examine the relationship between technology and stress and to find out what the sought to explain why “technostress” is created, how it varies across time, trapped in almost habitual multitasking and left with little time to. In this high-tech, high-pressure age, multitasking has become a national pastime. According to Meyer, juggling tasks can be very stressful. As reported at a conference for the Association for Computing Machinery, the average worker. our responsibilities are numerous and our connection to technology is constant? decreases productivity, impairs your cognitive ability, increases your stress, and In this podcast, I'll define multitasking and explain what happens in the . To maintain professional relationships, it's important to be available to others.
Heart rate relate specifically to stress, multi-tasking and computer variability HRV is considered a valid indicator of usage on the following day? It is possible that late night mental stress and is used extensively in research and "evening types"  may have different ICT usage clinical studies see [1, 25] for reviews. HRV refers to patterns than non "evening types.
The recommended of sleep, our measures allow us to examine the measure for calculating HRV is to use the standard relationship of time of end of day activity with the deviation sd of the normal-to-normal heart beat . Contrary to intuition, the lower the measure of HRV i. The sympathetic nervous system, a This study was conducted at a large public university on subsystem of the autonomic nervous system, responds to the U. A total of 48 undergraduates 27 stress the body responds to stressful circumstances by male and 21 female were recruited for the study from regulating itself.
The HRV measures the fluctuations in undergraduate classes, resident communities, and the autonomic nervous system. Thus, when a person is snowball sampling. Their majors included computer relaxed, HRV is higher, as the body is not regulating science, engineering, social sciences, biological and itself. Even if HRV is changed by mild exercise, it returns physical sciences, and humanities, with ages ranging to the baseline state very rapidly .
HRV was found to from 18 to 26; the mean age was The average age measure mental stress during computer usage in a when participants started using a computer was 9. A lowering of HRV has been using the Internet, The median college year was associated with increase in factors related to stress e. Their GPAs ranged from 1. With ICT use, it has been shown that when people do not use email, their stress, as measured by We conducted an in situ observational study where data HRV, is lowered .
The study used a mixed methods Survey measures. Participants completed an end-of-day design: We also conducted experience sampling of mood  this measures two dimensions: They noted the classes they attended, received end-of-the-day surveys. Full days of their productivity, and how influenced they were by computer usage are analyzed for most analyses; partial deadlines. A general survey asked for demographic days are excluded due to days of set up and finish. Most information, academic background and status, a general participants reported in the exit interviews that the week PANAS measure, technology habits and attitudes.
On Day 1 of the study, participants came to a or less computer use, more stressbecause of midterm campus laboratory where the computer logging software and final examinations. Participants who also had desktop computers were given software installation Overview of ICT use instructions. Participants were also provided with a HRM In this section we present an overview of computer and were instructed to wear the heart rate monitors all usage: Two or did exceptional strenuous activity.
They were told to coders independently coded the computer logs of the top take off the HRMs when ready for bed.
- The Multitasking Mind
Coding was based on the name of the application participants were asked to meet with researchers used and the domain name of the website if it was a URL.
During The coders iteratively developed 10 website categories. After discussion, the coders reached functioning properly, and reminded participants to consensus for all URLs. The coded categories of websites were 1 Social media: Semi-structured interviews were conducted on Day 7. We Facebook, Twitter, Tumblr, Wikipedia, etc. Of 48 participants, two one female, one male were Amazon. For one, our logging software was blocked by anti-virus software in their computer Overview of computer use by category from the second day.
Another was noncompliant, using Table 1 shows the average daily time in each category of another personal computer and not recording HR.
Based on full study days, participants averaged 4 We used Polar ProTrainer 5 software to do error hours, 40 min.
Some HR signals, such as a flat bpm or wild fluctuations, can be due to a loose chest strap or Total Computer 4: We eliminated such data: The computer log data was matched by Media Other timestamps with the HRV data in 15 minute time units.
We capturedcomputer window switches, and recorded 3, hours of heart rate reading, Gaming 0: Means and SD of daily time spent in different computer activities H: Switching behavior category of website use, averaging 84 minutes daily. Our first research question asks the extent to which this Daily Internet usage in our sample is almost an hour user group multitasks. One measure of multitasking is the longer than that found in other studies [10, 30].
FB usage duration of viewing a computer window before switching in our study is higher than previous studies [10, 23]. The results for overall usage show that when participants are on their computers, the average For the rest of our analyses, we focus on Social media, time on any computer window before switching to FB and Other SMEmail, Acad and Web Serv.
We another window is In terms of chose these categories because: Thus, as Table 2. Means SE of daily total durations for computer usage rises, stress rises as well. Heavy and light multitaskers and users We next compared heavy and light computer users and multitaskers MT Table 2. Based on a histogram of average daily computer duration, we chose the ten heaviest h: To identify heavy and light multitaskers, based on a histogram of average daily window switching frequency, we chose the ten highest and ten least frequent switchers.
