A novel voice interactive sleep log: concurrent validity with actigraphy and sleep diaries

This is a preliminary validation study of a novel approach to an interactive sleep data collection platform. We compared actigraphy, paper and pencil logs, and the novel voice interactive sleep log in a sample of 17 breast cancer survivors with insomnia symptoms and also report qualitative data on acceptability. We used correlation coefficients and Bland Altman plots to evaluate convergent validity across these measures and report means for acceptability ratings. The sleep log data collected via paper and pencil vs the voice interactive measure had comparable mean values and variable validity coefficients across key sleep variables compared to actigraphy except for wake after sleep onset, where the voice-interactive system had fair concurrent validity with actigraphy. The voice interactive sleep log has several advantages over pencil and paper logs and actigraphy as it reduces patient burden, automatically calculates sleep variables, documents the timeliness of response and provides daily feedback to respondents on calculated sleep metrics.

CLINICAL TRIAL REGISTRATION

Registry: ClinicalTrials.gov; Identifier: NCT05233800.

CITATION

Lewin D, Starling CM, Zhou ES, Greenberg D, Shaw C, Arem H. A novel voice interactive sleep log: concurrent validity with actigraphy and sleep diaries. J Clin Sleep Med. 2024;20(2):309-312.

Exploring Variations in Sleep Perception: Comparative Study of Chatbot Sleep Logs and Fitbit Sleep Data

BACKGROUND

Patient-generated health data are important in the management of several diseases. Although there are limitations, information can be obtained using a wearable device and time-related information such as exercise time or sleep time can also be obtained. Fitbits can be used to acquire sleep onset, sleep offset, total sleep time (TST), and wakefulness after sleep onset (WASO) data, although there are limitations regarding the depth of sleep and satisfaction; therefore, the patient's subjective response is still important information that cannot be replaced by wearable devices.

OBJECTIVE

To effectively use patient-generated health data related to time such as sleep, it is first necessary to understand the characteristics of the time response recorded by the user. Therefore, the aim of this study was to analyze the characteristics of individuals' time perception in comparison with wearable data.

METHODS

Sleep data were acquired for 2 weeks using a Fitbit. Participants' sleep records were collected daily through chatbot conversations while wearing the Fitbit, and the two sets of data were statistically compared.

RESULTS

In total, 736 people aged 30-59 years were recruited for this study, and the sleep data of 543 people who wore a Fitbit and responded to the chatbot for more than 7 days on the same day were analyzed. Research participants tended to respond to sleep-related times on the hour or in 30-minute increments, and each participant responded within the range of 60-90 minutes from the value measured by the Fitbit. On average for all participants, the chat responses and the Fitbit data were similar within a difference of approximately 15 minutes. Regarding sleep onset, the participant response was 8 minutes and 39 seconds (SD 58 minutes) later than that of the Fitbit data, whereas with respect to sleep offset, the response was 5 minutes and 38 seconds (SD 57 minutes) earlier. The participants' actual sleep time (AST) indicated in the chat was similar to that obtained by subtracting the WASO from the TST measured by the Fitbit. The AST was 13 minutes and 39 seconds (SD 87 minutes) longer than the time WASO was subtracted from the Fitbit TST. On days when the participants reported good sleep, they responded 19 (SD 90) minutes longer on the AST than the Fitbit data. However, for each sleep event, the probability that the participant's AST was within ±30 and ±60 minutes of the Fitbit TST-WASO was 50.7% and 74.3%, respectively.

CONCLUSIONS

The chatbot sleep response and Fitbit measured time were similar on average and the study participants had a slight tendency to perceive a relatively long sleep time if the quality of sleep was self-reported as good. However, on a participant-by-participant basis, it was difficult to predict participants' sleep duration responses with Fitbit data. Individual variations in sleep time perception significantly affect patient responses related to sleep, revealing the limitations of objective measures obtained through wearable devices.

The curious case of the Zzz's

Excessive daytime sleepiness is a common presenting symptom that may present a diagnostic challenge for the sleep medicine clinician. We present a case of an adolescent female with excessive daytime sleepiness and "sleep attacks" who was evaluated using a 2-week sleep log, wrist actigraphy, baseline polysomnogram, and Multiple Sleep Latency Test. Multiple Sleep Latency Test results noted a short mean sleep latency without sleep onset rapid eye movement periods, concerning for possible central disorders of hypersomnolence. However, actigraphy data noted a habitual bedtime of midnight or later, resulting in less than recommended total sleep time for her age on weekdays with extended sleep periods on the weekends. The most unique actigraphy finding was exposure to ambient light throughout most overnight sleep periods. When actigraphy results were discussed with the patient, she revealed recent onset of severe anxiety with fear of sleeping in the dark. This case highlights the importance of thorough clinical evaluation, and careful interpretation of objective tests, when evaluating for causes of excessive daytime sleepiness.

CITATION

Dang L, Kanney ML, Hsu DP. The curious case of the Zzz's. J Clin Sleep Med. 2023;19(5):1009-1012.

