Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| Center on Information and Communication Technologies | OTHER |
Not provided
Not provided
Not provided
Not provided
Introduction: Poor sleep quality is common in most older adults. Because of the progressive aging of the population in Spain, there are more and more nursing-home and day centers, which give care to older adults. However, the attention focused on some difficulty related to sleep has not been thoroughly investigated. The use of wearable devices, which measure some parameters such as the sleep stages, can help to determine the influence of quality sleep in the health state among nursing-home residents.
Objective: To analyze the sleep quality and its influence on the daily life of nursing-home residents through the use of assessment tools and Xiaomi MiBand 2.
Methods and analysis: This is an observational and analytical study whose objective is the observation and registration of variables of a determined population without the intervention of the researcher and establishing relations between association variables and causality. It is also considered as longitudinal since the follow-up of some of the characteristics of the population will be performed during a period of time. The study is set in a nursing-home in A Coruña (Spain). Xiaomi MiBand 2 will be used to measure biomedical parameters and different assessment tools will be administered to participants for evaluating their sleep quality, cognitive state, and daily functioning.
For the statistical analysis, T-Test and ANOVA analysis will be used to compare the means between variables. Also, a Chi-Square test will be used to study the association of qualitative variables. Finally, a multivariate analysis of logistic regression will be performed to determine the variables associated with the presence of the dichotomous variable of interest.
Introduction: In the aging, some disturbance in the health state, as poor sleep quality or a sleep disorder, are likely to appear. The disturbances in sleep stages can influence cognitive state, quality of life, and daily functioning. The progressive aging of the population has led to an increase in resources for the direct care of older people, with a 60.9% of increase in recent years in Spain. Yet, the sleep role in the health state and the activities of daily life from older adults in nursing-home and daily centers hasn't been thoroughly researched. On this issue, wearable devices, which were developed in the last years, monitor the sleep stages and the activity that people perform.
Objective: The main objective of this study will be to analyze the sleep quality and its influence on the daily life of nursing-home residents through the use of assessment tools and Xiaomi MiBand 2. Secondary objectives are 1) To know the situation of older people in a nursing-home, recording general data, results of assessment instruments and data obtained from Xiaomi MiBand 2; 2) To explore and determine the quality of life and daily functioning of the participating older people; 3) To determine the level of the cognitive state of the participating older people; 4) To analyze the level of physical activity and the quality of sleep, as well as the factors linked to both constructs, in the older adults who are in a residence; 5) to promote the use of technological devices in the daily life of older adults, especially for the empowerment and management of their health.
Methods and Analysis: It is proposed to carry out an observational and analytical study, whose objective is the observation and registration of variables of a determined population without the intervention of the researcher and establishing relations between association variables and causality. Likewise, this study is considered as longitudinal since the follow-up of the characteristics of this population will be carried out during a period of time (variables will be followed for 1 year). Specifically, the physical activity and the sleep of the participating population will be continuously registered and monitored throughout the entire study. The study will be developed with the resident population in a nursing-home in A Coruña (Spain). To measure biomedical parameters from users, it will be used the Xiaomi MiBand 2. Besides, different assessment tools will be administered to the participants related to self-perception of sleep quality, cognitive state, and daily functioning.
For the statistical analysis, quantitative variables will be expressed as mean and standard deviation, while qualitative variables will be expressed as absolute value and percentage.
To compare means between them, the Student t-test will be used, and for the multiple comparisons of means, the analysis of variance will be used. This design is applied when the data are paired, that is when they come from subjects with variables measured before and after treatment. This test makes it possible to determine whether the differences between the values of both variables are statistically significant or whether they are differences due to chance. To study the association of the qualitative variables, the Chi-square test will be used.
On the other hand, to determine the variables that are associated or not with the presence of the dichotomous variable of interest, a multivariate analysis of logistic regression will be performed, using as a dependent variable the presence or not of the event of interest, and as covariates, the variables that in the bivariate analysis are associated with the presence of said event or are clinically relevant.
