Chronic Sleep Deprivation Among the Poor: A Lab-in-the-field Approach
Phase: NA
Conditions: Blood Pressure, Depression
Sponsor: University of Pennsylvania

Chronic Sleep Deprivation Among the Poor: A Lab-in-the-field Approach 
NCT03322358 
12/18/2018 

Chronic Sleep Deprivation Among the Poor: A Lab-in-the-field Approach  
Study Protocol 
Overview. Given the potentially bidirectional relationship between sleep and the study’s key outcomes 
of interest, and the potential for omitted factors influencing some or all of these variables, we will 
utilize a randomized-controlled trial (RCT) to provide rigorous identification. We will conduct the 
main study by recruiting approximately 450 participants to work full-time for up to 28 business days 
in a data-entry job. After an eight-day baseline period, participants are stratified into four cells by work 
productivity and sleep quantity (above vs. below median for both). Within each cell, participants are 
then randomized into the following three groups, with an equal number of participants in each group:  
(1) Control Group: Participants in the control group continue to work in our lab office. They 
do not receive any of the below-mentioned sleep treatments, but they do receive placebo items so that 
any positive response from being able to take something home is similar across groups; 
 (2) Night-Sleep Treatment: Participants in the sleep treatment group receive sleep aid devices 
as well as feedback on their sleep, encouragement to sleep more if appropriate, and information 
regarding the benefits of sleep;  
(3) Night-Sleep Treatment + Incentives: Participants in the sleep treatment + incentives group 
receive the same sleep aid devices, encouragement, and information as participants in the sleep 
treatment, but participants in the sleep + incentives treatment are also provided modest financial 
incentives according to how much they increased their sleep over the previous two nights compared to 
their average sleep during the baseline period.   
Half of the participants across each of the three treatment groups will also be randomly assigned to 
take a half-hour nap each afternoon. The other half will be randomized into either taking a break or 
working during the same time slot. This results in six total experimental groups.  
Sleep will be objectively measured using wristwatch-like actigraphs, which accurately infer sleep from 
movement. In order to estimate the labor market effects of improved sleep, productivity, labor supply, 
and earnings will be measured using performance on the data-entry task. Variations on the data-entry 
task and a savings activity will be used to understand effects on economic decision-making, as 
measured by intertemporal choices and reaction to the salience of work incentives. All participants will 
also engage in standard lab tests of aspects of cognitive function as well as surveys and measurements 
of health. 
Sample. All participants will be low-income residents of Chennai, India. Given the importance of sleep 
to all genders, we will enroll both men and women.  
Process and timeline. During their participation in the study, individuals will attend the study office 
six days per week for 6 to 10 hours per day. During each of their visits, individuals will primarily work 
on a data-entry task, which will create precise measures of their labor supply and productivity, but will 
also complete a brief daily survey to assess self-reported sleep and covariates of interest (e.g. caffeine 
intake), undertake a battery of cognitive tasks, and make a daily decision whether to save money at the 
office at a favorable interest rate. More extensive surveys are also taken at enrollment and endline and 
additional health measures are collected as described below. All participants will follow a thorough 
informed consent procedure prior to enrollment. 
 
Baseline period. The experiment will begin with an eight-day baseline period without any 
experimental variation. This baseline period serves two main goals. First, it will generate baseline 

