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1000 results for “psychxr”
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19:00 Kefirowe poniedziałki / #pubrock, #ska, #szanty
20:00 garaże gitary / #noiserock, #garagerock, #psychrock + wiersz @dobrochna
https://pawarotaradio.pl/ -
Dziś #audycje
17:00 Dredaktorka Kasia #hardcore #punk
19:00 Kefirowe poniedziałki #pubrock #szanty
20:00 garaże gitary #noiserock #psychrock -
Dziś #audycje
17:00 Dredaktorka Kasia #hardcore #punk
19:00 Kefirowe poniedziałki #pubrock #szanty
20:00 garaże gitary #noiserock #psychrock -
The gang is back again 😏🤩🦆
Check out "Psyche", "Psyche Remixed", "The Medication Remixes", "Reconstrucdead", the "Isolation"-demos and soundtrack stuff here... more news coming soon:
www.linktr.ee/ARL3CCH1NO#ARL3CCH1NO #Psyche #PsycheRemixed #remix #remixculture #soundtrack #metal #postrock #industrial #industrialmetal #electro #triphop #synth #pop #postpunk #arsinetibe #frylee #dilutedmind #medication #lindenblattrecords #ducktales #vinyloftheweek #vinyl #vinyllovers
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The gang is back again 😏🤩🦆
Check out "Psyche", "Psyche Remixed", "The Medication Remixes", "Reconstrucdead", the "Isolation"-demos and soundtrack stuff here... more news coming soon:
www.linktr.ee/ARL3CCH1NO#ARL3CCH1NO #Psyche #PsycheRemixed #remix #remixculture #soundtrack #metal #postrock #industrial #industrialmetal #electro #triphop #synth #pop #postpunk #arsinetibe #frylee #dilutedmind #medication #lindenblattrecords #ducktales #vinyloftheweek #vinyl #vinyllovers
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La meva #CançóDelDia per al divendres 31 de març és aquesta dels #Trau #SantBoiDeLlobregat #Mod #PopRock #PsychRock 🥾 !
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CW: implied baby animal death
Krowk finds a hole in the ground and helps herself to the easy meals within.
#psychoraptor #hyenas #monster #ibispaint -
August 12th is National Vinyl Record Day (apparently) so I grabbed all the vinyl I could find in my house. It's not a lot. I used to have many crates full. But after many moves, I thinned the collection down to nearly nothing, as I do digital music mostly now (I have no turntable anymore either). But sometimes, I grab a couple. Bought the bottom row here recently. Odd I can't find my copy of Telekon. Pretty sure I still have that one somewhere. I hope so. And wow, I have two copies of Green Thoughts, one signed, one not. Check out that picture disc. I should get better photos of it eventually. It's rad.
#vinyl #NationalVinylRecordDay #Smithereens #TheSmithereens #80s #80smusic #PictureDisc #PictureDiscs #sabbath #BlackSabbath #Hendrix #JimiHendrix #Coltrane #JohnColtrane #jazz #FreeJazz #metal #psych #PsychRock #records #LPs
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And finally, tonight: freakin ridiculous double bill of the heaviest heavy-duty psych rock. Minami Deutsch heavy jammy and Earthless just relentless and overwhelmingly heavy, like getting punched in the face for 80 minutes. In the best way. Killer killer show at Elsewhere.
#nycfreaks #livemusic #brooklyn #bushwick #psychrock #heavy #tappedin
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Dziś #audycje
17:00 Dredaktorka Kasia #hardcore #punk
19:00 Kefirowe poniedziałki #pubrock #szanty
20:00 garaże gitary #noiserock #psychrock -
If Bob Dylan and Beck got together and formed a weird, lo-fi garage rock band that played rough, rowdy, raw, catchy songs that were recorded however & randomly cut off at the ends of em, they'd probably sound something like New Orleans' TWISTED TEENS. Bummed I missed this fantastic self-titled LP of theirs last year, but at least I have it #NowPlaying. Also Cake, Sonics or Wild Pink vibes sometimes, maybe. I suspect @jeffrey may dig.
https://cpnpc.bandcamp.com/album/twisted-teens
#GarageRock #PsychRock #NewOrleans #NewOrleansBands #LouisianaBands #punk #PunkRock
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If Bob Dylan and Beck got together and formed a weird, lo-fi garage rock band that played rough, rowdy, raw, catchy songs that were recorded however & randomly cut off at the ends of em, they'd probably sound something like New Orleans' TWISTED TEENS. Bummed I missed this fantastic self-titled LP of theirs last year, but at least I have it #NowPlaying. Also Cake, Sonics or Wild Pink vibes sometimes, maybe. I suspect @jeffrey may dig.
https://cpnpc.bandcamp.com/album/twisted-teens
#GarageRock #PsychRock #NewOrleans #NewOrleansBands #LouisianaBands #punk #PunkRock
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If Bob Dylan and Beck got together and formed a weird, lo-fi garage rock band that played rough, rowdy, raw, catchy songs that were recorded however & randomly cut off at the ends of em, they'd probably sound something like New Orleans' TWISTED TEENS. Bummed I missed this fantastic self-titled LP of theirs last year, but at least I have it #NowPlaying. Also Cake, Sonics or Wild Pink vibes sometimes, maybe. I suspect @jeffrey may dig.
https://cpnpc.bandcamp.com/album/twisted-teens
#GarageRock #PsychRock #NewOrleans #NewOrleansBands #LouisianaBands #punk #PunkRock
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https://youtu.be/1wajl4oCw9Q?si=gf2h0PyE8-3fgTQ5
La meva #CançóDelDia per al dijous 26 de desembre és aquesta de #TheApplesInStereo #Denver #IndieRock #PowerPop #PsychRock 🎢!
