#ukbiobank — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #ukbiobank, aggregated by home.social.
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https://www.europesays.com/at/392149/ Nocturie als Warnsignal: Warum nächtliches Wasserlassen die Herzgesundheit betrifft #AI #ARTIFICIALINTELLIGENCE #AT #Austria #Blutdruck #CPAP #Diabetes #Echokardiografie #EKG #Gesundheit #Health #Herzinsuffizienz #KI #KünstlicheIntelligenz #Licht #MRT #Nocturie #NtProBnp #Österreich #Parkinson #Schlafapnoe #Schlafdauer #Sturzrisiko #UKBiobank #Zungenschrittmacher
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DATE: September 11, 2026 at 12:00PM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Brain scans reveal how recurrent depression leaves a lasting mark on the amygdala
Brain scans reveal that elevated activity in the emotion-processing center is tied to a person’s history of recurrent depression, rather than their current mood. The large study, published in Psychological Medicine, suggests that each major depressive episode may leave a lasting biological mark that increases future vulnerability to the disease.
Major depressive disorder is a common psychiatric condition that affects millions of people worldwide. Currently, psychiatrists diagnose the condition based on clinical interviews and patient history. There are no biological markers, like a blood test or a brain scan, to guide treatment choices.
Functional magnetic resonance imaging, or fMRI, allows researchers to observe the brain in action by tracking blood-oxygen levels. When a brain region becomes active, it requires more oxygen, leading to localized changes in blood flow. The scanner detects these magnetic differences to map out neural activity.
Scientists often use this technology to study the amygdala, an almond-shaped structure deep inside the brain that processes fear and negative emotions. Early brain imaging research suggested that people with clinical depression have hyperactive amygdalae when looking at negative images. But a recent analysis of a massive dataset called the UK Biobank found no association between amygdala activity and current depression symptoms.
Jerke J. van den Berg, a biomedical researcher at the University of Amsterdam, and his colleagues designed a new study to better understand this discrepancy. They suspected that previous research might have missed the broader picture by only looking at a patient’s current mood. The researchers focused on a concept called the kindling theory.
The kindling theory proposes that an initial depressive episode makes the brain more sensitive to stress. After the brain has been sensitized by that first experience, it takes progressively less trauma to trigger a relapse. To test if the amygdala reflects this effect, the research team decided to look at a person’s lifetime history of depression, known as a trait, rather than their current symptoms, known as a state.
The researchers utilized data from the UK Biobank, a long-term population health study. They analyzed functional MRI scans from a subset of participants, totaling more than 11,000 individuals. While inside the scanner, participants completed a visual exercise called the Hariri task.
During the task, participants were shown a target image of an angry or fearful face at the top of a screen. They were then asked to select the matching face from two options at the bottom. This specific visual matching exercise is known to reliably stimulate the amygdala.
Brain activity can vary widely from person to person based on age, gender, and head movement during a scan. To account for this natural variation, the research team used a statistical technique called normative modeling. They analyzed scans from over 6,400 healthy participants to establish a baseline of expected amygdala activity. This works much like a pediatric growth chart, which maps out normal ranges for a child’s height and weight.
Next, the researchers evaluated how much the brain activity of nearly 5,000 other participants deviated from this baseline model. They categorized these individuals based on their self-reported mental health histories. The groups included healthy controls, people who had experienced a single depressive episode, those with moderate recurrence involving two to five episodes, and those with a high recurrence of six or more episodes.
For this initial cross-sectional analysis, the team focused strictly on participants who were currently in remission from their depression. The initial results were not statistically significant when the team analyzed the unaltered brain scans. However, once they applied the normative modeling technique to account for age and gender variations, a distinct pattern emerged.
The analysis revealed a measurable association between an individual’s history of depression and their amygdala response. Participants with a high recurrence of depressive episodes showed a heightened amygdala reaction to negative faces compared to healthy controls.
When the researchers looked at individuals actively experiencing a depressive episode, they found no distinct increase in brain activity compared to controls. This suggested that amygdala reactivity represents a long-term biological trait, rather than a temporary state reflecting current mood.
