Science topic

Sleep - Science topic

Sleep is a readily reversible suspension of sensorimotor interaction with the environment, usually associated with recumbency and immobility.
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I have a dataset for 500 participants and their total sleep time for a period of 10 days, some of these participants do not have data for all the days, e.g. 10 of them have data only for 4 days instead of 10. Can I perform a correlation analysis on this data for sleep time and temperature, without excluding these participants? What other methods can I use for this analysis? Can I use linear regression to explain the effect of temperature on sleep?
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Hello Christian Geiser , thank you for the recommendation. Do you think it would be right to average the sleep time for each day for all available participants and perform correlation with the corresponding temperature for that day with this data i.e we have 10 data points.
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I confront this problem when I using data from Neurosky. The eight EEG powers are: delta (0.5 - 2.75Hz), theta (3.5 - 6.75Hz), low-alpha (7.5 - 9.25Hz), high-alpha (10 - 11.75Hz), low-beta (13 - 16.75Hz), high-beta (18 - 29.75Hz), low-gamma (31 - 39.75Hz), and mid-gamma (41 - 49.75Hz). I have found the meanning of some, for example, Delta reflects sleep and unconscious. However, the resource decribing the meaning of low-Alpha, high-Alpha, low-Gamma, mid-Gamma is too much little.
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Like João noted, the boundaries of these frequency bands are quite flexible and at the end of the day, they're going to be somewhat arbitrary. The power of these different frequency bands even differs from person to person which is why some researchers extract individual frequencies' peaks. The function of these different frequency bands is hotly debated as well and again, as João mentioned, these functions change depending on where they originate in the brain and even the context of the task in some cases. For example, alpha activity from the visual cortex can be thought of as inhibitory activity but when the same frequency band is recorded from the motor cortex, it's called mu and thought to represent motor preparation. As of now, there is no real consensus on the functional significance and precise boundaries of neural oscillations but that's why we continue to research them!
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Insomnia is a form of sleep disorder. Having difficulty in sleeping may increase the symptoms of mental health problems. What are the common causes, effects and probable cure for insomnia? Sharing is caring. Thanks!!!
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Sleep problems such as insomnia are a common symptom of many mental illnesses, including anxiety, depression, schizophrenia, bipolar disorder and attention deficit hyperactivity disorder (ADHD).
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Ideally, a good sleep ranges from 5 hours to 8 hours. But, as a student and an adult, I think we all have the same problem: lots of work to do. The crowded schedule sometimes made us sacrifice our sleep duration to complete our work. What happens to our bodies if we get less sleep? How do you overcome it to finish the job and get enough sleep? Please leave your opinion below. Thank you.
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You might want to read my papers:
This will give ideas.
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In my experimental design there are three experimental groups and one control group measured pre- and post intervention. Each group has around 20 samples.
Groups / Interventions / Independent Variables
0) Control group
Experimental Groups:
1) Timelimit
2) Notifications disabled
3) Grayscale
Dependent variables measured:
  • Depression
  • Stress
  • Anxiety
  • Sleep quality
  • Smartphone use in minutes
  • Smartphone addiction
before and after the following treatments/interventions 0) doing nothing (control group), 1) using a timelimit, 2) disabling notifications or 3) using a grayscale.
Confounding variables measured:
  • Willingness to change
  • Neuroticism
  • Extraversion
  • Self-Control
Questions I want to answer:
A1) What is the effect of using a timelimit on depression, anxiety, stress, sleep, smartphone usage and smartphone addiction versus doing nothing?
A2) What is the effect of using a grayscale on depression, anxiety, stress, sleep, smartphone usage and smartphone addiction versus doing nothing?
A3) What is the effect of disabling notifications on depression, anxiety, stress, sleep, smartphone usage and smartphone addiction versus doing nothing?
B1a) Is there any difference between the effect of the inverventions on depression, anxiety, stress, sleep, smartphone usage and smartphone addiction?
B1b) If so, which intervention has most influence on the aforementioned dependent variables?
C1) How does willingness to change, neuroticism, extraversion and self-control mediate the effect of the intervention on the dependent variables among different groups?
(In other words: How do different people react to different interventions when looking at depression, anxiety, stress.. etc.?)
So far I have performed simple paired t-tests and investigated various variations of ANOVA and MANOVA. However, I am very much unsure which analysis I need to use to answer these questions as they feel more complex than I anticipated when starting this research.
Are the questions that I am trying to ask too complex, and are there too many variables involved?
Any suggestions for which analysis to use are highly welcome.
I attached a sample of my dataset.
Thanks in advance.
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To answer you questions I would do regression analysis to see how much ( %) of the variance is explained by
timelimit on depression, anxiety, stress, sleep, smartphone usage and smartphone addiction versus doing nothing?
grayscale on depression, anxiety, stress, sleep, smartphone usage and smartphone addiction versus doing nothing?
disabling notifications on depression, anxiety, stress, sleep, smartphone usage and smartphone addiction versus doing nothing?
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Cole-Kripke, Sadeh Catrine Tudor-Locke, The Munich Actimetry Sleep Detection Algorithm (MASDA) or Roenneberg algorithm, ACceleration-based Classification and Estimation of Long-term sleep–wake cycles (ACCEL) and Kyoko Nakazaki measured with the FS-750 actigraph:
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I have found myself that all are open.
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Hello everyone,
I am conducting a study evaluating the effects of product X on their sleep patterns over time. There are 3-4 time points and drop outs at each time point. These are the same participants and my client wants to take gender, age, and dosage into consideration when examining effects. I thought of conducting a repeated measures ANOVA but the drop outs would not allow me to conduct an accurate test. Is the only option to eliminate the incomplete cases? Would an MMRM work?
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I'd use a mixed model before considering imputation.
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I have collected data from 9 participants during the phases. The first phase the participants were asked to record their sleep throughout the night and fast from the evening before the lab. Blood glucose was then tested for 3 hours following a sugary drink. The second phase the participants were asked to restrict there sleep to 4-5 hours the night before and fast as well. The no participants would then have their blood glucose tested for 2 hours after consumption of sugary drink. The third phase the participants sleep was restricted and while in the lab they were asked to consume caffeinated coffee. Their blood Glucose was tested after the consumption of the sugary drink.
This study will therefore answer two important questions: (1) Does caffeinated coffee intake further impair blood sugar control after acute sleep restriction? And (2) Does caffeinated coffee supress appetite when consumed following sleep restriction? The participants were asked to fill out a 5 question Sprite questionnaire before each blood glucose test.