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https://youtu.be/1wajl4oCw9Q?si=gf2h0PyE8-3fgTQ5
La meva #CançóDelDia per al dijous 26 de desembre és aquesta de #TheApplesInStereo #Denver #IndieRock #PowerPop #PsychRock 🎢!
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https://youtu.be/1wajl4oCw9Q?si=gf2h0PyE8-3fgTQ5
La meva #CançóDelDia per al dijous 26 de desembre és aquesta de #TheApplesInStereo #Denver #IndieRock #PowerPop #PsychRock 🎢!
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https://youtu.be/1wajl4oCw9Q?si=gf2h0PyE8-3fgTQ5
La meva #CançóDelDia per al dijous 26 de desembre és aquesta de #TheApplesInStereo #Denver #IndieRock #PowerPop #PsychRock 🎢!
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DATE: May 12, 2026 at 07:49AM
SOURCE: SOCIALPSYCHOLOGY.ORGTITLE: Israel Legalizes Death Penalty for Those Guilty of Worst Oct. 7 Crimes
Source: United Press International - Health News
Israel's Knesset unanimously passed a death penalty law for Palestinians found guilty of genocide in the October 7, 2023, attacks on the country. Lawmakers on Monday voted 93-0 for the legislation, which also establishes a special military court to try about 300 suspects who were alleged to have been involved and were detained by security forces inside Israel. More than a fifth of Knesset Members either abstained or were absent for the vote.
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DAILY EMAIL DIGEST: Email [email protected] -- no subject or message needed.
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Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
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It's primitive... but it works... mostly...
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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #Israel #DeathPenalty #Genocide #October7 #Knesset #IsraelLegalizes #MilitaryCourt #Palestinians #SecurityForces #LegalNews
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DATE: May 12, 2026 at 07:49AM
SOURCE: SOCIALPSYCHOLOGY.ORGTITLE: Israel Legalizes Death Penalty for Those Guilty of Worst Oct. 7 Crimes
Source: United Press International - Health News
Israel's Knesset unanimously passed a death penalty law for Palestinians found guilty of genocide in the October 7, 2023, attacks on the country. Lawmakers on Monday voted 93-0 for the legislation, which also establishes a special military court to try about 300 suspects who were alleged to have been involved and were detained by security forces inside Israel. More than a fifth of Knesset Members either abstained or were absent for the vote.
-------------------------------------------------
DAILY EMAIL DIGEST: Email [email protected] -- no subject or message needed.
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
NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
EMAIL DAILY DIGEST OF RSS FEEDS -- SUBSCRIBE: http://subscribe-article-digests.clinicians-exchange.org
READ ONLINE: http://read-the-rss-mega-archive.clinicians-exchange.org
It's primitive... but it works... mostly...
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #Israel #DeathPenalty #Genocide #October7 #Knesset #IsraelLegalizes #MilitaryCourt #Palestinians #SecurityForces #LegalNews
-
DATE: May 12, 2026 at 07:49AM
SOURCE: SOCIALPSYCHOLOGY.ORGTITLE: Israel Legalizes Death Penalty for Those Guilty of Worst Oct. 7 Crimes
Source: United Press International - Health News
Israel's Knesset unanimously passed a death penalty law for Palestinians found guilty of genocide in the October 7, 2023, attacks on the country. Lawmakers on Monday voted 93-0 for the legislation, which also establishes a special military court to try about 300 suspects who were alleged to have been involved and were detained by security forces inside Israel. More than a fifth of Knesset Members either abstained or were absent for the vote.
-------------------------------------------------
DAILY EMAIL DIGEST: Email [email protected] -- no subject or message needed.
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
NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
EMAIL DAILY DIGEST OF RSS FEEDS -- SUBSCRIBE: http://subscribe-article-digests.clinicians-exchange.org
READ ONLINE: http://read-the-rss-mega-archive.clinicians-exchange.org
It's primitive... but it works... mostly...
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #Israel #DeathPenalty #Genocide #October7 #Knesset #IsraelLegalizes #MilitaryCourt #Palestinians #SecurityForces #LegalNews
-
DATE: May 12, 2026 at 07:49AM
SOURCE: SOCIALPSYCHOLOGY.ORGTITLE: Israel Legalizes Death Penalty for Those Guilty of Worst Oct. 7 Crimes
Source: United Press International - Health News
Israel's Knesset unanimously passed a death penalty law for Palestinians found guilty of genocide in the October 7, 2023, attacks on the country. Lawmakers on Monday voted 93-0 for the legislation, which also establishes a special military court to try about 300 suspects who were alleged to have been involved and were detained by security forces inside Israel. More than a fifth of Knesset Members either abstained or were absent for the vote.
-------------------------------------------------
DAILY EMAIL DIGEST: Email [email protected] -- no subject or message needed.
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
NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
EMAIL DAILY DIGEST OF RSS FEEDS -- SUBSCRIBE: http://subscribe-article-digests.clinicians-exchange.org
READ ONLINE: http://read-the-rss-mega-archive.clinicians-exchange.org
It's primitive... but it works... mostly...
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #Israel #DeathPenalty #Genocide #October7 #Knesset #IsraelLegalizes #MilitaryCourt #Palestinians #SecurityForces #LegalNews
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DATE: May 13, 2026 at 10:00AM
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: The human brain processes the passage of time across three distinct stages
URL: https://www.psypost.org/the-human-brain-processes-the-passage-of-time-across-three-distinct-stages/
A recent study mapping the human brain reveals that our perception of time does not happen all at once, but rather unfolds across a series of distinct physical processing stages. As visual information travels from the back of the brain to the front, different groups of neurons handle specific parts of the timing process, ultimately creating our subjective experience of how long an event lasts. These findings were published in the journal PLOS Biology.
