Hello everyone, my name is Thomas Breideband and I am here to present our work on Sleep
Patterns and Sleep Alignment in Remote Teams during COVID-19
As we are all aware, many information workers and their teams saw their daily co-working
experience radically change with the sudden shift to working from home.
Considering the kinds of forcing functions that typically exist when working in an office
and are absent when working from home --- that is, the daily commute, for example, or shared
work hours --- several studies have shown that work schedules became less rigid and
more fluid during the pandemic for those who worked from home.
Other studies have also indicated that work from home policies impacted general sleep behaviors.
In this paper, we studied sleep and remote teamwork from the perspective of team alignment,
specifically temporal alignment, and how differences in sleep patterns between members of the same
team may be related to individual perceptions of remote teamwork.
Therefore, our study asked the following research questions:
First, how is the shift from co-located work to work-from-home related to sleep and
work patterns of information workers?
Second, what is the relationship between individual sleep patterns and perceived team performance,
team productivity, and individual affect/mood?
And third, what does the (mis-)alignment of team members’ sleep patterns reveal about
their individual mood as well as their perceptions of teamwork?
With this in mind, we analyzed 10 weeks of daily sleep and survey data for 71 information
workers who belonged to 22 teams.
Alongside the wearable sleep data, we collected participants’ daily perceptions of team
states, team processes, team productivity, and personal affect via surveys sent to participants’ smartphones.
Team states included team members’ views on cohesion, climate, and conflict whereas
team processes refer to their perceptions of communication and coordination in the team.
To answer our research questions, we built linear mixed effects models because of the
repeated design of the study and the complex nested structure of team members nested in teams.
However, for RQ3, which looks at sleep misalignment we also conducted a thematic analysis of interviews,
specifically those with participants who belonged to the most and least misaligned teams.
For RQ1, we found significant differences between participants’ sleep patterns before
and during the pandemic.
The density plots here display sleep and work schedule measures over the course of a 24-hour
day. The vertical lines indicate average pre-pandemic sleep patterns…the two dashed lines on the
left, and average pre-pandemic work schedule measures, the dotted lines on the right. The solid vertical lines are a
reference to the traditional 9 to 5 workday.
As we can see, we found slight delays of roughly 20 and 36 minutes in sleep on- and offset
and a moderate increase of 16 minutes in average total sleep time during the pandemic, which replicates prior work.
On the right we see that participants started and ended their workdays later during the
pandemic, though they did not significantly increase their work hours.
A follow-up analysis where self-reported sleep data during the pandemic were exchanged for
wearable sleep data showed that the wearable sleep measures produced model results that
were consistent with the self-report measures relating to sleep during the pandemic.
For RQ2, we regressed the here shown outcome measures on study long averages of bedtime
and sleep duration along with other relevant covariates.
Teamwork was a combined measure that included the following team-related outcomes:
communication, coordination, cohesion, and climate due to high correlation.
Sleep duration predicted our teamwork measure suggesting that participants who slept longer
had a lower perception of team processes and team states.
Longer sleep duration was also associated with lower perceptions of team productivity
and positive affect.
These results may point to the potential hampering effects of oversleeping in work from home teamwork.
At the same time, participants who went to bed later reported higher team conflict and
negative affect, which may indicate either sleep deprivation or possibly bedtime procrastination.
For RQ3, we created a measure for sleep alignment --- or rather sleep misalignment because higher
values represent more misalignment --- by computing the average pairwise Euclidean Distance of
the study-long averages of bedtime and sleep duration.
That means, for each participant i in a team, we calculated the distance to every other
participant j in a team as the Euclidean distance of bedtime and sleep duration.
Average sleep misalignment in our sample was 1.65 hrs, ranging from .49
on average for members of the least misaligned team to 3.73 on average for the most misaligned team.
Looking at the models, we found that teams that were more misaligned in their sleep patterns
reported higher teamwork.
These teams also reported higher positive affect, but not higher productivity.
A thematic analysis of interviews with members from the five most and five least misaligned
teams revealed that those from the most misaligned teams were more likely to have explicit team-working
conventions and policies in place and that they were more likely to have developed a
collaborative mindset, compatible and suitable with asynchronous, remote work.
We then tested sleep misalignment as a curvilinear predictor.
We found moderate effects when predicting positive affect.
Here, an average sleep misalignment of about 2 to 2.5 hours showed the highest association
with positive affect.
This may indicate a sweet spot below and above which positive mood may be dampened by
factors such as too rigid or too lax work schedules in the team.
Taking a step back, what are our takeaways when it comes to sleep, sleep alignment, and
perceptions of remote teamwork and affect?
Overall, our findings in RQ1 replicated prior work that has shown delays in overall sleep
patterns during the pandemic.
In RQ2, we found problematic sleep behaviors that may contribute to perceptions of teamwork
and affect.
Longer sleep was also related to lower teamwork and lower productivity.
It is possible that participants who went to bed later or slept longer engaged in more
off-hour work and had more difficulty coordinating their work with other team members asynchronously.
Therefore, our findings suggests that employers may benefit from promoting healthy sleep habits
especially for those employees in full-time work from home positions.
Another option would be to offer full-time work from home employees a health and fitness tracker
for personal use similar to the one we used in our study.
Such an approach may circumvent any issues related to data privacy as no actual data
would be collected on the organizational level.
When it comes to sleep misalignment, higher sleep misalignment may be an indication of
more divergent work schedules.
Under these circumstances, team members in more misaligned teams may have to put more
effort into communication and coordination to have successful asynchronous collaborations.
When sleep misalignment was included as a curvilinear predictor we found a range above
and below which positive affect dipped.
Lower positive affect as an indicator of engagement may suggest lower active engagement among
teammates and, thus, lower viability when sleep misalignment is either too low or too high.
This study has shown the value that wearable sensors can provide in capturing bio-behavioral data.
However, bio-behavioral data like sleep are very personal and sensitive… and this raises
significant ethical and privacy concerns even before questions on how such data may be collected
in organizational contexts could be posed. For one, data inference problems are ever-present
in smaller-sized teams even if misalignment is only represented as the average sleep misalignment
in a team.
If data were still to be collected, alongside basic and hassle-free options to opt-in and
opt-out, average sleep misalignment scores could be generated for the whole team at regular
intervals and used for reflection.
A system could also notify teams in situations where misalignment lies outside the
team’s sweet spot and may negatively influence work from home collaborations.
However, more work is needed to develop optimal privacy practices for bio-behavioral data
collected in the workplace.
Thank you so much for watching.
We encourage everyone to read our paper for more details and discussion.
And if you have any questions, please feel free to contact me at: tbreideband@outlook.com