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Table 2 Pre-admission participant characteristics and secondary measures for observational sub-study

From: Feasibility of a stepped wedge cluster RCT and concurrent observational sub-study to evaluate the effects of modified ward night lighting on inpatient fall rates and sleep quality: a protocol for a pilot trial

Construct Tool Description Frequency of data collection
Pre-admission sleep Epworth Sleepiness Scale To explore whether any reported insomnia or sleep fragmentation is new or pre-existing, we will administer the Epworth Sleepiness Scale (ESS). The ESS is a widely used and valid 8-item self-administered instrument for measuring for excessive daytime sleepiness [78]. Excessive daytime sleepiness is associated with a range of disorders and has been associated with falls in certain older groups [79]. Initial interview only (day 0)
Vision impairment Impact of Visual Impairment Scale As participant visual status would influence the benefit derived from an environmental lighting solution we will ask participants to self-rate the functional impact of any visual impairment using the Impact of Visual Impairment Scale (IVIS). The IVIS is a widely cited and validated brief five-item instrument [80], which measures impact of vision impairment in terms of difficulties with simple tasks. Individual IVIS items are suited to older people in the inpatient setting and measure constructs relevant to study aims. As above.
Hearing impairment Hearing Handicap Inventory for the Elderly—Screening The presence of hearing impairment is of secondary interest to contextualise data on causes of sleep disruption as patients with hearing impairment may be less affected by environmental noise than those patients with unimpaired hearing. We will measure the functional impact of hearing impairment among study participants by using the Hearing Handicap Inventory for the Elderly—Screening (HHIE-S). The HHIE-S is a short ten-item measure of the social, emotional and functional impacts of hearing impairment rather than a definitive measure of the degree of hearing impairment [81]. However, as a self-report measure, it has demonstrated excellent reliability and specificity in detecting the level of impact of hearing loss [82]. As above.
Self-reported causes for disruptions to sleep Interview questions formulated by investigative team. Sleep disruptions can occur due to multiple factors in addition to light levels. Therefore, we will ask patients to what degree their sleep was disrupted by specific causes (rated on a 7-point Likert-type scale ranging from ‘Never’ to ‘Constantly’). Initial interview (day 0) and repeated on days 3, 7, and 12 Maximum of three follow-up interviews, unless patient is discharged or moved to another room prior to day 12. Follow-up data collection will occur ±1 day to accommodate for weekends and public holidays.
The specific items are ‘Pain or Discomfort’, ‘Anxiety and Thoughts’, ‘Feeling unwell’, ‘People talking in your room’, ‘Alarms and sounds from medical devices’, ‘Sounds made by other patients’, ‘Bright lights being left on overnight’, ‘Bright lights being switch on while you sleep’, ‘Staff providing care to you’, ‘Staff providing care to others’ and ‘Volume of someone else’s television’.
The current 11 items represent a refinement over a previous version that was developed after a review of the hospital sleep literature and modified following with admitted patients in the prior (unpublished) modelling research conducted by Chari S et al. to inform the present pilot RCT.
Functional status 5-item Barthel Index We will measure patient functional status using the 5-item Barthel Index [83] to capture any variations in functional status as this would influence the interpretation of mobility data collected through continuous direct monitoring. The Barthel Index is a widely used, valid and accepted tool for screening and assessing independence in activities of daily living (ADL) in geriatric settings, including older hospitalised patients. As above.
Satisfaction with the room environment Multiple choice question and free-text To evaluate overall participant satisfaction with the physical environment of the room and bathroom, we will ask participants to rate their level of satisfaction on a 5-point Likert-type scale ranging from ‘Very satisfied’ to ‘Very Dissatisfied’. We will ask participants to suggest potential improvements to the physical environment that could help patients to feel more confident to move about safely in their room and bathroom, to sleep better or to assist patients in any other way. As above.
Participant light dosage Philips Actiwatch 2—integrated light sensor The inbuilt light sensor will enable measurement of dosage of ambient white light over a 24-h period. We will set the sampling rate to one measurement every 30 s. Continuous measurement
(commenced at initial interview and continued for period of follow-up
Overnight maximum lighting levels and variation in patient room and toilet. HOBO U12-012 Light Data Logger As the modified lighting will be installed both inside the patient room and attached toilet, we will monitor variations in overnight lighting levels using a data logger (Onsetcomp HOBO U12-012) mounted on the wall in the patient room and toilet. The HOBO U12-012 data logger is a high-frequency, high-resolution device capable of a measuring range between 1 and 3000 lumens/square foot. As the Actiwatch sensor will be the primary measure of participant white light dosage, we will affix the data logger outside the immediate patient bedside environment (outside the area circumscribed by patient privacy curtains) in order to measure overall variation in room lighting profile. We will set the sampling rate to one measurement every 30 s. As above.
Frequency with which toilet doors are opened and closed overnight Onsetcomp HOBO UX90-001—State Change Data logger In order to understand whether participants may have been exposed to the modified lighting environment within the toilet overnight, we will log the times of door opening and closing. This will be done through an unobtrusive door mounted data logger that measures contact with a magnetic latch (Onsetcomp HOBO UX90-001). Thus, all state change events (door opening and closing) will be captured. The HOBO UX90-001 is a high-capacity data logger appropriate to measuring simple state changes and will allow us to contextualise activity levels at night. As above.