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Nursing-home residents | Older adults in a nursing-home who report a self-perception of poor sleep quality |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Xiaomi MiBand2 | Device | Recording of sleep and activity data to study their association with age. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Light sleep | Measured by Xiaomi MiBand 2 | Until the completion of the study (around 1 year) |
| Deep sleep | Measured by Xiaomi MiBand 2 | Until the completion of the study (around 1 year) |
| Awake time | Measured by Xiaomi MiBand 2 | Until the completion of the study (around 1 year) |
| Measure | Description | Time Frame |
|---|---|---|
| Number of steps | Measured by Xiaomi MiBand 2 | Until the completion of the study (around 1 year) |
| Distance (meters) | Measured by Xiaomi MiBand 2 |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Older adults in a nursing-home who reported a poor sleep quality self-perception.
Not provided
| Name | Affiliation | Role |
|---|---|---|
| Javier Pereira, PhD | Universidade da Coruña | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Universidade da Coruña | A Coruña | 15006 | Spain |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 20175759 | Background | Bonanni E, Tognoni G, Maestri M, Salvati N, Fabbrini M, Borghetti D, Di Coscio E, Choub A, Sposito R, Pagni C, Iudice A, Murri L. Sleep disturbances in elderly subjects: an epidemiological survey in an Italian district. Acta Neurol Scand. 2010 Dec;122(6):389-97. doi: 10.1111/j.1600-0404.2010.01324.x. | |
| 29332687 | Background |
| Label | URL |
|---|---|
| Life Expectancy in Spain | View source |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Socio-demographic questionnaire | Other | Self-made questionnaire to be administered at the beginning of the study with the following personal data: age, gender, marital status, residential environment, mobility aids, educational level, occupation, retirement type, socioeconomic status, medical records, treatment. |
|
| EuroQol-5D-5L | Other | Quality of life questionnaire to be administered at the beginning and completion of the study with the following information: severity index, social value index for each health condition. Subjective evaluation of health status from 0 to 100. |
|
| Mini mental State Examination | Other | Questionnaire to be administered at the beginning and completion of the study that measures cognitive impairment. |
|
| Tinetti Scale | Other | Physical test to be administered at the beginning and completion of the study that measures gait and balance of the participants. |
|
| Barthel Index | Other | Questionnaire to be administered at the beginning and completion that evaluates the level of independence in basic activities of life. |
|
| Pittsburgh Sleep Quality Assessment (PSQI) | Other | Questionnaire to be administered whose outcome is the perceived quality, quantity and efficient of sleep. To be given at the beginning and completion of the study. |
|
| Until the completion of the study (around 1 year) |
| Duration (minutes) | Measured by Xiaomi MiBand 2 | Until the completion of the study (around 1 year) |
| Calories | Measured by Xiaomi MiBand 2 | Until the completion of the study (around 1 year) |
| Quality of life self-perception | EuroQol 5D-5L measures the quality of life and health status. This questionnaire is made up by three elements: A descriptive system divided into 5 dimensions (mobility, personal care, daily activities, pain/discomfort and anxiety/depression);the levels of Severity considered by the person assessed: 1-Absence of problems, 2-Presence of mild problems, 3-Presence of moderate problems, 4-Presence of severe problems or 5- Presence of severe problems; and the Visual Analogue Scale (VAS) extends from 0 (the worst imaginable state of health), to 100, (the best imaginable state of health). | Baseline and completion of the study (two months). |
