The Negative Consequences Of Sleep Deprivation

Sleep deprivation has been a rising concern among clinicians, as more and more people are getting less sleep which causes harm on their health and quality of life (Lamberg, 2004). A study by the National Sleep Foundation (2015) suggested that adults in the US nowadays on average sleep two hours less than adults in the 19th century. The current amount of sleep hours is around 6. 7 to 7. 3 hours. The reduction in sleeping time has yet been associated with some health problems namely hypertension and obesity (Wolk, Shamsuzzaman & Somers, 2003), as well as some psychological impacts such as ego depletion, stress, depression, and anxiety (Lanaj, Johnson, & Barnes, 2014; Drake, Roehrs & Roth, 2003). Furthermore, the insufficiency of sleep is also costly to the economy, as it enhances productivity loss, lowers work-engagement, increases absenteeism, and lowers interpersonal effectiveness among leaders (Rosekind, et al, 2010; Lanaj, Johnson, & Barnes, 2014; Drake, Roehrs & Roth, 2003: Nowack, 2017).

The immense cost of sleep deprivation generates concern on what really causes people to sleep less. The Sleep Health Foundation (2011) of Australia suggests that there are at least ten common reasons why people do not get enough sleep, namely: sleep disorders like insomnia, sleep apnea and restless legs, consumption of caffeine and alcohol before sleep, stress, until the failure to wind down before bed due to television, smartphones, and other forms of entertainment use. Specifically for adult workers, Rocha & Debert-Ribeiro (2004) found that heavy workloads as for system analysts and computer scientists induces sleep disorder and difficulty to turn mind off work problems, thereby generating an intense cognitive effort prior to sleep thus causing sleep difficulties. A similar perspective was stated by Perlow (2012) while also acknowledging the technological advancement suggests that insufficient sleep can also be associated with smartphone use for work in the evening.

Taking all the aforementioned facts, we realized the urgency to take focus on workers’ sleep deprivation which can possibly affects productivity. We then took a deeper look on how important it is for workers to be able to get sufficient detachment from their work. Psychological detachment implies that an individual frees themselves from their job, whether it be physically or mentally (Sonnentag & Bayer, 2005), and it is especially important for oneself’s recovery state, replenishing depleted resources, and getting sufficient sleep (Etzion, Eden, & Lapidot, 1998; Sonnentag, et al, 2008) resulting in workers to be refreshed on the next day of work. But in light of the blurring of boundaries between being electronically “on” and away from work due to the existence of smartphones (Deal, 2013), it is essentially hard for workers to be able to entirely detach themselves from work when at home. Furthermore, the increasing demand of organizations regarding their employees’ availability suggests that employees feel compelled to immediately respond to work-related messages even during leisure time (Davis, 2002). This type of use of smartphones then proven to be one of the causes for the reduced quantity and quality of sleep, thus increases the likelihood of morning depletion which induces low work engagement on each particular day (Lanaj, Johnson & Barnes, 2014). In addition to that, Bakker & Bal (2010) found that the work engagement has a positive correlation to worker’s job performance, therefore a reduced engagement in work might lead to a deterioration of oneself’s performance in work, thus creating loss for the business and economy. This is proven by Rosekind, et al (2010) that sleepiness and tiredness issues are linked to the productivity loss ranging from 2. 5% for those that do not have any sleep problem until 6. 1% for those with insomnia.

One target group that engages in this type of situation are those working in the banking and financial sector. As stated by MacCormick, Dery and Kolb (2012) in their paper on smartphone use and employee engagement, investment banks are the ideal setting to explore employee engagement and patterns of smartphone use. The financial sector is a highly competitive and global sector where employees are generously rewarded for high levels of work. Investment banks sell a wide range of financial services and products, generally their operations function around the clock across the whole world. Working around the clock is the consequence of being employed in an industry where you are expected to work hours and to be conscious of customer and market needs. This is also affirmed in the paper of Kamstra, Kramer and Levi (2000), in which they mention that employees handling vast financial assets are over-represented in the population of those who have reduced average sleeping time through the years. This has led us to formulate the following research question:

“To what extent does sleep deprivation, which is possibly caused by smartphone use in the evening for work, affect the productivity of workers in the banking and financial sector?”

This research is socially relevant for the following two reasons. First, it analyzes the causes of sleep deprivation, providing an insight that might be useful for workers to improve their sleep behavior. Secondly, it looks at the consequences of sleep deprivation on productivity and may thus be helpful for banking and financial firms in shaping policies to enhance the productivity of their employees. This research is moreover scientifically relevant, as it builds up on previous research by considering different aspects. Whereas the most relevant past studies have considered the effect of sleep deprivation on morning depletion, we aim to find a relationship on productivity as this might be a more useful indicator of the negative consequences of low sleep quantity.

The introduction will be followed by a theoretical framework in which we will discuss past research and introduce our hypotheses. Afterwards, we will present our methodology and the modality in which we collected the data. Finally, our results will be presented and a conclusion with limitations and possible implications will be proposed.