1 Introduction

Smartphone and Tablet PCs are currently the most successful mobile devices. In 2015, 68% of U.S. adults had a smartphone and tablet PC ownership has increased 45% among adults (Pew Research Center). The operations of smartphones and tablet PCs are carried out via applications, or short apps that are primarily used through the devices’ screen, which allows for bidirectional interaction. There are different apps for different tasks. The most basic apps, for example, are apps for checking e-mails, apps for web browsing or apps for taking notes. Thereby, the task in question and the size of the device may determine how the device is held in the hands, and information input might vary from just taping with one finger to typing text with two fingers. Knowledge about how users hold their hands when interacting with touchscreens can impact ergonomic interface design by designing apps that consider the handheld position people are most likely to use for interaction. The study presented in this paper focuses therefore on an analysis of handheld positions for three different tasks and considers age-related differences.

1.1 Handheld Positions

Touchscreen devices can be operated either vertically or horizontally, with one or both thumbs, or one or more fingers of the same hand or another one. Thereby, it is essential to differentiate between tablets and smartphones since they have different sizes, weights and shapes. Therefore, different requirements are laid down when designing user interfaces [1]. Research conducted so far investigated approaches of finger placement and hand grasp during touchscreen interaction. With regard to the interaction with tablets, Oulasvirta et al. [2] recommended a symmetric bimanual grip while holding a tablet in landscape orientation as being the most appropriate for ergonomic text input. Odell and Chandrasekaran [1] examined this position in order to measure the thumb reachable areas for two different grips and for different anthropometric measures. What those researchers found was that the reachable distance of the thumb on the tablet is larger on the side grip than on the corner grip and therefore it can be inferred that the hand grip on the sides should be preferred to the position of the hands at the corners. Regarding smartphone interaction, Wobbrock, Myers and Aung [3] studied a total of eight different postures, four different two-handed postures and four different one-handed postures. They found that the posture of the hand has a significant effect on users’ touch performance and that interaction with the device should not only take place by placing fingers on the front of the device but also back-of-device performance should be investigated as a feasible means for interaction, which enables a richer set of finger and thumb interactions. This idea was studied by Le, Mayer, Wold and Henze [4]. Specifically, those researchers analyzed how users naturally position their hands for three different tasks aiming to develop ergonomic back-of-device interaction techniques. The tasks studied were derived from Böhmer, Hecht, Schöning, Krüger and Bauer [5], and involved writing a text message, reading a text, and watching a video. Thereby, writing and reading tasks were conducted in the portrait mode of the device, while watching a video task was conducted in the landscape mode. Since the sample consisted of ten right-handed subjects, results may lack reliability. In all tasks, it was found that the right hand touched the phone the most. Furthermore, a higher number of different hand positions was found for the landscape mode compared to the portrait mode, which let the researchers conclude that people might be less used to the landscape mode.

1.2 Perception of Peripersonal Space in the Elderly

The space surrounding the body that is within reach of the hands is called peripersonal space. Most interaction with handheld devices takes place within peripersonal space. Past studies have shown that there are differences in the perception of peripersonal space with regard to age. Bloesch, Davoli, and Abrams [6] studied reach-and-point actions, such as the movement needed to dial a phone, and found that distractor objects placed along a movement path slowed the performance of younger participants more than distractors outside the movement path. However, older subjects perceived interference in their movement when an object was placed in front of their body. The authors thus concluded that younger subjects adopt an action-centered reference frame, as peripersonal space has a different neural representation compared to the rest of the body. While using the hand to perform an action, this reference frame activates brain areas that allow the movement path to be planned and executed more accurately. Older subjects, however, may exhibit declines in those brain areas (parietal cortex [7] and intraparietal cortex [8]), which may make the use of an action-centered reference frame more difficult or impossible. As the older subjects’ performances in reaching movements were slowed down when a distractor object was placed near their bodies, the authors concluded that older subjects make use of a body-centered reference frame. An explanation for an action-centered reference frame is the fact that individuals prioritize objects near their hands, as these may be candidates for potential actions and thus automatically encode the location of those objects in reference to their hands. As perihand space and the corresponding neural representations might become less accurate with age, the authors hypothesized that the dominant reference for spatial coding might move from the hand to the trunk, which may lead to a body-centered reference frame. In line with these findings, research by Gabbard, Cacola, and Cordova [9] that investigated mental models supports the assumption of age-related differences in action representation. These authors tested the ability of individuals to estimate whether an object is within reach or out of grasp. The results indicated that older subjects made significantly more errors and both age groups performed worse in extrapersonal space (beyond reach) compared to peripersonal space. Further evidence for an altered representation of perihand space in the elderly comes from studies by Ghafouri and Lestienne [10]. These authors studied three-dimensional arm movements and found that space representation changes with aging. In particular, subjects in the study were requested to draw ellipses in three spatial planes (sagittal, frontal, and horizontal) to measure the deviations in the orientation of the ellipses with regard to the planes. The results showed that older subjects made larger errors than the younger ones, supporting the assumption of an age-related representation of perihand space.