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It is not easy to answer your question without knowing the data set. The number of the participants seems to be also too low to for me. You should certainly have a statistician at your University, so I advise you to contact him to address your problem. This will be the best way.
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Currently we are working on a sleep project to study the efficacy of herbals in the context of sleep.
From the literature it was understood that pentobarbital / diazepam /ketamine were used to study effect of herbals on sleep in rodents.
Here are my doubts -
1. On what basis we should select hypnotic agent ?
2. Even if the herb/plant is showing efficiency in sleep latency as well as duration (after pento barbital injection), how can we attribute the same to plant, as it is showing in the presence of established hypnotic ?
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Sergiu Groppa
I need the PSQI scoring and interpretation for my study. Do you know where I can find it? Thanks a lot!
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Dear Dr. Bulcsu Szekely
This research survey is about all kinds of athletes and sports players including football players. It would be really great if you participate in this research.
Best Regards
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Please help to circulate this questionnaire, which is part of a big international study (you can find below the questionnaire in different languages):
The project has the collaboration of researchers (including sport scientists) from 6 continents.
Globally, the coronavirus (COVID-19) pandemic has transformed people’s day-to-day life. The world’s sporting calendar, recreational and professional, is almost unrecognisable. Athletes have seen access to training facilities and/or the ability to even leave their homes (i.e., to run, cycle) severely restricted, if not removed entirely. This questionnaire will investigate how the lockdown is affecting (or has affected) athletes’ lifestyle (including nutritional, psychological and sleep aspects) and how athletes are responding (have responded) to the pandemic.
Why participate in this project? Project outcomes will be used for research purposes and to inform current/future guidelines for athletes, coaches, sports scientists and (potentially) policymakers. It will reveal what has happened globally, across every inhabited continent, during the pandemic relative to athletes and their training practices. Your participation will contribute to improving the current and future lifestyle of athletes.
Target population: Elite or sub-elite athletes (amateur or professional from both genders, including Para athletes) from any country that is experiencing, or has experienced, a lockdown during the COVID-19 pandemic.
Privacy, confidentiality, and Data security : All responses will be de-identified and processed anonymously (you will not be asked to provide us with your name, ensuring total anonymity). No other identifying information, including IP address will be recorded. At the end of the study, the data will be destroyed in compliance with international regulations. Precautions will be taken to control access to all data. Only authorized individuals (principal investigators) will have access to the dataset. We’re minimizing the risk of breach of confidentiality by collecting and storing the data anonymously, and by saving data with password protection. This international survey has been approved by the Ethics Committee of Imam Khomeini International University.
Results : The results of this project will be used for scientific publications where it will not possible to identify any of the participants. To inquire about the results of the survey, please email the principal investigator. For any inquiries, please feel free to contact the principal investigator: Morteza Taheri E-mail: m.taheri@soc.ikiu.ac.ir
English
Arabic
Persian:
Turkish:
Portuguees
Germany
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Hello dear colleague.
A very interesting study. I can join.
I have experience in questioning student-athletes.
As well as the correction of their nutrition in order to increase immunity and endurance.
I would be happy to work together.
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Hi,
Just checking if anyone has an Excel scoring synthax for the Pittsburgh Sleep Quality Index that they would be happy to share
Thanks
Kate
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Hannah Beaman Thank you! That saved me a lot of time on a short deadline.
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Sleep is known for its immuno-modulatory and immune strengthening effects. Different sleep stage specific deprivations studies across animal kingdom are found correlated with many patho-physiological, immune-weakening and health detrimental issues. Is the lack of sleep with modern stress and socio-economical changes are driving the immuno-deficiency in humans to combat virus challenges?
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A disrupted circadian rhythm caused by poor sleep may decrease night-time melatonin levels increasing the susceptibility for SARS-CoV-2 infection
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I have been trying to acquire 2P images during awake and sleep states, however according to the EEG recordings, the mice are not falling asleep. I have recorded around 2-3 h but nothing happens. Any suggestions on what I can do to make it more "comfortable" for the mice to fall asleep while recording?
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Hola, yo haría lo que Fernanda recomienda. Privar de sueño para que cuando haga el registro me asegure de que está dormido. Tambien puedes intentar inducirlo farmacológicamente. O habituar a los animales a los aparatos, tal vez acostumbrarlos a dormir con algo que simule tus aparatos del día de registro.
Saludos
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Our lab is looking into actigraphy devices for sleep study including insomnia and metabolic measurements such as heart rate. Are there any well-validated devices, wearable for 7+ days and with easily exportable data that would be applicable in this setting?
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Jawac device to measure mandibular movements. Read the Bassam Chakar's article.
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To: All Students
Cc: Faculty Members
Subject: Invitation to participate in research about the inter-relationship between sleep pattern, physical activities and quality of life in students
Dear students
Within an international scientific research framework approved by the Institutional Review Board of Qatar University (QU-IRB 1510-EA/21) led by the College of Education, we would like to invite you to answer the following online survey about The inter-relationship between sleep pattern, physical activities and quality of life in students.
We would like to kindly ask you to do your best to answer all questions, if possible, because this will allow us to anonymously process and analyze the data, and thus, improve the knowledge in the field.
The estimated time to complete the survey is of about 20 minutes and it is available in three languages:
In case of any query, please feel free to email the lead principal investigator Imen Moussa-Chamari:
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Ok with great pleasure
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I am conducting repeated measures research on sleep quality (outcome variable) assessed daily over 2 weeks (14 time points). My research question is about determining which behaviours engaged in on the previous day contribute to the outcome variable. These behaviours are mostly dichotomous ("Yes, I did this behaviour" vs "No, I did not") and there are 15+ behaviours assessed.
I have several questions I hope people can help with:
1) Am I ok to use all behaviours in the model as fixed factors given I have data from almost 100 participants to draw from? I suspect that the model might become too complex with more than 15 factors but I do not know for sure, nor am I familiar with the pros and cons for analysing all behaviours together or having separate models for each behaviour.
2) If I assume that I can use all behaviours in one model would I be correct in fitting the participants as a random factor?
3) Should I also be considering interactions? As I expect that certain behaviours may have bigger impacts on sleep depending on the participant. If so, how do I account for this in the model - am I able to fit the interaction as fixed even if participants are fitted as random?
4) If there are deviations from normality of residuals, am I able to use GLMM instead, or should I consider using GLMM from the get-go? (I'm not entirely clear on the differences) but I have seen this come up in my search for an approriate analysis.
Many thanks in advance,
Tom
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Hi Tom,
I think the first question you have to ask yourself is how your dependent variable (DV) would look like. You say yourself that you have 14 time points for the DV, but L(M)M (linear (mixed) models) can only handle one column of DV. You may come up with a way to create it from your time points, but that depends on the theoretical bases of your research, not stats.
