1 Introduction

Technostress is a phenomenon that arises from “[d]irect human interaction with ICT [information and communication technologies], as well as perceptions, emotions, and thoughts regarding the implementation of ICT in organizations and its pervasiveness in society in general” [1, p. 18]. Technostress has become an established topic in Information Systems (IS) research. Evidence indicates a steadily increasing number of publications during the past years [2].

To advance research in this area, we reviewed technostress research before and called for several methodological adaptations. First, we called for more frequent measurement outside of research laboratories, mainly in order to create more externally valid findings [3]. Second, we recently highlighted that there is an overreliance on self-report measures and advocated the more frequent use of multi-method designs [2], predominantly because such an approach can explain additional variance in outcome variables that can hardly be explained through the use of single data collection methods [4]. Third, we provided an overview of previous organizational technostress research and the use of neurophysiological measures in this context [5]. In the last of these reviews we showed that only few studies applied neurophysiological measures (e.g., [6]). However, we also revealed that in those rare cases in which neurophysiological measures were used, measurement of cardiovascular indicators of stress (e.g., heart rate, heart rate variability and blood pressure) was most popular.

Despite the fact that heart rate and heart rate variability would come more easily to a researcher’s mind when thinking about longitudinal stress or technostress measurement in the field (e.g., using chest belts common in sports applications), in this paper we highlight why blood pressure should become an important method in IS technostress research. In the next section, we briefly summarize fundamental knowledge on blood pressure and its measurement, followed by a review of empirical technostress studies that used blood pressure as a stress indicator. We close this paper by providing insight on future research directions.

2 Blood Pressure Measurement

Blood pressure refers to the pressure that blood is exerting on the walls of blood vessels, typically in large arteries of the systemic circulation (e.g., brachial artery). The actual pressure is usually estimated through measurements of systolic and diastolic pressure levels on the outside of the vessel. Systolic blood pressure (SBP) represents the maximal force of the blood against vessel walls when the left ventricle of the heart is contracting (“systole”), while diastolic blood pressure (DBP) represents the minimal force when the left ventricle is relaxed (“diastole”) [7]. Normal blood pressure levels are usually defined as a maximum of 120 mm HgFootnote 1 SBP and a maximum of 80 mm Hg DBP [8].

In the past, blood pressure has been referred to as “the commonest measurement made in clinical practice” [9, p. 23]. Considering that hypertension (i.e., elevated blood pressure levels with SBP above 135/140 mm Hg and DBP above 85/90 mm Hg, [10, 11]) is prevalent in about one third of the population in Western countries such as Germany [12] or the USA [13], this statement is not surprising. Importantly, as shown in a review by Juster et al. [7], SBP and DBP have been used frequently in studies focusing on the effects of chronic stress, far more frequently than any other cardiovascular or respiratory indicator of stress.

In clinical practice, the auscultatory method is still frequently applied to measure blood pressure. Here, a trained person places a cuff on the upper arm (on the level of the brachial artery), inflates it above the level of systolic blood pressure and checks for specific sound patterns during deflation which indicate systolic and diastolic blood pressure (see [11] for more details, particularly on the phases and the varying sounds that are used as indicators). As this method requires a well-trained observer and is influenced particularly by noise in the environment, it was criticized in the literature [10, 11].

Mostly used in automated self-measurement devices, the oscillometric method uses oscillations of the blood vessel, instead of sounds, to estimate systolic and diastolic blood pressure [11]. This method is less susceptible to noise and also the cuff placement is less of an issue, though systolic and diastolic blood pressure are only estimated by algorithms of the involved devices, and not directly measured. It follows that measurements made with different devices should only be compared with caution [14]. However, evidence indicates high correlations between measurements using the auscultatory and oscillometric methods [11]. Thus, the use of self-measurement devices to determine blood pressure in IS research settings is an important measurement option.