For decades, researchers have mapped out a broad network of brain regions that become active when people estimate how much time has passed. Studies involving both animals and humans have shown that certain groups of neurons respond to specific durations of time.
These specialized cells are often arranged in topographic maps across the brain. In these maps, neurons that prefer similar lengths of time are located physically close to one another on the folded outer layer of the brain, known as the cerebral cortex.
Despite knowing where these timing regions are located, researchers have struggled to understand exactly how they work together. It has been unclear how a physical feature like the duration of a flashing light is transformed into an abstract feeling of passing time.
To piece together this puzzle, neuroscientist Valeria Centanino and her colleagues Gianfranco Fortunato and Domenica Bueti at the International School for Advanced Studies in Italy conducted an imaging study. They wanted to track how the properties of time-tracking neurons change as signals move through the brain.
The researchers recruited thirteen healthy volunteers to perform a visual categorization task. First, the participants were trained to memorize a specific reference duration of half a second, which they would use as a mental benchmark.
During the main experiment, the volunteers watched a series of blurry, flickering circles appear on a screen. Each circle stayed on the screen for a random amount of time, ranging between two-tenths of a second and eight-tenths of a second.
After each circle disappeared, the participants pressed a button to indicate whether the shape was visible for a longer or shorter time than their internalized reference. While the volunteers performed this task, the researchers recorded their brain activity using an ultra-high-field functional magnetic resonance imaging scanner.
Functional magnetic resonance imaging is a technology that measures brain activity by detecting changes in blood flow. When a specific area of the brain works harder, it requires more oxygen, and the scanner tracks the oxygen-rich blood rushing to that region.
The scanner used in this study operates at a magnetic field strength of seven Tesla. This is much stronger than standard hospital scanners, allowing the team to capture highly detailed images of the brain surface.
With these detailed images, Centanino and her team modeled the behavior of individual populations of neurons. They looked for unimodal tuning, which happens when a group of brain cells responds most strongly to one specific stimulus and less strongly to anything else.
The researchers found that the way neurons tuned into time changed depending on their location in the brain. They identified three distinct processing stages that form a hierarchy of time perception.
The first stage occurs in the occipital visual areas, located at the back of the head where the brain first processes sight. Here, the neurons acted like simple timers that gathered sensory information from the eyes.
In these visual areas, the brain cells showed a strong preference for the longest durations. Their activity increased steadily the longer the shape stayed on the screen, encoding the physical length of the visual event.
The second stage takes place in the parietal and premotor regions, which sit near the top and middle of the brain. In these areas, the researchers observed a complete topographic map of time.
Neurons in these middle regions were tuned to the entire range of presented durations. Some groups of cells responded only to brief flashes, while others responded only to medium or long appearances.
These specialized cells were neatly organized into clusters based on their preferred durations. This suggests that the parietal and premotor regions are responsible for reading out the specific duration of the visual event, allowing the brain to track exactly how much time just passed.
The final stage happens in the frontal regions of the brain, including the anterior insula and the rostral supplementary motor area. These areas are heavily involved in complex thought, decision making, and self-awareness.
In these frontal areas, the neurons did not represent the full range of time. Instead, they showed a strong preference for the middle of the time range, which was close to the half-second reference duration the participants had memorized.
This central preference represented the boundary that participants used to decide whether a duration was short or long. By tracking the exact time at which participants switched their answers from “shorter” to “longer,” the researchers calculated each person’s unique subjective boundary.
The activity in these frontal regions matched up perfectly with these subjective boundaries. This indicates that the frontal areas take the raw measurement of time and turn it into a personal, abstract categorization.
“Our results show that time perception is not a unitary process, but the outcome of multiple processing stages distributed across the cerebral cortex,” the authors wrote. “Each stage contributes differently, from encoding physical duration to constructing the subjective experience of time.”
To interpret the brain scan data, the research team used a mathematical approach called population receptive field modeling. This technique allowed them to estimate the exact time preference of neurons in tiny sections of the brain.
By mapping these preferences, the team could see exactly which brain folds contained neurons tuned to brief moments and which contained neurons tuned to longer stretches. They also evaluated how these preferences clustered together physically.
In the visual areas at the back of the brain, the physical clustering of time-sensitive cells was relatively weak. However, in the parietal and frontal regions, neurons with the exact same time preferences were grouped tightly together.
This tight grouping implies that organizing time into structured maps becomes more important as the brain moves from simply seeing an event to making a decision about it. The brain physically structures its cells to handle the demands of categorizing information.
Additionally, the researchers noticed a difference between the left and right sides of the brain in the motor areas, which control physical movement. Because the participants used their right hands to press the response buttons, the motor areas in the left hemisphere showed distinct activity patterns.
These motor areas consistently showed a preference for the shortest possible durations. The researchers suspect this was a byproduct of the brain preparing to make a physical movement as soon as the shape appeared, rather than a true measurement of passing time.
Another surprising detail emerged in the supplementary motor area, a part of the brain near the top of the head that helps plan movements. The researchers found a clear split in how the front and back sections of this region handled time.
The back half of the supplementary motor area contained cells tuned to the entire range of durations, reading out the time like a stopwatch. The front half contained the boundary cells that helped categorize the time as short or long.
This split within a single brain region had been seen previously in animal studies. Finding it in humans suggests that this specific area might act as a central hub where actual time and subjective time are integrated.
While this imaging study provides a detailed roadmap of visual time perception, it does have a few limitations. The research focused entirely on the cerebral cortex, which is the brain’s folded outer layer.