| Cognitive state | Measured by the Mini Mental State Examination (MMSE) test. This tool is used to detect the presence of cognitive impairment. It presents 6 values for each section (Orientation, Fixation, Concentration and calculation, Memory and Language and construction) and their final score. The test has a maximum score of 35 points, with different levels of cognitive impairment from the following scores: Geriatric patients: cut-off point 23/24 (a score lower than 23 implies the existence of cognitive impairment, whereas a score higher than 24 means the absence of cognitive impairment). Non-geriatric patients: cut-off point 27/28 (a score lower than 27 implies the existence of cognitive impairment, whereas a score higher than 28 means the absence of cognitive impairment). | Baseline and completion of the study (two months). |
| Independence on Activities of daily life | Measured by Barthel Activities of Daily Living (ADL) Index. This tool allows the measurement of the variable "performance in daily life activities". It presents 11 values: one for each item and one for the final score. The person's performance is evaluated based on these scores: < 20: total dependence, 20-40: severe dependence, 45-55: moderate dependence, and 60 or more: slight dependence. | Baseline and completion of the study (two months). |
| Sleep quality | Measured by the Pittsburgh Sleep Quality Index (PSQI). This questionnaire consists of 24 items, of which 19 are answered by the person him/herself and the other 5 by his/her roommate. This tool analyzes the quantity, quality, duration, latency and efficiency of sleep. The total score of the PSQI scale is the result of adding 7 components. Each component is scored from 0 to 3. The total value of this tool can vary from 0 to 21 points, where a score equal to or less than 5 points corresponds to the absence of difficulties in sleep. | Baseline and completion of the study (two months). |
| Gait and balance | Measured by the Tinetti scale. This tool is used to determine the falling risk of an older person. The tool is divided into two parts, the assessment of balance on the one hand and the assessment of gait on the other. The range of scores goes from 0 (most impairment) to 2 (represents independence) for each item. The maximum score for the balance test is 16 points, and 12 points for the gait test, so the total score is 28. The higher the final score, the better the patient's functionality and the lower the risk of a fall. | Baseline and completion of the study (two months). |
| Matthews KA, Patel SR, Pantesco EJ, Buysse DJ, Kamarck TW, Lee L, Hall MH. Similarities and differences in estimates of sleep duration by polysomnography, actigraphy, diary, and self-reported habitual sleep in a community sample. Sleep Health. 2018 Feb;4(1):96-103. doi: 10.1016/j.sleh.2017.10.011. Epub 2017 Dec 13. |
| 26618039 | Background | El-Amrawy F, Nounou MI. Are Currently Available Wearable Devices for Activity Tracking and Heart Rate Monitoring Accurate, Precise, and Medically Beneficial? Healthc Inform Res. 2015 Oct;21(4):315-20. doi: 10.4258/hir.2015.21.4.315. Epub 2015 Oct 31. |
| 26424155 | Background | Brown DT, Westbury JL, Schuz B. Sleep and agitation in nursing home residents with and without dementia. Int Psychogeriatr. 2015 Dec;27(12):1945-55. doi: 10.1017/S1041610215001568. Epub 2015 Oct 2. |
| 27132701 | Background | Shelgikar AV, Anderson PF, Stephens MR. Sleep Tracking, Wearable Technology, and Opportunities for Research and Clinical Care. Chest. 2016 Sep;150(3):732-43. doi: 10.1016/j.chest.2016.04.016. Epub 2016 Apr 29. |
