Digital Technology In Psychiatry: Expectations, Barriers And Understanding Of Clinicians (Preprint)
BACKGROUND Digital technology has the potential to transform psychiatry, but adoption has been limited. The proliferation of telepsychiatry during COVID increases urgency of optimizing technology for clinical practice. Understanding clinician attitudes and preferences is crucial to effective implementation and patient benefit. OBJECTIVE Our objective was to elicit clinician perspectives on emerging digital technology. METHODS Clinicians in a large psychiatry department (inpatient and outpatient) were invited to complete an online survey about their attitudes towards digital technology in practice, focusing on implementation, clinical benefits, and expectations about patients’ attitudes. The survey consisted of 23 questions that could be answered on either a 3-point or 5-point Likert scale. We report frequencies and percentages of responses. RESULTS 139 clinicians completed the survey. They represented a variety of years-experience, credentials and diagnostic sub-specialties (response rate of 69.5%). Eighty-three percent (n=116) stated that digital data could improve their practice. Twenty-three percent of responders reported that they had viewed patients’ profiles on social media (n=32). Among anticipated benefits, clinicians rated symptom self-tracking (n=101, 72.7%) as well as clinical intervention support (n=90, 64.7%) as most promising. Among anticipated challenges, clinicians mostly expressed concerns over greater time demand (n=123, 88.5%) and whether digital data would be actionable (n=107, 77%). Ninety-five percent (n=132) of clinicians expected their patients to share digital data. CONCLUSIONS Overall, clinicians reported a positive attitude toward the use of digital data to improve patient outcomes but also highlight significant barriers that implementation need to overcome. Although clinicians’ self-reported attitudes about digital technology may not necessarily translate into behavior, results suggest that technologies that reduce clinician burden and are easily interpretable have the greatest likelihood of uptake.