The team did not measure activity in deeper brain structures or the cerebellum, which are also known to play roles in processing time. Future studies will need to look at these deeper regions to see how they interact with the cortical maps.
The experiment was also restricted to visual time perception. It remains an open question whether the brain uses this exact same pathway to process the duration of sounds or physical touches.
To fully understand the boundary neurons in the frontal lobe, the researchers suggest conducting experiments that test multiple different reference durations. This would reveal whether the boundary cells physically shift their preferences when the rules of the task change.
Despite these limitations, the research offers a clearer picture of how a simple flash of light turns into a conscious experience of time. It reveals that our sense of time is a collaborative effort, passed along a specialized assembly line inside the head.
The study, “Neuronal populations across the cortex underlie discrete, categorical, and subjective representations of visual durations,” was authored by Valeria Centanino, Gianfranco Fortunato, and Domenica Bueti.
URL: https://www.psypost.org/the-human-brain-processes-the-passage-of-time-across-three-distinct-stages/
-------------------------------------------------
DAILY EMAIL DIGEST: Email [email protected] -- no subject or message needed.
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
NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
EMAIL DAILY DIGEST OF RSS FEEDS -- SUBSCRIBE: http://subscribe-article-digests.clinicians-exchange.org
READ ONLINE: http://read-the-rss-mega-archive.clinicians-exchange.org
It's primitive... but it works... mostly...
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #TimePerception #BrainTimeProcessing #CorticalTimeMaps #NeuronalTiming #VisualTimeProcessing #PopulationalFieldModeling #PLOSBiology #Neuroscience #TemporalEncoding #BrainHierarchy
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DATE: May 14, 2026 at 10:00AM
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: Real-world evidence shows generative AI is making human creative output more uniform
Using artificial intelligence for creative tasks tends to make human output more uniform on a collective level. A recent preprint study provides evidence that while these tools might boost individual performance, they contribute to an overall reduction in the diversity of ideas across different users. This widespread reliance on automated assistance could lead to a narrower range of concepts in collaborative environments.
Generative artificial intelligence refers to computer programs capable of creating new text, images, or other media based on user instructions. The most common of these tools rely on large language models. Developers build these models by feeding them billions of sentences from the internet, allowing the software to recognize patterns and predict how words should follow one another.
Since many users interact with similar systems trained on overlapping data, scientists have raised concerns about how this technology shapes human thought. Researchers Alwin de Rooij, assistant professor in creativity research at Tilburg University and associate professor at Avans University of Applied Sciences, and Michael Mose Biskjaer, associate professor in design creativity and innovation at Aarhus University, designed a new study to assess these concerns. They noticed that previous research often focused on how these tools help individuals work faster or overcome temporary mental blocks.
They wanted to know if this individual assistance comes at a collective cost. “There are growing concerns that using Generative AI may lead people toward similar creative ideas,” the authors explained. “While AI can enhance creativity at the individual level, these benefits might come at a cost for creativity at a collective, or even societal, level.”
The authors sought to answer whether generative software makes people think alike. “We sought to address this by conducting a systematic review and meta-analysis of 19 empirical studies,” they noted. “More concretely, we wanted to examine whether and to what extent generative AI use is associated with convergence at the level of creative output, such as people’s ideas, designs, and creative writing.”
A meta-analysis is a statistical technique that combines the results of multiple independent studies to find common patterns or overall trends. By pooling data from various experiments, scientists can draw more robust conclusions than they could from a single test. The authors searched academic databases for studies published between 2022 and early 2026.
This time frame covers the period following the public release of popular chatbots, capturing the first wave of empirical research on this topic. The researchers selected 18 eligible articles containing 19 distinct experimental studies. These studies provided a total of 61 individual effect sizes, which are mathematical values indicating the strength of a specific phenomenon.
To be included in the analysis, the original experiments had to compare humans working with generative software against humans working alone. The original studies measured homogenization using several techniques. Many relied on advanced text analysis tools that translate written responses into mathematical coordinates.
This process allows computers to measure the semantic distance between words, essentially calculating how closely related different ideas are to one another. Other studies used human experts to rate the variety of meanings produced by participants. The analysis revealed a statistically significant homogenization effect associated with the use of artificial intelligence.
When people co-created with these systems, their final products tended to be more similar to the work of other users. “The meta-analysis shows that using generative AI can indeed lead people to think alike,” the authors noted. “Across individuals, AI use tends to make ideas, designs, and creative texts more similar to one another.”
“This suggests that AI may contribute to a form of homogenization of creative thought at the collective level,” they continued. “Importantly, this does not necessarily reflect a failure of human-AI co-creation but may instead be an inherent feature of how these systems currently support creative work at scale.”
The scientists also evaluated whether the type of task influenced the degree of uniformity. They categorized the experiments into four groups, which included divergent thinking, idea generation, writing, and visual art. Divergent thinking tasks are highly open-ended exercises, such as asking someone to list creative uses for a paperclip.
Idea generation tasks provide more specific constraints, such as asking for solutions to improve public transportation. The analysis showed that the homogenization effect was strongest in the idea generation tasks. Because these exercises require specific solutions to defined problems, users likely rely more heavily on the predictable suggestions provided by the computer algorithms.
The researchers did not find strong statistical evidence for differences among the other three categories, suggesting that open-ended tasks lead to less convergence. They also checked if these patterns only happen in highly controlled laboratory settings. The authors compared traditional laboratory experiments with real-world scenarios, such as analyzing published essays and visual artworks created before and after the widespread adoption of automated writing tools.
