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1.
  • Dahlin, Mats, 1975-, et al. (author)
  • Internet-based self-help using automatic messages and support on demand for generalized anxiety disorder : an open pilot study
  • 2020
  • In: Digital Psychiatry. - : Taylor & Francis. - 2575-517X. ; 3:1, s. 12-19
  • Journal article (peer-reviewed)abstract
    • Generalized anxiety disorder (GAD) is a disabling and often chronic condition. Internet-based treatments for GAD have been shown to be effective, but many studies include weekly contact with a therapist with the aim to increase adherence and clinical outcomes. The current study evaluated a less therapist-intensive alternative: support on demand and automatic messages. Thirty-three participants with GAD went through a self-help program targeting excessive worry. Treatment lasted 9 weeks and consisted of seven modules. Participants received short messages with reminders and encouragement. Therapist support was given when asked for. The intervention led to significant and large within-group effects on the primary outcome, Penn State Worry Questionnaire (PSWQ; Cohen’s d = 1.17), as well as on secondary outcomes such as Generalized Anxiety Disorder Questionnaire-IV (GAD-Q-IV; Cohen’s d = 2.71) and Patient Health Questionaire-9 (PHQ-9; Cohen’s d = 1.05). The exception was a small effect on quality of life (d = −0.34). Twenty-four (74.9%) were satisfied with the treatment and one dropped out. Therapist support was used by 65.6%. Limitations include lack of control condition and a small sample. While preliminary, the findings suggest that self-guided internet interventions can work and be acceptable when automated messages and support on demand is provided.
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2.
  • Gremyr, Andreas, et al. (author)
  • A learning health system for people with severe mental illness : a promise for continuous learning, patient coproduction and more effective care
  • 2019
  • In: Digital Psychiatry. - : Taylor & Francis. - 2575-517X. ; 2:1, s. 8-13
  • Journal article (peer-reviewed)abstract
    • A Learning Health System (LHS) promotes the patient being at the very center of his or her care. Patient coproduction of care in an LHS is enabled by a focus on improving outcomes through the use of tools and visualizations that use the harnessed knowledge obtained from every previous treatment of similar patients. Interest in the concept of LHS is growing, and there are promising results in real-world applications. Almost no research has focused on LHSs for severe mental illness (LHS4SMI). By using a user-centered system design approach, a persona and use-case scenarios were created to illustrate how schizophrenia care could be co-produced in an LHS compared to standard care in a non-LHS. The illustration highlight increased participation through decisions informed by all treatments for all similar patients through the use of user interfaces that support continuous evaluation, increased understanding, compensation for cognitive impairment and participation of next of kin in the care process. We propose that an LHS4SMIs like schizophrenia has enormous potential in enabling continuous learning, patient coproduction, and more effective care.
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3.
  • Maron, Eduard, et al. (author)
  • Manifesto for an international digital mental health network
  • 2019
  • In: Digital Psychiatry. - 2575-517X. ; :1
  • Journal article (peer-reviewed)abstract
    • Current mental health services across the world remain expert-centric and are based on traditional workflows, mostly using impractical and ineffective electronic record systems or even paper-based documentation. The international network for digital mental health (IDMHN) is comprised of top-level clinicians, regulatory and ICT experts, genetic scientists, and support organizations. The IDMHN has been formed to enable the implementation of digital innovations in clinical practice, hereby facilitating the transformation of current mental health services to be more personalized and more responsive to patients and healthcare needs. This consensus statement summarizes the consortium’s vision and strategy for further development of digital mental Health.
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