The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Direct Comparison of Two New Actigraphs and Polysomnography in Children and Adolescents
Open accessAbstract
STUDY OBJECTIVES: To evaluate the validity and reliability of 2 new models of commercially available actigraphs compared to polysomnography for children and adolescents. DESIGN AND SETTING: Subjects concurrently wore the Ambulatory Monitoring Inc. Motionlogger Sleep Watch (AMI) and the Phillips Respironics Mini-Mitter Actiwatch-2 (PRMM) while undergoing overnight polysomnography (PSG) in a pediatric sleep laboratory housed in a tertiary care children's hospital. PARTICIPANTS: 115 youth (59 girls, 56 boys), ages 3-18 years (mean 8.8 years, SD 4.4 years). MEASUREMENTS: Outcome variables were total sleep time (TST), wake after sleep onset (WASO), and sleep efficiency (SE). Epoch-by-epoch comparisons were made between the 2 devices and PSG to determine sensitivity, specificity, and accuracy. Agreement between the 2 devices was determined with t-tests and the Bland-Altman concordance technique. Different algorithms/sensitivities, developmental age groups, and sleep disordered breathing (SDB) status were also examined. RESULTS: For both device brands, sensitivity (0.89-0.97), specificity (0.54-0.77), and accuracy (0.87-0.90) were similar to previous reports. Notably, compared to PSG, both device brands significantly overestimated WASO, while the AMI device also significantly underestimated TST. Inter-device comparison of the 2 brands found poor agreement for TST, WASO, and SE. Agreement with PSG differed depending on the scoring algorithm (AMI) or sensitivity setting (PRMM), as well as across developmental age group and sleep disordered breathing (SDB) status. CONCLUSIONS: Similar to previous reports, both new actigraph brands were found to have good sensitivity (to detect sleep), but poorer specificity (to detect wake). Study results also suggest that researchers should adjust the scoring algorithm/sensitivity depending on a study's design (e.g., young children vs. adolescents, healthy children vs. youth with SDB). Further, inter-device reliability was poor, suggesting the need for caution when comparing results across studies that use different brands of actigraphic devices.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT
Martin Bland, J., & Altman, D. (1986) · The Lancet · doi:10.1016/s0140-6736(86)90837-8 · Cited by 47,965
Statistical methods for assessing agreement between two methods of clinical measurement
Bland, J. M., & Altman, D. G. (2010) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2009.10.001 · Cited by 5,220
The Role of Actigraphy in the Study of Sleep and Circadian Rhythms
Ancoli-Israel, S., Cole, R., Alessi, C., Chambers, M., Moorcroft, W., & Pollak, C. P. (2003) · Sleep · doi:10.1093/sleep/26.3.342 · Cited by 2,751
The role and validity of actigraphy in sleep medicine: an update
Sadeh, A. (2011) · Sleep Medicine Reviews · doi:10.1016/j.smrv.2010.10.001 · Cited by 1,415
Cited by
Marino, M., Li, Y., Rueschman, M. N., Winkelman, J. W., Ellenbogen, J. M., Solet, J. M., Dulin, H., Berkman, L. F., & Buxton, O. M. (2013) · Sleep · doi:10.5665/sleep.3142 · Cited by 1,056
Wearable Sleep Technology in Clinical and Research Settings
DE ZAMBOTTI, M., CELLINI, N., GOLDSTONE, A., COLRAIN, I. M., & BAKER, F. C. (2019) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000001947 · Cited by 564
Natural Sleep and Its Seasonal Variations in Three Pre-industrial Societies
Yetish, G., Kaplan, H., Gurven, M., Wood, B., Pontzer, H., Manger, P. R., Wilson, C., McGregor, R., & Siegel, J. M. (2015) · Current Biology · doi:10.1016/j.cub.2015.09.046 · Cited by 395
Quante, M., Kaplan, E. R., Cailler, M., Rueschman, M., Wang, R., Weng, J., Taveras, E. M., & Redline, S. (2018) · Nature and Science of Sleep · doi:10.2147/nss.s151085 · Cited by 298
The Sleep of the Ring: Comparison of the ŌURA Sleep Tracker Against Polysomnography