Devices used for self-measurement of blood pressure (SBPM) are mostly offered for placement on the upper arm, wrist, or finger [10]. Due to the importance of measurement on heart level and the distance from the heart, upper arm devices are usually recommended, while finger monitors are less reliable, or even unreliable [10, 11]. Measurements on the wrist have some advantages. As an example, it is not susceptible to the circumference of the arm (which can have detrimental influence on the measurement with upper arm devices if a false cuff size has been chosen). However, measurements on the wrist are more susceptible to the right positioning of the arms, which requires thorough patient education to ensure measurement on heart level [14].

In the next section, we present the results of a review on the types of blood measurement methods and devices that have been applied in previous technostress research, followed by a section on further topics which have also already been investigated based on blood pressure measurement; also we briefly discuss the relationship of blood pressure with other neurophysiological measures.

3 Blood Pressure in Technostress Research

In order to identify relevant papers for our review, we used twelve papers drawn from previous reviews of technostress research (i.e., [15,16,17,18,19,20,21,22,23,24,25,26] taken from [1, 2, 5]) as the basis for a forward search in Google scholar (02/21/2017 to 02/24/2017). We opted for a forward search as we were interested in additional technostress research that used blood pressure as a stress indicator since the publications by the research groups of Werner Kuhmann and Wolfram Boucsein in the 1980s and 1990s.

Nine of these papers were drawn from previous reviews, though, as we focused on empirical research, we did not include the review paper by Boucsein [27]. Instead, four of the six papers that constituted the basis for the review paper by Boucsein [27] were included (i.e., two studies were excluded as they are only available in German). Based on a review of title and abstract of query results, we found three additional papers, thus resulting in a selection of fifteen papers for this review.

In Table 1, we summarized key features of these studies, including the main characteristics of used samples, setting of the study (i.e., laboratory or field research), measurement location (i.e., “arm” for measurement on the upper arm, finger, or wrist), measurement method (i.e., auscultatory, oscillometric, or other, if specified), and used devices.

Table 1 Overview of technostress studies applying blood pressure measurement
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Importantly, of the reviewed studies, only six were published in IS outlets (highlighted with an * in Table 1), while the remaining nine publications were published in non-IS outlets (e.g., six publications in Ergonomics). Hence, in total we found only six studies which have applied blood pressure measurement in three decades of IS technostress research. In addition, though we explicitly conducted a forward research in order to identify more recent publications, we only identified two technostress studies after 2000 that included blood pressure measurement.

As a showcase for the potential of blood pressure measurement in longitudinal research designs, we found several studies that collected data over several days or even weeks. Schleifer and Okogbaa [25] collected data at three points during the day over four consecutive days. Johansson and Aronsson [19] collected blood pressure at five points during a work day (approximately every 2 h) over three non-consecutive days. Lundberg et al. [26] measured blood pressure every 10 min during their test phases (either 90 or 60 min) over three consecutive days. Wastell and Newman [17, 18] measured blood pressure every hour (from 9 a.m. to 1 p.m.) on work days over a period of twelve weeks (six weeks before and after system implementation). Most other studies, mainly conducted in laboratory settings, collected blood pressure during a baseline condition (first measurement) and then again at the end of their test (second measurement).

Amongst the reviewed studies, measurement on the upper arm using the auscultatory method was most common. Some studies (i.e., [20, 28, 29]) measured blood pressure continuously using a volume clap on the finger [11], though this method can restrict the mobility of participants (due to constant connection to a monitor).

It is important to note that in none of the reviewed studies participants were advised to make self-measurements of their blood pressure, even in those studies in which self-measurement devices based on the oscillometric method were used (i.e., [17, 18, 20, 30]). Hence, one of the main advantages of self-measurement devices, that is the reduction of the so-called “white-coat effect” (i.e., elevated blood pressure levels in the presence of medical professionals conducting blood pressure measurements, [31]) was not derived in these studies.