The analysis of these real-world conditions showed a small but significant reduction in idea diversity. “In many ways, the findings resemble classic fixation effects from the psychology literature, where exposure to examples constrains later thinking, but here they appear amplified by the scale and synchronicity of generative AI model use,” the researchers stated. “This homogenization effect was observed not only in controlled lab studies but also in real-world quasi-experiments. This suggests that it is not merely a lab-based phenomenon, but a practical concern affecting concrete creative processes and practices.”
De Rooij and Biskjaer also investigated whether this narrowing of ideas persists after a person stops using the software. They isolated a subset of studies that tested participants on new creative tasks after their initial interaction with the computer models. The results suggest that the homogenization effect carries over into these subsequent activities.
“The findings also provide preliminary evidence that homogenization effects may persist beyond moments of direct AI use,” the researchers told PsyPost. “In other words, interacting with these generative AI systems may shape how people think and generate ideas even after the interaction has ended. This potential ‘rub-off’ effect on creative cognition warrants further research and is something we would like to explore in more depth.”
These results closely align with another recent study published in the journal PNAS Nexus. Scientists Emily Wenger and Yoed N. Kenett tested how large language models affect human creativity by evaluating 22 different commercial chatbots. They recruited 102 human participants to complete a series of verbal creativity tests, including the alternative uses task, and then asked the chatbots to complete the exact same assignments.
Wenger and Kenett found that individual language models performed at or slightly above the level of the average human on most exercises. When viewed in isolation, a single chatbot provided highly original and creative responses. However, when the scientists compared all the responses from the different models, a stark pattern of similarity emerged.
Across all tasks, the computer programs produced answers that were significantly more alike than the answers provided by the human participants. Both sets of researchers point to similar underlying mechanisms for this phenomenon. Because the major technology companies train their models on massive, overlapping datasets scraped from the internet, the programs naturally gravitate toward the most statistically common word associations.
When thousands of people use these tools to generate ideas, the software acts as a semantic anchor. The models pull human users toward a shared set of typical concepts, reducing the overall variety of ideas. Wenger and Kenett attempted to fix this issue by adjusting the internal settings of the chatbots to force more random text generation, but this caused the models to produce nonsensical sentences.
Readers should avoid interpreting these findings as proof that human beings are becoming entirely uncreative. De Rooij and Biskjaer note that the reduction in collective diversity does not equal a total loss of individual ability. “A key point is that our findings do not show that using AI reduces creativity,” the researchers emphasized.
“Rather, they point to a shift in where and how creative diversity occurs, and where it may be constrained,” the authors said. “Individual output can improve in creative quality while becoming more similar across people. While these effects are often subtle in single instances, they may become meaningful when considered at the scale at which generative AI is now being used.”
The authors point out some limitations to their current analysis. The review primarily focuses on text-based tools and large language models, meaning the findings might not apply to other types of computer systems. For instance, adaptive machine learning programs or tools used for music composition were not adequately represented in the available data.
This restricts how broadly the scientific community can apply these conclusions across different artistic domains. Additionally, the analyses regarding long-term persistence and real-world applications relied on relatively small groups of studies. The limited data makes these specific conclusions tentative and open to revision.
Future research should explore different forms of human and machine collaboration over extended periods of time. “An important next step is rethinking how generative AI systems are designed and used in creative contexts to mitigate homogenization effects,” the authors noted. “This includes exploring alternative workflows, interaction designs, and creative strategies that sustain diversity rather than encourage early convergence.”
“One step in this direction has already been taken by mapping creative strategies for working with generative AI and machine learning, based on analyses of AI art practices,” they added, referencing a recently published article outlining this approach. “We believe these strategies can transfer to other creative domains.”
The preprint study, “Does Generative AI Make Us Think Alike? A Systematic Review and Meta-Analysis of Homogenization Effects in Human-AI Co-Creation,” was authored by Alwin de Rooij and Michael Mose Biskjaer.
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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #GenerativeAI #CreativityDiversity #AICoCreation #Homogenization #CreativeThinking #AIImpact #CreativeDiversity #LLMs #TechEthics #InnovationScience
-
DATE: May 14, 2026 at 10:00AM
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: Real-world evidence shows generative AI is making human creative output more uniform
Using artificial intelligence for creative tasks tends to make human output more uniform on a collective level. A recent preprint study provides evidence that while these tools might boost individual performance, they contribute to an overall reduction in the diversity of ideas across different users. This widespread reliance on automated assistance could lead to a narrower range of concepts in collaborative environments.
Generative artificial intelligence refers to computer programs capable of creating new text, images, or other media based on user instructions. The most common of these tools rely on large language models. Developers build these models by feeding them billions of sentences from the internet, allowing the software to recognize patterns and predict how words should follow one another.
Since many users interact with similar systems trained on overlapping data, scientists have raised concerns about how this technology shapes human thought. Researchers Alwin de Rooij, assistant professor in creativity research at Tilburg University and associate professor at Avans University of Applied Sciences, and Michael Mose Biskjaer, associate professor in design creativity and innovation at Aarhus University, designed a new study to assess these concerns. They noticed that previous research often focused on how these tools help individuals work faster or overcome temporary mental blocks.
They wanted to know if this individual assistance comes at a collective cost. “There are growing concerns that using Generative AI may lead people toward similar creative ideas,” the authors explained. “While AI can enhance creativity at the individual level, these benefits might come at a cost for creativity at a collective, or even societal, level.”
The authors sought to answer whether generative software makes people think alike. “We sought to address this by conducting a systematic review and meta-analysis of 19 empirical studies,” they noted. “More concretely, we wanted to examine whether and to what extent generative AI use is associated with convergence at the level of creative output, such as people’s ideas, designs, and creative writing.”