information on key covariates, which will allow us to stratify treatment conditions based on baseline 
outcomes, boosting statistical power and reducing the danger of baseline imbalances across treatment 
groups along key dimensions. Second, it ensures a population with sufficiently high attendance, 
promoting internal validity, since only participants who complete the baseline period are entered into 
the main study. 
Treatment conditions. Upon completion of the baseline period, experimental variation in sleep is 
created in two ways: (1) two interventions to improve individuals’ home sleep environments and 
attitudes towards sleep (randomized across individuals), and (2) a napping intervention (randomized 
across individuals). 
(1) Night-sleep treatment. Existing evidence suggests that environmental irritants such as noise 
and light markedly disrupt sleep. To help combat these irritants as well as other disruptors of sleep 
common to low income populations, treated participants will be provided the option to take home 
eyeshades, earplugs, a basic mattress and sheet, a pillow, a cot, a heavier blanket, and a table fan. 
Treated participants will also be provided with instructions on proper usage of sleep aids with 
which they are less familiar (e.g. earplugs) to ensure safety, comfort and effectiveness. Multiple 
varieties of some of the products such as ear plugs and mattresses are provided, so participants can 
choose the ones they like most. A sub-set of individuals in the control arm of the study will not 
receive any sleep aids, but they will be provided the option to take home “neutral” items including 
utensils, a flash light, a shoulder bag, a plastic chair, a table mate, a clothing drying stand, toys, or 
a blender. These placebo items are designed to ensure that any positive emotions that participants 
may feel when they receive items to take home are experienced among participants in both the 
treatment and control groups. Participants are not required to accept the sleep aids or the placebo 
items, although most choose to accept at least some.  
Treated participants will also receive daily encouragement to sleep more (if their current levels of 
sleep are below recommended levels) as well as information regarding the benefits of sleep and 
strategies to improve sleep. Half of the treated participants will also be randomly assigned to a 
Night-Sleep+Incentives group where they receive modest financial incentives according to how 
well they slept the previous two nights. We expect the paid out amounts to be approximately Rs 
50 ($0.80) per day. To ensure that participants in the Night-Sleep+Incentives group do not earn 
more overall than other participants, the remaining participants are matched with a participant in 
the Night-Sleep+Incentives group and are paid the amount this participant receives for their sleep 
throughout the course of the study.  
(2) Napping. A substantial body of evidence suggests that napping can effectively ameliorate sleep 
deprivation, and provides meaningful benefits in terms of improved alertness, reaction time, short-
term memory, and vigilance, as well as physiological benefits (Sallinen et al, 1998). To assess 
whether the cognitive effects associated with napping translate into meaningful economic impacts 
in our context, half of all participants are randomly assigned to a workplace nap condition. These 
participants will be provided with the same sleep aids as those offered in the sleep intervention, 
and they will have a quiet gender-segregated place to lie down and take a half-hour nap. The 
remaining individuals will be randomly assigned each day either to take a mandatory half-hour 
break from work or to continue working without such a break.  The randomization is constrained 
such that each of the non-nap participants breaks for half of the study and works for the other half. 
This between-person randomization greatly improves statistical power to detect the potential 
effects of naps and allows a comparison between the effects of naps, breaks, or working 
continuously.  

Data-entry work task. We employ study participants in a data-entry task for three reasons. First, the 
data-entry task will allow us to measure productivity and labor supply at an extremely fine-grained 
level, while simultaneously maintaining realism and external relevance to “real-world” work 
environments. Second, the task allows for variation in piece rates, allowing comparison of the impact 
of sleep to a common metric, money. Third, by hiring participants as full-time employees, we are able 
to allocate time towards napping as well as to the cognitive tasks at a high frequency.  
The task involves typing English words from a display into a data-entry field. The strings vary in length 
to mimic true data-entry work. The incentives provided vary over time; the piece rate for correct entries 
changes in approximatively half-hour intervals over the course of each day. All data from this task is 
automatically captured and stored in a custom-built database in real time.  
Outcomes. A key contribution of this project is the careful construction of precise and novel outcome 
measures of interest, namely sleep, health, cognitive function, and economic outcomes and decisions.  
(A) Sleep and sleep deprivation both constitute outcomes of interest of the study and serve as a “first 
stage” for the analysis of the impact of sleep on the remaining outcomes of interest. We will measure 
sleep and sleep deprivation via two objective and two subjective measurements. The primary measure 
of sleep relies on data from actigraphs, which resemble wristwatches and reliably and cost-effectively 
measure sleep/wake cycles via body movement. In addition, we will conduct a standard (in sleep 
medicine) psychomotor vigilance test (PC-PVT) on a daily basis, a reaction-time test used in sleep 
research as a proxy for sleep deprivation. These objective data will be complemented with self-reported 
sleep quantity and quality. 
(B) Cognitive function is measured throughout the study period via a battery of laboratory tests 
conducted on a rotating basis. The tasks measure two key aspects of cognitive function, short-term 
memory (Corsi Block-tapping Task) and inhibitory control (Hearts and Flowers Task). The tasks are 
modified to cater to a low-literacy population. 
(C) Health and subjective well-being. Happiness and life satisfaction reports will be elicited and 
anthropometric measurements taken at enrollment and exit. Additionally, participants will be asked to 
self-report health outcomes known to influence or be influenced by sleep including physical pain, 
hunger, mood, and stress. As sleep can also have an influence on self-control, we will track daily 
alcohol consumption through self-reports and objective measurements in the morning when 
participants arrive at the office. Finally, because sleep restriction has been shown to affect 
cardiovascular function, we will collect blood pressure readings multiple times.  
(D) Stationary biking task. A significant portion of our population of interest faces employment 
opportunities that involve physical labor, from working as a rickshaw driver to a construction worker. 
In order to gather policy-relevant information on whether sleep also improves productivity on such 
tasks, we want to measure the impact of sleep on physical activity by having participants ride a 
stationary bike for up to 30 mins at the end of the study. We will collect information on the total 
distance participants cover while biking (in kilometers) and the maximum speed the participant 
reaches. Participants can always opt not to participate in this task. The incentives for task completion 
are relatively low—participants are offered Rs. 10 per kilometer biked, with expected average earnings 
of roughly Rs. 90. To ensure that participants are not overexerted, the participants can set their own 
cycling speed, the bike tension will be set at a low level, participants are welcome to take breaks, and 
we provide participants with water. We will also screen out participants whose blood pressure is over 
200 or who show other signs of cardiovascular disease. From this task, we hope to estimate the impact 
of sleep deprivation on potential productivity in jobs that require physical labor. This task is a 
simplification of one previously implemented by PI Schofield with a similar study population in the 

