Physical factors that influence patients’ privacy perception toward a psychiatric behavioral monitoring system: a qualitative study

Abstract

BackgroundPsychiatric patients have privacy concerns when it comes to technology intervention in the hospital setting. In this paper, we present scenarios for psychiatric behavioral monitoring systems to be placed in psychiatric wards to understand patients’ perception regarding privacy. Psychiatric behavioral monitoring refers to systems that are deemed useful in measuring clinical outcomes, but little research has been done on how these systems will impact patients’ privacy.MethodsWe conducted a case study in one teaching hospital in Malaysia. We investigated the physical factors that influence patients’ perceived privacy with respect to a psychiatric monitoring system. The eight physical factors identified from the information system development privacy model, a comprehensive model for designing a privacy-sensitive information system, were adapted in this research. Scenario-based interviews were conducted with 25 patients in a psychiatric ward for 3 months.ResultsPsychiatric patients were able to share how physical factors influence their perception of privacy. Results show how patients responded to each of these dimensions in the context of a psychiatric behavioral monitoring system.ConclusionSome subfactors under physical privacy are modified to reflect the data obtained in the interviews. We were able to capture the different physical factors that influence patient privacy.

Health informatics publication trends in Saudi Arabia: a bibliometric analysis over the last twenty-four years

“…The study location was mostly in Saudi Arabia (57.5%, n=140). Other study locations included the United States (1.9%, n=3) [22][23][24], Malaysia (1.9%, n=3) [25][26][27], and Canada (0.8%, n=2) [28,29]. The majority of publications (35.1%, n=85) used quantitative methods, and the minority of publications (9.1%, n=22) used mixed methods.…”

“…For publications in 2000-2009, data sources used were surveys or questionnaire data [30], patient or medical data [31][32][33], clinical or health care research datasets [34], and patient or disease registries [35]. For publications in 2010-2019, more data sources were used, including surveys or questionnaire data [12,24,26,, interviews or focus groups [25,27,28,37,69,94,, patient or medical data [23,, clinical or health care research datasets [23,[143][144][145][146][147][148][149][150][151][152][153], patient or disease registries [29,67,154,155], and social media (Facebook [156,157], Twitter [158,159], Quora [22], and WhatsApp [160]) and new social media datasets [161].…”

The use and impact of surveillance-based technology initiatives in inpatient and acute mental health settings: A systematic review

“…Most studies reported data from a mix of ward types (n = 8), followed by acute wards (n = 6), low/medium secure wards (n = 5), forensic wards (n = 5) and psychiatric intensive care units (PICUs) (n = 3). Only two studies specified that they included wards with inpatients under the age of 18 [48, 63]. The remaining studies either exclusively focused on inpatient wards for adults or did not specify the age of the inpatient populations.…”

“…Thirteen studies explored CCTV/video surveillance [39,41,43,48,52,54,55,56,57,58,60,61,63]. No studies declared conflicts of interest, seven studies were rated as high quality [41,43,52,55,56,57,63], three were rated medium quality [48,58,61] and three low quality [39,54,60].…”

“…The functions of CCTV/video surveillance described in the papers included: monitoring patient behaviour [41,52,57,63] and staff behaviour [41]; monitoring who is leaving the ward [52], monitoring safety during mechanical restraint [57], reducing institutional incidents [58] and preventing violence [57].…”