Public art and public space – Waiting stress and waiting pleasure

Abstract

The study presented here applies from an interdisciplinary perspective the “temporal know-how” of art and communication design as well as the social sciences to the exploration of the impact of two types of holistic artistic waiting room transformations on waiting experience and behaviour. The quasi-experiment was conducted in a hospital and in an administrative setting. Contrary to current information centred types of waiting management stressing ‘clock-time’ only and attempting to reduce objective waiting times, the artistic intervention follows a holistic concept by appealing to all the senses influencing felt time and social time. It comprises visual, acoustic, tactile/haptic and olfactory elements (fragrance management). The “observation-oriented” artistic intervention uses contemplative video works, ornamentation, relaxing fragrances and a corresponding seating design. The “action-oriented” room climate promotes communication and stimulating object and surface design, coupled with a subliminally stimulating fragrance environment. After a simultaneous one-week baseline measurement in both organizations, follow-up measures were conducted during one week of each type of intervention. Results are based on 482 personal interviews and 1950 observations of waiting clients: Perceived waiting time and objective waiting time correlated only moderately (rp = 56) and expected waiting time was overestimated. In both waiting room settings, room transformations – compared to baseline measures – reduced waiting stress behaviour (however not perceived stress) and increased both positive overall room perception and the evaluation of specific room characteristics among clients/patients. Differences between the two room climates were not significant and effects appear to be stronger in the administrative space. The relatively short waiting times (16–20 min) and high levels of waiting satisfaction at baseline might have limited the effect size of the holistic interventions. At the same time observed positive outcomes can be plausibly expected in waiting zones with much longer waiting times.

Keywords

Time perception waiting management stress servicescape experiment public space Switzerland public art

Social time and social space

Time as a social institution was analysed early on within the framework of the sociological study of time (cf. Bergmann’s literature review, 1992). In their classical methodological-functional analysis of time, Sorokin and Merton established that restricting time to purely quantitative, uniform and linear “astronomical time” is not appropriate for an analysis of social dynamics: “Social duration does not equal astronomical duration, since the former is a symbolic, the latter an empirical duration” (p. 625). Social time(s) are event-related, are not always linear, tick at different speeds depending on the situation, and have varying qualities (Klingemann, 2000: 1231–1232, 2001). Although there have been numerous theoretical social-scientific analysis of time (for example, Durkheim, 1965; Elias, 1992; Giddens, 1979; Lippincott, 1999), it has been scarcely the subject of empirical research. The study presented here addresses the dimensions and correlates of waiting times as a specific aspect of social temporal experience, which is particularly relevant in the service sector, as ‘time is money’. Focusing on quality control (Helbig et al., 2009) and cost-efficiency (Koopmanschap et al., 2005), organizations usually make efforts to shorten objective waiting times, considering also that there are studies showing that waiting times have a significant influence on a patient’s propensity to seek treatment (Tak et al., 2014). However, objective waiting time and perceived waiting time need not correlate closely and positively. The experience of time in health services, such as when waiting for an operation, could be influenced by a number of factors including the feeling of pain and functional difficulties (Johnson et al., 2014; Tom and Lucey, 1997). Pruyn and Smidts (1998) assumed: “The adverse effects of waiting can be soothed more effectively by improving the attractiveness of the waiting environment than by shortening the objective waiting time …” (p. 321); in other words, by making an effort to reduce objective waiting time by influencing people’s perception of waiting (cf., for example, Bournes and Mitchell, 2002), by changing the waiting situation. Such efforts – if they are undertaken at all – are often situated at the cognitive or information level. Apart from attempts to use waiting times for preventive or educational purposes (Auran and Burger, 1985; Fry, 1983), the waiting subjects are typically provided with information about the waiting process (e.g. remaining waiting time and position in waiting line). An experiment on telephone waiting times found that when the waiting persons were given information about the remaining (objective) waiting time, this reduced their subjective estimation of the waiting period (which they tend to overestimate), but still had a negative effect on their general appraisal of the waiting experience (Antonides et al., 2002).