The researchers also wanted to know how medication might influence these brain signals. They noticed that a higher percentage of people in the severe recurrence group were taking antidepressants compared to those with a single past episode. They repeated their cross-sectional analysis, this time removing any participants who were actively taking antidepressant medications.
Excluding medicated individuals strengthened the observed differences between the healthy controls and the recurrent depression groups. The findings indicated that antidepressants might dampen the hyperactive amygdala signal associated with a history of recurrent depression. Because the medication reduced amygdala reactivity, including these participants in the initial data pool slightly masked the true extent of the brain changes.
To see how the brain changes over time, the team conducted a longitudinal analysis. They focused on a smaller group of participants who returned for a second brain scan roughly two and a half years after their initial visit. The researchers categorized these individuals based on whether they had suffered new depressive episodes between the two scans.
For this longitudinal evaluation, the team specifically analyzed people who were in remission during both of their imaging sessions. Participants who began the study with a history of just one depressive episode, but then experienced multiple new episodes before their second scan, exhibited an increase in amygdala reactivity over time.
This brain change supported the kindling theory. It suggests that new depressive episodes incrementally alter how the brain processes negative emotional information, leaving a biological mark even after symptoms fade.
The study relied on a large dataset, but the researchers noted that the effect sizes were relatively small. These findings do not mean that a functional MRI scan can be used to diagnose depression in a clinical setting right now. The results are not robust enough to predict an individual’s exact risk of a relapse based on a single brain scan.
The data collection methods also presented certain limitations. The study depended on participants accurately recalling their own mental health histories, which can introduce memory biases. People might misremember exactly how many distinct depressive episodes they experienced over the course of their lives.
The mental health questionnaires also combined treatments for nerves, anxiety, and depression into a single metric. Because of this, the researchers could not strictly isolate the effects of anxiety disorders from the effects of clinical depression. Future studies will need to track larger groups of symptomatic individuals over extended periods of time to untangle these variables.
Scientists hope that advancing neuroimaging techniques will eventually reduce the normal fluctuations seen in brain scans. Over time, mapping the biology of recurrent depression could help psychiatrists tailor treatments to a patient’s individual history, moving away from the current trial-and-error approach to prescribing medication.
The study, “Normative amygdala fMRI response during emotional processing as a trait of depressive symptoms in the UK Biobank,” was authored by Jerke J. van den Berg, Henricus G. Ruhé, Henk A. Marquering, Liesbeth Reneman, and Matthan W. A. Caan.
-------------------------------------------------
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #DepressionResearch #Amygdala #fMRI #Neuroimaging #KindlingTheory #UKBiobank #MentalHealthAwareness #BiomarkersInDepression #LongitudinalStudy #NeuroscienceAdvances
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DATE: September 11, 2026 at 12:00PM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Brain scans reveal how recurrent depression leaves a lasting mark on the amygdala
Brain scans reveal that elevated activity in the emotion-processing center is tied to a person’s history of recurrent depression, rather than their current mood. The large study, published in Psychological Medicine, suggests that each major depressive episode may leave a lasting biological mark that increases future vulnerability to the disease.
Major depressive disorder is a common psychiatric condition that affects millions of people worldwide. Currently, psychiatrists diagnose the condition based on clinical interviews and patient history. There are no biological markers, like a blood test or a brain scan, to guide treatment choices.
Functional magnetic resonance imaging, or fMRI, allows researchers to observe the brain in action by tracking blood-oxygen levels. When a brain region becomes active, it requires more oxygen, leading to localized changes in blood flow. The scanner detects these magnetic differences to map out neural activity.
Scientists often use this technology to study the amygdala, an almond-shaped structure deep inside the brain that processes fear and negative emotions. Early brain imaging research suggested that people with clinical depression have hyperactive amygdalae when looking at negative images. But a recent analysis of a massive dataset called the UK Biobank found no association between amygdala activity and current depression symptoms.
Jerke J. van den Berg, a biomedical researcher at the University of Amsterdam, and his colleagues designed a new study to better understand this discrepancy. They suspected that previous research might have missed the broader picture by only looking at a patient’s current mood. The researchers focused on a concept called the kindling theory.