4 Blood Pressure Measurement in IS Technostress Research and in Other IS Domains

Our results indicate that blood pressure measurement was mainly used in laboratory studies. Moreover, we identified the examination of the blood pressure effects of duration and variability of system response times (SRT) as the most prevalent topic (i.e., 7 out of 15 papers [15, 16, 21,22,23,24, 28]). Importantly, research results have been mixed. Considering that the individual studies used different types of stressors (e.g., different implementations of “slow” and “fast” response times, or presence or absence of time pressure to perform a task), it is likely that the mixed results are a consequence of differences in stimuli.

Other stressors that have been investigated include the general impact of computer-based work on individual well-being [17,18,19], the effects of system breakdowns [19], levels of monotony of computer-based tasks and physiological consequences [26], task monitoring and related perceptions of performance pressure [29], lack of social support or even an unfriendly social environment and physiological consequences [20], and the physiological effects of separation from mobile devices [30].

Based on a database search,Footnote 2 we identified additional recent applications of blood pressure measurement that could be interesting to IS researchers and that are not directly related to stress. Turel et al. [32] investigated the effect of videogame addiction on blood pressure and other cardio-metabolic indicators (mediated by sleep patterns and level of obesity). Their study revealed a positive relationship between obesity and blood pressure and they concluded that elevated blood pressure is an important addiction-related health risks. Stafford et al. [33] investigated the acceptance of conversational robots by older people. Among other tasks, participants had to draw a representation of the conversational robots before interaction with the robot, while physiological parameters including blood pressure were measured. The study found that larger drawings were related to higher SBP after interacting with the robot. Finally, Why and Johnston [34] investigated the relationship between cynicism, state anger, and cardiovascular reactivity outside of social interaction, involving a computer-based task where the mouse was manipulated to arouse anger. They found that state anger moderated the positive relationship between individual cynicism and blood pressure (i.e., cynicism was only positively related to blood pressure when state anger was high).

5 Blood Pressure and Its Physiological Correlates

In the fifteen reviewed technostress studies, blood pressure has frequently been paired with other neurophysiological measures. In particular, further cardiovascular indicators (heart rate, heart rate variability) were applied in all studies, while measures of electrodermal activity (e.g., SCL, SCR) were applied in five studies, electromyography in three studies, and stress hormones were measured in two studies.

A number of the reviewed studies found similar correlation patterns for cardiovascular indicators (e.g., blood pressure positively correlates with heart rate, and negatively correlates with heart rate variability, [19, 24, 25]), though there have also been studies which found different correlation patterns. For example, a number of studies that investigated changes in workload (e.g., due to varying SRT) found that higher workload positively affects SBP, while no change in heart rate could be observed [16,17,18, 21]. Kuhmann et al. [21] argue that such differences might be caused by workload type. In essence, they argue that blood pressure is more closely related to physical workload, while heart rate is more closely related to mental workload. In a further study, Kohlisch and Kuhmann [23] showed in the context of a data entry task that low motor demands (i.e., a small number of keystrokes per minute) may also result in elevated blood pressure. It follows that the moderating effect of workload type is not well established.

Another potential explanation for differences between blood pressure reactivity and heart rate reactivity was provided by Hjortskov et al. [20]. They argued that blood pressure frequently stays elevated because it is influenced by local mechanisms (e.g., muscle activity) and is therefore not as sensitive to changes in mental load as HRV. They showed that though HRV (LF/HF ratio) returned to baseline after elimination of an experimentally induced stressor, blood pressure stayed high throughout the experiment and DBP even further increased during control sessions. It follows that HRV could be a good indicator of the presence of a stressor, BP could be a good indicator for the level of individual relaxation. In the context of general job stress, this argumentation has been established by Steptoe et al. [35] who showed that elevated blood pressure levels were still present after work.

For electrodermal activity, Thum et al. [24] reported that higher workload (due to short SRT) led to elevated blood pressure. Yet, electrodermal activity increased when individuals where confronted with a long SRT, which can be a sign of emotional strain, as was also reflected in self-ratings of the emotional state (i.e., short SRT was rated positively, while long SRT was rated negatively). In the same study a positive correlation was found for blood pressure and frontalis EMG activity.