The one-dimensional ‘information bias’ of waiting management is enriched by conceptual studies taking the influence of space and context of service organizations into consideration when addressing waiting clients’ needs. The use of space design management for waiting time management has been tentatively tested in the hospital/health sector (e.g. Pricewaterhouse Coopers, 2004), but rarely in the public administration sector, an exception being Paris’s (2001) study of “waiting in administrative office corridors”. The analytical framework suggested by Bitner (1992) in her analysis of the physical environment of service covers three dimensions: “spatial arrangement and functionality”; “signs, symbols and artefacts”; and “ambient conditions.” The latter are the “… background characteristics of the environment such as temperature, lighting, noise, music and scent. As a general rule, ambient conditions affect the five senses. Sometimes these dimensions may be totally imperceptible …, yet may have profound effects.” (Bitner, 1992: 66). However, with few exceptions (e.g. Andeane and Villalobos, 2003; Chun-Yen Tsai et al., 2007), empirical studies using a holistic approach including both the physical environment of waiting rooms and addressing the role of affect and emotions on the perceived attractiveness of the waiting space are scarce, as the review by Biddiss et al. (2014) in health care waiting spaces showed. Interventions in waiting situations that are not cognitively oriented largely focus on the influence of music (Bailey and Areni, 2006; North and Hargreaves, 1999; Stratton, 1992) and olfactory stimuli (scent environments) affecting moods, physiological processes and behavioural patterns (Chebat et al., 1993; Herz, 2009; Lehrner et al., 2000; Vilaplana and Yamanaka, 2014). From a multidisciplinary perspective, various functions of art and artistic room design are particularly suited to merge these various influences or factors (e.g. Nanda et al., 2012). The general link between art and health has been illustrated by a review by Clift et al. (2009) entitled “The State of Arts and Health in England.” The authors concluded that, “The view that the creative arts have a role in health promotion and health care settings is firmly established in England” (Clift et al., 2009: 24). A review by Byrne and Tony O'Connor (2008) highlighted the effects of spatial parameters and art and design interventions on hospital personnel and patients. According to this study, “key findings from the review include evidence that exposure to the arts may reduce anxiety and depression in specific groups of patients … the arts can positively affect clinical and behavioural outcomes” (Byrne and Tony O'Connor, 2008: 92). Finally, a literature survey by Dijkstra et al. (2006) came to the conclusion that “the physical environment of the healthcare setting can encourage the healing process and patients’ feelings of well-being …” (p. 166; see also Daykin et al., 2008).

Study objectives and hypotheses

We investigated the influence of temporary artistic interventions and transformations of selected waiting rooms on individual waiting experience (including waiting/service stress and subjective waiting time) and waiting behaviour. Firstly, we predicted that artistic interventions which have been designed to appeal holistically to all the senses will facilitate a “more pleasurable” or at least more “relaxed” waiting experience, independently from the objective time one spends waiting. We assumed further that artistic room transformations would have a positive effect on the perception of the waiting room features compared with baseline measures. Secondly, based on Flaherty’s theory of lived time (Flaherty, 1999; Flaherty et al., 2005), we predicted that subjective waiting time in terms of pace of time will differ significantly between changed and unchanged room conditions: The artistic room transformations are a departure from routine and confront the visitors of the waiting room with an unusual, unexpected situation. This represents an abnormally intensified stimulus complexity and leads to a great cognitive involvement with the self and the situation, which in turn assumingly produces a ‘protracted duration’ of the waiting time (Flaherty, 1993: 404). ‘Temporal compression’, the impression that time passes more quickly than usual, is assumed for baseline conditions when visitors come to the expected, familiar waiting room with low cognitive involvement and low stimulus complexity. Thirdly, we predicted that the level of emotional concern and anxiety related to the waiting purpose as an intervening variable will amplify and modify the effects of the artistic interventions.

As a first waiting context, we chose a Municipal Residents’ Registration Office, an administrative setting (AS), because of its assumed relatively high percentage of routine waiting purposes. As for the second waiting context, a polyclinic waiting room at a university hospital was selected because a hospital setting (HS) was assumed to have a higher share of emotionally charged reasons for waiting. The two different waiting room settings allowed for the consideration of the influence of the level of waiting tension and the general social waiting context. The artistic interventions in the AS compare to a baseline situation with a relatively higher ‘density of experience’ or ‘stimulus complexity’ (Flaherty, 1991) than in the AS.

Finally, we established the hypothesis that not only the overall stimulus complexity is relevant but also the type and quality of the stimuli the waiting client is exposed to. Drawing upon empirical, social-scientific findings about the perception of art (e.g. still lives and healing arts), two types of artistic interventions (“action-oriented” vs. “observation-oriented”, see “Artistic room interventions/transformations” section) were developed and administered at both study sites. We assumed the impact of the action-oriented artistic intervention package relative to the observation-oriented artistic intervention package will be stronger in the HS than in the AS. Diversion and action assumingly will reduce waiting anxiety more efficiently than introspective meditative stimuli. The latter is likely to amplify the effects of seemingly ‘empty times’, when waiting clients “… are covertly, actively, and self-consciously engrossed by the circumstances, regardless of the apparent uneventfulness” (Flaherty, 1991: 81).

To test the hypotheses outlined above, the first part of the following analysis established a basic framework by addressing the issue of synchronicity or the relation between subjective and objective waiting times and by comparing socio-demographic characteristics, waiting reasons and their attributed importance by study site and intervention type. The second part systematically focused on the impact of the artistic interventions by analysing individual temporal experience (self-reported and observed waiting stress, felt pace of time) followed by an analysis of space-related outcome parameters (individual satisfaction with general and intervention-related waiting room characteristics). Finally, the relative impact of the artistic room transformations is addressed by a multivariate analysis of the predictors of a room-satisfaction summary score. Statistical procedures conducted with SPSS 21 included bivariate comparisons, comparison of means (t tests) correlational and linear regression analyses.