same local setting, in a project on the economic effects of nutrition also approved by Harvard CUHS 
(Schofield 2014; IRB #21201).     
 
(E) Productivity, labor supply, and earnings. Individual's’ work performance on the data-entry task, 
the primary work activity for participants for the duration of the study, will be precisely tracked. This 
task is compensated according to performance, and workers may choose the number of hours they 
work (i.e. their labor supply). Every day, the study office is open from 9.30 am till 8.00 pm. In order 
to disentangle the labor supply effect from the productivity effect, on some days, participants have 
“short days” during which they can only type from 11am to 5pm, and will receive a bonus if they type 
during this full period. Key outcomes of interest are (i) labor supply, defined as the number of hours 
worked, (ii) productivity, as determined by variable payments, (iii) overall earnings, a function of both 
hours worked and productivity, and (iv) quantity and quality measures in terms of the number of 
submitted entries and the percent of correct entries.  
(F) Attention to non-salient features. An important topic of study in behavioral economics is attention 
to non-salient features of pricing (DellaVigna, 2009). For example, individuals do not pay enough 
attention to taxes that are not directly incorporated in the prices of goods (Chetty et al., 2009). To 
measure this, the pay structure of the typing task is salient on some days and non-salient on others, 
determined by the color of the payment box and signals on the screen, which are varied in terms of 
salience. We hypothesize that sleep deprived individuals are less likely to attend to the incentive 
scheme on non-salient days. 
 
(G) Intertemporal choice: self-control. There is ample reason to hypothesize that sleep influences self-
control, and thus inter-temporal choice. Sleep deprivation has been shown to worsen inhibitory control 
and affect the functioning of the ventromedial prefrontal cortex, the region of the brain implicated in 
the exercise of self-control. We will measure the impact of sleep on intertemporal choice using a 
savings task. To study savings behavior, all individuals are given the opportunity to save money daily 
at an interest rate of 0% or 1% in an individual savings box at the study office. 
 
(H) Susceptibility to present bias. The tendency to prefer immediate gratification to receiving the same 
consumption bundle in the future is well known in behavioral economics. What is less known is 
whether sleep deprivation affects the extent of this preference. Sleep, by increasing self-control, could 
help individuals to make less present-biased decisions when allocating effort. We intend to address 
this question by following a standard procedure used in behavioral economics (e.g. Augenblick et al., 
2015) wherein we ask participants how many pages (which are similar to those they work with in the 
data-entry task but shorter) they would be willing to type when offered different piece rates. 
Participants make two decisions, first one or two days before the work task, and then again right before 
the work task. One of the two decisions is randomly chosen to be implemented and the participant is 
asked to type the number of pages he or she selected in that choice. We will compare the difference in 
the number of pages participants are willing to enter across the two days. We hypothesize that 
participants choose higher work task goals in the future than the present, and that this difference will 
be lower among those with better sleep. Participants will always have the choice to not type any pages, 
and to go home instead.  
 
(I) Risk and social preferences. Another outcome of interest is the influence of sleep on risk aversion, 
loss aversion, and social preferences. To measure these outcomes, we use standard lab experimental 
techniques outlined in the literature with modest stakes (e.g. Eckel and Grossman, 1996; Gneezy and 
Potters, 1997). For the risk or loss aversion activities, participants choose between an amount of money 
for sure or playing a lottery in which they can earn different amounts of money or nothing (with the 

chance of losing negative amounts in the case of loss aversion.). For the social preferences activities, 
participants play the standard dictator, ultimatum (sender and receiver), and trust (sender and receiver) 
games. Participants are paired with another participant in the study, but we ensure that it is impossible 
for participants to know who they are paired with. Participants are asked to make these decisions twice 
in the study, once in the baseline period and once on the last day of treatment.    
 
Note: Only health related outcomes were considered in the clinicaltrials.gov pre-registration. 
Economic outcomes were registered and analyzed according to the AEA clinical trials registration.