Regarding stress hormones and blood pressure, we refer the reader to a study by Johansson and Aronsson [19] who reported on an improvised study during an unforeseen computer breakdown. They found that the breakdown led to elevated adrenaline excretion, which was accompanied by increased DBP.

As in the study by Thum et al. [24], other studies also reported deviations of blood pressure from individual self-reports. For example, while Kuhmann [22] found that participants rated a short SRT more positively, this was not reflected in any physiological changes, eventually caused by a lack of time pressure during task execution. Kohlisch and Kuhmann [23], in contrast, found differences in physiological states due to changes in SRT, which were not accompanied by significant changes in self-reported states. Replicating the results of Thum et al. [24], Harada et al. [28] also found that physiological activation was highest when SRT was fast, but self-reports on emotional states showed an opposite pattern. Clayton et al. [30] found that self-reports on emotional states (unpleasantness and anxiety) reflected physiological responses.

Against the background of the discussion in this section, it is important to consider the specific context of a study to understand potential increases, or decreases, of blood pressure. Overall, we see the application potential of blood pressure as a complement to other cardiovascular measures (e.g., heart rate), predominantly because it can be a good indicator of individual relaxation after stress onset. A general review of blood pressure and its regulation in the human body can be found in [36]. IS researchers are advised to consider the insights provided in this and similar reviews in their study design.

6 Conclusion and Further Directions

Blood pressure measurement has not played a significant role in IS technostress research so far, though we identified and reviewed a number of studies that could inform future studies. What is striking is the variety of study designs and different procedures (e.g., number of measurements, frequency, timing, methods, measurement location) that is observable in those few studies alone. To foster the application of blood pressure measurement in IS research in general, and specifically in technostress studies, we therefore recommend that researchers refer to the guidelines that are provided and regularly updated by international health organizations (e.g., [10, 11, 14, 31]). These guidelines also list potential confounders (see Table 2) that should be taken into account, and which have been controlled for in some of the reviewed studies (e.g., smoking, coffee or alcohol consumption, arm position), but, importantly, not in all studies (e.g., importance of uncrossed legs for blood pressure measurement).

Table 2 Overview of important confounders in blood pressure measurement
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An important point that is reiterated in all of these guidelines, and not only valid for blood pressure measurement, is that device selection should be made carefully. As a consequence of the prevalence of blood pressure-related health issues in human society, researchers are in the advantageous situation that numerous organizations exist worldwide which continuously pay attention to the validation of new blood pressure measurement devices (on the general importance of measurement issues in NeuroIS research, see [37]). An overview of validated devices and related studies can be found online (http://www.dableducational.org/). By using this list, we found, for example, that devices used in the reviewed studies [20] and [30] have been validated in accordance with international standards (i.e., [9]).

As there were no technostress studies in our review that actually applied self-measurement of blood pressure and due to the lack of studies that used wrist devices for this purpose, our own research group is currently concerned with the comparison of seven corresponding devices (i.e., OMRON RS8, RS6, RS3; BEURER BC40, BC57; BOSO Medistar+, Medilife PC3). Among other reasons, such comparison studies are important because recent research indicates that blood pressure could be an important stress indicator in stress-sensitive adaptive enterprise systems [38].

In conclusion, we hope that this review paper provides a useful overview of previous IS technostress studies and helps to establish blood pressure measurement as an extension to the current measurement toolset of technostress researchers. It should be noted though that the interpretation of blood pressure levels should be made with caution, because it is affected by many factors, all of which are potential confounders in scientific research. However, if blood pressure measurement is used as a complement to other neurophysiological measures (e.g., [1, 2, 4, 5, 39]), including measurement of brain activity (e.g., EEG; for details see Müller-Putz et al. [40]), then blood pressure will likely become a valuable extension in the IS researchers’ toolset.