Methods

Artistic room interventions/transformations

The elaboration of the artistic interventions was a central part of the study and represented a process of artistic research. The challenge was to define the criteria, which would allow for the selection of specific pieces of art for the room transformation. With no available reference studies, the individual elements of the intervention originated as a result of associative strategies of art production and not within a framework of functional design. Nevertheless, the installations needed to be combined in a meaningful way. The challenge was to create two different, but comparable artistic interventions (action-oriented/observation-oriented) for two waiting areas differing from each other by various factors such as ceiling height, colours and structure; dominant colours of walls and floors, as well as parameters which could not be changed such as furniture and artworks, daylight/artificial light, and disturbing passageways.

More specifically, the ‘action-oriented artistic intervention package’ (ART) is defined as a room intervention/transformation that first introduces a set of new unfamiliar artistic objects that can be played with or used by the waiting population (see also Biddiss et al., 2013). The installations do not have any labels that would suggest an obligation to use them. Secondly, with this set up, the general characteristics and the pre-existing interior of the waiting environment were transformed to facilitate and indirectly stimulate individual action and social interaction in the waiting zone. The ‘observation-oriented artistic intervention package’ (ORT) is defined as a room intervention/transformation that firstly brings new unfamiliar artistic objects into the waiting zone and that do not provide an invitation for action, but favour observation. Secondly, with this arrangement, the general characteristics and the pre-existing interior of the waiting environment were transformed to create a contemplative atmosphere inviting ‘to watch and lean back’. Both intervention packages pursue an integrative approach with a coherent and comprehensive room intervention (contrary to eclectic, particularistic interventions – ‘change the wall colour, hang a nice picture’) and use visual, acoustic, tactile and olfactory elements as well as address the sense of spatial perception. The interplay and selection of the various design elements were guided by a distinction between primary and secondary room interventions/installations. While the former was assumed to be directly and functionally connected to the type of room intervention that is the creation of an ‘action-oriented’ or an ‘observation-oriented’ room climate, the latter had to aesthetically harmonize with the overall room intervention and may or may not have additional supportive functions. Specifically, the observation-oriented room interventions package (ORT) included four monitors that show a natural sound scape with birds and water, and ornamental textile panels (making references to rococo decorations) as primary interventions. Olfactory design elements (aroma stream devices) and haptic elements (changes in the type of the basic seating and addition of four ‘special chairs’) served as secondary, supporting interventions. The action-oriented intervention package (ART) featured as primary interventions one transparent column with air bubbles in highly viscous fluid with red ‘action buttons’, a monitor with mobile waiting interactive shadows, and as a new element, three consoles with integrated i-Pads whose visual or screen view invites one to play the Bloom application (http://www.youtube.com/watch?v=YJkMdm5T1PY) (with a minimal music-like component) positioned in between chairs in the waiting rooms. Again, different versions of the aroma streams and a selection of three specific chairs grouped around the ‘bubble column’ and bright-colour textile panels qualified as secondary interventions as defined above. For the visualization of the room transformations, the artistic installations and the pre-test phase, see the picture gallery: https://picasaweb.google.com/115805555114842963323/WAITING?authuser=0&authkey=Gv1sRgCMWrwub3puXLJA&feat=directlink

Impact measures/instruments

Interviews with the waiting clients covered, among other aspects, socio-demographic data including cultural background, subjective waiting time estimations, reason and importance of waiting purpose, and the perception of various dimensions of the waiting room partially based on the study by Chun-Yen Tsai et al. (2007). After discussions with the practice partners and the staff of the study sites, neutral time windows were defined in a way that neither the waiting client nor the service staff would lose additional time when an interview is conducted. More specifically, in the administrative context, staff members would check the inclusion criteria (e.g. minimum waiting time of 10 min) and the availability of a standby interviewer when servicing the client and then, informing the client that additional time would still be needed to complete his/her request and asking if he/she would be willing to give an interview. After completion of the interview, the client was accompanied back to the waiting room to check out. The drawing of a number slip upon arrival allowed access to system data on the objective waiting time. In the hospital context, staff at the reception desk would estimate the minimum waiting time of a patient (10 min as minimum) who would be contacted by an interviewer 15 min prior to the end of the estimated total minimum waiting time. The simultaneous work of several doctors however made this solution more precarious compared with the administrative working context. In both sites, admission forms were filled out. Two observers collected structured observation data in each setting by using tablets as event recorders. Each observer watched two waiting persons simultaneously following a sampling procedure alternating between defined direct exposure and indirect exposure areas in the waiting room (seats directly in front of a monitor or the ‘bubble column’ vs. remote seats). Event recording was related to three major behavioural categories, namely, ‘indicators of stress, relaxation and social interaction’ (e.g. Smidt, 1994); ‘indicators of perception and use of the artistic room interventions’ and ‘general waiting activities’ (e.g. reading, using electronic devices). This procedure allowed for the inclusions of parameters of ‘time work’ or how waiting populations actively customize their temporal experience (Flaherty, 2003).

Fieldwork and data collection

The intervention phase took place in March 2012. During the first week, baseline measures were collected simultaneously in the unchanged waiting rooms of the university hospital/polyclinic (HS) and the Municipal Resident Services as the AS. By the following week, the intervention ‘action-oriented room transformation (ART)’ took place, followed by the ‘observation-oriented room transformations (ORT)’ during the third week. To ensure an undisturbed course of the three ‘experimental weeks’ and to avoid curious outsiders’ visits, a press release was issued, coupled with an information embargo on media reports about the study until the last week of the experimental phase.

