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Cheng, Ju, Sun, and Lin investigated what LED light levels are preferred by older viewers.  They report on their research with people 55 – 65 years old: “In this study, experiments were conducted under LED lighting with . . . three different illuminance levels (30lux; 100lux; 1000lux). . . .  they [study participants] prefer higher illuminance, which makes them find the lighting environment more comfortable, brighter, and better for reading.”

Wenting Cheng, Jiaqi Ju, Yaojie Sun, and Yandan Lin.  2016.  “The Effect of LED Lighting on Color Discrimination and Preference of Elderly People.”  Human Factors and Ergonomics in Manufacturing and Service Industries, vol. 26, no. 4, pp. 483-490.

Barbieri and team set out to learn more about how people use sit-stand desk options.  They “compared usage patterns of two different electronically controlled sit-stand tables during a 2-month intervention period among office workers. . . . Twelve workers were provided with standard sit-stand tables (nonautomated table group) and 12 with semiautomated sit-stand tables programmed to change table position according to a preset pattern, if the user agreed to the system-generated prompt (semiautomated table group). Table position was monitored continuously. . . . On average, the table was in a ‘sit’ position for 85% of the workday in both groups; this percentage did not change significantly during the 2-month period. Switches in table position from sit to stand were, however, more frequent in the semiautomated table group than in the nonautomated table group. . .  A semiautomated sit-stand table may effectively contribute to making postures more variable among office workers and thus aid in alleviating negative health effects of extensive sitting.”  More on the test conditions: the semiautomated tables were “equipped with a system designed to control table configuration according to a programmable schedule.”  This schedule was 10 minutes of standing (i.e., having the table at a taller height) for each 50 minutes spent sitting (i.e., having the table at a shorter height). Table height could be adjusted only when change prompts were received and overall 82% of all change prompts were followed. Ten percent of change suggestions were rejected and 8% were either postponed or ignored.

Dechristian Barbieri, Divya Srinivasan, Svend Mathiassen, and Ana Oliveira.  2017.  “Comparison of Sedentary Behaviors in Office Workers Using Sit-Stand Tables With and Without Semiautomated Position Changes.”  Human Factors:  The Journal of the Human Factors and Ergonomics Society, vol. 59, no. 5, pp. 780-795.

Bratt-Eggen and her team researched sound levels in open-plan study spaces.  The investigators collected information in “five open-plan study environments at universities in the Netherlands. A questionnaire was used to investigate student tasks, perceived sound sources and their perceived disturbance, and sound measurements were performed to determine the room acoustic parameters. This study shows that 38% of the surveyed students are disturbed by background noise in an open-plan study environment. Students are mostly disturbed by speech when performing complex cognitive tasks like studying for an exam, reading and writing. Significant . . . correlations were found between the room acoustic parameters and noise disturbance of students [so measured noise levels were higher in the spaces where students were most likely to have difficulty studying].”

P. Bratt-Eggen, Anne van Heijst, Maarten Hornikx, and Armin Kohlrausch.  2017.  “Noise Disturbance in Open-Plan Study Environments:  A Field Study on Noise Sources, Student Tasks and Room Acoustic Parameters.”  Ergonomics, vol. 60, no. 9, pp. 1297-1314.

Cotter and team’s research adds to our understanding of human beings’ preference for curved items.  They report that  “A preference for smooth curvature, as opposed to angularity, is a well-established finding for lines, two-dimensional shapes, and complex objects. . . .  We [found that] people preferred curved over angular stimuli. . . . For one stimulus set—the irregular polygons. . . . People with more knowledge about the arts . . . showed greater curvature preferences, as did people higher in openness to experience. . . . Unlike other low-level factors that appear largely among novices, such as preferences for realistic over abstract images (Parsons, 1987), curvature preference was heightened among people with greater knowledge and interest in art, at least for this set of images [irregular polygons].”

Katherine Cotter, Paul Silvia, Marco Bertamini, Letizia Palumbo, and Oshin Vartanian. 2017.   “Curve Appeal:  Exploring Individual Differences in Preference for Curved Versus Angular Objects.”  i-Perception, vol. 8, no. 2,

Schloss and Palmer investigated why people tend to prefer particular colors.  Their findings align with common sense: “There are well-known and extensive differences in color preferences between individuals . . . there are also within-individual differences from one time to another. . . . they have the same underlying cause: people’s . . . experiences with color-associated objects and events. . . . preference for a given color is determined by the combined valence (liking/disliking) of all objects and events associated with that color.”

Karen Schloss and Stephen Palmer.  “An Ecological Framework for Temporal and Individual Differences in Color Preferences.”  Vision Research, in press.

An article published in Environmental Science and Technology reports that exposure to dust can affect how much someone weighs.  The study’s findings indicate that easy dust removal/low dust accumulation environments (as well as curtailing the use of certain chemicals) may help keep our BMIs in healthy zones.  A press release from the American Chemical Society indicates that “Poor diet and a lack of physical activity are major contributors to the world’s obesity epidemic, but researchers have also identified common environmental pollutants that could play a role. Now one team reports . . . that small amounts of house dust containing many of these compounds can spur fat cells to accumulate more triglycerides, or fat, in a lab dish. . . . The researchers collected samples of indoor dust from 11 homes in North Carolina and tested extracts from the samples. . . .  Extracts from seven of the 11 dust samples triggered the pre-adipocytes to develop into mature fat cells and accumulate triglycerides. Extracts from nine samples spurred the cells to divide, creating a larger pool of precursor fat cells. Only one dust sample had no effect. . . . This suggests that the mixture of these chemicals in house dust is promoting the accumulation of triglycerides and fat cells. . . . house dust is a likely exposure source of chemicals that may be able to disrupt metabolic health, particularly in children.”