| 25199910 | Background | Chen JH, Waite L, Kurina LM, Thisted RA, McClintock M, Lauderdale DS. Insomnia symptoms and actigraph-estimated sleep characteristics in a nationally representative sample of older adults. J Gerontol A Biol Sci Med Sci. 2015 Feb;70(2):185-92. doi: 10.1093/gerona/glu144. Epub 2014 Sep 8. |
| 29141837 | Background | Puri A, Kim B, Nguyen O, Stolee P, Tung J, Lee J. User Acceptance of Wrist-Worn Activity Trackers Among Community-Dwelling Older Adults: Mixed Method Study. JMIR Mhealth Uhealth. 2017 Nov 15;5(11):e173. doi: 10.2196/mhealth.8211. |
| 25312049 | Background | Kim M, Yoshida H, Sasai H, Kojima N, Kim H. Association between objectively measured sleep quality and physical function among community-dwelling oldest old Japanese: A cross-sectional study. Geriatr Gerontol Int. 2015 Aug;15(8):1040-8. doi: 10.1111/ggi.12396. Epub 2014 Oct 14. |
| 28479556 | Background | Rohne M, Boysen ES, Ausen D. Wearable and Mobile Technology for Safe and Active Living. Stud Health Technol Inform. 2017;237:133-139. |
| 29650506 | Background | Xie J, Wen D, Liang L, Jia Y, Gao L, Lei J. Evaluating the Validity of Current Mainstream Wearable Devices in Fitness Tracking Under Various Physical Activities: Comparative Study. JMIR Mhealth Uhealth. 2018 Apr 12;6(4):e94. doi: 10.2196/mhealth.9754. |
| 23273670 | Background | Valenza MC, Cabrera-Martos I, Martin-Martin L, Perez-Garzon VM, Velarde C, Valenza-Demet G. Nursing homes: impact of sleep disturbances on functionality. Arch Gerontol Geriatr. 2013 May-Jun;56(3):432-6. doi: 10.1016/j.archger.2012.11.011. Epub 2012 Dec 27. |
| 29397315 | Background | Bernaola-Sagardui I. Validation of the Barthel Index in the Spanish population. Enferm Clin (Engl Ed). 2018 May-Jun;28(3):210-211. doi: 10.1016/j.enfcli.2017.12.001. Epub 2018 Feb 4. No abstract available. English, Spanish. |
| 3944402 | Background | Tinetti ME. Performance-oriented assessment of mobility problems in elderly patients. J Am Geriatr Soc. 1986 Feb;34(2):119-26. doi: 10.1111/j.1532-5415.1986.tb05480.x. No abstract available. |
| 26163057 | Background | Mollayeva T, Thurairajah P, Burton K, Mollayeva S, Shapiro CM, Colantonio A. The Pittsburgh sleep quality index as a screening tool for sleep dysfunction in clinical and non-clinical samples: A systematic review and meta-analysis. Sleep Med Rev. 2016 Feb;25:52-73. doi: 10.1016/j.smrv.2015.01.009. Epub 2015 Feb 17. |
| 27163822 | Background | Li H, Jia J, Yang Z. Mini-Mental State Examination in Elderly Chinese: A Population-Based Normative Study. J Alzheimers Dis. 2016 May 7;53(2):487-96. doi: 10.3233/JAD-160119. |
| 29768372 | Background | Nieto-Riveiro L, Groba B, Miranda MC, Concheiro P, Pazos A, Pousada T, Pereira J. Technologies for participatory medicine and health promotion in the elderly population. Medicine (Baltimore). 2018 May;97(20):e10791. doi: 10.1097/MD.0000000000010791. |
| 36060611 | Derived | Concheiro-Moscoso P, Groba B, Martinez-Martinez FJ, Miranda-Duro MDC, Nieto-Riveiro L, Pousada T, Pereira J. Use of the Xiaomi Mi Band for sleep monitoring and its influence on the daily life of older people living in a nursing home. Digit Health. 2022 Aug 29;8:20552076221121162. doi: 10.1177/20552076221121162. eCollection 2022 Jan-Dec. |
| Residential statistics: distribution of centers and nursing-home places by provinces | View source |
| Euroqol group | View source |
| ID | Term |
|---|---|
| D060825 | Cognitive Dysfunction |
| ID | Term |
|---|---|
| D003072 | Cognition Disorders |
| D019965 | Neurocognitive Disorders |
| D001523 | Mental Disorders |
Not provided
Not provided
| ID | Term |
|---|---|
| D000073216 | Mental Status and Dementia Tests |
| ID | Term |
|---|---|
| D009483 | Neuropsychological Tests |
| D011581 | Psychological Tests |
| D004191 | Behavioral Disciplines and Activities |
Not provided
Not provided