During this data collection period, 482 face-to-face interviews (HS n = 178; AS n = 304) were conducted during the three-week intervention period and 1950 waiting clients/patients have been observed (HS n = 667; AS n = 1283). A total of 979 persons who checked in at the admission/service counters were disregarded because they did not meet the inclusion criteria (language skills, minimum waiting time of 10 min, and age of 18 years old or older) or did not agree to be interviewed. Sixty-eight percent of the administrative waiting room population and 20% of the clinic patients who registered during that period were not included in the study. As to the AS, the drop-out rate was due to clients who were serviced directly by the floor manager and consequently did not show up at the service counter and also included customers who left the waiting area prematurely for several reasons, before it was their turn. Dropouts in the HS were partially a function of the short waiting times in the polyclinic during the study. In the particularly difficult HS, if patients were reluctant to leave the waiting room temporarily, the interviewers conducted their interviews at the seating place. The overall flow of clients/patients in both settings – for unknown reasons – was qualified as relatively low.

Results

Times felt and spent while waiting

The basic assumption from the sociology of time that clock time and subjective time do not necessarily coincide is supported: The average objective waiting time during the three experimental weeks amounted to only 18.1 min (n = 476, SD. 9.047) ranging from 16 to 20 min, without significant differences between the hospital and the AS. The mean of the estimated time, that is, how long a person thought he/she had waited, was 19.08 (n = 479, SD: 11.6) within a range from 18 to 21 min. Both time horizons correlate significantly, but with rp = .56 (n = 473; .000 sig. 2-tailed) only moderately. The expected waiting time prior to arrival in the waiting zones was on average 31 min (n = 466, SD = 28.7) ranging from 24 to 36 min, thus representing a stark overestimation of the actual waiting time. With rp = .036 (n = 438, NS), objective and expected waiting times do not co-vary at all. In other words, clients/patients have no clear vision what to expect in terms of waiting. This represents a challenge for the information policy of the organizations involved.

Who waited, why and what was at stake

A comparison of the socio-demographics of the waiting populations pointed to significant differences between the study sites but not across the study weeks within the same setting: Compared with the AS (n = 304), the HS population (n = 178) is older, consists of mainly Swiss citizens, with lower educational background and with a higher proportion of individuals no longer working. The proportion of women in the waiting populations is similar between HS and the AS (see Table 1). The major waiting reason at the AS is the registration of a new address (fluctuating between 34% and 45% over the study weeks) and at the HS, a diagnostic preparation for surgery (35–39%). As to the attributed subjective importance of the waiting reason during the three experimental weeks, 44% (baseline), 31% (ART) and 21% (ORT), respectively, of the respondents in the HS setting considered the visit a formality compared with 54% (baseline), 60% (ART) and 59% (ORT) in the AS. This result validated, at least indirectly, the selection criteria for the study sites assuming a higher level of anxiety in the HS compared with a routine climate in the AS allowing for a test of a differential effect of the two types of artistic interventions by study sites.

Table 1.

Socio-demographic characteristics of study samples and importance of waiting reason by study site and type of artistic intervention.

Study site by experimental week	Women	Age (mean)	Swiss citizen	Importance: ‘formality’¹	University degree	Not in work force
AS baseline	50% (n = 54)	x = 34 (SD = 11.6)	41% (n = 23)	54% (n = 59)	45% (n = 49)	14% (n = 15)
AS ART	51% (n = 40)	x = 35 (SD = 12.1)	41% (n = 39)	60% (n = 58)	46% (n = 44)	12% (n = 11)
AS ORT	40% (n = 40)	x = 36 (SD = 12.7)	47% (n = 46)	59% (n = 58)	35% (n = 35)	10% (n = 10)
HS baseline	40% (n = 19)	x = 43 (SD = 17.6)	86% (n = 38)	44% (n = 21)	9% (n = 4)	27% (n = 12)
HS ART	49% (n = 32)	x = 49 (SD = 16.8)	82% (n = 51)	31% (n = 20)	8% (n = 5)	34% (n = 21)
HS ORT	43% (n = 26)	x = 49 (SD = 17.8)	83% (n = 50)	21% (n = 13)	7% (n = 4)	44% (n = 26)

¹“How much was at stake for you with today’s appointment?” “It was a formality” – “much was at stake” – “very much was at stake”.

Changing the waiting room environment – Was the waiting experience improved?

(Pace of time and self-reported/observed stress) No significant differences in terms of experienced pace of time between baseline measures and intervention weeks were found (see Table 2, fifth column). As to ‘felt waiting time’ the meditative ORT in the ART led to the impression of having waited on average longer compared with active ART and baseline conditions in the ART (Table 2, sixth column).

Table 2.

Self-reported and observed waiting stress and subjective pace of time by study site and type of artistic intervention.