A meta-analysis is a statistical technique that combines the results of multiple independent studies to find common patterns or overall trends. By pooling data from various experiments, scientists can draw more robust conclusions than they could from a single test. The authors searched academic databases for studies published between 2022 and early 2026.
This time frame covers the period following the public release of popular chatbots, capturing the first wave of empirical research on this topic. The researchers selected 18 eligible articles containing 19 distinct experimental studies. These studies provided a total of 61 individual effect sizes, which are mathematical values indicating the strength of a specific phenomenon.
To be included in the analysis, the original experiments had to compare humans working with generative software against humans working alone. The original studies measured homogenization using several techniques. Many relied on advanced text analysis tools that translate written responses into mathematical coordinates.
This process allows computers to measure the semantic distance between words, essentially calculating how closely related different ideas are to one another. Other studies used human experts to rate the variety of meanings produced by participants. The analysis revealed a statistically significant homogenization effect associated with the use of artificial intelligence.
When people co-created with these systems, their final products tended to be more similar to the work of other users. “The meta-analysis shows that using generative AI can indeed lead people to think alike,” the authors noted. “Across individuals, AI use tends to make ideas, designs, and creative texts more similar to one another.”
“This suggests that AI may contribute to a form of homogenization of creative thought at the collective level,” they continued. “Importantly, this does not necessarily reflect a failure of human-AI co-creation but may instead be an inherent feature of how these systems currently support creative work at scale.”
The scientists also evaluated whether the type of task influenced the degree of uniformity. They categorized the experiments into four groups, which included divergent thinking, idea generation, writing, and visual art. Divergent thinking tasks are highly open-ended exercises, such as asking someone to list creative uses for a paperclip.
Idea generation tasks provide more specific constraints, such as asking for solutions to improve public transportation. The analysis showed that the homogenization effect was strongest in the idea generation tasks. Because these exercises require specific solutions to defined problems, users likely rely more heavily on the predictable suggestions provided by the computer algorithms.
The researchers did not find strong statistical evidence for differences among the other three categories, suggesting that open-ended tasks lead to less convergence. They also checked if these patterns only happen in highly controlled laboratory settings. The authors compared traditional laboratory experiments with real-world scenarios, such as analyzing published essays and visual artworks created before and after the widespread adoption of automated writing tools.
The analysis of these real-world conditions showed a small but significant reduction in idea diversity. “In many ways, the findings resemble classic fixation effects from the psychology literature, where exposure to examples constrains later thinking, but here they appear amplified by the scale and synchronicity of generative AI model use,” the researchers stated. “This homogenization effect was observed not only in controlled lab studies but also in real-world quasi-experiments. This suggests that it is not merely a lab-based phenomenon, but a practical concern affecting concrete creative processes and practices.”
De Rooij and Biskjaer also investigated whether this narrowing of ideas persists after a person stops using the software. They isolated a subset of studies that tested participants on new creative tasks after their initial interaction with the computer models. The results suggest that the homogenization effect carries over into these subsequent activities.
“The findings also provide preliminary evidence that homogenization effects may persist beyond moments of direct AI use,” the researchers told PsyPost. “In other words, interacting with these generative AI systems may shape how people think and generate ideas even after the interaction has ended. This potential ‘rub-off’ effect on creative cognition warrants further research and is something we would like to explore in more depth.”
These results closely align with another recent study published in the journal PNAS Nexus. Scientists Emily Wenger and Yoed N. Kenett tested how large language models affect human creativity by evaluating 22 different commercial chatbots. They recruited 102 human participants to complete a series of verbal creativity tests, including the alternative uses task, and then asked the chatbots to complete the exact same assignments.
Wenger and Kenett found that individual language models performed at or slightly above the level of the average human on most exercises. When viewed in isolation, a single chatbot provided highly original and creative responses. However, when the scientists compared all the responses from the different models, a stark pattern of similarity emerged.
Across all tasks, the computer programs produced answers that were significantly more alike than the answers provided by the human participants. Both sets of researchers point to similar underlying mechanisms for this phenomenon. Because the major technology companies train their models on massive, overlapping datasets scraped from the internet, the programs naturally gravitate toward the most statistically common word associations.
When thousands of people use these tools to generate ideas, the software acts as a semantic anchor. The models pull human users toward a shared set of typical concepts, reducing the overall variety of ideas. Wenger and Kenett attempted to fix this issue by adjusting the internal settings of the chatbots to force more random text generation, but this caused the models to produce nonsensical sentences.
Readers should avoid interpreting these findings as proof that human beings are becoming entirely uncreative. De Rooij and Biskjaer note that the reduction in collective diversity does not equal a total loss of individual ability. “A key point is that our findings do not show that using AI reduces creativity,” the researchers emphasized.
“Rather, they point to a shift in where and how creative diversity occurs, and where it may be constrained,” the authors said. “Individual output can improve in creative quality while becoming more similar across people. While these effects are often subtle in single instances, they may become meaningful when considered at the scale at which generative AI is now being used.”
The authors point out some limitations to their current analysis. The review primarily focuses on text-based tools and large language models, meaning the findings might not apply to other types of computer systems. For instance, adaptive machine learning programs or tools used for music composition were not adequately represented in the available data.
This restricts how broadly the scientific community can apply these conclusions across different artistic domains. Additionally, the analyses regarding long-term persistence and real-world applications relied on relatively small groups of studies. The limited data makes these specific conclusions tentative and open to revision.
Future research should explore different forms of human and machine collaboration over extended periods of time. “An important next step is rethinking how generative AI systems are designed and used in creative contexts to mitigate homogenization effects,” the authors noted. “This includes exploring alternative workflows, interaction designs, and creative strategies that sustain diversity rather than encourage early convergence.”
