(Cost-) Effectivity of a personalized e-health intervention for patients with psychiatric disorders on waiting lists for treatment- a randomized controlled trial.

Access to timely mental health care in the Netherlands has become increasingly
challenging, with waiting times steadily increasing in recent years. Extended
waiting times for treatment in mental health care can be harmful due to
increased severity of symptoms, poorer treatment engagement and outcomes,
reduced quality of life, and an elevated risk of self-harm or suicide. Existing
literature suggests that unguided e-health interventions can be helpful and
could provide rapid access to mental healthcare during the waiting period,
without further burdening our healthcare professionals, facilities, or
caregivers. We aim to enhance the effectiveness of this intervention through
personalized allocation of e-health modules. We hypothesize that personalized
e-health is not only more effective but also less costly from both healthcare
and societal perspectives compared to care as usual (CAU).

The objective of this project is to test the clinical and cost effectiveness of
utilizing the assessment of transdiagnostic dynamics of symptoms to provide a
personalized e-health treatment intervention as an automated tool during the
waiting list period before the psychiatric intake takes place. By implementing
this approach, we aim to address the current gap in providing timely and
effective interventions during the waiting period, ultimately improving patient
outcomes and optimizing the utilization of mental healthcare resources.

A Randomized Controlled Trial (RCT) with two trial arms will be conducted: the
intervention condition and the treatment as usual waiting list condition. Both
trial arms will include repeated measures during the waiting period. Data will
be collected by means of validated psychometric questionnaires. Psychometric
questionnaires are completed at the moment of referral (baseline), and every
month (for the e-health group) or every 3 months (for the TAU group) during the
waiting time (for a maximum of 1 year), and at the moment of intake.
Additionally, participants will be asked to install the Behapp app at the start
of the study. This app will passively collect data from the participant's
smartphone throughout the entire inclusion period (digital phenotyping).
Participants in the intervention arm will gain access to a selection of modules
that are available at the Therapieland website. Participants in the
intervention condition will also be asked to complete a revised daily
ecological momentary assessment (EMA) for a period of four weeks. The EMA data
will assess the main trajectories of psychiatric symptomatology over time.

The intervention arm will receive online access to a selection of existing
online eHealth modules provided by Therapieland. Personalization will be
achieved by employing both innovative and traditional methods to identify
symptoms that are most influential for each individual patient, followed by
tailored recommendations of eHealth modules.

The intervention group will undergo a monthly SQ-48 questionnaire (5 minutes)
and the TAU group every 3 months, with an additional questionnaire (3 minutes)
administered at the beginning and endpoint. The intervention arm will also be
asked to complete a brief smartphone questionnaire daily (which takes
approximately 2 minutes) through the m-Path app for the initial 4 weeks.
The intervention arm benefits from timely access to e-health modules, which
could aid in understanding and self-management of symptoms. Data collected
through daily EMA during the initial 4 weeks together with the results of the
SQ-48 is used to select the modules fitting the specific symptom profile of the
participant. Potential risks of e-health have not been extensively studied, but
few and mild risks have been described in the literature. Thus, this study
carries low burden and risk, with evidence suggesting potential benefits from
the intervention.