Assuming you get a clear outcome DV, here are some answers to your questions:
1 - It's not really about how many participants you have (in terms of model convergence; statistical power is a different question), but whether the experimental design is filled (you have data points for each cell). Let's assume you do. In that case, since I guess you collected all the independent variables (IV, i.e., behaviours) because you are interested in their effect on the DV, you definitely should add them in the model. You should not build separate models for behaviours, because that would inflate errors and because you'd miss the interplay of them on the DV.
2 - It's always advisable to add a random intercept for participant, if your model can handle it. However, mind that if you only have one row of data per subject, random effects cannot be fitted.
3 - Whether you should fit interactions or not is not a stats question, but it depends on your hypotheses. If you hypothesise there is an interaction, you need to fit it, regardless of it being or not being statistically significant. However, if you're rather running an exploratory model, you may want to add all possible IVs (if the model converges) and run a step-wise procedure which would choose the best model based on AIC/BIC. Do mind that the fact that one IV would have a bigger impact on DV than another would not be reflected in an interaction. Instead, you'd want to look into how much variance in the DV each IV explains - check how much bigger is the R^2 of the model with this IV in comparison to one without it. Of course, p-values also tell you if the IV explains statistically significant amount of variance (however you want to interpret it).
4 - If you have theoretical reasons to believe that the relation between DV and IVs is linear, you should start with an LMM. However, it's crucial to check the model's assumptions, which include normality of the residuals. If these are not normal, you need to either transform your data, or go to GLMMs. GLMM, though, is more complicated than LMM, so I'd suggest you first really understand your steps in LMM before you move on. You may also want to check papers discussing transformations/GLMMs, e.g., https://www.frontiersin.org/articles/10.3389/fpsyg.2015.01171/full.
Good luck!
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Assume vehicle is off and windows are closed. Can enough fresh air enter through door seals or fresh air intake in cowling to provide enough oxygen. Assume one person is in car.
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Richard Muscoplat I guess its actually carbon monoxide maximum!
However, According to a recent research by Swedish sensors maker Senseair, CO2 levels reach 1,000 ppm in 1.5 minutes, 2,500 ppm in 5 minutes, and frightening 6,000 ppm after 22 minutes, although with air flow ventilation powered on! Drowsiness is also a factor for 10% to 30% of car accidents annually, with high CO2 levels being a significant contributor. The usage of CO2 sensors in automobiles can help manage ventilation and perhaps protect fatalities. Modern automotive interiors are modeled to constantly deliver adequate air flow to manage CO2 levels for an individual traveler around or underneath 2,500 ppm. Therefore, by switching on "recirculate," the relatively stable flow of fresh air is halted, resulting in CO2 accumulation.
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A self report after 6 to 7 months of May 2021 operation ( proGAV 2 + Miethke blue + peritoneal catheter change)
Implantation settings: proGAV 2 was 1 and Miethke blue was on 20. After operation supine headache was remarkably improved compared to preoperative (supine adjustment postoperative was 1 compared to 3 preoperative). This was my main preoperative complaint which motivated me to go for valve replacement (proSA stopped going up).
My preoperative standing was 20 (3 + 17). Postoperative adjustments were 1) proGAV 1 to zero and 2) Miethke blue from 20 to 19. Before adjustments I noticed a crescendo increase in headaches followed by spontaneous relief after around 1 week. This happened in cycles. Currently I am at sum of 19 standing and zero supine. This Miethke blue cycle disappeared. I think this is a very important advancement in M. blue.
My self current evaluation:
In case our grading scale is 0 to 10 regarding headache; when 0 refers to no headache and 10 is worst headache:
My standing or sitting headache is 1 to 2 and my supine headache is 5 to 6
Examples of self report improvements:
1)Comfort of sleep and dream qualities are fair.
2)Time spent in preparing and taking morning medicines (5 tablets from strips + eyedrops + inhaler) improved: from 10 min. to 4 to 5 min.
3)Improvement of my medical reading.
4)Social relation improvements which included strategic planning of things and solving problems.
5)Some hobbies occasionally like swimming, walking and enjoying watching football matches.
The above are good positive things. I hope I will be able to write a second report after 1 year. Also a new MRI for comparison.
The point of this discussion is a trial to improve supine adjustment and sleep which is described as elixir of life. This logically apply to all vp shunted patients.
Suggestions and comments are wellcomed.
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I found that sleeping in a slope about 30 degrees improves supine headaches. I will watch in the coming period the standing situation. I hope nothing, but theoritcally if supine csf pressure is lowered, on getting up we I am starting daily activity with a lower csf pressure.
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As far as I know, these ideas have been used mainly in theological discussions. However, it seems to me that such ideas would also have application in more general discussions of Cartesian dualism and the mind–body problem, e.g. they could be used to describe what happens to the Cartesian soul or mind when one is sleeping dreamlessly or when one is unconscious.
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Interesting. I will search for information.
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I am interested in the scoring guide for the ASKME (Assessing Sleep Knowledge in Medical Education) survey. In addition to the correct answers, I am also interested in how the different questions are divided into the categories. Thanks!
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Hi everyone,
I want to simulate different energy plus models with different occupancy profiles from excel using python. Could you suggest a library to do so and in which format I should import my occupancy profiles? As of now, excel sheets has activity data such as sleeping, cooking and so on and different IDF files with default 24*7 occupancy schedule from Design Builder.
Thanks in advance!
Divyanshu
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Hey Divyanshu,
We have an open source platform BESOS developed at the Energy Systems and Sustainable Cities lab at UVic for running E+ parametric simulations using Python. You can modify any parameter of your occupancy profile in the IDF within the platform. Let me know if that is something you are after.
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I am looking for a short questionnaire to assess the quality of sleep, ideally it should not have more than 5 questions, but I am having difficulty finding one. Any suggestions ?
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I need Theory for Continous Care Model for sleep quality
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Hi,
Maybe some of the cross-references in the articles given below can be of help to you
Otaghi M, Bastami M, Borji M, Tayebi A, Azami M. The Effect of Continuous Care Model on the Sleep Quality of Hemodialysis Patients. Nephrourol Mon. 2016 Mar 19;8(3):e35467. doi: 10.5812/numonthly.35467
Khosravan S, Alami A, Golchin Rahni S. Effects of continuous care model based non-pharmacological intervention on sleep quality in patients with type 2 diabetes mellitus: a randomized controlled clinical trial. Int J Community Based Nurs Midwifery. 2015 Apr;3(2):96-104
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People have to eat and drink because of hunger, thirst and basic requirement to live. People rest and sleep because it's also a requirement to continue living. Both eating and sleeping come naturally and instinctively. Exercise, however, requires work and motivation and does not have the same natural instinctive behavior to stay alive as eating and sleeping.