“One step in this direction has already been taken by mapping creative strategies for working with generative AI and machine learning, based on analyses of AI art practices,” they added, referencing a recently published article outlining this approach. “We believe these strategies can transfer to other creative domains.”
The preprint study, “Does Generative AI Make Us Think Alike? A Systematic Review and Meta-Analysis of Homogenization Effects in Human-AI Co-Creation,” was authored by Alwin de Rooij and Michael Mose Biskjaer.
-------------------------------------------------
DAILY EMAIL DIGEST: Email [email protected] -- no subject or message needed.
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
NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
EMAIL DAILY DIGEST OF RSS FEEDS -- SUBSCRIBE: http://subscribe-article-digests.clinicians-exchange.org
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It's primitive... but it works... mostly...
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #GenerativeAI #CreativityDiversity #AICoCreation #Homogenization #CreativeThinking #AIImpact #CreativeDiversity #LLMs #TechEthics #InnovationScience
-
DATE: May 14, 2026 at 10:00AM
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: Real-world evidence shows generative AI is making human creative output more uniform
Using artificial intelligence for creative tasks tends to make human output more uniform on a collective level. A recent preprint study provides evidence that while these tools might boost individual performance, they contribute to an overall reduction in the diversity of ideas across different users. This widespread reliance on automated assistance could lead to a narrower range of concepts in collaborative environments.
Generative artificial intelligence refers to computer programs capable of creating new text, images, or other media based on user instructions. The most common of these tools rely on large language models. Developers build these models by feeding them billions of sentences from the internet, allowing the software to recognize patterns and predict how words should follow one another.
Since many users interact with similar systems trained on overlapping data, scientists have raised concerns about how this technology shapes human thought. Researchers Alwin de Rooij, assistant professor in creativity research at Tilburg University and associate professor at Avans University of Applied Sciences, and Michael Mose Biskjaer, associate professor in design creativity and innovation at Aarhus University, designed a new study to assess these concerns. They noticed that previous research often focused on how these tools help individuals work faster or overcome temporary mental blocks.
They wanted to know if this individual assistance comes at a collective cost. “There are growing concerns that using Generative AI may lead people toward similar creative ideas,” the authors explained. “While AI can enhance creativity at the individual level, these benefits might come at a cost for creativity at a collective, or even societal, level.”
The authors sought to answer whether generative software makes people think alike. “We sought to address this by conducting a systematic review and meta-analysis of 19 empirical studies,” they noted. “More concretely, we wanted to examine whether and to what extent generative AI use is associated with convergence at the level of creative output, such as people’s ideas, designs, and creative writing.”
A meta-analysis is a statistical technique that combines the results of multiple independent studies to find common patterns or overall trends. By pooling data from various experiments, scientists can draw more robust conclusions than they could from a single test. The authors searched academic databases for studies published between 2022 and early 2026.
This time frame covers the period following the public release of popular chatbots, capturing the first wave of empirical research on this topic. The researchers selected 18 eligible articles containing 19 distinct experimental studies. These studies provided a total of 61 individual effect sizes, which are mathematical values indicating the strength of a specific phenomenon.
To be included in the analysis, the original experiments had to compare humans working with generative software against humans working alone. The original studies measured homogenization using several techniques. Many relied on advanced text analysis tools that translate written responses into mathematical coordinates.
This process allows computers to measure the semantic distance between words, essentially calculating how closely related different ideas are to one another. Other studies used human experts to rate the variety of meanings produced by participants. The analysis revealed a statistically significant homogenization effect associated with the use of artificial intelligence.
When people co-created with these systems, their final products tended to be more similar to the work of other users. “The meta-analysis shows that using generative AI can indeed lead people to think alike,” the authors noted. “Across individuals, AI use tends to make ideas, designs, and creative texts more similar to one another.”
“This suggests that AI may contribute to a form of homogenization of creative thought at the collective level,” they continued. “Importantly, this does not necessarily reflect a failure of human-AI co-creation but may instead be an inherent feature of how these systems currently support creative work at scale.”
The scientists also evaluated whether the type of task influenced the degree of uniformity. They categorized the experiments into four groups, which included divergent thinking, idea generation, writing, and visual art. Divergent thinking tasks are highly open-ended exercises, such as asking someone to list creative uses for a paperclip.
Idea generation tasks provide more specific constraints, such as asking for solutions to improve public transportation. The analysis showed that the homogenization effect was strongest in the idea generation tasks. Because these exercises require specific solutions to defined problems, users likely rely more heavily on the predictable suggestions provided by the computer algorithms.
The researchers did not find strong statistical evidence for differences among the other three categories, suggesting that open-ended tasks lead to less convergence. They also checked if these patterns only happen in highly controlled laboratory settings. The authors compared traditional laboratory experiments with real-world scenarios, such as analyzing published essays and visual artworks created before and after the widespread adoption of automated writing tools.
The analysis of these real-world conditions showed a small but significant reduction in idea diversity. “In many ways, the findings resemble classic fixation effects from the psychology literature, where exposure to examples constrains later thinking, but here they appear amplified by the scale and synchronicity of generative AI model use,” the researchers stated. “This homogenization effect was observed not only in controlled lab studies but also in real-world quasi-experiments. This suggests that it is not merely a lab-based phenomenon, but a practical concern affecting concrete creative processes and practices.”
De Rooij and Biskjaer also investigated whether this narrowing of ideas persists after a person stops using the software. They isolated a subset of studies that tested participants on new creative tasks after their initial interaction with the computer models. The results suggest that the homogenization effect carries over into these subsequent activities.