On average, light MT switch 0. Stress and ICT use Fig.
Multitasking and Stress
The right axis shows HRV. Note the stress in the Millennials, we developed a model using HRV measure is inversely related to stress. Error bars HRV as a dependent measure. We used measures are SE. Email duration was not significant. However, we can FB. This value will underestimate the amount of variance Table 3. Model for stress, as measured by HRV. The higher explained by not including random effects participantsthe HRV value, the lower the stress.
Beta coefficients of log- but it will provide a reasonable estimate since the random transformed variables are adjusted for interpretability. The variance inflation factors for all variables in Table 3 range from 1. The data was segregated into minute time multi-collinearity is not a problem.
We note that the beta units throughout the day. To account for the fact that our data was correlated within participants each person was observed for 7 dayswe Q3.
Activity the night before: We had no a priori conception ICT usage the next day. Participants were instructed to of what variables might be associated with stress; wear the HRMs all waking hours and to take them off therefore, we entered our target variables, durations of before they went to bed.
We was taken off as a measure we call 'end of day activity'. We controlled sleep, we can calculate a precise time i. This could be a reasonable proxy for self-reportedwhether in class, and number of course close to the time when participants went to sleep.
The Multitasking Mind
To test gender effects, we looked at all 2-way reduce error even further, we grouped the timestamps interactions with gender. To correct for lack of normality, estimating end of day activity into three wide time bins. We also used 2 a. We procedure for linear mixed models, we built the model by created three time intervals: Single days of four people who stepwise regression, where we started with all variables removed their HRMs early in the evening were excluded in the model and then eliminated variables until we found from the analysis.
We only used data from nights before the best fitting model based on the BIC criterion1. Table 3 weekdays, and excluded Friday and Saturday nights as shows the beta coefficients for the best fitting model for they may have different late night activity patterns . None of our control variables were significant.
Using a linear mixed model to account for the The model shows a direct relationship between computer correlations within participants, we compared the duration and stress; as time spent on the computer difference in means of the following variables, measured increases, stress increases.
With more window switches, the following day: Table 4 shows the results. Means well-established measure of model selection, is used to find the reported are all within 15 minute time units. We best fitting model . As reported at a conference for the Association for Computing Machinery, the average worker needed a staggering 25 minutes to return to their original task after the interruption was over.
To make things worse, Meyer says, multitasking can interfere with short-term memory. For example, a person who tries to read email while talking on the phone will have a hard time retaining any of the information.
And if the phone rings while a person's in the middle of a thought, it will take a while to find that thought again -- assuming it can be recovered at all. Short-term memory loss isn't always a short-term problem. The flood of adrenaline and other stress hormones unleashed by trying to do too much at once can actually cause permanent damage to the brain cells that store memories, Meyer says. After years of multitasking, a person might eventually have trouble doing just one thing at a time.
So what should a person do when the phone rings and the email pings? Meyer urges people to organize their work life to cut down on multitasking as much as possible. That means ignoring the phone and turning off your email alerts while you're working on an important project. You can always check your messages later. When that task is over, take a break to clear your thoughts and refresh your mind.
No matter how demanding your job is, you can take steps to protect yourself from stress. Meyer recommends meditation, regular exercise and a healthy diet. Just don't try doing all three at once.
Is multitasking more efficient? Shifting mental gears costs time, especially when shifting to a less familiar task. Rubenstein JE et al. Executive control of thought processes in task switching. Journal of Experimental Psychology. The participants also made three times as many errors as they had made when attempting only two tasks. According to Koechlin, the ease with which we juggle tasks depends on just how engaged the prefrontal cortex is. For instance, natural activities such as eating or walking place less demand on the prefrontal cortex compared with activities like reading or driving.
And, while extensive practice can lead a task to become more natural, Koechlin says mastering a single activity to the point it becomes automatic is unlikely to make you better at multitasking in general. In fact, a study of university students found that those who report spending more hours concurrently consuming multiple forms of media frequent media multitaskers actually perform worse on tests that assess their ability to switch from one task to the next.
Frequent media multitaskers also have a harder time ignoring external distractions. Harder with age Because the simultaneous processing of tasks requiring attention is so tough on the brain, often, when we multitask, the brain switches attention back and forth between activities. While studies show multitasking compromises working memory the ability to store information over short periods of time in people of all ages, Gazzaley wanted to know why anecdotal evidence suggests multitasking is harder on older adults.
To test, Gazzaley and a team of researchers asked a group of young adults and seniors to observe and remember the details of a natural scene for about 15 seconds while undergoing an fMRI.