Study site by experimental week/ type of intervention	One or more specific stress indicators observed¹	General observer rating ‘waiting client clearly at ease’	Self-reported tension while waiting (‘pretty tense’ or ‘very tense’)²	“Time passing at the speed of a snail”³	“Felt waiting time”⁴ Mean (minutes)
AS baseline	33% (n = 138)	83% (n = 208)	18% (n = 19)	21% (n = 23)	9 (SD = 9)
AS ART	10% (n = 43)	93% (n = 221)	21% (n = 20)	14% (n = 13)	7 (SD = 6)
AS ORT	10% (n = 44)	93% (n = 214)	17% (n = 17)	15% (n = 15)	20 (SD = 11)
HS baseline	40% (n = 115)	85% (n = 154)	15% (n = 7)	15% (n = 7))	18 (SD = 12)
HS ART	31% (n = 60)	94% (n = 125)	23% (n = 15)	18% (n = 12)	17 (SD = 7)
HS ORT	37% (n = 69)	94% (n = 133)	20% (n = 12)	13% (n = 8)	16 (SD = 9)

¹In both settings a total of N = 1950 waiting clients/patients were observed; observers were trained to record indicators such as: waiting person pacing, hiding or scratching one’s head, going to the counter before being called, sitting on the edge of the chair, making a fist, fast eye lid movements, staring at the service screen. ²“How did you feel altogether today in the waiting room?” ‘very relaxed’ – ‘rather relaxed’ – ‘rather tense’ – ‘very tense’; ³interview item: “Did time pass for you like ‘flying by’, ‘as usual’, ‘at snail’s speed’?”; ⁴interview item: “And how long, how many minutes, do you think you have been waiting – please don’t check your watch – before you were called?”.

As to self-reported stress and tension, baseline measures showed that also only a minority reported feeling ‘tense’ or ‘very tense’ (see Table 2, fourth column). From this relatively positive baseline situation, neither the ART nor the ORT significantly reduced self-reported waiting stress further.

However, a different result emerged when the large database of observed stress behaviour among 1950 waiting subjects was evaluated. Even though stress-related behaviour accounted for only 5% on average of the individual waiting time, the artistic room transformations reduced stress behaviour significantly even under these circumstances: Similar to the picture provided by the interview data, two-thirds of the waiting population did not show any signs of stress behaviour (see Table 2, second column). The analysis of individuals who did show at least one stress-related action (or more) between the experimental weeks and the settings confirmed that the percentage of this stressed group declined at the AS from 33% (n = 417) at baseline to 10% each in the ART and ORT environments. At the HS, the decline was from 40% at baseline to 31% and 37% for ART and ORT, respectively. This supports the initial assumption that in the HS, with a higher level of anxiety, the diversion of the ART tends to have a slightly higher stress reduction effect than the more meditative and reflective ORT. Finally, participant observers were also asked to provide an overall assessment of the state of the observed target person. Results confirm the findings from the specific observation data: Observers rating at baseline during the AS week was that 17% (n = 41)/HS 14% (n = 24) of the waiting population were clearly ‘not at ease’; this percentage dropped to 6% for ART (HS: 5%) and 7% for ORT (HS: 6%). At the same time, the percentage of individuals ‘clearly at ease’ increased in the AS by 10% both for ART and ORT, and in the HS, also by 9% again both for ART and ORT.

To conclude, firstly, the sensitivity of the observational data is higher compared with the self-reported waiting stress when waiting stress is limited to a minority of the waiting population. Secondly, in the HS, the assumption that the ART improves the waiting experience compared with baseline and that ORT does not significantly reduce waiting stress in situations where much is at stake, is only tentatively supported by the data without reaching statistical significance. In the AS, the effect is even stronger, and no differences between ART and ORT were detected.

Perception of the waiting room characteristics

The perception of the waiting room, that is the physical environment, by the waiting population, has been taken into consideration as an additional indicator for the quality of the waiting experience. Respondents were presented with a list of specific room features/functions (partially based on the scale used by Chun-Yen Tsai et al., 2007) and rated their satisfaction on a scale from 1 (very dissatisfied) to 5 (very satisfied). Open-ended questions were also asked, if the respondent had noticed anything ‘particularly positive’ and anything ‘particularly negative’ in the waiting area.

Table 3 shows a comparison between sites and experimental weeks of the clients’/patients’ satisfaction with the seven room features which had been manipulated during week two and week three. In the AS, the waiting populations rated the artistic room changes during week two and week three significantly more positive than the unchanged baseline situation in terms of the average room-satisfaction summary score. With the exceptions of reduced daylight (by the textile window panels), which led to a decrease of satisfaction and the number of seats, the other room characteristics were perceived as improved (ORT vs. baseline, five aspects; ART vs. baseline, three aspects).

Table 3.

Satisfaction with waiting room features by waiting study site and type of artistic intervention (‘0’ very dissatisfied–‘4’ very satisfied; n = 473).

Site/week	Room light	Room furnishing	Colour design	Distract. options	Relax. options	Number of seats	Seating comfort	Total score (0–28)
AS baseline	x = 3.1*	2.6*	2.3*	2.1/*	2.2/*	3.3	2.7*	2.56/*
AS ART	2.8*	2.8	2.5	2.6*	2.5*	3.4	2.8	2.78*
AS ORT	2.9	2.9*	2.8*	2.5**	2.7**	3.3	3.0*	2.85**
HS baseline	2.8	2.6	2.3*	2.6*	2.5	3.4*	2.7	2.69
HS ART	3.0	2.6	2.6	2.6**	2.6	3.2	2.7	2.76
HS ORT	2.9	2.7	2.8*	2.1/*	2.5	3.2*	2.7	2.64

AS t tests* sig. (2-tailed): baseline vs. ART: light: .01/distraction: .001/relaxation .009.

