The Precision in Psychiatry (PIP) study: Testing an internet-based methodology for accelerating research in treatment prediction and personalisation

Abstract

Background: Evidence-based treatments for depression exist but not all patients benefit from them. Efforts to develop predictive models that can assist clinicians in allocating treatments are ongoing, but there are major issues with acquiring the volume and breadth of data needed to train these models. We examined the feasibility, tolerability, patient characteristics, and data quality of a novel protocol for internet-based treatment research in psychiatry that may help advance this field.

Methods: A fully internet-based protocol was used to gather repeated observational data from patient cohorts receiving internet-based cognitive behavioural therapy (iCBT) (N = 600) or antidepressant medication treatment (N = 110). At baseline, participants provided > 600 data points of self-report data, spanning socio-demographics, lifestyle, physical health, clinical and other psychological variables and completed 4 cognitive tests. They were followed weekly and completed another detailed clinical and cognitive assessment at week 4. In this paper, we describe our study design, the demographic and clinical characteristics of participants, their treatment adherence, study retention and compliance, the quality of the data gathered, and qualitative feedback from patients on study design and implementation.

Results: Participant retention was 92% at week 3 and 84% for the final assessment. The relatively short study duration of 4 weeks was sufficient to reveal early treatment effects; there were significant reductions in 11 transdiagnostic psychiatric symptoms assessed, with the largest improvement seen for depression. Most participants (66%) reported being distracted at some point during the study, 11% failed 1 or more attention checks and 3% consumed an intoxicating substance. Data quality was nonetheless high, with near perfect 4-week test retest reliability for self-reported height (ICC = 0.97).

Conclusions: An internet-based methodology can be used efficiently to gather large amounts of detailed patient data during iCBT and antidepressant treatment. Recruitment was rapid, retention was relatively high and data quality was good. This paper provides a template methodology for future internet-based treatment studies, showing that such an approach facilitates data collection at a scale required for machine learning and other data-intensive methods that hope to deliver algorithmic tools that can aid clinical decision-making in psychiatry.

Keywords: Antidepressant; Big data; Internet-based methodology; Internet-delivered cognitive behavioural therapy; Mental health treatments; Treatment outcomes; Treatment prediction; Treatment response.

Fig. 1

An overview of study design. Participants who gave informed consent and met our inclusion/exclusion criteria were invited to complete the baseline assessment, comprising cognitive tests, and a variety of self-report questions concerning participants’ treatment, clinical symptoms, psychosocial factors, lifestyle, and socio-demographics. Participants were sent an invitation for a weekly check-in assessment on a scheduled basis for 3 consecutive weeks, which tracked any changes in clinical symptoms and treatment adherence. Participants completed the study with a fifth and final assessment after 4 weeks of treatment, which was an abbreviated version of the baseline assessment

Fig. 2

Participant flow chart (CONSORT chart). Once they completed the assessment at each study timepoint, participants were progressed onto the next stage of the study. Participants were progressed if they completed the assessments fully at each study stage. If due to technical errors participants were not able to complete specific components of their assessments, it was deemed appropriate to progress them onto the next stage of the study or be financially compensated

Fig. 3

Recruitment Rates. Number of participants recruited from each arm from February 2019 to July 2021. The antidepressant arm launched first, initiating recruitment in February 2019. Paid recruitment efforts were focused on a 13-month period from that date to March 2020, when the iCBT arm commenced. The iCBT arm was initiated in March 2020 via Aware Ireland, and in August 2020 recruitment began through Talking Therapies, Berkshire, South London, U.K

Fig. 4

Baseline clinical symptom score distribution of depression (QIDS) and impairment (WSAS) for participants in the iCBT and antidepressant arm

Fig. 5

Clinical change in QIDS-SR. (A) Pre-post 4-week QIDS-SR score reduction. Both treatment arms experienced significant decreases in depression score measured by QIDS-SR from the baseline to the final assessment. (B) Effect sizes and statistical significance of clinical symptom reduction in both treatment arms. All clinical symptoms reduced significantly from the baseline to final assessment in both treatment arms except for schizotypy, eating disorder symptoms, and impulsivity in the antidepressant arm. (C) Percentages of early response, response, and remission achieved by participants in the iCBT arm at each study timepoint. (D) Percentages of early response, response, and remission achieved by participants in the antidepressant arm at each study timepoint

Fig. 6

Distributions of overlapping completions dates of each study section for (A) the iCBT arm and (B) the antidepressant arm. Day ‘0’ depicts treatment start date

Fig. 7

Data Quality indicators. Correlation of height (in inches) was gathered at the baseline and final assessments in (A) the Antidepressant arm, r = 0.98 and (B) the iCBT arm, r = 0.97. Participants who failed at least 1 attention check are coloured grey. Internal consistency of the self-report questionnaires (Cronbach’s alpha) for the (C) Antidepressant arm and the (D) iCBT arm