theory-informed, user-led online intervention for improving self-management and well-being in CVD. The use of multiple evaluation tests informed improvements to content and usability. Preliminary acceptability and feasibility has been demonstrated. The Space from Heart Disease intervention is now ready to be tested for effectiveness. This work has also identified that people with CVD symptoms and comorbid distress would be the most appropriate sample for a future randomized controlled trial to evaluate its effectiveness.

Psychotherapy practice is a human endeavour. Research on the specific and non‐specific factors of treatment has helped crystallise its relevance and clinical impact. The challenges currently faced by the field revolve around ensuring access to evidence‐based treatments and enhancing their effectiveness. Digitally delivered formats of empirically supported treatments increase access while supporting the relevance of the treatment‐specific ingredients and the necessity for human guidance. Excitement surrounds the potential integration of novel artificial intelligence (AI) machine learning methods to advance psychotherapy effectiveness. The abundance of data in digitally delivered formats positions them well to harness the capabilities of AI. Recent work provides proof of concept in areas including detection and diagnosis, predicting outcomes, treatment adherence, remission and relapse. A potential risk emerges when applying machine learning methods, in which an overreliance on AI inferences may overshadow the human aspect of psychotherapy. The contrast is simple: we may over‐invest in the rationality and relevance of our AI inferences, blindly obeying the algorithmic counsel that may lead to unintended consequences, such as oversimplifying human complexity. This would amount to changing psychotherapy from a human‐centric to a techno‐centric endeavour, something we should steadily avoid. This perspective highlights the importance of balancing enthusiasm for AI advancements with a cautious approach. The discussion outlines the risks associated with overdependence on AI and provides reasons to avoid a scenario in which psychotherapy loses its human essence. In conclusion, the perspective suggests avenues for future research to prevent such a transformation and maintain the human‐centric nature of psychotherapy. [ABSTRACT FROM AUTHOR]

Background: Citizen science is a way to democratise science by involving groups of citizens in the research process. Clinical guidelines are used to improve practice, but their implementation can be limited. Involving patients and the public can enhance guideline implementation, but there is uncertainty about the best approaches to achieve this. Citizen science is a potential way to involve patients and the public in improving clinical guideline implementation. We aimed to explore the application of citizen science methods to involve patients and the public in the dissemination and implementation of clinical guidelines in oral health and dentistry. Methods: We developed GUIDE (GUideline Implementation in oral health and DEntistry), a citizen science online platform, using a participatory approach with researchers, oral health professionals, guideline developers and citizens. Recruitment was conducted exclusively online. The platform focused on prespecified challenges related to oral health assessment guidelines, and asked citizens to generate ideas, as well as vote and comment on other citizens' ideas to improve those challenges. Citizens also shared their views via surveys and two online synchronous group meetings. Data were collected on participant's demographics, platform engagement and experience of taking part. The most promising idea category was identified by an advisory group based on engagement, feasibility and relevance. We presented quantitative data using descriptive statistics and analysed qualitative data using inductive and deductive thematic analysis. Results: The platform was open for 6 months and we recruited 189 citizens, from which over 90 citizens actively engaged with the platform. Most citizens were over 34 years (64%), female (58%) and had a university degree (50%). They generated 128 ideas, 146 comments and 248 votes. The challenge that led to most engagement was related to prevention and oral health self‐care. To take this challenge forward, citizens generated a further 36 ideas to improve a pre‐existing National Health Service oral care prevention leaflet. Citizens discussed motivations to take part in the platform (understanding, values, self‐care), reasons to stay engaged (communication and feedback, outputs and impact, and relevance of topics discussed) and suggestions to improve future platforms. Conclusion: Citizen science is an effective approach to generate and prioritise ideas from a group of citizens to improve oral health and dental services. Prevention and oral health self‐care were of particular interest to citizens. More research is needed to ensure recruitment of a diverse group of citizens and to improve retention in citizen science projects. Patient or Public Contribution: This project was inherently conducted with the input of public partners (citizen scientists) in all key aspects of its conduct and interpretation. In addition, two public partners were part of the research team and contributed to the design of the project, as well as key decisions related to its conduct, analysis, interpretation and dissemination and are co‐authors of this manuscript. [ABSTRACT FROM AUTHOR]

Background: Tightly connected symptom networks have previously been linked to treatment resistance, but most findings come from small-sample studies comparing single responder v. non-responder networks. We aimed to estimate the association between baseline network connectivity and treatment response in a large sample and benchmark its prognostic value against baseline symptom severity and variance. Methods: N = 40 518 patients receiving treatment for depression in routine care in England from 2015–2020 were analysed. Cross-sectional networks were constructed using the Patient Health Questionnaire-9 (PHQ-9) for responders and non-responders (N = 20 259 each). To conduct parametric tests investigating the contribution of PHQ-9 sum score mean and variance to connectivity differences, networks were constructed for 160 independent subsamples of responders and non-responders (80 each, n = 250 per sample). Results: The baseline non-responder network was more connected than responders (3.15 v. 2.70, S = 0.44, p < 0.001), but effects were small, requiring n = 750 per group to have 85% power. Parametric analyses revealed baseline network connectivity, PHQ-9 sum score mean, and PHQ-9 sum score variance were correlated (r = 0.20–0.58, all p < 0.001). Both PHQ-9 sum score mean (β = −1.79, s.e. = 0.07, p < 0.001), and PHQ-9 sum score variance (β = −1.67, s.e. = 0.09, p < 0.001) had larger effect sizes for predicting response than connectivity (β = −1.35, s.e. = 0.12, p < 0.001). The association between connectivity and response disappeared when PHQ-9 sum score variance was accounted for (β = −0.28, s.e. = 0.19, p = 0.14). We replicated these results in patients completing longer treatment (8–12 weeks, N = 22 952) and using anxiety symptom networks (N = 70 620). Conclusions: The association between baseline network connectivity and treatment response may be largely due to differences in baseline score variance. [ABSTRACT FROM AUTHOR]

Background: Outcome research has highlighted the efficacy of internet-based cognitive behavioural therapy (iCBT). Some process research has examined users experiences of iCBT. Understanding the user experience provides valuable feedback to developers of internet-delivered interventions. Aim: The present study aimed to evaluate user's experiences and engagement with the design features of an internet-delivered treatment programme for anxiety. Methods: Semi-structured interviews were conducted with 7 participant users of the "Space from Anxiety" programme. A thematic analysis framework was employed to analyse the data collected. Results: Identified themes related to participants engagement and adherence with the programme material, participant's experience of personal development through interaction with the programme content and participants experience of the social features employed in the programme. Another theme investigated the various attributes or conditions necessary for internet-delivered therapy to be helpful to an individual. Conclusion: Considering the experiences of users of online interventions provides insight into what works for whom both in terms of technological features and the various skills and strategies that may compose the treatment intervention. Knowing more about what design features and strategies/components of the intervention are attractive and keep users involved can only enhance the delivery of effective internet-delivered interventions for anxiety disorders.