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As the holiday season comes into full gear and the year comes to an end, many people may be thinking about starting regular physical exercise as a new activity for the new year whether to keep fit or maintain ideal body weight. Throughout the years, there have been so many commercially well-known products from gym membership to home gadgets that people can do at home. Whether the gyms are used for exercises or for socializing, the lure to get new members to replace the members that quit is pretty much constant. Why do people quit the gym? As for home gadgets are concerned, they lure people with all kinds of gimmicks. They even make gadgets that require no actual conscious muscle contractions. The gadgets have electrodes to actually stimulate and contract the muscle fibers for you. People can buy a very expensive stationary bicycle and have a coach appear on a monitor screen cheering you on while exercising. Whether it's the gym or home gadgets to do exercises, most have failed and do not have much staying power. People eventually quit the gym for whatever reason, and the gadgets end up collecting dust or parts of a garage sale. Physical exercise to keep fit and to spend the extra calories consumed requires both work and commitment. One form of natural activity that people forget and underestimate that can still be used as an exercise to keep fit and healthy is "walking". The long lower limbs are perfectly made and have evolved to be used so we can be mobile and independent to move from one place to another and not only from the couch to a dining chair or inside the house to a driver's seat of a car.
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Hi. It is well known that we lose consciousness when we fell asleep, as an individual, we stop being conscious of external and internal stimuli, at least, in most cases. In no-dream sleep, brain activity should be one that can unconsciously manage internal and external stimuli, and should not experiment significant changes in blood flow to the brain, as if we were to observe with fMRI, nearly no BOLD signal would appear. Am I right about this last thing? If not, please reply. Thanks to all.
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I have to find the correlation and causality between participants’ smartphone uses pattern and loneliness. For that, i have the dependent variable loneliness (both baseline (0 to 80) and daily: in an 0 to 10 numeric scale), and independent variables listed from daily smartphone uses screen time, spend time in several categorized apps like social media, entertainment, communication, physical activity, sleep, and some social variables and moods like how much the person felt bored, anxious, satisfied, productive, etc. I will collect these independent variables for 10 days, and the psychosocial variables will be collected three times a day. I also have to use a couple of prediction algorithms for predicting loneliness with the above-mentioned independent variables. But first, I have to find the correlation and causality between the dependent and independent variables. I just have programming experience until now with python, no statistics knowledge. I have about 9 months remaining to complete my thesis. Please share your valuable guideline and resources on how can I proceed with this challenge where I can get the most meaningful results.
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Abiodun Christian Ibiloye Thank you so much sir for your enormous suggestions.
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Hi sir/madam,
Hope you are Healthy and doing well,
In my study I have 2 experimental groups (patients with neck pain and sleep disturbances at baseline) these two groups are equal at baseline in almost all variables and one control group (healthy participants).
After 6 weeks of interventions I have taken the post readings.
Is 2 way repeated measure ANOVA suitable test to use ? Or other test could be more accurate?
If 2 way repeated measure is suitable, should I incorporate covariate in the analysis or keep it blank ?
Thank you
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Hi Mosab,
I hope you are doing well.
In this case, where you have got 3 groups and 2 time points of measurement, you should go for 3X2 repeated measured ANOVA. ANOVA will be applicable subject to type of data (only if the data is continous, you can go ahead with ANOVA) and normality of the data (log transform the if non-normal). These are basic assumptions to any parametric test.
Regarding including the covariates, you need not to add any co-variate if you have not proposed any co-variate adjusted analysis. If in case, any variable comes out to be significantly different between the groups at baseline, then, you can go for analysis of covariance (ANCOVA) where in you can put the baseline value as a covariate.
Thanks & regards,
Dr. Pooja
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Can anyone give instructions for the scoring of Global Sleep Assessment Questionnaire? The original authors (Roth, et al, 2002) do not provide clear-cut scoring criteria
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Hi,
A new quetionnaire to detect sleep disorders
  • April 2002
  • Sleep Medicine 3(2):99-108
  • Follow journal
  • DOI:
  • 10.1016/S1389-9457(01)00131-9
  • This is a request article in Research Gate. Place a request with authors and ask for instruction details.
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Many times, I will get new ideas in the early morning, but sometimes at late night when I am unable to sleep. Which time is best?
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Suddenly the question attracted my notice. Though the discussion started a long time ago, I would like to add my experience to this interesting discussion now.
There is no definite time for me to have new ideas. But in most of the time, it is late night for me when I study and when everybody sleeps and there is a calm and quite environment at my home. Sometimes after completing all the morning duties when I make preparations to start work in laptop.@Jayaram as.
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I would like to see the association between predictive study variables and outcome variable (e.g., Depression) by using binary logistic regression. I'm planning to draw three models. Model-1 will be unadjusted -estimates. Model-2 will be adjusted for socio-demographic variables (age, gender, grade, residence), and model-3 will be adjusted for level of physical activity, duration of daily screen time, satisfaction about daily sleep, sleep habit, and perceived weight category.
In this case, how will I control the p-level for variables in model-2 & 3?
<<Thanks for help>>
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Hello Sahadat,
The answer depends on what you're planning to do. If your plan is to determine whether the study variables (as a group) contribute significantly to the explanation of the outcome variable status (either alone: model 1, or after controlling for other variables: models 2 and 3), then you're talking about three tests, total. If you wish to evaluate each study variable as to whether it is a significant predictor in your model, you have 3*k tests, where k is the number of study variables.
With the first option (3 tests), it won't make a whole lot of difference what type I risk control you impose: ordinary Bonferroni adjustment should work about as well as any fancier method.
With the second option, you might consider the Benjamini-Hochberg method (see this link for quick explanation: https://www.statisticshowto.com/benjamini-hochberg-procedure/
Good luck with your work.
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I am looking to use the SynWin test in an upcoming study. I have found many articles using and describing the test however cannot seem to find any way in which I can actually obtain the test.
Does anyone know how I could access SynWin or a similar multitask test?
Many thanks.
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Ah many thanks Stephen Joy! Yeah I had a look and couldn't find anything on their existence today so I'm guessing its now defunct. Though I have seen articles this year and last year use the test so the test itself must still be around.
Ill try email that email there and see if I can find anything more anyway.
Cheers again!
