Task productivity

Task productivity was assessed using typing speed (words/min) and by absolute and relative number of errors. The computer software program used to present the essays and generate the scores was “Typing Master Pro^TM

• Gross speed indicates the total number of keystrokes divided by total time.

(Typing Master Finland, Inc., Helsinki, Finland).” This program saves personal typing data by subject case number, and automatically calculates 6 productivity measurements: gross speed, net speed, accuracy, gross hits, net hits, and error hits.

In order to calculate typing speed (i.e., gross and net speed) and accuracy, three variables (i.e., gross, net, and error hits) are required. Each definition used in this study is as follows;

• Net speed is calculated by taking the number of correct words typed (i.e., total number of keystrokes – number of error hits), divided by total time.

• Accuracy is calculated by taking the number of correct words typed (i.e., total number of keystrokes – number of error hits), divided by the total number of keystrokes, and then multiplying by 100 to provide a percentage.

• Gross hits are the total number of keystrokes.

• Net hits are calculated by subtracting the error hits from the total number of keystrokes.

• Error hits are the total number of incorrect words typed.

The essays typed by the subjects were provided in the typing software program. These essays were at the fourth-grade reading level. The PI selected six essays that were long enough to allow subjects to type for 10 minutes regardless of their personal typing speed. Each essay was

then randomly assigned to one of the six simulated laptop workstation setups (see Table 4-3). A software timing routine began when a word was typed, and automatically terminated after 10 minutes.

Table 4-3. Essay Types for Laptop Workstation Setups Laptop workstation setups Essay types

Desktop sitting Flickerbridge

Lying prone The Adventures of Huckleberry Finn

Lying supine The Enchanted Typewriter

Floor sitting The History of the Telephone

Chair sitting Difficult People

Lap sitting Wanted Alive! Tigers in the Wild

4.2.5 Procedures

Subjects were provided a general description of the research study (e.g., purpose, procedure, inclusion eligibility, risk factors, and benefits) by the principal investigator (PI) before signing the consent form approved by the University of Pittsburgh Institutional Review Board (IRB#PRO09030092/MOD09030092-01). Each subject randomly picked one of six sheets outlining the essay type to determine the order of the six simulated laptop workstation setups, and then filled out the LCUSS. While subjects completed the LCUSS, the PI prepared the first laptop workstation setup and camera configuration.

After completing the LCUSS, subjects performed the keyboard text-entry task in each of the six simulated laptop workstation setups. Each subject typed for 10 minutes at each simulated laptop workstation setup with a 5-minute break in between. Prior to the laptop keyboarding tasks,

subjects were asked to be as natural as possible, while typing in the simulated laptop workstation setups. The subjects were, however, shown a picture of each laptop workstation setup to provide basic guide (see Figure 4-1). Subjects could change the height of the chair and monitor angle to their preferred height and angle, and these changes in the workstation setup parameters (e.g., LCD monitor tilt angle, laptop depth from the edge of a desk, chair height) were recorded by the PI at the completion of each of the tasks.

After completing each of the six simulated laptop workstation setups, all subjects were asked to immediately rate their discomfort levels on the VAS. In the meanwhile, the PI set up the next laptop workstation setup and camera configuration. The level of lighting in the laboratory room was kept constant during the experimental session across all subjects. The amount of time required to complete this experiment was approximately 2 ½ hours, including 50 minutes for the LCUSS and consent form, 60 minutes for the six simulated laptop workstation setups, and 40 minutes for the rest breaks between workstation setups.

4.2.6 Data management and processing

All subjects’ identities were indicated by case number. All information about subjects obtained from this study was stored in a locked file cabinet. All data (i.e., LCUSS, upper body angles, K-PeCS, discomfort, and task productivity) were entered into Microsoft Office Excel 2007, and then transferred into a SPSS 17.0 software program for analysis.

To obtain the upper body angles, the data in the videotape was downloaded to a personal computer into video clip types using an external DVD movie burner for digital storage (HP DVD movie writer dc 4000) and later scoring of angles. Subjects’ postures were analyzed using a

time-of specific behaviors during the observation period (Li & Buckle, 1999). In time sampling, subjects’ postures were recorded in real time using the video recording system, and divided into a number of equal time intervals (David, 2005; Suen & Ary, 1986). In this study, the video file was divided into 1-minute intervals during the 10-minute laptop keyboarding task. To prevent a rater from identifying a snapshot (i.e., electronic picture in jpg format) at a preferred starting point, a starting point was randomly selected from either 1, 2, 3, 4, or 5 seconds. After selecting the first snapshot, ten time points for each body angle were selected at 1-minute intervals. Each snapshot was analyzed by the ImageJ software to obtain a numerical value of body angles. These angles were entered into a database and averaged across the 10 data sets. Each snapshot had a time stamp (e.g., day, hour, minute, and second) that the picture was taken.

