Termination of short term melatonin treatment in children with delayed Dim Light Melatonin Onset: Effects on sleep, health, behavior problems, and parenting stress

2011 ◽  
Vol 12 (9) ◽  
pp. 875-879 ◽  
Author(s):  
Annette van Maanen ◽  
Anne Marie Meijer ◽  
Marcel G. Smits ◽  
Frans J. Oort
Keyword(s):  
Health Behavior ◽  
Behavior Problems ◽  
Parenting Stress ◽  
Short Term ◽  
Sleep Health ◽  
Melatonin Treatment ◽  
Dim Light Melatonin Onset ◽  
Dim Light

Melatonin and sleep effects on health, behavior problems and parenting stress

2011 ◽  
Vol 9 (3) ◽  
pp. 165-171 ◽  
Author(s):  
Annette VAN MAANEN ◽  
Anne Marie MEIJER ◽  
Marcel G. SMITS ◽  
Frans J. OORT
Keyword(s):  
Health Behavior ◽  
Behavior Problems ◽  
Parenting Stress

Sensor-Based Estimation of Dim Light Melatonin Onset Using Features of Two Time Scales

2021 ◽  
Vol 2 (3) ◽  
pp. 1-15
Author(s):  
Cheng Wan ◽  
Andrew W. Mchill ◽  
Elizabeth B. Klerman ◽  
Akane Sano
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Light Exposure ◽  
Biological Activities ◽  
Second Step ◽  
Sampled Data ◽  
Dim Light Melatonin Onset ◽  
Dim Light ◽  
Using Data ◽  
Mean Square Errors

Circadian rhythms influence multiple essential biological activities, including sleep, performance, and mood. The dim light melatonin onset (DLMO) is the gold standard for measuring human circadian phase (i.e., timing). The collection of DLMO is expensive and time consuming since multiple saliva or blood samples are required overnight in special conditions, and the samples must then be assayed for melatonin. Recently, several computational approaches have been designed for estimating DLMO. These methods collect daily sampled data (e.g., sleep onset/offset times) or frequently sampled data (e.g., light exposure/skin temperature/physical activity collected every minute) to train learning models for estimating DLMO. One limitation of these studies is that they only leverage one time-scale data. We propose a two-step framework for estimating DLMO using data from both time scales. The first step summarizes data from before the current day, whereas the second step combines this summary with frequently sampled data of the current day. We evaluate three moving average models that input sleep timing data as the first step and use recurrent neural network models as the second step. The results using data from 207 undergraduates show that our two-step model with two time-scale features has statistically significantly lower root-mean-square errors than models that use either daily sampled data or frequently sampled data.

Clinical efficacy of dim light melatonin onset testing in diagnosing delayed sleep phase syndrome

2009 ◽  
Vol 10 (5) ◽  
pp. 549-555 ◽  
Author(s):  
Shadab A. Rahman ◽  
Leonid Kayumov ◽  
Ekaterina A. Tchmoutina ◽  
Colin M. Shapiro
Keyword(s):  
Clinical Efficacy ◽  
Sleep Phase ◽  
Dim Light Melatonin Onset ◽  
Delayed Sleep Phase Syndrome ◽  
Delayed Sleep Phase ◽  
Dim Light ◽  
Delayed Sleep

The Dim Light Melatonin Onset as a Marker for Orcadian Phase Position

1989 ◽  
Vol 6 (1) ◽  
pp. 93-102 ◽  
Author(s):  
Alfred J. Lewy ◽  
Robert L. Sack
Keyword(s):  
Dim Light Melatonin Onset ◽  
Dim Light

Ambulatory monitoring in humans: a new method to objectively assess circadian phase as compared with dim light melatonin onset (DLMO)

2013 ◽  
Vol 14 ◽  
pp. e79
Author(s):  
M. Bonmati-Carrion ◽  
B. Middleton ◽  
V. Revell ◽  
D. Skene ◽  
A. Rol ◽  
...  
Keyword(s):  
Ambulatory Monitoring ◽  
New Method ◽  
Circadian Phase ◽  
Dim Light Melatonin Onset ◽  
Dim Light

scholarly journals Motherhood in Complex Families

2016 ◽  
Vol 39 (1) ◽  
pp. 245-270 ◽  
Author(s):  
Paula Fomby
Keyword(s):  
Parenting Stress ◽  
Father Involvement ◽  
The United States ◽  
Short Term ◽  
Biological Father ◽  
Boundary Ambiguity ◽  
Kin Support ◽  
Using Data ◽  
Biological Fathers ◽  
Poor Relationship