The kindling theory proposes that an initial depressive episode makes the brain more sensitive to stress. After the brain has been sensitized by that first experience, it takes progressively less trauma to trigger a relapse. To test if the amygdala reflects this effect, the research team decided to look at a person’s lifetime history of depression, known as a trait, rather than their current symptoms, known as a state.
The researchers utilized data from the UK Biobank, a long-term population health study. They analyzed functional MRI scans from a subset of participants, totaling more than 11,000 individuals. While inside the scanner, participants completed a visual exercise called the Hariri task.
During the task, participants were shown a target image of an angry or fearful face at the top of a screen. They were then asked to select the matching face from two options at the bottom. This specific visual matching exercise is known to reliably stimulate the amygdala.
Brain activity can vary widely from person to person based on age, gender, and head movement during a scan. To account for this natural variation, the research team used a statistical technique called normative modeling. They analyzed scans from over 6,400 healthy participants to establish a baseline of expected amygdala activity. This works much like a pediatric growth chart, which maps out normal ranges for a child’s height and weight.
Next, the researchers evaluated how much the brain activity of nearly 5,000 other participants deviated from this baseline model. They categorized these individuals based on their self-reported mental health histories. The groups included healthy controls, people who had experienced a single depressive episode, those with moderate recurrence involving two to five episodes, and those with a high recurrence of six or more episodes.
For this initial cross-sectional analysis, the team focused strictly on participants who were currently in remission from their depression. The initial results were not statistically significant when the team analyzed the unaltered brain scans. However, once they applied the normative modeling technique to account for age and gender variations, a distinct pattern emerged.
The analysis revealed a measurable association between an individual’s history of depression and their amygdala response. Participants with a high recurrence of depressive episodes showed a heightened amygdala reaction to negative faces compared to healthy controls.
When the researchers looked at individuals actively experiencing a depressive episode, they found no distinct increase in brain activity compared to controls. This suggested that amygdala reactivity represents a long-term biological trait, rather than a temporary state reflecting current mood.
The researchers also wanted to know how medication might influence these brain signals. They noticed that a higher percentage of people in the severe recurrence group were taking antidepressants compared to those with a single past episode. They repeated their cross-sectional analysis, this time removing any participants who were actively taking antidepressant medications.
Excluding medicated individuals strengthened the observed differences between the healthy controls and the recurrent depression groups. The findings indicated that antidepressants might dampen the hyperactive amygdala signal associated with a history of recurrent depression. Because the medication reduced amygdala reactivity, including these participants in the initial data pool slightly masked the true extent of the brain changes.
To see how the brain changes over time, the team conducted a longitudinal analysis. They focused on a smaller group of participants who returned for a second brain scan roughly two and a half years after their initial visit. The researchers categorized these individuals based on whether they had suffered new depressive episodes between the two scans.
For this longitudinal evaluation, the team specifically analyzed people who were in remission during both of their imaging sessions. Participants who began the study with a history of just one depressive episode, but then experienced multiple new episodes before their second scan, exhibited an increase in amygdala reactivity over time.
This brain change supported the kindling theory. It suggests that new depressive episodes incrementally alter how the brain processes negative emotional information, leaving a biological mark even after symptoms fade.
The study relied on a large dataset, but the researchers noted that the effect sizes were relatively small. These findings do not mean that a functional MRI scan can be used to diagnose depression in a clinical setting right now. The results are not robust enough to predict an individual’s exact risk of a relapse based on a single brain scan.
The data collection methods also presented certain limitations. The study depended on participants accurately recalling their own mental health histories, which can introduce memory biases. People might misremember exactly how many distinct depressive episodes they experienced over the course of their lives.
The mental health questionnaires also combined treatments for nerves, anxiety, and depression into a single metric. Because of this, the researchers could not strictly isolate the effects of anxiety disorders from the effects of clinical depression. Future studies will need to track larger groups of symptomatic individuals over extended periods of time to untangle these variables.
Scientists hope that advancing neuroimaging techniques will eventually reduce the normal fluctuations seen in brain scans. Over time, mapping the biology of recurrent depression could help psychiatrists tailor treatments to a patient’s individual history, moving away from the current trial-and-error approach to prescribing medication.