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Some PSG studies found patients with epilepsy had decreased REM sleep compared to healthy controls (TLE and JME). Furthermore, patients with refractory epilepsy had decreased percentage of REM sleep compared to those with medically controlled epilepsy.
Medications ( i.e, BZDs) are well known to decrease REM sleep. However, decreased REM sleep has also been observed among drug-naive patients with epilepsy.
-> Is the decrease of rapid eye movement sleep a cause or consequence of epilepsy?
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Hi,
Here are some references in this area:
Frauscher B, Gotman J. Sleep, oscillations, interictal discharges, and seizures in human focal epilepsy. Neurobiol Dis. 2019 Jul;127:545-553. doi: 10.1016/j.nbd.2019.04.007
Wang YQ, Zhang MQ, Li R, Qu WM, Huang ZL. The Mutual Interaction Between Sleep and Epilepsy on the Neurobiological Basis and Therapy. Curr Neuropharmacol. 2018;16(1):5-16. doi: 10.2174/1570159X15666170509101237
Hamdy MM, Elfatatry AM, Mekky JF, Hamdy E. Rapid eye movement (REM) sleep and seizure control in idiopathic generalized epilepsy. Epilepsy Behav. 2020 Jun;107:107064. doi: 10.1016/j.yebeh.2020.107064
Foldvary-Schaefer N, Grigg-Damberger M. Sleep and epilepsy. Semin Neurol. 2009 Sep;29(4):419-28. doi: 10.1055/s-0029-1237115
Kellaway P. Sleep and epilepsy. Epilepsia. 1985;26 Suppl 1:S15-30. doi: 10.1111/j.1528-1157.1985.tb05720.x
Khachatryan SG, Tunyan YS. Vliianie épilepsii na strukturu sna [An effect of epilepsy on sleep structure]. Zh Nevrol Psikhiatr Im S S Korsakova. 2017;117(9. Vyp. 2):88-94. Russian. doi: 10.17116/jnevro20171179288-94
Kang X, Boly M, Findlay G, Jones B, Gjini K, Maganti R, Struck AF. Quantitative spatio-temporal characterization of epileptic spikes using high density EEG: Differences between NREM sleep and REM sleep. Sci Rep. 2020 Feb 3;10(1):1673
Nakamura M, Jin K, Kato K, Itabashi H, Iwasaki M, Kakisaka Y, Nakasato N. Differences in sleep architecture between left and right temporal lobe epilepsy. Neurol Sci. 2017 Jan;38(1):189-192. doi: 10.1007/s10072-016-2731-6
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I'm looking to use a self-report measure of sleep in further cross-sectional/longitudinal research on lifestyle behaviours and mental health. Any sleep measures that are easy to administer, relatively short to answer, and quantitatively sound.
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I INSIST: The PSQI requires, by definition -as any "paper and pencil" test that the subject is aware of having been asleep and, I reiterate, that this does not occur in most cases for the purposes of the Investigation -although YES THAT IT IS TRUE THAT, IN THOSE WHO ARE CONSCIOUS, THE "PSQI" IS COMPLETELY VALID-; By virtue of this, I would dare to advise that, when the interesting results are going to be published, undoubtedly, the results ARE SPECIFIED AMONG THE "EXCLUSION CRITERIA" that, by pure logic, those subjects who were not or are aware of having slept, as explained in my previous answer, for the reasons stated; in the same way, among the "INCLUSION CRITERIA" specify that the subjects WHO WERE OR ARE AWARE OF HAVING SLEEP have been used in the samples.
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Our family and some experts told us that sleeping on the left side is not good for health. However, when I looked on the internet, I read that on the contrary, it is necessary to lie on the left side for lymph circulation and brain cleansing. I am really confused.
Has science reached clear information on this subject?
Which side should we prefer to lie down while sleeping?
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Face towards west side is a good for health during sleeping time
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The tittle of my research project is the relationship between physical exercise, sleep quality, mental health and suicide ideation. I'm confusing with my IV and DV. Is it the IV would be the condition of mental health and DV is suicide ideation? The measure of IV is physical exercise and sleep quality, is it appropriate?
Please correct me if I'm wrong, thank you.
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You do not have to put everything in one sole analysis.
Sleep quality is a good measure of feeling well = being mentally healthy.
Why not put Sleep quality as dependent variable explained by the independents physical exercise and depression and suicidal ideation.
Your first IV is positively correlated and depression and suicidal ideation. are negatively correlated with sleep quality.
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There are other methods of sleep deprivation that includes some of the automated setups validated and published couple of years back. But I am looking for the wet cage method of restricting sleep. If you got any reference please do share and comment.
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Kincheski et al. (2017) performed two interesting sleep deprivation protocols in this paper ( ). I don't know if any of them interest you, but my intention was to help you. Good luck!
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Official PSQI scoring for Component 3 does not clearly define boundaries for scoring:
  • > 7 hours: score 0
  • 6-7 hours: score 1
  • 5-6 hours: score 2
  • < 5 hours: score 3
I have found several scoring scripts and they are quite inconsistent in this regard. Unfortunately affected numbers (7, 6, and 5) are the majority in my data and the choice of scoring will have an impact on overall results for this component (and might affect models for the global score as well), so I would like to make this decision before the analysis to avoid possible bias. Is there some kind of guideline or common practice for this calculation?
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Hi,
Scores between 5 and 7 show the normal distribution in the population too.I think we have to analyze according to the observed values.
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1.For example there are 3 groups taking different medication and I want to assess how well they sleep while taking this medication.
I have I have the categories: excellent, good, intermediate, poor, very poor and I want to see if there is a difference between the 3 groups.
I was thinking maybe a Kruskal- Wallis test but am not sure if i'm overthinking it as its three groups?
2. Also if I have the same scenario but my data is continuous should I use one-way ANOVA or can I use a T-test between each of the 3 groups?
Thank you
Sophie
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For the second query on time of symptoms, there are a few simple summary statistics or tests you might perform...
That being said, it sounds like maybe you are doing actual pharmacology research. For this kind of question, I would advise consulting with someone in your department or university that is familiar with this kind of research.
I can imagine a relatively complex analysis that takes into account the fact that each respondent is responding over multiple times. I can imagine a multinomial mixed effects (hierarchical) logistic regression. But again, this is probably something you probably want to consult with someone about with your specific data and design.
Can people check off multiple options? This might make a big difference in what approach makes sense.
For some simple things, yes, you can count the number of times each option is selected. Reporting a proportion of each might may be sufficient as a summary statistic, and you might just stop there. A simple test would be the chi-square test of independence of the counts of options across the groups. But this ignores the fact that each respondent is responding over multiple times. And I think I wouldn't use this at all if people can check off multiple options.