In order to rate typing style using the K-PeCS, 1-minute video clips were extracted from original video files. These video clips include two lateral views (i.e., right and left side) and one transverse view (i.e., hand and wrist side). The PI selected the last minute of typing to avoid the potential of conscious actions about being video-recorded and to observe a more stereotypical moment (Baker, Sussman, & Redfern, 2008; James, Harburn, & Kramer, 1997).

Intensity of discomfort was assessed using the 10-cm VAS. The VAS was manually scored by measuring how far along the line (in centimeter) from the ‘no discomfort’ anchor that the line was marked. Task productivity (e.g., typing speed and number of errors) was automatically stored in a preinstalled keyboarding program, Typing Master Pro^TM (Typing Master Finland, Inc., Helsinki, Finland).

4.2.7 Data analyses

All statistical analyses were performed using the SPSS 17.0 statistical package program.

Demographic characteristics of the study sample (N = 30) were summarized using relative frequency distributions for the nominal and ordinal data, and means and standard deviation (SD) for the continuous data. Prior to analysis, we identified the three most common workstation setups used: desktop sitting, lying supine, and chair sitting (Shin, 2010). All further data analysis for this study was delimited to these three workstation setups.

Research question 1.1: Difference in upper body angles

The average angle for each upper body area was calculated using mean and standard deviation.

Data were analyzed by a repeated measures analysis of variance (ANOVA). A separate ANOVA model was used for each body angle as the dependent variables, and each of the three simulated laptop workstation setups as the independent variables. If there were significant main effects between the three simulated laptop workstation setups, Bonferroni post-hoc comparisons were conducted to determine significant differences in the outcome variables among the laptop workstation setups.

Effect size was determined by partial eta-squared (ηP2

). In a repeated measures ANOVA model, the partial eta-squared is commonly used in conjunction with statistical significance, and it is interpreted as “the proportion of variance that a variable explains that is not explained by other variables” (Field, 2009, p. 791). In a repeated measures ANOVA model with only a single factor, effect size scores for partial eta-squared and eta-squared are identical. Interpretation for

strength of these values was: small (ηp2

= .01), medium (ηp2

= .06), and large (ηp2

Research question 1.2: Difference in typing style

= .14) (Cohen, 1998).

We completed descriptive statistics for the K-PeCS to identify frequency and percentage distribution of each item. We compared the K-PeCS items among the three simulated laptop workstation setups using a Friedman’s ANOVA and the Wilcoxon signed rank test for post-hoc comparisons (asymptotic significance, 2-tailed). Statistical significance was set at p < .05.

Research question 2.1 and 3.1: Difference in physical discomfort and task productivity

Repeated measures ANOVAs were used to analyze differences in physical discomfort and task productivity (i.e., gross speed, net speed, accuracy, gross hits, net hits, and error hits) among the three simulated laptop workstation setups. If the main effect was significant between the laptop workstation setups, Bonferroni post-hoc comparisons were conducted. In addition to statistical significance, we reported the partial eta-squared, a measure of effect size. The selected critical level of alpha significance for all tests was p < .05.

4.3 RESULTS

4.3.1 Participants

Table 4-4 presents the demographic characteristics of 30 subjects, 25 females and 5 males, who were enrolled in this study. All subjects were full-time students from the University of Pittsburgh.

Most subjects were graduate students (56.7%), followed by junior (20%) and senior (20%), and sophomore (3.3%). The ages of students ranged from 20 years to 48 years, with mean age of 25.97 ± 7.29. The majority of subjects were also non-Hispanic or Latino (100%), white (63.3%), right-handed (90%), and never married (86.7%).

Table 4-4. Participants’ Demographic Characteristics

Demographics Mean ± SD or number (%)

Age, years 26.0 ± 7.3

Male 28.4 ± 5.2

Female 25.5 ± 7.6

Gender

Female 25 (83.3%)

Ethnicity

Non Hispanic or Latino 30 (100.0%)

Race

Asian 10 (33.3%)

Black or African American 1 (3.3%)

White or Caucasian 19 (63.3%)

Dominant hand

Right 27 (90.0%)

Left 2 (6.7%)

Both 1 (3.3%)

Current enrollment status

Full time student 30 (100.0%)

Class level

Sophomore 1 (3.3%)

Junior 6 (20.0%)

Senior 6 (20.0%)

Graduate students 17 (56.7%)