Clinically significant discrepancies between sleep problems assessed by standard clinical tools and actigraphy

Blytt, Kjersti Marie; Bjorvatn, Bjørn; Husebø, Bettina S.; Flo, Elisabeth

doi:10.1186/s12877-017-0653-7

Cited by 31 publications

(41 citation statements)

References 48 publications

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“…The NPI-NH sleep item comes with a description similar to the NPI, followed by six follow-up questions (including "other nighttime behaviors"). Previous studies have suggested a cut-off product score of frequency (1-4) multiplied by severity (1-3) of ≥4 to define the presence of sleep disturbance on this single item from the NPI-NH (25,41). In contrast to the SDI, the NPI-NH followup questions do not ask about excessive daytime sleep (SDI item 7) or if the patient wake up during the night without engaging in any specific behaviors (SDI item 4).…”

Section: Measurementsmentioning

confidence: 99%

“…Actigraphs are wrist-worn devices that can measure activity across several days, and even weeks (42). The actigraphs were placed on the dominant wrist, in accordance with previous studies in this population (8,25). Each 1-min epoch was scored as either sleep or wake by the Actiware 6.0.9 (Philips Respironics) software, based on activity from the two epochs immediately preceding and following the relevant epoch.…”

Section: Measurementsmentioning

confidence: 99%

“…Activity data were collected for 7 days and patients had to complete at least five nights of recordings to be included in the analyses. We initially planned to score the actigraphic recordings manually, in line with a premediated scoring protocol (25). However, it was challenging to determine the start and end of the rest intervals.…”

Section: Measurementsmentioning

confidence: 99%

“…The event buttons were not consistently pressed by the nursing home staff. Additionally, many dementia patients have severely fragmented sleep, thus, there were rarely clear indications of bedtime and rise time in the actograms, normally indicated by a marked and sustained decrease/increase in activity and/or light levels (25,43). These challenges are common in this population, and researchers have typically solved these issues by setting a fixed rest interval [e.g., (8,14,(44)(45)(46)(47)(48)(49)(50)(51)(52)(53)].…”

Section: Measurementsmentioning

confidence: 99%

“…Unfortunately, research suggests that nursing home staff often provide unreliable and inaccurate reports of their patients' sleep when not using adequate instruments (25)(26)(27). For example, using the sleep items of the Cornell Scale of Depression in Dementia (CSDD) and the Neuropsychiatric Inventory (NPI) in a nursing home population, Blytt et al (25) found that staff reported significantly fewer sleep problems than measured by actigraphy. Their study suggested that disturbed sleep may go largely undetected in the nursing home population when measured by staff rated instruments with only one or a few items.…”

Section: Introductionmentioning

confidence: 99%

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An Actigraphy-Based Validation Study of the Sleep Disorder Inventory in the Nursing Home

et al. 2020

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Background: Disrupted sleep is common among nursing home patients with dementia and is associated with increased agitation, depression, and cognitive impairment. Detecting and treating sleep problems in this population are therefore of great importance, albeit challenging. Systematic observation and objective recordings of sleep are time-consuming and resource intensive and self-report is often unreliable. Commonly used proxy-rated scales contain few sleep items, which affects the reliability of the raters' reports. The present study aimed to adapt the proxy-rated Sleep Disorder Inventory (SDI) to a nursing home context and validate it against actigraphy.Methods: Cross-sectional study of 69 nursing home patients, 68% women, mean age 83.5 (SD 7.1). Sleep was assessed with the SDI, completed by nursing home staff, and with actigraphy (Actiwatch II, Philips Respironics). The SDI evaluates the frequency, severity, and distress of seven sleep-related behaviors. Internal consistency of the SDI was evaluated by Cronbach's alpha. Spearman correlations were used to evaluate the convergent validity between actigraphy and the SDI. Test performance was assessed by calculating the sensitivity, specificity, and predictive values, and by ROC curve analyses. The Youden's Index was used to determine the most appropriate cut-off against objectively measured sleep disturbance defined as <6 h nocturnal total sleep time (TST) during 8 h nocturnal bed rest (corresponding to SE <75%). Results:The SDI had high internal consistency and convergent validity. Three SDI summary scores correlated moderately and significantly with actigraphically measured TST and wake-after-sleep-onset. A cut-off score of five or more on the SDI summed product score (sum of the products of the frequency and severity of each item) yielded the best sensitivity, specificity, predictive values, and Youden's Index.Hjetland et al. Sleep Disorder Inventory ValidationConclusion: We suggest a clinical cut-off for the presence of disturbed sleep in institutionalized dementia patients to be a SDI summed product score of five or more. The results suggest that the SDI can be clinically useful for the identification of disrupted sleep when administered by daytime staff in a nursing home context. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT03357328.