The study, “Normative amygdala fMRI response during emotional processing as a trait of depressive symptoms in the UK Biobank,” was authored by Jerke J. van den Berg, Henricus G. Ruhé, Henk A. Marquering, Liesbeth Reneman, and Matthan W. A. Caan.
-------------------------------------------------
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #DepressionResearch #Amygdala #fMRI #Neuroimaging #KindlingTheory #UKBiobank #MentalHealthAwareness #BiomarkersInDepression #LongitudinalStudy #NeuroscienceAdvances
-
DATE: September 11, 2026 at 12:00PM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Brain scans reveal how recurrent depression leaves a lasting mark on the amygdala
Brain scans reveal that elevated activity in the emotion-processing center is tied to a person’s history of recurrent depression, rather than their current mood. The large study, published in Psychological Medicine, suggests that each major depressive episode may leave a lasting biological mark that increases future vulnerability to the disease.
Major depressive disorder is a common psychiatric condition that affects millions of people worldwide. Currently, psychiatrists diagnose the condition based on clinical interviews and patient history. There are no biological markers, like a blood test or a brain scan, to guide treatment choices.
Functional magnetic resonance imaging, or fMRI, allows researchers to observe the brain in action by tracking blood-oxygen levels. When a brain region becomes active, it requires more oxygen, leading to localized changes in blood flow. The scanner detects these magnetic differences to map out neural activity.
Scientists often use this technology to study the amygdala, an almond-shaped structure deep inside the brain that processes fear and negative emotions. Early brain imaging research suggested that people with clinical depression have hyperactive amygdalae when looking at negative images. But a recent analysis of a massive dataset called the UK Biobank found no association between amygdala activity and current depression symptoms.
Jerke J. van den Berg, a biomedical researcher at the University of Amsterdam, and his colleagues designed a new study to better understand this discrepancy. They suspected that previous research might have missed the broader picture by only looking at a patient’s current mood. The researchers focused on a concept called the kindling theory.
The kindling theory proposes that an initial depressive episode makes the brain more sensitive to stress. After the brain has been sensitized by that first experience, it takes progressively less trauma to trigger a relapse. To test if the amygdala reflects this effect, the research team decided to look at a person’s lifetime history of depression, known as a trait, rather than their current symptoms, known as a state.
The researchers utilized data from the UK Biobank, a long-term population health study. They analyzed functional MRI scans from a subset of participants, totaling more than 11,000 individuals. While inside the scanner, participants completed a visual exercise called the Hariri task.
During the task, participants were shown a target image of an angry or fearful face at the top of a screen. They were then asked to select the matching face from two options at the bottom. This specific visual matching exercise is known to reliably stimulate the amygdala.
Brain activity can vary widely from person to person based on age, gender, and head movement during a scan. To account for this natural variation, the research team used a statistical technique called normative modeling. They analyzed scans from over 6,400 healthy participants to establish a baseline of expected amygdala activity. This works much like a pediatric growth chart, which maps out normal ranges for a child’s height and weight.
Next, the researchers evaluated how much the brain activity of nearly 5,000 other participants deviated from this baseline model. They categorized these individuals based on their self-reported mental health histories. The groups included healthy controls, people who had experienced a single depressive episode, those with moderate recurrence involving two to five episodes, and those with a high recurrence of six or more episodes.
For this initial cross-sectional analysis, the team focused strictly on participants who were currently in remission from their depression. The initial results were not statistically significant when the team analyzed the unaltered brain scans. However, once they applied the normative modeling technique to account for age and gender variations, a distinct pattern emerged.
The analysis revealed a measurable association between an individual’s history of depression and their amygdala response. Participants with a high recurrence of depressive episodes showed a heightened amygdala reaction to negative faces compared to healthy controls.
When the researchers looked at individuals actively experiencing a depressive episode, they found no distinct increase in brain activity compared to controls. This suggested that amygdala reactivity represents a long-term biological trait, rather than a temporary state reflecting current mood.
The researchers also wanted to know how medication might influence these brain signals. They noticed that a higher percentage of people in the severe recurrence group were taking antidepressants compared to those with a single past episode. They repeated their cross-sectional analysis, this time removing any participants who were actively taking antidepressant medications.