If respondents can check off multiple options, I might think about looking at each option separately as a yes/no question at each time for each participant. Counting these and reporting the proportions of each may make sense here. Again, I can imagine using a mixed effects logistic regression, here, and might actually be a little easier to interpret that the multinomial model mentioned above.
Obviously this can get complicated, and it's difficult to advise without really understanding what kind of summary statistics or analysis results would be useful for your purpose.
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I have data from 6 EEG channels (F3-A2, C3-A2, A1-A2, F4-A1, C4-A1, A2-A1) sleep data. And 1 channel for ECG and EOG, are these enough to run ICA to remove artifacts caused by EOG and ECG from the EEG channels?
Also which algorithm would be recommended to use?
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Uttara u Khatri : Yes that should be sufficient. But when PSG signals are considered for analysis. It also depends upon how many features you have extracted from each of these channels. Make sure all the features of PSG contribute equally in the analysis.
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sleep Deprivation or insufficient sleep can cause fatigue.
So, how long does it take to cause ?? your comments are highly welcomed.
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Sleep deprivation leads to hypertension, irregular heart beat, obesity, depression, cognitive decline and impairment in immune system.
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In LEACH protocol cluster head is active all the time even if there is no data transmission from the cluster head to sink. I need an algorithm to make cluster head sleep when there is no or very less data to be transmitted to sink. This helps to improve lifetime of the sensor network.
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When viewed from health science, what time of sleep is the best for us?
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Thanks dear Mohammed Jaafar Ali Alatabe and Charles Obinwanne Okoye for your kind reply.
Have a good time.
Nazar
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BMJ now mentions that "Long Covid" symptoms occur:
-Covid foot
-rashes
-numb hands/feet after sleeping
Covid symptoms are still occurring 6 months after infection in "mild cases that have NOT gone to hospital
PHOSP-Covid at Leicester Uni to study log term effects
see fb "Long Covid Support Group"
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£18.5 million to tackle ‘Long-COVID’ in the community. Imperial College & 2 other study centres.
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My experiment design is like this:
We randomly pick up different time periods in pre-test recording and capture specific sleep states for the animal and do the same thing in post-treatment recording. Then the problem is I gathered (for example) 30 REM sleep bouts in pre-treatment group but 25 REM sleep bouts in post-treatment group. So it is like a repeated measurement but the numbers of observations before and after the treatment are different. I was wondering what kind of statistics approach I should use for analysis?
Thank you very much!
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SAMPLE SIZES are different from the same group of observed animals. I suggest trying this approach: GROUP 1 vs GROUP 2.
GROUP 1 calculate: (i) sample mean (X1^), (ii) expected mean (sigma1), (iii) var1
GROUP 2 calculate: (i) sample mean (X2^), (ii) expected mean (sigma2), (iii) var2
Use the pair means T test:
T = (A - B) / sqrt(C)
A = (mean1 - mean2)
B = (sigma1 - sigma2)
C = (var1/n1) + (var2/n2)
H(0): T < 1.64 ..... not significant difference
H(A): T = > 1.64 .... significant difference
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We have publish a report before"" The Effectiveness of Occupational Therapy-Based Sleep Interventions on Quality of Life and Fatigue in Patients with Multiple Sclerosis: A Pilot Randomized Clinical Trial Study ", So we are going to compare this protocol with another one. we need your comments and suggestions. Thank you
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Vanilla is the most prone to night theft. Farmers fail to sleep so to guard their vanilla during harvest period. Hire gunmen but still a problem?
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Dear Dr Bruce Robin Nyamweha , Use of electronic devices connected with surveillance camera along with dogs - may be an option. Warm regards Yoganandan G
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ABSTRACT: Symptoms of psychological distress and disorder have been widely reported in people under quarantine during the COVID-19 pandemic; in addition to severe disruption of peoples’ daily activity and sleep patterns. This study investigates the association between physical-activity levels and sleep patterns in quarantined individuals. An international Google online survey was launched in April 6th, 2020 for 12-weeks. Forty-one research organizations from Europe, North-Africa, Western-Asia, and the Americas promoted the survey through their networks to the general society, which was made available in 14 languages. The survey was presented in a differential format with questions related to responses “before” and “during” the confinement period. Participants responded to the Pittsburgh Sleep Quality Index (PSQI) questionnaire and the short form of the International Physical Activity Questionnaire. 5056 replies (59.4% female), from Europe (46.4%), Western-Asia (25.4%), America (14.8%) and North-Africa (13.3%) were analysed. The COVID-19 home confinement led to impaired sleep quality, as evidenced by the increase in the global PSQI score (4.37 ± 2.71 before home confinement vs. 5.32 ± 3.23 during home confinement) (p < 0.001). The frequency of individuals experiencing a good sleep decreased from 61% (n = 3063) before home confinement to 48% (n = 2405) during home confinement with highly active individuals experienced better sleep quality (p < 0.001) in both conditions. Time spent engaged in all physical-activity and the metabolic equivalent of task in each physical-activity category (i.e., vigorous, moderate, walking) decreased significantly during COVID-19 home confinement (p < 0.001). The number of hours of daily-sitting increased by ~2 hours/days during home confinement (p < 0.001). COVID-19 home confinement resulted in significantly negative alterations in sleep patterns and physical-activity levels. To maintain health during home confinement, physical-activity promotion and sleep hygiene education and support are strongly warranted. CITATION: Trabelsi K, Ammar A, Masmoudi L et al. Globally altered sleep patterns and physical activity levels by confinement in 5056 individuals: ECLB COVID-19 international online survey. Biol Sport. 2021;38(4):495–506.
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In the long term perspective for future lockdown, it will be necessary to develop an educational program for health (food, exercise, mental and etc.) in order to reduce the stresses and the negative impacts.
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Experiences of sleep hygiene education as an intervention for sleep problems in children with developmental disabilities : findings from an exploratory study
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Hi Thanks for this- I managed to contact ersearch gate and they resolved it. Have a good day
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- What is the true meaning of life? Is it to eat, sleep, shit, reproduce, or just simply trying to stay alive as long as possible?
- Should we believe something although we knew it is bullshit?
- Should we die for what we believe, or simply accept the lie and live in silence?
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Life is a struggle, a Struggle of continuity. With the rising of life comes the end result of it which is called death, the end of continuity similar to every other organism. This defines life. From eating to every other major activity we do is to ease this struggle of survival. Reproduction is the 'plan B', where we pass on our genes to bring the eternal survival of self.
We are nothing but a collection of cells which are programmed to complete certain amount of work that we are assigned for.