Baseline vs. ORT: distraction: .006/relaxation: .000/furnishing: .026/colours: .001/seating comfort: .008.

ART vs. ORT: no significant differences.

HS t tests *sig. (2-tailed): baseline vs. ORT: distraction: .017/colour design: .007/number of seats: .014 ART vs. ORT: distraction: .011. **indicate the pair of means of which the comparison is significant.

At the same time, no significant differences were detected between the ART and the ORT: the ART also had a significantly higher satisfaction with the individual room characteristic ‘options to relax’ and the ORT with a significantly higher satisfaction with the room aspect ‘options for distraction’. In the HS, only satisfaction with the colour design improved significantly between baseline measurement and ORT. Baseline measurement compared with ORT showed that in the HS, the creation of a more meditative climate was perceived rather negatively as a lack of distraction not an opportunity to relax and meditate. This result is partially in line with the assumption that in an anxiety-loaded environment, distraction is perceived as more functional than inner-directed relaxation.

While the data on the satisfaction with specific features of the physical waiting environment point to a more focused and limited effect of the artistic room transformations in the HS, the open-ended questions on the more holistic, overall perception (“Did you notice something particularly positive (negative) today in the waiting room?”) showed a different picture: During baseline measurement, only one-third of the patients in the HS (n = 48) mentioned something particularly positive (most frequent category ‘staff’) and 21% made particularly negative observations (most frequent category with 6% ‘other waiting patients’); the percentages of positive observations more than doubled with the ART to 76% (n = 67) (most frequently mentioned was the column with air-bubble installation with 22%) and with ORT to 70% (n = 63) (most frequently mentioned was the textile panels with 24%). The latter is in line with the positive evaluation of the room colour design expressed with the dimensional standardized rating discussed above.

In the AS at baseline, half of the clients (n = 109) mentioned particularly positive aspects mainly related to the staff behaviour (32%); under ART and ORT conditions, these percentages increased even more by a quarter to 77% (n = 96) (most popular was the column with air-bubble installation) and 75% (n = 99) (most popular were the monitors with still images). In both settings, the proportion of particularly negative observations varied between 21% and 33%. With two exceptions, ‘negative highlights’ were not related to the artistic interventions but for example, to other waiting individuals, organizational aspects, staff behaviour and reading material. In the ART under ORT conditions, the 29% positive monitor highlights contrasted with 10% negative comments about the monitors. From the additional remarks, it became clear that a misinterpretation of the real-time still images on the monitors or screens as ‘broken television sets’ fed into these negative comments. Other user-related new interpretations of the installations, such as the assumption that the waiting shadow projection represents a projection of body temperatures in different colours, do not necessarily entail negative connotations.

Taken together, the open-ended questions probing for positive and negative observations cannot be linked directly to the structured evaluation reported earlier: In the HS, the significantly increased observation of positive room highlights seems not to be directly related to satisfaction with specific room categories. For instance, mentioning the bubble column as a particularly positive feature does not necessarily translate to a higher satisfaction in HS conditions with distraction options while waiting. When ‘scanning’ the waiting room, clients/patients might not proceed by assigning analytical categories based on what the measurement instruments include, but might see environmental characteristics and highlights embedded in spatial context.

Waiting room features ‘as a package’

The core concept of the artistic interventions as a holistic room transformation appealing to all senses – contrary to piece-meal engineering by introducing isolated art objects in the waiting zones – is mirrored in the perception of the waiting population: The change parameters on which the interventions focused were all significantly correlated (at .000 level) within the total sample of interviewees (n = 472). For example, both satisfaction with distraction and relaxation while waiting were linked with colour design (rp = .36/rp = .46) and room furnishing (rp = .33/rp = .37). In addition, distraction features and relaxation features were seen as rather complementary (rp = .49) than competing room elements. While ‘seating comfort’ and ‘colour design’ showed somehow stronger links with ‘relaxation satisfaction’ than ‘distraction satisfaction’ (rp = .44 vs. rp = .29 and rp = .46 vs. rp. = 36), once again the initial assumptions underlying the ART and ORT room climate concepts seem to be only of minor relevance in practice.

Furthermore a ‘spill-over effect’ was observed: Changes in the satisfaction with room elements during the experimental weeks which have been targeted by the artistic interventions also led to changes in the perception of room conditions which have objectively remained largely unchanged: For example, the more positively the colour design was evaluated, also the more favourable were the ratings of the temperature, air quality and noise level in the rooms (rp = .28; rp = .31; rp = .36). People also felt more adequately informed about the waiting time when they were satisfied with the relaxation features of the waiting area (rp = .30) even though the information policy/scheme was the same during the whole time. Finally, the share of clients/patients who were very satisfied with the services provided, increased by 15% both in the AS and the HS when baseline conditions were compared with ORT. Again, it seems remotely plausible that the customer orientation or service mentality of the personnel has changed during the three study weeks.