Excluding medicated individuals strengthened the observed differences between the healthy controls and the recurrent depression groups. The findings indicated that antidepressants might dampen the hyperactive amygdala signal associated with a history of recurrent depression. Because the medication reduced amygdala reactivity, including these participants in the initial data pool slightly masked the true extent of the brain changes.
To see how the brain changes over time, the team conducted a longitudinal analysis. They focused on a smaller group of participants who returned for a second brain scan roughly two and a half years after their initial visit. The researchers categorized these individuals based on whether they had suffered new depressive episodes between the two scans.
For this longitudinal evaluation, the team specifically analyzed people who were in remission during both of their imaging sessions. Participants who began the study with a history of just one depressive episode, but then experienced multiple new episodes before their second scan, exhibited an increase in amygdala reactivity over time.
This brain change supported the kindling theory. It suggests that new depressive episodes incrementally alter how the brain processes negative emotional information, leaving a biological mark even after symptoms fade.
The study relied on a large dataset, but the researchers noted that the effect sizes were relatively small. These findings do not mean that a functional MRI scan can be used to diagnose depression in a clinical setting right now. The results are not robust enough to predict an individual’s exact risk of a relapse based on a single brain scan.
The data collection methods also presented certain limitations. The study depended on participants accurately recalling their own mental health histories, which can introduce memory biases. People might misremember exactly how many distinct depressive episodes they experienced over the course of their lives.
The mental health questionnaires also combined treatments for nerves, anxiety, and depression into a single metric. Because of this, the researchers could not strictly isolate the effects of anxiety disorders from the effects of clinical depression. Future studies will need to track larger groups of symptomatic individuals over extended periods of time to untangle these variables.
Scientists hope that advancing neuroimaging techniques will eventually reduce the normal fluctuations seen in brain scans. Over time, mapping the biology of recurrent depression could help psychiatrists tailor treatments to a patient’s individual history, moving away from the current trial-and-error approach to prescribing medication.
The study, “Normative amygdala fMRI response during emotional processing as a trait of depressive symptoms in the UK Biobank,” was authored by Jerke J. van den Berg, Henricus G. Ruhé, Henk A. Marquering, Liesbeth Reneman, and Matthan W. A. Caan.
-------------------------------------------------
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #DepressionResearch #Amygdala #fMRI #Neuroimaging #KindlingTheory #UKBiobank #MentalHealthAwareness #BiomarkersInDepression #LongitudinalStudy #NeuroscienceAdvances
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DATE: September 2, 2026 at 02:00PM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Heavy caffeine drinkers sleep less but have deeper sleep, study finds
URL: https://www.psypost.org/heavy-caffeine-drinkers-sleep-less-but-have-deeper-sleep-study-finds/
A recent study using UK Biobank and HypnoLaus cohort data found that individuals drinking four or more caffeinated beverages per day tend to have shorter total sleep time compared to those drinking three or fewer caffeinated drinks per day. While statistical models estimated reductions in sleep length varying from 11 to 229 minutes, the researchers noted that the highest estimates were likely unrealistic, with more reliable causal matching pointing to a reduction of about 11 to 13 minutes per night. The paper was published in the Journal of Psychopharmacology.
Caffeine has been part of human diets for centuries. It is now considered the most widely consumed psychoactive substance in the world. Caffeine occurs naturally in foods and beverages such as coffee, tea, and chocolate. It is added to many energy drinks. Because of this, the regular consumption of caffeine is extremely common.
When intentionally consuming caffeine-rich beverages, people generally do it to feel more alert and energetic, to improve concentration, or to cope with stress. They also consume caffeine-rich beverages because they enjoy their taste and smell, and because these drinks are parts of social customs that facilitate social interaction (e.g. drinking coffee or tea). Because caffeine use is so widespread, its possible effects on health have attracted considerable scientific interest.
One particularly important topic related to caffeine consumption is sleep. Sleep supports essential processes ranging from memory and emotional regulation to immune and cardiovascular functioning. However, studies have shown that caffeine can make it harder to fall asleep, that it shortens sleep duration, reduces sleep efficiency, and alters the depth and structure of sleep.