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Dear community , during processing my dataset ( physionet sleep edf ) , I created epoched data , and then created different lists , each list representing a sleep stage and containing the epochs , I want to apply a feature extraction on each one of those lists , but my epochs are under the format (time , channel , epochs) , how can I apply the feature extraction ? with creating a labels list and a signals list ?
Thank you
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I am measuring sleep spindle activity in 3 groups: schizophrenia, bipolar disorder and healthy individuals.
I aim to compare their activities and the sleep study will only do once.
Do you think this is a cross-sectional study since I measure it at one-time point?
Or do you think it is a case-control study?
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In my understanding, both the terms are NOT mutually exclusive. So a case control study can be cross-sectional too and vice versa.
Please see here:
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The use of MSLT to support a diagnosis of narcolepsy is suspect if Total Sleep Time on prior night sleep study is less than 6 hours
My query is what are the other ways to confirm the diagnosis of narcolepsy, if the Total Sleep Time is less than 6 hours in the preceding overnight PSG. Should one redo the PSG if the Total Sleep Time is lesser than 6 hours and run the MSLT again.
Looking forward for your help
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Interesting question. Have a look at Machine Learning and PSG in this field as techniques are being developed that are more sensitive and specific than MSLT. For example see the below paper as an example.
I hope this helps
Zhang, Z., Mayer, G., Dauvilliers, Y., Plazzi, G., Pizza, F., Fronczek, R., Santamaria, J., Partinen, M., Overeem, S., Peraita-Adrados, R. and Da Silva, A.M., 2018. Exploring the clinical features of narcolepsy type 1 versus narcolepsy type 2 from European Narcolepsy Network database with machine learning. Scientific reports, 8(1), pp.1-11.
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I am analysing the EEG data to classify the Rapid Eye Movement Behaviour Disorder and control health patients. I have to separate the sleep interval from EEG data.
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bonsoir monsieur Shahzeb Shahzeb
est se que vous pouvais me donner le lien où vous avez eu ses donné
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Hi,
So I collected data on sleep positions for 5 nights. Each position (4 in total) were recorded as a percentage of total time asleep (e.g. 40% left, 30%, right, 20% back and 10% on stomach). Each participant then filled in a pain scale (from 0-10) to determine the level of back pain in the morning. My question is what is the best statistical test to see if there is a correlation between sleep positions and back pain scores? I'm doing my analysis on SPSS.
Any help would be greatly appreciated.
Thanks,
Roman
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I suggest initially do a univariate regressions of pain score on %L.%R, %S,%B for each subject separately ( 5 data points for each ).
Then ,depending on results, you may be able to pool the subjects.
A multiple regression would not work as the position variables are not independent of each other.,
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Hello everyone,
I have a pressing question. I would like to investigate the way differences in average scores based on region, place of work (two groups) in interaction with anxiety scores affected sleep. My specific research question refers to the interaction between societal level factors (region of work), social (specific work variable) and individual (anxiety) would affect sleep.
I would like to better understand which method would be most suitable. I wanted to use ANOVA and investigate the interaction between region, place of work and anxiety scores (treating it as a five groups categorical variable), however when I try to do Levene test I recieve an error.
Another option would be to investigate the MLM-way. Having two level variables and looking into their effects in comparison to the individual level variable in its prediction.
Can somebody help me what method would be most suitable to use?
Thank you in advance!
All best, Nina
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Hi Nina, actually for your sample, I was talking about hierarchical regression rather than HLM, which is multilevel modeling. Many confuse HLM with hierarchical regression (although both are based in regression to a large degree). But you could just as easily use standard multiple regression and create interaction terms to include in the model.
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We require a research based device for children to wear to monitor sleep over a period of time. We have looked at Evenson et al. (2015), Lee et al. (2018) and Liang and Chapa-Martell (2019). The consensus appears to be that FitBit is the best brand, but we specifically need to know which device to use as they all use different.
As technology is changing all the time and devices are updated all the time, we wondered if anyone knows of any current research being done with sleep and wearable devices that may help us.
Regards
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Who do you consider as the authority to differentiate sleep vs. no sleep or which accuracy of the data/result do you want?
Consumer devices such as the Fitbit and others do not output you some raw values but they interpret data and just give you their estimate – sometimes based on guessing, sometimes based on something else. These devices can give you acceptable results, but you need to be aware that professional sleep research labs might use something different. Are you ok with the device software’s interpretation about when the participant was sleeping or would you like to collect raw data and do the analysis and interpretation by yourself? Also think about the data interface – do you want to further process the data? If yes, check which software/app can output you the sleep data. Do you need to synchronize the data with something else?
Another thing you mentioned is ‘children’. They have smaller wrists circumferences and not all devices (consumer of professional) cover a wrist range from children to obese adults – many devices might rather cover a range rather at the upper than the lower end.
Would such a device disturb children to an extent that they would exhibit different sleep patterns?
Sorry for raising more questions instead of answering some. But think about these questions before the experiment if you plan to publish the research afterwards and try peer-review ;-)
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Dreams are hallucinations that occur during certain stages of sleep. They're strongest during REM sleep, or the rapid eye movement stage, when you may be less likely to recall your dream. Much is known about the role of sleep in regulating our metabolism, blood pressure, brain function, and other aspects of health.
Read more:
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Fares Khalifa Dreams are reflections of our subconscious mind.
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I have used TNS & TMS & TACS systems which resulted in the patients awakening.TDCS was a bit effective but even this caused the patient to wake up after some time .
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Although it is difficult to stimulate a human brain while sleeping, however, it's not entirely impossible. TMS would be the best bet at a low RMT keeping the coil holder and navigation fixed beforehand. Also, tDCS can be helpful, however, due to relatively large circumference preferably use TMS.
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I would like to test if there is a significant difference between pre and post predictor on the same dependent variable.
So far t-test provides information on the difference between before and after, but how do we test the difference on how it perform on a same dependent variable?
For example, sample of 10 patients before taking any prescribed medication, how many hours they can sleep, as opposed to the same 10 patients after taking the prescribed medication, how many hours they can sleep.
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Paired sample t test.
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While using Instron tension test machine in the lab, I have come across this error couple of times now. And the machine suddenly shuts down. The manufacturer has asked to check a couple of things like if the wire is not broken, to check network connection setting, check computer not going to sleep mode etc. But the error still pops up sometimes. Does anyone have experience with this error. And could you kindly share your observation and solution to this.
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That's a good question
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I've used the GUI code on GitHub load_open_ephys_data.m
I'm able to open smaller files with this code but larger files matlab shows an error.