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Section: Measurementsmentioning

confidence: 99%

Section: Measurementsmentioning

confidence: 99%

Section: Measurementsmentioning

confidence: 99%

Section: Measurementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Actigraphy-Based Validation Study of the Sleep Disorder Inventory in the Nursing Home

et al. 2020

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Psychosis symptoms in nursing home residents with and without dementia—Cross‐sectional analyses from the COSMOS study

Habiger

Achterberg

Flo

et al. 2019

Int J Geriat Psychiatry

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Objective To investigate the characteristics of nursing home residents with psychosis and the association with potential underlying factors, such as pain, sleep disturbances, and antipsychotic medication. Method Five hundred forty‐five residents with and without dementia from 67 Norwegian nursing home units were included in the cross‐sectional analyses. Psychosis was the main outcome measure in our study; other outcome measures include quality of life (QoL), activities of daily living (ADL) function, cognitive function, pain, and antipsychotic medication. Results One hundred twelve residents had one or more symptoms of psychosis, and compared with residents without psychosis, they had lower QoL (p < 0.001), ADL function (p = 0.003), and cognitive functioning (p = 0.001). Adjusted logistic regression analyses showed that psychosis was associated with the prevalence of pain (OR: 3.19; 95% CI, 1.94‐5.24), sleep disturbances (OR: 4.51; 95% CI, 2.91‐6.99), and total number of medication (OR: 1.10; 95% CI, 1.03‐1.17). Residents with psychosis but without antipsychotic medication had better QoL (p = 0.005) compared with residents receiving any antipsychotics. Conclusion Psychosis in NH residents is associated with pain, sleep disturbances, and number of medications. Residents with psychosis have poor QoL, although better QoL was observed among those who did not use antipsychotic medication.

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The minimum clinically important difference on the sleep disorders inventory for people with dementia

Webster¹,

Martin²,

Livingston³

2020

Int J Geriat Psychiatry

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Objectives: Sleep disturbances in dementia causes distress to people with dementia and their family carers and are associated with care home admission. The Sleep Disorders Inventory (SDI) is a validated questionnaire of sleep disturbances in dementia often used to measure treatment effectiveness, but the minimum clinically important difference (MCID) is unknown. Methods: We triangulated three investigative methods to determine the MCID of the SDI. Using data on SDI from a randomised controlled trial (RCT) with 62 participants in an intervention for sleep disorders in dementia, we (1) calculated distribution-based values where MCID = 0.33 of a SD (SD) (2) an anchor based approach using quality of life (measured using DEMQOL-Proxy) as an anchor. We also employed a Delphi consensus process asking 12 clinicians, sleep researchers and family carers to rate which changes on vignettes were equivalent to a MCID. Results: We found that 0.33 SD in the SDI = 4.86. Reduction in SDI total score was not significantly correlated with improvement in DEMQOL-Proxy (Pearson's correlation = −0.01; P = 0.96) score. The Delphi consensus required two rounds to reach a consensus and concluded that changes equivalent to three points on the SDI equated to the MCID. Conclusions: Taking into account both the distribution-based values and the Delphi process we used a whole number at the midpoint and judged the minimum clinically

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Clinically significant discrepancies between sleep problems assessed by standard clinical tools and actigraphy

Cited by 31 publications

References 48 publications

An Actigraphy-Based Validation Study of the Sleep Disorder Inventory in the Nursing Home

An Actigraphy-Based Validation Study of the Sleep Disorder Inventory in the Nursing Home

Psychosis symptoms in nursing home residents with and without dementia—Cross‐sectional analyses from the COSMOS study

The minimum clinically important difference on the sleep disorders inventory for people with dementia

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