Moreover, studies looking for substances that help people avoid sleepiness and stay awake regularly examine the effects of caffeine. However, much of this evidence comes from controlled laboratory experiments in which regular caffeine users temporarily abstain before receiving caffeine or consume caffeine as an experimental treatment, situations that may differ substantially from everyday consumption.
Study author Benjamin Stucky and his colleagues conducted a Mendelian randomization study with the goal of estimating the causal effect of habitual caffeine intake on sleep quality. A Mendelian randomization study uses naturally occurring genetic differences associated with a studied characteristic to test whether that characteristic is likely to have a causal effect on an outcome. In this case, study authors wanted to estimate the effects of different habitual caffeine consumption levels on both objective and subjective sleep characteristics recorded at home.
The study authors used data from the UK Biobank and the HypnoLaus cohort. The UK Biobank is a very large open access prospective study conducted in the UK involving a total of 485,511 participants. The HypnoLaus cohort is a population-based study conducted in Lausanne, Switzerland. Its dataset contains data on caffeine intake, genetic data, and objective sleep characteristics data collected using at-home polysomnography (a comprehensive sleep study that records brain waves, oxygen levels, heart rate, and breathing) for 1,702 participants. The polysomnography data were collected during one night.
The study authors used UK Biobank data to estimate the association between various gene variants and caffeine intake, and the HypnoLaus data to estimate the association between each gene variant and objective and subjective measures of sleep quality. Aside from genetic data, study authors used data on the consumption of caffeinated beverages, expressed as the number of cups per day, and data on sleep characteristics.
The sleep characteristics included total sleep time, sleep latency (the time between lights-off and N2 sleep, the second stage of non-rapid-eye-movement sleep, which is a light-to-moderate stage characterized by slower brain activity), number of awakenings during the night, percentage of REM sleep per total sleep time, and some characteristics of EEG (electroencephalogram) activity during sleep, which measures the brain’s electrical signals. Participants also completed self-report assessments of sleep quality (the Pittsburgh Sleep Quality Index), daytime sleepiness (the Epworth Sleepiness Scale) and morningness-eveningness (the Morningness-Eveningness Questionnaire).
The results showed that participants’ self-rated sleep quality and morningness-eveningness (i.e., whether they are an evening or a morning person) did not depend on the consumption of caffeinated beverages. However, statistical models revealed that four or more caffeinated beverages consumed per day shorten total sleep time compared to three or fewer caffeinated drinks per day.
The estimated reduction in sleep length varied from 11 to 229 minutes, though the researchers caution that the higher end of this range is an overestimation caused by statistical uncertainty in the genetic modeling. Interestingly, the shorter sleep in high habitual caffeine consumers was characterized by increased non-rapid-eye-movement sleep depth (as indicated by a specific pattern of electrical brain activity known as delta power).
“The data show that high habitual caffeine intake alters the characteristics of sleep in the general population, while sparing the major physiological principles of sleep-wake regulation possibly due to adaptation,” the study authors concluded. In other words, while people slept less, their bodies compensated by sleeping more deeply, maintaining the natural homeostatic balance of sleep.
The study contributes to the scientific understanding of the likely effects of caffeine on sleep quality. However, it should be noted that the key piece of data the study was based on the number of cups of caffeinated beverages consumed per day was self-reported, leaving room for recall bias and estimation errors to have affected the results. Additionally, the study did not take into account the type of caffeinated beverage consumed, even though different beverages can contain substantially different amounts of caffeine. It also did not consider dietary sources of caffeine that are not beverages.
The paper, “Community-based causal evidence that high habitual caffeine consumption alters distinct polysomnography-derived sleep variables,” was authored by Benjamin Stucky, Leonard Henckel, Marloes H. Maathuis, José Haba-Rubio, Pedro Marques-Vidal, Francesca Siclari, Raphaël Heinzer, and Hans-Peter Landolt.
URL: https://www.psypost.org/heavy-caffeine-drinkers-sleep-less-but-have-deeper-sleep-study-finds/
-------------------------------------------------
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #CaffeineAndSleep #SleepQuality #CaffeineConsumption #SleepDepth #HypnoLaus #UKBiobank #SleepScience #NightTimeRest #CircadianHealth #WakefulnessToRest