One of the key findings from these papers is that older people on average encounter more problems in performing actions in peripersonal space. Thereby these difficulties are not only present while performing actions but also when predicting actions in peripersonal space. This finding indicates that these effects are not caused by impairments in motor skills of elderly people but indicate tendencies to perceive peripersonal space in a different way than younger aged subjects do.

1.3 Technology Generations

Understanding user requirements is one essential part of design. Taking chronological age into account, however, is often not productive as aging processes are highly individual, resulting in ambiguous measurements. Therefore, considering the subject’s age in combination with period and cohort effects seems promising. Age, period, and cohort effects must be considered as being interrelated, as it is impossible to deal with one without also dealing with the others. Age effects are the result of getting older and deal with specific effects in different age groups. Period effects are the consequences of influences that vary through time and are associated with all age groups simultaneously. Cohort effects are the consequences of being born at different times and are associated with variations in successive age groups in successive time periods (e.g. long-term habits or long-term exposures), so different generations are exposed to different factors. Estimating the effects of either one of those is not easy because the effects may be confounded with the others [11].

Building on existing theories regarding age-period-cohort models, the concept of technology generations was introduced by German sociologists in the early 1990s [12]. These researchers defined a technology generation as “groups of birth cohorts whose conjunctive experience with technology is differentiated by social change” (p. 493). The authors state further that technological change, and especially changes in basic technologies, enhances inter-cohort differences, thereby raising the likelihood of a conscious perception and description of differences as generational differences. The concept of technology generations includes technologically-related cohort effects and refers to cohort variations with regard to changes in the social and cultural environment.

A range of birth cohorts that show behavioral similarities or shared norms and values based on common sociological environments and predominant developments during the formative period (the period of time between adolescence and young adulthood, operationalized between 10 and 25 years) is called a generation. Studies about age cohorts have shown that after young adulthood, individuals are less likely to change their attitudes, norms and values. During the formative period, subjects undergo a number of crucial transitions, like from school to university or from parental home to independent living. Researchers found out that acquired norms, skills and values during that period tend to be constant and influence behavior later in life [13]. Sackmann and Weymann [12] point out that individuals experiencing the availability of the same types of products during the formative period display similar product usage many years later. Thus, different technology generations appear to behave differently with respect to technology, which is the result of differences in their experience gained in their formative years. Going further, Docampo Rama, Ridder and Bouma [14], whose approach consisted of distinguishing technology generations by interface usage, infer that generation-specific technology experience could induce differences in the usage behavior of current consumer products. Older people may be at a disadvantage in using present complex user interfaces, as they did not acquire that skill in their formative period earlier in life.