“House Dust Spurs Growth of Fat Cells in Lab Tests.”  2017.   Press release, American Chemical Society,

Researchers associated with the Massachusetts Institute of Technology have found that where we work has a significant effect on who we work with, still (Claudel, Massaro, Santi, Murray, and Ratti, 2017).  The investigators report that “Academic research is increasingly cross-disciplinary and collaborative, between and within institutions. . . . We examine the collaboration patterns of faculty at the Massachusetts Institute of Technology . . . over a 10-year time span.”  A press release issued by MIT reviewing the work of Claudel and his team states that their research “revealed the importance of spatial relations on campus, above and beyond departmental and institutional structures. . . . .the study finds that cross-disciplinary and interdepartmental collaboration is fueled by basic face-to-face interaction. . . .When it comes to co-authoring papers, researchers located in the same workspace [office suite, for example] are more than three times as likely to collaborate compared to those who are 400 meters apart. The frequency of collaboration further drops in half when researchers are 800 meters apart. For patents, that curve is slightly less steep. Researchers in the same workspace are more than twice as likely to collaborate compared to those who are 400 meters apart. But the frequency of collaboration does not diminish as quickly, and only drops in half again when researchers are 1,600 meters apart. . . . as the paper notes, however, for both papers and patents there is ‘a persistent relationship between physical proximity and intensity of collaboration.’"

Matthew Claudel, Emanuele Massaro, Paolo Santi, Fiona Murray, and Carlo Ratti.  2017.  “An Exploration of Collaborative Scientific Production at MIT Through Spatial Organization and Institutional Affiliation.”  PLoS ONE, vol. 12, no. 6.

Peter Dizikes.  2017.  “Proximity Boosts Collaboration on MIT Campus.”  MIT press release,

Taking a photograph of something influences our sensory memories of it.  Barasch and her team (in press) found that “even without revisiting any photos, participants who could freely take photographs during an experience recognized more of what they saw and less of what they heard, compared with those who could not take any photographs. Further, merely taking mental photos had similar effects on memory. These results provide support for the idea that photo taking induces a shift in attention toward visual aspects and away from auditory aspects of an experience. . . . Participants with a camera had better recognition of aspects of the scene that they photographed than of aspects they did not photograph. Furthermore, participants who used a camera during their experience recognized even nonphotographed aspects better than participants without a camera did.”  These findings may be useful to people analyzing research data, particularly if space/object users have been asked to take photographs of specific spaces/objects, such as those where they feel they work most creatively.

Previously, Diehl, Zauberman, and Barasch (2016) learned that “taking photos enhances enjoyment of positive experiences across a range of contexts. . . . This occurs when photo taking increases engagement with the experience, which is less likely when the experience itself is already highly engaging, or when photo-taking interferes with the experience. . . .  we also find that this greater engagement due to photo-taking results in worse evaluations of negative experiences.”

Kristin Diehl, Gal Zauberman, and Alixandra Barasch. 2016.  “How Taking Photos Increases Enjoyment of Experiences.”  Journal of Personality and Social Psychology, vol. 111, no. 2, pp. 119-140.

Alexandra Barasch, Kristin Diehl, Jackie Silverman, and Gal Zauberman.  “Photographic Memory:  The Effects of Volitional Photo Taking on Memory for Visual and Auditory Aspects of an Experience.”  Psychological Science, in press.

Recent research indicates that it’s easier for people to discard “cluttering” objects after they photograph them.  Reczek, Winterich, and Irwin “found that people were more willing to give away unneeded goods that still had sentimental value if they were encouraged to take a photo of these items first. . . . ‘What people really don’t want to give up is the memories associated with the item,’ said Rebecca Reczek  . . . . ‘We found that people are more willing to give up these possessions if we offer them a way to keep the memory and the identity associated with that memory.’ . . . This memory preservation strategy won’t work for items that don’t have sentimental value, she [Reczek] said. It also won’t work for items you want to sell instead of donate. She also suspects there may be a limit to what some people are willing to give away. ‘It may not work for something that has a lot of sentimental value, like a wedding dress,’ Reczek said.”  The Reczek, Winterich, and Irwin study is published in the Journal of Marketing.

“Scientists Find a Clever Way to Help You De-Clutter Your Home.”  2017.  Press release, The Ohio State University,

Min and Min linked exposure to loud-ish noises and male infertility.  The researchers report that they “examined an association between daytime and nocturnal noise exposures over four years . . .. and subsequent male infertility.  We used the National Health Insurance Service-National Sample Cohort (2002–2013), a population-wide health insurance claims dataset. A total of 206,492 males of reproductive age (20–59 years) with no history of congenital malformations were followed up for an 8-year period. . . . Data on noise exposure was obtained from the National Noise Information System.  . . . Based on WHO criteria, adjusted odds for infertility were significantly increased . . . in males exposed to night time noise ≥ 55 dB. We found a significant association between exposure to environmental noise for four years and the subsequent incidence of male infertility, suggesting long-term exposure to noise has a role in pathogenesis of male infertility.”  Statistical tools were used to eliminate factors such as age, income, and BMI as possible explanations for the effects found.

Kyoung-Bok Min and Jin-Young Min. 2017.  “Exposure to Environmental Noise and Risk for Male Infertility:  A Population-Based Cohort Study.”  Environmental Pollution, vol. 226, pp. 118-124.


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