Families formed through multipartner fertility, where children with a common biological mother were conceived by different biological fathers, represent a growing share of all families in the United States. Using data from four waves of the Fragile Families Child and Wellbeing Study ( N = 3,366), I find that women who have engaged in multipartner fertility are more likely to experience parenting stress and depression compared with mothers whose children share the same biological father. Mothers’ depression is explained in the short term by poor relationship quality with the father of her prior children and in the longer term by indicators of boundary ambiguity in complex families. Mothers’ parenting stress was only weakly explained by variation in perceived kin support, father involvement, or boundary ambiguity.

scholarly journals 0039 The Clinical Utility of Dim Light Melatonin Onset in Treatment of Delayed Sleep-Wake Phase Disorder: Preliminary Findings

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A16-A16
Author(s):  
L Swanson ◽  
J Arnedt ◽  
K DuBuc ◽  
T de Sibour ◽  
H Burgess
Keyword(s):  
Sleep Onset ◽  
Onset Time ◽  
Sleep Diary ◽  
Double Blind ◽  
Exogenous Melatonin ◽  
Research Award ◽  
Dim Light Melatonin Onset ◽  
Wrist Actigraphy ◽  
Dim Light ◽  
Delayed Sleep

Abstract Introduction Delayed sleep-wake phase disorder (DSWPD) is common, debilitating, and challenging to treat. In an ongoing randomized trial, we are comparing exogenous melatonin treatment outcomes in DSWPD participants for whom dim light melatonin onset (DLMO) is measured objectively vs. estimated. Methods Thus far, 13 participants (27±6 years old, 67% female) have completed a randomized, controlled, double-blind 4-week trial of 0.5 mg of exogenous melatonin timed to either 3 h before measured DLMO (M-DLMO, n = 6) or 3 h before DLMO estimated at 2 h before average sleep onset time based on at least 7 days of wrist actigraphy and sleep diary (E-DLMO, n = 7). All participants met International Classification of Sleep Disorders-3 diagnostic criteria for DSWPD and were otherwise healthy. Participants completed 4 weekly treatment sessions with a blinded psychologist; time of melatonin administration and bed-rise schedule were advanced up to 1 h/week. A validated home saliva collection kit measured DLMO in all participants. Between-group t-tests and Hedges’ g effect sizes (ES) were calculated at post-treatment for the following outcomes: DLMO; Pittsburgh Sleep Quality Index (PSQI) global score; Morningness-Eveningness Questionnaire (MEQ); and the actigraphy parameters sleep efficiency (SE) and clock time of sleep onset and offset. A paired-sample t-test compared the measured vs. estimated DLMO at baseline. Results The M-DLMO group had a 65±88 mins DLMO advance vs. 27±30 mins in the E-DLMO group (ES=0.51 p=.381). PSQI scores were similar between groups (M-DLMO=6.67±2.06, E-DLMO=7.1± 1.57, ES=-0.24, p=.646), as were MEQ scores (M-DLMO=43±4.98, E-DLMO=48±12.72, ES=-0.47, p=.387). Sleep onset time (M-DLMO=0:32±1:02, E-DLMO=0:31±1:38, ES=0.01, p=.98) and offset time (M-DLMO=8:05±1:03, E-DLMO=8:08±2:14, ES=-0.02, p=.968) were similar between the groups, although sleep was more efficient in M-DLMO vs. E-DLMO (84%±3% vs. 76%±10%, ES=0.94, p=.096). On average, baseline measured DLMO occurred 123±83 mins earlier than estimated DLMO (p=.001). Conclusion We are continuing to enroll participants in this trial. Preliminary results suggest some potential benefit of measuring the DLMO, but results will need to be clarified in a larger sample. Support American Sleep Medicine Foundation Strategic Research Award

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