“The findings also provide preliminary evidence that homogenization effects may persist beyond moments of direct AI use,” the researchers told PsyPost. “In other words, interacting with these generative AI systems may shape how people think and generate ideas even after the interaction has ended. This potential ‘rub-off’ effect on creative cognition warrants further research and is something we would like to explore in more depth.”
These results closely align with another recent study published in the journal PNAS Nexus. Scientists Emily Wenger and Yoed N. Kenett tested how large language models affect human creativity by evaluating 22 different commercial chatbots. They recruited 102 human participants to complete a series of verbal creativity tests, including the alternative uses task, and then asked the chatbots to complete the exact same assignments.
Wenger and Kenett found that individual language models performed at or slightly above the level of the average human on most exercises. When viewed in isolation, a single chatbot provided highly original and creative responses. However, when the scientists compared all the responses from the different models, a stark pattern of similarity emerged.
Across all tasks, the computer programs produced answers that were significantly more alike than the answers provided by the human participants. Both sets of researchers point to similar underlying mechanisms for this phenomenon. Because the major technology companies train their models on massive, overlapping datasets scraped from the internet, the programs naturally gravitate toward the most statistically common word associations.
When thousands of people use these tools to generate ideas, the software acts as a semantic anchor. The models pull human users toward a shared set of typical concepts, reducing the overall variety of ideas. Wenger and Kenett attempted to fix this issue by adjusting the internal settings of the chatbots to force more random text generation, but this caused the models to produce nonsensical sentences.
Readers should avoid interpreting these findings as proof that human beings are becoming entirely uncreative. De Rooij and Biskjaer note that the reduction in collective diversity does not equal a total loss of individual ability. “A key point is that our findings do not show that using AI reduces creativity,” the researchers emphasized.
“Rather, they point to a shift in where and how creative diversity occurs, and where it may be constrained,” the authors said. “Individual output can improve in creative quality while becoming more similar across people. While these effects are often subtle in single instances, they may become meaningful when considered at the scale at which generative AI is now being used.”
The authors point out some limitations to their current analysis. The review primarily focuses on text-based tools and large language models, meaning the findings might not apply to other types of computer systems. For instance, adaptive machine learning programs or tools used for music composition were not adequately represented in the available data.
This restricts how broadly the scientific community can apply these conclusions across different artistic domains. Additionally, the analyses regarding long-term persistence and real-world applications relied on relatively small groups of studies. The limited data makes these specific conclusions tentative and open to revision.
Future research should explore different forms of human and machine collaboration over extended periods of time. “An important next step is rethinking how generative AI systems are designed and used in creative contexts to mitigate homogenization effects,” the authors noted. “This includes exploring alternative workflows, interaction designs, and creative strategies that sustain diversity rather than encourage early convergence.”
“One step in this direction has already been taken by mapping creative strategies for working with generative AI and machine learning, based on analyses of AI art practices,” they added, referencing a recently published article outlining this approach. “We believe these strategies can transfer to other creative domains.”
The preprint study, “Does Generative AI Make Us Think Alike? A Systematic Review and Meta-Analysis of Homogenization Effects in Human-AI Co-Creation,” was authored by Alwin de Rooij and Michael Mose Biskjaer.
-------------------------------------------------
DAILY EMAIL DIGEST: Email [email protected] -- no subject or message needed.
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
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NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
EMAIL DAILY DIGEST OF RSS FEEDS -- SUBSCRIBE: http://subscribe-article-digests.clinicians-exchange.org
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It's primitive... but it works... mostly...
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #GenerativeAI #CreativityDiversity #AICoCreation #Homogenization #CreativeThinking #AIImpact #CreativeDiversity #LLMs #TechEthics #InnovationScience
-
DATE: May 21, 2025 at 08:30AM
SOURCE: BioWorld MedTechDirect article link at end of text block below.
.@galvanizetx #Aliya could enable one-step tumor #biopsy and #ablation
Here are any URLs found in the article text:
Articles can be found by scrolling down the page at https://www.bioworld.com/topics/85-bioworld-medtech .
-------------------------------------------------
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
.
NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
.
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
.
EMAIL DAILY DIGEST OF RSS FEEDS -- SUBSCRIBE:
http://subscribe-article-digests.clinicians-exchange.org
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READ ONLINE: http://read-the-rss-mega-archive.clinicians-exchange.org
.
It's primitive... but it works... mostly...
.
-------------------------------------------------#healthcare #healthtech #healthcaretech #healthtechnology #medgadget #medicine #doctor #hospital #medtech
-
DATE: May 21, 2025 at 08:30AM
SOURCE: BioWorld MedTechDirect article link at end of text block below.
.@galvanizetx #Aliya could enable one-step tumor #biopsy and #ablation
Here are any URLs found in the article text:
Articles can be found by scrolling down the page at https://www.bioworld.com/topics/85-bioworld-medtech .
-------------------------------------------------
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
.
NYU Information for Practice puts out 400-500 good quality health-related research posts per week but its too much for many people, so that bot is limited to just subscribers. You can read it or subscribe at @PsychResearchBot
.
Since 1991 The National Psychologist has focused on keeping practicing psychologists current with news, information and items of interest. Check them out for more free articles, resources, and subscription information: https://www.nationalpsychologist.com
.
EMAIL DAILY DIGEST OF RSS FEEDS -- SUBSCRIBE:
http://subscribe-article-digests.clinicians-exchange.org
.
READ ONLINE: http://read-the-rss-mega-archive.clinicians-exchange.org
.
It's primitive... but it works... mostly...
.
-------------------------------------------------#healthcare #healthtech #healthcaretech #healthtechnology #medgadget #medicine #doctor #hospital #medtech