Determinants of waiting room perception, a tentative multidimensional analysis

A multiple regression analysis with the confounded study sample and performed separately by study site showed a significant effect only for the joint artistic intervention (β = .268). The consolidated room-satisfaction score was used as the dependent variable and the socio-demographics and other waiting-related background variables were controlled for, which explain the 18% (R²= .182) and 10% (adjusted R²= .100) of the variance, respectively. Performing the analysis separately by study site, the intervention effects on the total room satisfaction in the HS are not supported by the data, whereas a strong effect (β = .334) of the confounded artistic room intervention (ART and ORT) on the consolidated room-satisfaction score can be observed under AS conditions (Table 4). Proximity/exposure of the waiting client to the main artistic installations also seemed to have a positive effect on the room satisfaction, however, without reaching statistical significance (sig. = .087). The more is at stake for the waiting client and the older he/she is, the more significantly satisfied he/she is with the room features. The independent effect of the objective waiting time did not reach a statistically significant level, even though there was a tendency to evaluate the room features more positively with decreasing waiting time. Finally, the female and more educated customers were slightly less happy with the room features. The model explains 33% (R²= .330) and 23% (adjusted R²= .230), respectively, of the variance in the dependent variable.

Table 4.

Artistic intervention and exposure, socio-demographic waiting-related characteristics of the waiting population in the administrative setting as predictors of waiting room satisfaction – a linear multiple regression analysis.^a

Waiting room-satisfaction summary score
Predictors/variables	b	Std. error	β	t	Sig.
(1) Nationality	−.91	1.67	−.06	−.54	(.586)
(2) Previous visits	.16	.41	.04	.40	(.689)
(3) Accompanied	1.12	1.66	.07	.67	(.500)
(4) Highest education	−.43	.36	−.13	−1.19	(.237)
(5) Sex	−2.36	1.55	−.17	−1.51	(.134)
(6) Room transformation	4.75	1.53	.33	3.19	.003
(7) Objective waiting time	−.11	.08	−.14	−1.36	(.176)
(8) Importance	2.06	.87	.26	2.37	.021
(9) Age	.14	.06	.26	2.31	.024
(10) Proximity/exposure	−2.45	1.4	−.18	−1.73	.08
R²= .330; n = 304

Predictors were measured as follows: (1) dummy: 1 = foreigner-Swiss citizen; (2) number of waiting room visits in the past; (3) dummy 1 = came alone; 2 = accompanied; (4) range: 1 (no school) to 7 (university); (5) dummy 1 = female, 2 = male; (6) 0 = baseline; 1 = ART or ORT artistic intervention; 0 = baseline; (7) in minutes; (8) 1 = formality, 2 = much at stake, 3 = very much at stake; (9) in years; (10) 0 = waiting sector with no direct exposure to artistic installation; (1) waiting sector with direct exposure to artistic installation.

Dependent variable: total satisfaction score with 12 room features (light, furnishing, colour design, noise level, air quality, room temperature, number of seats, seating comfort, reading/information material, information on waiting time, options to relax (1 = very dissatisfied to 5 = very satisfied); observed range of total satisfaction score: 8–53.

Discussion

This study is a first attempt to analyse the effect of comprehensive ‘real-life’ room transformations on waiting behaviour and perception of waiting time and stress from a trans-disciplinary perspective of the ergonomics of the art. The findings of this quasi-experiment shed light on the effects of artwork to people in relation to their time in a specific social context (the waiting context).

Results lend support to the assumptions that subjective time and clock time among waiting populations are only moderately correlated (see “Times felt and spent while waiting” section) and that comprehensive artistic room transformations appealing to all senses yield positive effects in terms of general and specific room perception as well as waiting stress behaviour. As to the latter, self-reported stress data were limited compared with collected observational data. This was possibly due to people not wanting to admit being stressed.

Effects in the AS proved to be more distinct than in the HS.

Even though the comparability is limited by different compositions of the waiting populations, qualitative observations make it appear plausible that the degree of consistency and harmony of the overall room transformations and ‘the social chemistry’ of the waiting zone played a role: The AS with the strongest intervention effects proved to be more harmonic than in the HS also in terms of the staff’s team spirit compared with the HS with a variety of different actors in the waiting area. There is anecdotal evidence that in the harmonic context of the administration, the interventions were more likely to become a factor of identification and a bonding element between staff members and waiting people beyond the official/instrumental reason for their dealings with each other. While the interior design of the former was relatively recent and consistent in itself, the design of the HS was several decades old, with many layers of modification and changes in use leading to a much more heterogeneous general ambiance. Whereas the AS made it relatively easy for the artistic interventions to appear as a unified and harmonic whole, the jumble of visual distractions already present in the hospital waiting room posed the danger that any further additions (however well balanced among themselves) would serve to highlight the air of ramshackle improvisation of the room. The AS provided more of a neutral canvas for the interventions.