de Zambotti, M., Rosas, L., Colrain, I. M., & Baker, F. C. (2019) · Behavioral Sleep Medicine · doi:10.1080/15402002.2017.1300587 · Cited by 287
Changes in Children’s Sleep Duration on Food Intake, Weight, and Leptin
Hart, C. N., Carskadon, M. A., Considine, R. V., Fava, J. L., Lawton, J., Raynor, H. A., Jelalian, E., Owens, J., & Wing, R. (2013) · Pediatrics · doi:10.1542/peds.2013-1274 · Cited by 276
de Zambotti, M., Baker, F. C., Willoughby, A. R., Godino, J. G., Wing, D., Patrick, K., & Colrain, I. M. (2016) · Physiology & Behavior · doi:10.1016/j.physbeh.2016.03.006 · Cited by 222
Fonseca, P., Weysen, T., Goelema, M. S., Møst, E. I. S., Radha, M., Lunsingh Scheurleer, C., van den Heuvel, L., & Aarts, R. M. (2017) · SLEEP · doi:10.1093/sleep/zsx097 · Cited by 148
Kang, S.-G., Kang, J. M., Ko, K.-P., Park, S.-C., Mariani, S., & Weng, J. (2017) · Journal of Psychosomatic Research · doi:10.1016/j.jpsychores.2017.03.009 · Cited by 146
Evaluation of a consumer fitness-tracking device to assess sleep in adults
de Zambotti, M., Claudatos, S., Inkelis, S., Colrain, I. M., & Baker, F. C. (2015) · Chronobiology International · doi:10.3109/07420528.2015.1054395 · Cited by 127
Lunsford-Avery, J. R., LeBourgeois, M. K., Gupta, T., & Mittal, V. A. (2015) · Schizophrenia Research · doi:10.1016/j.schres.2015.03.013 · Cited by 119
Sustained benefits of delaying school start time on adolescent sleep and well-being
Lo, J. C., Lee, S. M., Lee, X. K., Sasmita, K., Chee, N. I. Y. N., Tandi, J., Cher, W. S., Gooley, J. J., & Chee, M. W. L. (2018) · Sleep · doi:10.1093/sleep/zsy052 · Cited by 114
Godino, J. G., Wing, D., de Zambotti, M., Baker, F. C., Bagot, K., Inkelis, S., Pautz, C., Higgins, M., Nichols, J., Brumback, T., et al. (2020) · PLoS ONE · doi:10.1371/journal.pone.0237719 · Cited by 107
“[37] In that study, authors analyzed in-lab overnight sleep in 115 children and adolescents (3–18 y old).”
BackgroundMethodConcurrent Validity of Wearable Activity Trackers Under Free-Living Conditions
Brooke, S. M., An, H.-S., Kang, S.-K., Noble, J. M., Berg, K. E., & Lee, J.-M. (2017) · Journal of Strength and Conditioning Research · doi:10.1519/jsc.0000000000001571 · Cited by 79
Liang, Z., & Chapa-Martell, M. A. (2019) · JMIR mHealth and uHealth · doi:10.2196/13384 · Cited by 76
Hamilton, J. L., Tsypes, A., Zelazny, J., Sewall, C. J. R., Rode, N., Merranko, J., Brent, D. A., Goldstein, T. R., & Franzen, P. L. (2023) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13651 · Cited by 71
Monitoring sleep with a smartphone accelerometer
NATALE, V., DREJAK, M., ERBACCI, A., TONETTI, L., FABBRI, M., & MARTONI, M. (2012) · Sleep and Biological Rhythms · doi:10.1111/j.1479-8425.2012.00575.x · Cited by 73
McCrae, C. S., Chan, W. S., Curtis, A. F., Nair, N., Deroche, C. B., Munoz, M., Takamatsu, S., McLean, D., Davenport, M., Muckerman, J. E., et al. (2021) · Autism · doi:10.1177/1362361320949078 · Cited by 72
Lee, P. H., & Suen, L. K. P. (2017) · Sleep And Breathing · doi:10.1007/s11325-016-1406-0 · Cited by 60
De Bernardi Rodrigues, A. M., da Silva, C. D. C., Vasques, A. C. J., Camilo, D. F., Barreiro, F., Cassani, R. S. L., Zambon, M. P., Antonio, M. Â. R. D. G. M., Geloneze, B., & for the Brazilian Metabolic Syndrome Study (BRAMS) Investigators (2016) · JAMA Pediatrics · doi:10.1001/jamapediatrics.2015.4365 · Cited by 47
Alterations in Daytime and Nighttime Activity in Piglets after Focal and Diffuse Brain Injury
Olson, E., Badder, C., Sullivan, S., Smith, C., Propert, K., & Margulies, S. S. (2016) · Journal of Neurotrauma · doi:10.1089/neu.2015.4085 · Cited by 16
Metadata
- Authors
- Meltzer, L. J., Walsh, C. M., Traylor, J., & Westin, A. M. L.
- Venue
- SLEEP
- Publisher
- Oxford University Press (OUP)
- Published
- 2012-01-01
- Volume
- 35
- Issue
- 1
- Pages
- 159-66
- ISSN
- 0161-8105 (ISSN-L)
- 1550-9109
- OpenAlex
- W2046104003
- Cited by
- 332
- References
- 4
- FWCI
- 11.86
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