The question then arises where the boundary between different birth cohorts occurred. Following earlier investigators [15, 16], Docampo Rama et al. [14] define changes in basic technology causing generational differentiation as the point in time where 20% diffusion within the population has been reached. At that point, it is regarded as likely that persons who do not have such technologies themselves have experienced them in their social surroundings (e.g. in their families, with their friends or at work). In order to get information about the degree of diffusion of a technology, Sackmann and Weymann [12] used qualitative interviews, group discussions, surveys, and secondary data analysis to develop and test their concept of technology generations. As a result of this, Sackmann and Weymann [12] distinguished generations from birth cohorts that currently are displaying similar behavior with regard to technology based on technological achievements in their formative periods. Hence, four different technology generations were initially identified:

  • the mechanical generation (born before 1939)

  • the generation of the household revolution (born between 1939 and 1948)

  • the generation of technology spread (born between 1949 and 1963), and

  • the computer generation (born between 1964 and 1979).

In 2013, a new generation was added by the authors to this typology of technology generations:

  • the internet generation (born in 1980 and later)

In summary, generation-specific experience with technology might influence the usage of currently available technologies, as older people did not encounter the complex interaction patterns that are necessary to handle modern technologies in their formative period. Therefore, age differences in this study are analyzed with regard to different technology generations.

1.4 The Present Study

While previous work provides some approaches of hand positions analyses, none of them takes a large group of users, a thorough differentiation of hand positions, and a comparison between smartphone and tablet PC interaction into account. Therefore, the study presented in this paper provides an analysis of handheld positions while interacting with smartphones and tablet PCs and differentiates between three different tasks. To obtain a large sample size, the study was administered via an online questionnaire. Participants were assigned to four age groups according to the four youngest of the five technology generations proposed by Sackmann and Weymann [12].

2 Method

2.1 Procedure

The questionnaire started with a short introduction of the study and demographic questions. After that, subjects were asked to specify how they would position their hands by choosing between five different positions:

  1. (1)

    Holding the device vertically and interacting with the thumb of the same hand.

  2. (2)

    Holding the device vertically with one hand and interacting with a finger of the other hand.

  3. (3)

    Holding the device vertically with both hands and interacting with both hands.

  4. (4)

    Holding the device horizontally and interacting with both thumbs.

  5. (5)

    Holding the device horizontally with one hand and interacting with a finger of the other hand.

In order to simplify the answering process, images of the handholding positions were added to the questionnaire (Fig. 1).

Fig. 1.
figure 1

Depiction of the handling positions studied

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The tasks that were studied were inspired by those used by Böhmer et al. [5] and Le et al. [4], although not fully identical. The tasks were: typing short text, typing long text, and reading.

2.2 Participants

A total of 1022 subjects aged 20–77 took part in the online questionnaire. Their mean age was M = 48.08 years (SD = 12.03). The age structure was not equally distributed, but showed a middle age peak (Fig. 2). As people usually tend to use their dominant hand when operating their phone [17], we only included right-handed subjects in our analysis. For the analysis, participants were classified according to four age groups in accordance with the technology generations proposed by Sackmann and Winkler [18]. Due to a lack of participants, the fifth group could not be studied. The resulting age groups were as follows:

Fig. 2.
figure 2

Age distribution of participants

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  • The first group, called “the internet generation” and aged 19–36, consisted of N = 196 persons (M = 30.8, SD = 4.37)

  • The second group, called “the computer generation” and aged 37–52, consisted of N = 457 persons (M = 45.21, SD = 4.63)

  • The third group, called “the generation of technology spread” and aged 53–67, consisted of N = 316 persons (M = 59.06, SD = 4.18)

  • The fourth group, called “the generation of the household revolution” and aged 68–77, consisted of N = 52 persons (M = 71.63, SD = 3.0)

3 Results

Chi-square tests were used to study the effects of handheld positions for the three different tasks separately, as the measurement was at the nominal level. The level of significance was set to α = 0.05.

3.1 Overall Age Effects

In order to analyze differences between the four age groups, chi square tests were analyzed for the three tasks and for smartphone and tablet interaction separately. An overview of the results is shown in Table 1. Overall, significant differences were found between the tasks with regard to the handholding positions for the four different age groups.

