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| Name | Class |
|---|---|
| Western Norway University of Applied Sciences | OTHER |
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This qualitative feasibility study investigates a digital health app designed for patients who are frequently admitted to the psychiatric acute ward, to facilitate crisis support outside of office hours to avoid unnecessary readmissions, as well as self-harm. As this is a novel app to be implemented in an already existing service, key uncertainties regarding the intervention content and its delivery needs to be addressed before potentially conducting a full-scale trial, or, alternatively, to inform further intervention refinement. Such uncertainties are appropriate to explore in a feasibility study according to the Medical Research Council (MRC) framework for the development and evaluation of complex interventions.
There is a need to investigate whether the app is acceptable and useful to the patients using it, and to the healthcare providers who respond to it. There is also a need to know whether the healthcare providers responding to the app find the task manageable. The context in which the staff are to deliver the intervention, i.e. the in-bed ward, may be subject to different barriers, such as a staff shortage due to sick leave and heavy workload in the ward. Such barriers are essential to identify ahead of possible future trials in other contexts.
The present study is a part of the larger Revolving Door Project, a collaborative service innovation project between a university hospital and two municipalities in Norway. The revolving door project aims to create a more sustainable service to prevent unnecessary hospital readmissions, reducing the strain repeated rehospitalisations can produce and also reducing financial costs. By collecting valuable insights from key stakeholders, critical points in the healthcare services have been identified and outlined in the "emergency loop". This loop illustrates how the current service solution can worsen the revolving door problem by failing to offer timely and adequate help and ultimately risking an escalation of the patient's difficulties. To address these issues, a new healthcare service has been developed to meet the needs of the stakeholders. The service is aimed at individuals who are repeatedly readmitted and discharged from the psychiatric acute ward, who have emotionally unstable traits (not necessarily diagnosis specific), where previously attempted measures have proven insufficient and where there is an insecurity in the help apparatus as to how to help the patient.
The Muli-service The muli-app is a part of a new service, called The Muli-service. This service comprises a collaborative multidisciplinary team (Muli-team), with representatives from municipal mental health services, local psychiatric hospital, psychiatric acute ward, and police. This team coordinates admissions and collaborates with individuals to improve communication and cooperation between services and patients. As such, the Muli-service isn't a new treatment but an intervention meant to complement and enhance existing treatment and mental health provision.
The collaborative part of the service is already established. In addition, the revolving door project has developed the Muli-app, which is the focus of the present feasibility study. A Person-Based Approach has been used to guide the development the app, where stakeholders have been consulted iteratively. The app was created based on stakeholders reported needs, to provide them with an alternative means to seek help outside of office hours, which is a typical time for emergency hospital admissions. The goal is to provide timely and adequate help and thus prevent further escalation of the situation. This aligns with recommendations in the European Psychiatric Association (EPA) guidance on the quality of mental health services.
The Muli-app At the point of download, the app consists of a few predefined sets of emotion regulation exercises and contact information for emergency services. Tailored content (i.e crisis plan and crisis measures) will be written in collaboration between patient and therapist/Muli-contact. Possible crisis measures for each individual patient will be discussed and agreed upon in the Muli-team in advance, ensuring that these measures are in fact feasible. The patient will be presented with the options, and from this the patient and therapist agree upon the most fitting crisis measures to be put into the app. This is communicated back to the Muli-team.
Patients admitted into the Muli-service will be informed of the app through their Muli-contact in the collaborative team and receive an invitation to participate in this study. Study participants who consent to participation will be set up with a user profile in the Muli app and receive a text message from the developers informing them of how to access the app on their own smartphones. The Muli-app will be available to download in app-stores but won't work unless an existing profile is connected to the patient. study participants will receive training from their Muli-contact on how to use the app.
One in-patient ward at the local psychiatric hospital responds when patients activate the contact-based measures through the app outside of office hours. The ward will be provided smart-phones connected to the app-software, notifying them when a patient makes contact through the app. For every evening and night shift (and all shifts during weekends), one healthcare worker will be assigned to carry the Muli-phone and reply when a patient activates the contact-based functions.
The staff who respond at the ward all have bachelor's degrees as registered nurses or learning disability nurses, while some are specialized mental health nurses. Staff have received training in principles of Mentalization-Based Therapy by a licensed psychologist, which will be applied when study participants make contact. Staff will also receive training on the app technology and protocol by a Muli representative.
As this intervention is meant to complement existing treatment, no limitations are made regarding the type of treatment study participants receive parallel to the feasibility testing of the app.
The present feasibility study addresses several aims. To assess acceptability, perceived usefulness, implementation feasibility and fidelity, narrative data will be collected through qualitative interviews with participants. App usage data and information regarding the number of hospital admissions and emergency services during the trial phase will be collected at the end of trial, to identify possible change and enable further contextualization of the narrative data. The findings may bring forth hidden aspects of how the intervention works in practice.
Data collection methods Patient perspectives will be monitored using semi-structured interviews (N=5). These interviews will be conducted in a safe and undisturbed location chosen by the users themselves or digitally if they prefer. Each interview is expected to last approximately one hour and will be audio recorded.
Three months after the app has been tested, focus group interviews with staff (N=20) will be conducted. These interviews will take place in a suitable location at the district psychiatric center. All interviews will be transcribed into text, excluding identifying information. All audio files will be deleted after transcription.
Quantitative data on patient app usage will be collected through the Muli app, with the patient's consent given via the app. Data on the number of readmissions and/or contacts with emergency services will be gathered through interviews with patients.