Any ideas on why and what I could change? I'm new to using MATLAB.
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I collected a data of 305 people regarding their leisure time activities, to compile these, I tried to analyze using Factor analysis, wherein, I tried both PAF and PCA, PCA is giving better results, but two items, about watching news and sleeping are loading with the factors/components that are about socializing. Practically, this doesn't sound justifiable. What statistical method can help me get better results?
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As David L Morgan says first start with scatter plots, examine these, and then correlation matrices if appropriate. THere is a lot of preliminary work to do prior to conducting a latent variable model.
The advice to simply get rid of variables or data or whatever until you get results you like is not a wise approach.
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Hello. I working on a sleep project. Sleep is of paramount importance for resetting brain and body function. While newborns tend to sleep most of their day hours, geriatric population often suffers of lack of enough sleep. Most of the people will subjectively complain about their sleep, at least at one point in their life. While life requirements and schedule might play a major aspect in this, other sleep disorders should be ruled out. There is thus a need to use objective measures to better assess sleep quality and quantity. Can anyone please suggest the objective measures of sleep quality?
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Nice Contribution Dirk Cysarz
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it is well known fact that there is a 2 way interaction between brain and bowel ,,and probiota is a concern , also the patients with hepatic failure trasmits bad signals with the presence of protein inside the gut,
i noticed that people with empty bowel after attach of diarrhoea have better sleep and moral??
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Good Answer Bernard Maroy
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Imagine a non-contact, non-intrusive sleep monitor that automatically stages sleep at an accuracy close to PSG. What would be your research question? What would you use this system for?
How will objective measurements of completely uninterrupted sleep change the landscape of sleep research?
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Lukas Krondorf the paper ( http://downloads.hindawi.com/journals/wcmc/2019/2786837.pdf) of my friend José R. Torres Neto presents an architecture that uses Publish-subscribe paradigm. The validation process is done with applications on the recognition of emotions.
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There is a long history in design of using blue colors as 'calming' and 'relaxing'. If you want someone to feel peaceful, you paint the walls blue. With the more recent studies on the impact of blue light from screen for sleeping, it seems there is a physiological response that does not match this design rule.
Is there a difference in wavelength, or is there a cutoff of exposure from when it is calming to when it becomes a response to stay awake? Or am I misunderstanding something in the two cases?
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There is a rule in interior design color proportion , 10- 20% of the area could be with saturated color ( in this case true blue ). approximately 30% with 50-50 in saturation color and neutral color , and remaining 50% of the interior area must be in neutral colors as white or ligth gray .
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Hi all!
What do you think is the best EEG cap system for sleep studies? We need to use it for sleep (comfortable enough to sleep), but also for some cognitive tasks when the participant is awake. We were thinking about EasyCap, but we never worked with it...
I would appreciate your opinions/experiences!
Thanks!
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We are successfully using the hd Geodesic Sensor Net (GSN, https://www.egi.com/research-division/geodesic-sensor-net) , which stays overnight without any problems. Unfortunately, it looks like the production of these nets will be discontinued. The closest analogue is the R-net produced by Brain Products (fttps://pressrelease.brainproducts.com/r-net/), but we never used it so far.
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Sleep is known for its immuno-modulatory and immune strengthening effects. Different sleep stage specific deprivations studies across animal kingdom are found correlated with many patho-physiological, immune-weakening and health detrimental issues. Is the lack of sleep with modern stress and socio-economical changes are driving the immuno-deficiency in humans to combat virus challenges?
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Proper sleep is must for healthy immune system which may help avoid the risk of coronavirus (COVID-19) infection.
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Hi all,
I am currently studying the link between sleep quality and emotion regulation using daily measures through digital self-report. A key component that differentiates sleep quality from sleep quantity is the sleeper's subjective experience. To capture this, I have pulled question 6 from the Pittsburgh Sleep Quality Index (during the past month, how would you rate your sleep quality overall?), and modified it to better fit my research, which gathers a report for each circadian cycle (during the past 24 hours, how would you rate your sleep quality overall?). There are four possible responses from the PSQI which I have kept the same (very good, fairly good, fairly bad, and very bad). Are there better measures of subjective sleep quality that could be used on a daily basis? Thanks.
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Dear Evan Vidas , are you still on course with your research? How much value would your study gain from comparing subjective to OBJECTIVE sleep quality measures? There is new research on a non-contact sleep monitor, that might be of interest to you:
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Which is the best sleep quality measurement device currently available/in development?
Contact vs. Non-contact
EEG vs. Non-EEG
All validated against sleep phase detection of the gold standard: polysomnography.
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Thank you so much, Franklin Lue , much has changed since we last spoke. Check out this new research which compares a non-contact sleep monitor to polysomnography:
Even though, you have been sceptical towards even the validity of PSG, would you think that measuring sleep without interrupting the subject would yield better results?
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Is there any publicly accessible database which has simultaneously recorded polysomnogram data and electrodermal activity data?
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You can search it from the website: physionet.
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Which parts of the sleeping process can be manipulated (physiologically & genetically) in aquatic animals (especially in fish)?
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Yes, you can google too. You're doing the research. You have to read it yourself to understand the literature first. If you read the literature, this question might not have arisen in the first place. I am sure, someone might give the exact answer to you! Good luck!
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Sleep problems can be seen in patients with Parkinson's disease. Can it be about serotonin?
In mice, ablation of the raphe and no production serotonin increases wakefulness and impairs the homeostatic response to sleep deprivation.(DOI:https://doi.org/10.1016/j.neuron.2019.05.038)
Even in the absence of depression, the CSF levels of 5-I-HAA of patients with Parkinson’s disease are lower than those of age-matched controls.
( DOI: 10.1176/jnp.2.1.88 )
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Thank you for great articles. They gave me a new perspective about PD.
I want to suggest an article: Serotonergic dysregulation is linked to sleep problems in Parkinson's disease (doi:10.1016/j.nicl.2018.03.001)
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Purpose (Public Health): Please share it to your community.Prevention is better than Cure :
If we have mild symptoms, stay at home until COVID-19 will be recovered under prompt treatment of experts. ,In addition to it,You have to take Self care with
(1).rest and sleep in self quarantine room
(2).keep warm,
(3).drink plenty of liquids,
(4).use a room humidifier or take a hot shower to help ease a sore throat and cough
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It depends on your country procedure, and you have to stay away from your family snd call your doctor...
Wish you all healthy life my friends...
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For example specific recommendations for hours of sleep, exercises, relaxations strategies.
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IN ADDITION, BEHAVIORAL COGNITIVE TECHNICALS
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