Table 1. Results of chi-square tests for overall differences between technology generations
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3.2 The Internet Generation

Smartphone Interaction

Results of the analysis of handheld positions with regard to smartphone interaction of the youngest age group showed significant effects for typing short text (χ2(4, N = 193) = 169.46, p = .00), typing long text (χ2(4, N = 189) = 62.03, p = .00), and reading text (χ 2 (4, N = 186) = 95.13, p = .00). The visual analysis of the bar graphs (Fig. 3) shows that for typing short text and reading, the most prominent position is holding the smartphone vertically and interacting with a finger of the same hand, whereas the most prominent position for typing long text is holding the smartphone vertically and interacting with a finger of the other hand.

Fig. 3.
figure 3

Bar graphs for the three different tasks in relation to handheld positions for smartphone and tablet PC interaction for “the internet generation”

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Tablet PC Interaction

Results of the analysis of handheld positions with regard to tablet PC interaction of the youngest age group showed no significant effects for typing short text (χ2(4, N = 184) = 6.87, p = .14), typing long text (χ2(4, N = 187) = 7.2, p = .13), and reading text (χ2(4, N = 189) = 8.65, p = .07). The visual analysis of the bar graphs (Fig. 3) shows that the distribution of the handheld positions is rather evenly distributed, with a peak for the position of holding the tablet PC vertically and interacting with a finger of the other hand for all three tasks.

3.3 The Computer Generation

Smartphone Interaction

Results of the analysis of handheld positions with regard to smartphone interaction of the “computer generation” showed significant effects for typing short text (χ2(4, N = 450) = 434.98, p = .00), typing long text (χ2(4, N = 432) = 401.91, p = .00), and reading text (χ2(4, N = 426) = 246.61, p = .00). The visual analysis of the bar graphs (Fig. 4) shows that the most prominent position for all three tasks is holding the smartphone vertically and typing with a finger of the other hand, followed by holding the smartphone vertically and typing with a finger of the other hand for typing short text and reading, but not for typing long text.

Fig. 4.
figure 4

Bar graphs for the three different tasks in relation to handheld positions for smartphone and tablet PC interaction for “the computer generation”

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Tablet PC Interaction

Results of the analysis of handheld positions with regard to tablet PC interaction of the “computer generation” showed significant effects for typing short text (χ2(4, N = 424) = 175.18, p = .00), typing long text (χ2(4, N = 425) = 152.85, p = .00), and reading text (χ2(4, N = 431) = 95.65, p = .00). The visual analysis of the bar graphs (Fig. 4) shows that the most prominent position for all three tasks is by far holding the tablet PC vertically and interacting with a finger of the other hand.

3.4 The Generation of the Technology Spread

Smartphone Interaction

Results of the analysis of handheld positions with regard to smartphone interaction of the “generation of technology spread” showed significant effects for typing short text (χ2(4, N = 314) = 422.59, p = .00), typing long text (χ2(4, N = 309) = 449.72, p = .00), and reading text (χ2(4, N = 313) = 166.95, p = .00). The visual analysis of the bar graphs (Fig. 5) shows that by far the most prominent position for all three tasks is holding the smartphone vertically and typing with a finger of the other hand.

Fig. 5.
figure 5

Bar graphs for the three different tasks in relation to handheld positions for smartphone and tablet PC interaction for “the generation of technology spread”

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Tablet PC Interaction

Results of the analysis of handheld positions with regard to tablet PC interaction of the “generation of technology spread” showed significant effects for typing short text (χ2(4, N = 312) = 157.52, p = .00), typing long text (χ2(4, N = 315) = 150.57, p = .00), and reading text (χ2(4, N = 312) = 70.95, p = .00). The visual analysis of the bar graphs (Fig. 5) shows that the most prominent position for all three tasks is by far holding the tablet PC vertically and interacting with a finger of the other hand, followed by holding the tablet PC horizontally and interacting with a finger of the other hand.