Any adverse events during trial phase, will be monitored by the Muli-service team and reported to research team on a weekly basis.
Data analysis Qualitative data from in-depth interviews and focus group interviews will be analyzed using reflexive thematic analysis. Quantitative and qualitative data will be triangulated and analyzed together to gain a broader understanding of the findings.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Muli-app | Other | The feasibility study will be conduced using a concurrent mixed methods design, where quantitative and qualitative data are collected simultaneously. The trial will be run in two neighbouring municipalities in Norway that are affiliated with the same university hospital. To allow for sufficient time to engage with the intervention, the two trial-phases will be run, each lasting 3 months. For patients, the intervention will be tested in real-life situations, wherever they lead their everyday lives. Qualitative data will be collected through individual interviews in the patients' preferred settings. App-usage data will be collected through the app-platform. For staff, qualitative data will be collected through focus group interviews at the local psychiatric hospital tasked with responding when patients make contact through the app. Suitable meeting rooms will be provided to ensure privacy. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Muli-app | Behavioral | The Muli-app is designed after a traffic-light model, indicating different levels of severity of emotional distress and need for help. Green parts represent self-management measures that can be taken to try to regulate themselves (coping plan, write notes for their next appointment , and exercises to reduce emotional distress.) Yellow parts represent contact-based measures when the patient needs someone to talk to outside office hours, to de-escalate emotional distress and to avoid further crisis. This function connects study participants with mental health professionals at the local psychiatric hospital outside office hours (chat, phone or videocall). When the patient activates this function, the staff at the local hospital have 30 minutes to reply. The red part also activates contact with the local psychiatric hospital, but with a need of acute response, activating acute measures stated in the coping plan, such as access to an open bed in the municipality. |
| Measure | Description | Time Frame |
|---|---|---|
| Acceptability of the digital mental health intervention for patients | Acceptability refers to the degree to which patients feel that the digital health service is appropriate, comfortable, and aligned with their needs and values. Focus: How patients perceive the app in terms of relevance, usability, and emotional response. Data Source: Semi-structured interviews. Research Questions:
| From enrollment to the end of trial phase, 3 months. |
| Acceptability of the digital mental health intervention for healthcare providers | Acceptability refers to the extent to which the digital intervention fits within clinical routines, professional standards, and ethical expectations. Focus: How healthcare workers perceive the app's fit with their workflow, values, and patient care. Data Source: Focus group interviews. Research Questions:
| From enrollment to end of trial phase, 3 months |
| Perceived usefulness of the digital mental health intervention for patients | Usefulness is understood as the degree to which the intervention helps users achieve their goals or solve a problem. Focus: Whether the app is seen as beneficial in supporting patient self-management. Data Source: Interviews with patients Research Questions:
| From enrollment to the end of trial phase, 3 months. |
| Perceived usefulness of the intervention for healthcare providers | Usefulness is understood as the extent to which the digital service contributes to improved care delivery, decision-making, or communication with patients. Focus: Whether the app is seen as beneficial in supporting clinical care. Data Source: Focusgroup interviews. Research Questions:
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| Measure | Description | Time Frame |
|---|---|---|
| Number of contacts with health services | Number of readmissions and/or contacts with emergency services during the feasibility trial phase. Data source: interviews with patients. | From enrollment to the end of trial, 3 months |
| Implementation feasibility of the digital intervention |
| Measure | Description | Time Frame |
|---|---|---|
| Exploration of unintended negative effects | Qualitative assessment of any adverse or unintended effects reported by participants during interviews or focus groups. Unintended effects could be: emotional distress, increased dependence or avoidance, misinterpretation or misuse, privacy and trust concerns. These will be monitored on a weekly basis through the Muli-service (treatment team). | From enrollment to end of trial phase, 3 months |
Inclusion Criteria patients:
Inclusion criteria, healthcare workers:
- staff members at the local psychiatric hospital who respond to patient contacts made through the app
Exclusion criteria, staff:
- staff members at the local psychiatric hospital who rare not tasked with responding to patient contacts made through the app.
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Ane A Buer, Phd candidate | Contact | +47 45054749 | anabu@hvl.no | |
| Mette Senneseth, Phd | Contact | +47 41208207 | mette.senneseth@helse-bergen.no |
| Name | Affiliation | Role |
|---|---|---|
| Mette Senneseth, Phd | Centre for research and education in forensic psychiatry, Haukeland Univeristy Hospital. | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Haukeland University Hospital | Bergen | Norway |
To protect the integrity and anonymity of study participants, IPD will not be shared due to the sensitive nature of the data being collected from a very limited sample size.
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The present study is a feasibility study of a digital mental health intervention, "the Muli-app". The app is developed through an iterative process with different stakeholders, peers and service users, and will be tested with 5 service users (patients) in this feasibility study.
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| From enrollment to the end of trial phase, 3 months. |
Implementation feasibility is understood as the extent to which the digital intervnetion can be practically and successfully delivered in a real-world setting, considering technical, organizational, and contextual factors. Focus: Technical, organizational and contextual factors affecting the delivery and use of the app. Data Source: focus group interviews with healthcare workers (implementation staff) Research Questions:
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| From enrollment to the end of trial phase, 3 months. |
| Fidelity to protocol | Fidelity to protocol is understood as the degree to which the digital intervention is delivered and used as originally intended, according to the planned procedures, content, and timing. Focus: Whether the app is used as intended and what deviations occur. Data Source: Interviews (with patients) and focus-group interviews (with health care providers), and app-usage logs Research Questions:
| From enrollment to the end of trial phase, 3 months |