Concerning the difference between the baseline and the two interventions, one detail seems noteworthy: In both baseline settings, there were artworks already present, which were not removed (in the AS: a barcode print on the elevator; in the HS: a big canvas with an abstract painting and a landscape-like wall relief). The evaluation results show that in neither place, these pre-existing artworks had been noticed and mentioned spontaneously. As mentioned earlier, contrasting this finding, between 33% and 77% of the respondents in the transformed waiting zones referred to a component of the art interventions as particularly positive. This supports the notion that a single piece of artwork needs to be part of an entire room concept. It also becomes clear that the interaction between specific intervention elements such as colour design and the architectural features leads to a subjective overall experience.

Contrary to the initial assumptions, the effects of the artistic room transformations were largely independent from the type of intervention. Only partially, qualitative data about the perception of installations perceived as positive, pointed to a more central role of the action-/diversion-oriented intervention type in the HS with a higher anxiety level among waiting patients. A closer look at the components of ART and ORT in fact reveals latent commonalities and blurred the distinction between action and observation interventions as central features of the room climates in practice. The ‘dosage’ of action-oriented installations would possibly have to be increased and be more aggressive to discriminate more clearly for the meditative type of observation-oriented room climate. More specifically, the interventions of the ART had latent, very strong sensuous components inviting contemplation and observation, such as the air bubbles from the column rising once in a while in the silicone oil. As to the ORT, intensive observation can be considered also as a kind of physical activity, for example, when a child touches the screen trying to grasp a frog on the monitor, or somebody moves his chair to get a better view of the still images on the monitors.

The discussion of the scientific findings presented here in the context of a consensus meeting revealed a number of important issues and led to recommendations that will inform both future research and practice in the field: It was pointed out that the need to improve waiting conditions is currently of important relevance both in the health and administrative sector, given financial cuts and staff reductions in public services. In addition, in multicultural settings and with heterogeneous customer profiles, artistic room transformations, being language independent, appear as particularly suitable. With regard to both study sites, the necessity to consider the needs of the waiting populations as well of the staff was acknowledged and interaction effects between client satisfaction and staff satisfaction were highlighted. As to the waiting populations, questions have been raised if waiting room transformations should cater to different patient/client types: Patients returning regularly, for example, for radiation therapy and possibly at the end of their life might have different room preferences than clients waiting for a check-up at a polyclinic or children waiting at a children’s hospital. ‘Basic waiting needs’ should be identified, while group-specific waiting room designs should be incorporated into a framework/concept of the overall organization to avoid the impression of ‘exotic waiting islands’. In both cases, the client perspective has to serve as a starting point (happy bright colours in an area for radiation therapy are meant to cheer up, but can be seen also as making fun of the patients, as an example mentioned).

The authors recognize several limitations of the study which at the same time point to future research needs and priorities: The overall relatively short waiting times in the two research settings have limited the effect size of the artistic interventions reported. At the same time, observed positive outcomes can be plausibly extrapolated in waiting zones with much longer waiting times than observed here. Furthermore, even though efforts had been made to ensure the comparability of the two waiting spaces (e.g. by simultaneous data collection in the same city, thus, controlling for background factors such as weather conditions and local events), the different compositions of the waiting populations as well as architectural and general organizational specificities do not allow for a comprehensive inter-organizational comparisons. Consequently, the hypotheses concerning the relative impact of the two room transformations as a function of varying waiting stress levels could not be fully tested. The cross-sectional design cannot control for potential habituation effects of the room transformations among multiple users. On the one hand, positive effects may gradually be reduced, on the other, the feeling of security and familiarity could enhance the impact of the changed room design. Finally, the innovative holistic approach, using intervention ‘packages’ with a combination of cognitive-emotive elements excludes the identification of the exact nature and strength of the interaction of the individual components, for example, of scent, and audio and visual elements. This issue could only be addressed by a series of experimental settings varying the composition of the intervention packages systematically.

Even with these drawbacks and research gaps, the study has demonstrated that a trans-disciplinary collaboration paves the way to develop new powerful interventions in service organizations catering to the needs of their customers with their complex and multi-dimensional experience of time.

Footnotes

Acknowledgement

The authors would like to thank the reviewers for their comments that helped improve the manuscript. We are very grateful that the interview partners gave us their precious time and special thanks go to the practice partner Alexander Ott, Director of the Municipal Resident’s Registration Office of the City of Bern of the city of Bern; Michel Winterberg as media artist providing essential technical support with his interactive installation ‘waiting shadows’; Anne-Käthi Bischof of Keller Unternehmensberatung AG for her co-ordination support and Magdalena Dampz as chief interviewer with her interviewer team – data collection was conducted by GFS Zürich Markt + Sozialforschung AG directed by Dr Peter Spichiger who provided valuable feed-back; Matthias Berger, executive partner of Schäuffelhut-Berger GmbH for Software Engineering – München acted as a consultant and prepared the complex observation data for the joint analysis.

Declaration of Conflicting Interest

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The project Waiting Times in Organizations and Artistic Interventions (Wartezeiten in Organisationen und künstlerische Intervention) was funded by the Swiss National Research Foundation, Division CoRe (Abteilung Interdivisionäre Koordination und cooperative Forschung) under grant no. CR3113_135575.

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