3.5 The Generation of Household Revolution

Smartphone Interaction

Results of the analysis of handheld positions with regard to smartphone interaction of the “generation of household revolution” showed significant effects for typing short text (χ2(4, N = 52) = 93.58, p = .00), typing long text (χ2(4, N = 52) = 90.12, p = .00), and reading text (χ2(4, N = 52) = 31.46, p = .00). The visual analysis of the bar graphs (Fig. 6) shows that once again, the most prominent position for all three tasks is holding the smartphone vertically and typing with a finger of the other hand.

Fig. 6.
figure 6

Bar graphs for the three different tasks in relation to handheld positions for smartphone and tablet PC interaction for “the generation of household revolution”

Full size image

Tablet PC Interaction

Results of the analysis of handheld positions with regard to tablet PC interaction of the “generation of household revolution” showed significant effects for typing short text (χ2(4, N = 52) = 38.81, p = .00), typing long text (χ2(4, N = 52) = 27.81, p = .00), and reading text (χ2(4, N = 52) = 17.04, p = .00). The visual analysis of the bar graphs (Fig. 6) shows that the most prominent position for typing long text and reading is holding the tablet PC horizontally and typing with a finger of the other hand, whereas for typing short text the most prominent position is holding the tablet PC vertically and typing with a finger of the other hand.

4 Discussion

Developing ergonomic user interfaces requires to understand how users naturally hold their devices. The analyses presented in this paper show how users hold and interact with their smartphones and their tablet PC in three common tasks. To understand how different age groups interact with mobile devices, the results were analyzed for four different technology generations.

Overall, the results show significant differences in the way different technology generations hold their hands while interacting with smartphones and tablets as well as differences in the interaction patterns between smartphones and tablet PCs. While the most prominent positions when interacting with a smartphone are holding the phone vertically and interacting with a thumb or a finger, there is more variability in the results of the analysis of the interaction with a tablet PC. Specifically, the internet generation as the youngest age group shows no significant differences between the hand positions for interacting with a tablet PC, while the other three user groups do show significant differences. This implies that apps for tablet PCs that are used by younger people do not need to account for different hand positions but can be designed in such a way that they fit the needs of the older groups. Regarding smartphone interaction, the most prominent position for the three older-aged groups is holding the smartphone with one hand, while interacting with a finger of the other hand, the most prominent position for the youngest age groups is holding the smartphone and interacting with the thumb of the same hand. This finding implies that a difference should be made in designing smartphone apps for a younger group aged 19–36 but that the three older groups can be taken together resulting in the same design for people aged 37–77. Another interesting finding is the fact that the oldest group prefers holding the tablet PC horizontally for reading and typing long text, whereas the three younger groups prefer holding the tablet PC vertically or have no clear preference, as was evident in the youngest group. With regard to the different tasks that were studied, the prominent hand position did not differ much between the tasks. This finding implies that although the tasks vary with regard to the amount of information input, this has no influence on the handheld position.

4.1 Limitations

With regard to the classification of the sample of the study some limitations are worth noting. The participants studied were analyzed with regard to four different technology generations. As was already mentioned, age processes are highly individual and this makes the arrangement of participants in groups according to chronological age difficult. Furthermore, there are aging processes which might as well account for the differences in handheld positions, as amyosthenia or impairments in fine motor skills. To derive a complete picture, these factors need to be included as well in future research.

Another point of criticism is the fact that most research related to grouping of birth cohorts corresponds to studies that were done in highly industrialized European societies. Actually, the data had to be adapted to local technological spread patterns for other regions of the world in order to be reliable. Furthermore, with regard to the sample of our research, the group sizes of the technology generations were not equally distributed, and this might cause a bias in the data between the different age groups.

4.2 Conclusion

Overall, the results of the questionnaire study show significant differences in the way technology generations interact with their mobile devices. On the one hand, this supports the structure of those age groups and, on the other hand, this points out the importance of studying age effects in human-system interaction and does only partially support design for all approaches. With regard to interface design, the findings imply further research to test if interfaces that are designed taking the handheld position that they are used in into account profit positively with regard to ergonomic criteria.