The Impact of Cognitive Behavioral Therapy for Insomnia on Sleep Log and Actigraphy Outcomes in People with Multiple Sclerosis: A Secondary Analysis

PURPOSE

While studies indicate cognitive behavioral therapy for insomnia (CBT-I) improves self-report sleep outcomes from questionnaires in people with multiple sclerosis (MS), it is unclear if CBT-I improves outcomes from a sleep log or sleep assessed objectively via actigraphy in people with MS. This study aimed to determine if CBT-I improves sleep log and actigraphy outcomes in individuals with MS.

PATIENTS AND METHODS

Twenty-five participants (Mage = 53.04, SD= 10.90) were included in this secondary analysis of data from a pilot randomized control study to assess the feasibility and treatment effect of CBT-I in individuals with MS. Participants were asked to maintain a sleep log and wear an actigraph for a week at baseline and post-intervention. Participants were randomized into one of three groups (CBT-I, active control, or one-time brief education control group). One-way ANOVAs were used to assess for group differences and within group change in sleep latency, sleep efficiency (SE), time in bed, total sleep time (TST), wake after sleep onset, variability of SE, and variability of TST.

RESULTS

CBT-I resulted in an increase in sleep efficiency (SE) and decrease in time in bed (TIB) and variability of SE from the sleep log. The CBT-I group also experienced a decrease in TIB and total sleep time (TST) from actigraphy. The active control group demonstrated an increase in variability of SE from actigraphy.

CONCLUSION

This study indicates that individuals with MS may experience an improvement in sleep log and actigraphy sleep outcomes following CBT-I, but findings need to be replicated in a larger prospective study. The decrease in TST from actigraphy mirrors results from prior studies.

Subjective sleep measurement: comparing sleep diary to questionnaire

PURPOSE

The sleep diary is the gold standard of self-reported sleep duration, but its comparability to sleep questionnaires is uncertain. The purpose of this study was to compare self-reported sleep duration between a sleep diary and a sleep questionnaire and to test whether sleep-related disorders were associated with diary-questionnaire differences in sleep duration.

PARTICIPANTS AND METHODS

We compared self-reported sleep duration from 5,432 questionnaire-sleep diary pairs in a longitudinal cohort of 1,516 adults. Participants reported sleep information in seven-day sleep diaries and in questionnaires. Research staff abstracted average sleep durations for three time periods (overall; weekday; weekend) from diaries and questionnaires. For each time period, we evaluated diary-questionnaire differences in sleep duration with Welch's two-sample t-tests. Using linear mixed effects regression, we regressed overall diary-questionnaire sleep duration difference on several participant characteristics: reporting any insomnia symptoms, having sleep apnea, sex, body mass index, smoking status, Short Form-12 Physical Health Composite Score, and Short Form-12 Mental Health Composite Score.

RESULTS

The average diary-reported overall sleep duration (7.76 hrs) was longer than that of the questionnaire (7.07 hrs) by approximately 41 mins (0.69 hrs, 95% confidence interval: 0.62, 0.76 hrs). Results were consistent across weekday- and weekend-specific differences. Demographic-adjusted linear mixed effects models tested whether insomnia symptoms or sleep apnea were associated with diary-questionnaire differences in sleep duration. Insomnia symptoms were associated with a 17 min longer duration on the diary relative to the questionnaire (β=0.28 hrs, 95% confidence interval: 0.22, 0.33 hrs), but sleep apnea was not significantly associated with diary-questionnaire difference. Female sex was associated with greater diary-questionnaire duration differences, whereas better self-reported health was associated with lesser differences.

CONCLUSION

Diaries and questionnaires are somewhat disparate methods of assessing subjective sleep duration, although diaries report longer duration relative to questionnaires, and insomnia symptoms may contribute to greater perceived differences.

Differences Between Sleep Logs and Actigraphy Combined With Electroencephalography in Adults With Sleep Disturbances

BACKGROUND

Actigraphy plus single-channel electroencephalography (EEG) has a high agreement with polysomnography and is considered a simple method for monitoring sleep at home. No studies, however, have evaluated its agreement with sleep logs.

PURPOSE

A sleep log was compared to a single-channel EEG in adults with sleep disturbances. The determinants of the agreement between the two recording methods were explored.

METHOD

This prospective comparison substudy included 71 participants aged 22-67 years sampled from a previous study of nonpharmacological therapy for sleep disturbances. The participants concurrently used a sleep log and a single-channel EEG machine for 6 days to measure their sleep at home. Total sleep time (TST) and sleep onset latency (SOL) were compared.

RESULTS

Correlations between measurements were .43 for TST ( p < .001) and .30 ( p < .01) for SOL. Bland-Altman analysis revealed that the mean bias between methods was 81.54 min (standard deviation [ SD] = 66.72 min) for TST and 5.58 min ( SD = 25.38 min) for SOL. SDs for both TST and SOL were higher for the sleep log than for EEG. A multivariate linear regression model demonstrated that age (standardized coefficient β = .42, p = .001) was a significant predictor of the mean difference in SOL measurements, accounting for 13.7% of the total variance in the mean difference.

CONCLUSION

Sleep log and single-channel EEG sleep measures are distinct from one another, and age predicts the mean level of disagreement between the two measures in adults with sleep disturbances.