So, that example looks like an example of time pressure, rather than just being aware of time.
My understanding is that the literature on time pressure is considerably more nuanced and interesting. At its simplest, increased pressure (e.g. tight deadlines or expectation of evaluation) seem to improve performance on tasks where it’s clear exactly what needs to be done. On tasks that require creativity or novel problem solving, pressure seems to reduce performance compared to low to moderate time pressure. E.g. Ted Talk and study. I haven’t actually looked at this since college, so I can send you the dozen or so other papers I read then if you want to look at it with fresh eyes.
From that, I would expect your concern to be accurate only some of the time, albeit for some important work.
On the other hand, I have several anecdotal data points that regular time tracking is valuable for improving prioritization, though I expect the return is more varied than for short periods of time. I expect time tracking to be extremely valuable for short time spans (about 2 weeks) as a sanity check/improving knowledge of where time is spent.
Additionally, I expect people to be pretty bad at estimating productive time without tracking their time, hence the concern that prompted my original comment. The data means less if people are highly inaccurate when estimating time.
Last year, I looked at some studies to try understanding how correlated self-reported and objective measures are. There was a wide variance, with generally low to moderate correlations. When I looked just at the couple data points that are easily and/or frequently measured, the correlation was much higher, above r=0.7. Things that aren’t frequently measured have average correlations closer to r=0.3. Here’s that data if you want to reexamine it:
For numbers that were not frequently measured, the correlation between self-reported and directly measured was moderate: for one meta-analysis on physical activity, the mean r coefficient = 0.37 (range −0.71 to 0.96); for various measures of ability, mean r = 0.29 (range −0.6 to 0.80); for sedentary time, r<0.31; for physical activity, r=0.11.
A few more studies reported r coefficient ranges, but not mean r: for another measure of sedentary time, the coefficients ranged from 0.02 to 0.36; for another study on physical activity, the coefficients ranged from 0.46 to 0.53 (p value did not meet .05 threshold); for various other measures of sedentary time, the coefficients ranged from 0.50 to 0.65. If these are included in the above graph, the mean R goes up closer to .33.
For numbers that are frequently measured, the correlation between self-reported and directly measured was noticeably higher: for course grades, median r = .76 (range.70 to .84); for height and weight, median r = .94 (range .90 and above). This mildly sketchy unpublished review of hundreds of comparisons found an average of 85% perfect match between self-reports and objective records. The examples they give (e.g. self-report of hospitalizations or how many ambulatory physician visits compared with medical records) range from 89% to 100% exact match, and are mostly more frequently/easily measured.
Cool, I think a lit review of this territory would be valuable. (You’ve already got a start on one with this comment!) Could be an interesting opportunity to work with Elizabeth / deploy the methodology she’s working on.
I’ve worked at places where I’ve tracked time actively, places where I’ve tracked time passively (e.g. with RescueTime), and places where I haven’t tracked time at all.
I still get some value from RescueTime, but overall time-tracking has felt like a distraction on net, based on my experience so far. (YMMV etc.)
Thanks for the plug Milan. For those who don’t want to click through: via a grant from LTFF, I’ve been working on a method for bootstrapping a deep grounding in a subject, starting from knowing nothing. I don’t want to take over the thread, but I’m happy to talk about it with anyone who’s interested.
Burnout is on the rise because people are confusing screen time with leisure time. NOTHING that occurs on the screen is rejuvenating by giving your Sympathetic Nervous System a break. Video games and Netflix are optimized to be engaging = emotional agitation. Social media and news feeds induce comparison mindset, outragism and dopamine spirals. Worse, the fact that these tasks are interspersed throughout the day means you don’t get the longer time blocks that are necessary for your SNS to actually calm down. Instead you are periodically jolted. Sleep problems increase when such a block of time doesn’t occur before rest.
What gets measured gets managed, rescue time is helpful even if you don’t do anything in particular with the data.
Before you yell at me yes creating art is an exception. But doing this one tab away from a distraction is more stressful than the alternative. I get a decent amount more writing done in places without wifi.
So, that example looks like an example of time pressure, rather than just being aware of time.
My understanding is that the literature on time pressure is considerably more nuanced and interesting. At its simplest, increased pressure (e.g. tight deadlines or expectation of evaluation) seem to improve performance on tasks where it’s clear exactly what needs to be done. On tasks that require creativity or novel problem solving, pressure seems to reduce performance compared to low to moderate time pressure. E.g. Ted Talk and study. I haven’t actually looked at this since college, so I can send you the dozen or so other papers I read then if you want to look at it with fresh eyes.
From that, I would expect your concern to be accurate only some of the time, albeit for some important work.
On the other hand, I have several anecdotal data points that regular time tracking is valuable for improving prioritization, though I expect the return is more varied than for short periods of time. I expect time tracking to be extremely valuable for short time spans (about 2 weeks) as a sanity check/improving knowledge of where time is spent.
Additionally, I expect people to be pretty bad at estimating productive time without tracking their time, hence the concern that prompted my original comment. The data means less if people are highly inaccurate when estimating time.
Last year, I looked at some studies to try understanding how correlated self-reported and objective measures are. There was a wide variance, with generally low to moderate correlations. When I looked just at the couple data points that are easily and/or frequently measured, the correlation was much higher, above r=0.7. Things that aren’t frequently measured have average correlations closer to r=0.3. Here’s that data if you want to reexamine it:
For numbers that were not frequently measured, the correlation between self-reported and directly measured was moderate: for one meta-analysis on physical activity, the mean r coefficient = 0.37 (range −0.71 to 0.96); for various measures of ability, mean r = 0.29 (range −0.6 to 0.80); for sedentary time, r<0.31; for physical activity, r=0.11.
A few more studies reported r coefficient ranges, but not mean r: for another measure of sedentary time, the coefficients ranged from 0.02 to 0.36; for another study on physical activity, the coefficients ranged from 0.46 to 0.53 (p value did not meet .05 threshold); for various other measures of sedentary time, the coefficients ranged from 0.50 to 0.65. If these are included in the above graph, the mean R goes up closer to .33.
For numbers that are frequently measured, the correlation between self-reported and directly measured was noticeably higher: for course grades, median r = .76 (range.70 to .84); for height and weight, median r = .94 (range .90 and above). This mildly sketchy unpublished review of hundreds of comparisons found an average of 85% perfect match between self-reports and objective records. The examples they give (e.g. self-report of hospitalizations or how many ambulatory physician visits compared with medical records) range from 89% to 100% exact match, and are mostly more frequently/easily measured.
Cool, I think a lit review of this territory would be valuable. (You’ve already got a start on one with this comment!) Could be an interesting opportunity to work with Elizabeth / deploy the methodology she’s working on.
I’ve worked at places where I’ve tracked time actively, places where I’ve tracked time passively (e.g. with RescueTime), and places where I haven’t tracked time at all.
I still get some value from RescueTime, but overall time-tracking has felt like a distraction on net, based on my experience so far. (YMMV etc.)
Thanks for the plug Milan. For those who don’t want to click through: via a grant from LTFF, I’ve been working on a method for bootstrapping a deep grounding in a subject, starting from knowing nothing. I don’t want to take over the thread, but I’m happy to talk about it with anyone who’s interested.
Also here’s a recent take from Romeo: