Extensiveness of Cyberloafing for Nurse Managers
Chapter VI
Results
The purpose of this chapter was to describe the results of the study which was designed to explore whether there is a relationship between cyberloafing and employees' productivity from a nursing personnel perspective.
The program was used for statistical analysis is statistical Package for the Social Sciences (IBM-SPSS) (version 24.0). Descriptive (frequency, mean, and standard deviation) statistics was used to describe the characteristics of participants, how extent nurse managers engaged in cyberloafing behavior, and employees' productivity. Pearson Correlation and multilinear regression was used to determine the relationship between cyberloafing and employees' productivity. It will examine whether specific demographic characteristics (such as gender, age, education, occupation, marital status, and years of experience) have any association between study variables.
For inferential statistics and an Independent t-test were used to determine the relationship between the categorical variables. ANOVA test is a nonparametric that does not require that dependent variable has a normal distribution. However, it does assume that the distribution of the dependent variable has approximately the same shape in each group, which implies that the variance is approximately equal across the groups. A p value of P≤ 0.05 was considered statistically significant. A Two-way ANOVA test was computed to check for homogeneity of variance in the independent variable in order to reduce the risk o f a Type Ⅲ error. A non-significant result (p >.05) meant that the variances of the two groups were assumed to be equal (Burns & Grove, 2005).
The study aim was to explore the relationship between cyberloafing and nurse managers' productivity in healthcare settings. In the following sections, the results of the descriptive and inferential statistical analyses of the study variables are presented as they relate to each research question.
The following questions were answered:
- What is the demographic profile of the ‘nurse managers’ in terms of age, nationality, educational background, years of managerial experience, marital status, working unit, hospital where employed?
- To what extent are ‘nurse managers’ engaged in cyberloafing behaviors?
- What is the ‘nurse managers’ attitude and behavior towards work performance and their productivity?
- What is the bivariate relationship between cyberloafing and productivity?
- Is there a difference among nurse managers' cyberloafing behavior and their productivity in the Two study settings?
- Is there an association between nurse managers' demographic characteristics and their cyberloafing behavior and productivity in the Two study settings?
Analysis |
Exclusion |
Returned |
Distributed |
|
58 |
0 |
58 |
58 |
KFH |
39 |
0 |
39 |
39 |
KAAH |
97 |
0 |
97 |
97 |
Total |
From all questionnaire sheets distributed (n = 97), 97 sheets had returned, with a response rate of 100%. All the filled sheets had been filled by nurse managers after a full explanation about each item to be easy for them to answer the whole questionnaire. So, 97 survey sheets had been used for analysis and result acquisition.
Demographic Data:Selected Participants characteristics
A total of 97 nurse managers completely filled both the cyberloafing and productivity questionnaires. Participants’ demographic characteristics are summarized in Table (2) Fifty-eight nurse managers were recruited from KFH while 39 nurse managers were recruited from KAAH.
Research question 1
What is the demographic profile of the ‘nurse managers’ in terms of age, nationality, educational background, years of managerial experience, marital status, working unit, hospital where employed?
The majority of participants were; female nurses 85.6%, supporting the fact that nursing is perceived as a female-dominant position. In terms of the degree of recruited nurse managers, 68% of the respondents were head nurses, while 32% participants were nursing supervisors.
According to the highest educational level received, a total of 71.1% of the study participants reported receiving bachelor degree and certified as nursing specialists, whereas 28.9% were nurse managers received diploma as their highest degree of education and certified as nursing technicians.
According to the years of experience, about one third of the participants had one up to three years practicing nursing management in the nursing profession, accounting for a total of 38.1% of the study population. A total of 28.9% of nurse managers had four to six years of clinical experience. Less percentage of respondent had higher experience level of seven to nine years of experience (18.6% of nurse managers). Far less respondents had ten to twelve years of experience within the nursing profession, accounting for 9.3% of nurse managers from the total population.
Table 2. Descriptive Statistics of Participant’s Demographic Data (N=97)
Group |
Frequency |
Percent |
|
Sex |
Male |
14 |
14.4 |
Female |
83 |
85.6 |
|
Marital Status |
Single |
29 |
29.9 |
Married |
56 |
57.7 |
|
Divorced |
6 |
6.2 |
|
Widow |
6 |
6.2 |
|
Education |
bachelor degree |
69 |
71.1 |
Diploma |
28 |
28.9 |
|
Age |
less than 30 |
12 |
12.4 |
30-35 |
45 |
46.4 |
|
36-40 |
20 |
20.6 |
|
41-45 |
13 |
13.4 |
|
greater than 45 |
7 |
7.2 |
|
Nationality |
Saudi |
55 |
56.7 |
Asian |
41 |
42.3 |
|
Arab |
1 |
1.0 |
|
Hospital |
King Fahad Hospital |
58 |
59.8 |
King Abdulaziz Hospital |
39 |
40.2 |
|
Level |
Head Nurse |
66 |
68.0 |
Supervisor |
31 |
32.0 |
|
Years of Practicing Management |
1-3 |
37 |
38.1 |
4-6 |
28 |
28.9 |
|
7-9 |
18 |
18.6 |
|
10-12 |
9 |
9.3 |
|
13+ |
5 |
5.2 |
|
|
Total |
97 |
100.0 |
Research question 2
To what extent are ‘nurse managers’ engaged in cyberloafing behaviors?
From the descriptive statistics of independent variable in tables (3-7) we can answer two of the research questions regarding to what extent Nurse Managers are engaged in cyberloafing behaviors. Herein, a report of the findings of the cyberloafing activity questionnaire in respect to certain questions related to nurses’ behavior.
Table 3. Descriptive Data of Cyberloafing
|
X |
SD |
|
ALCS |
ALCS-A |
1.68 |
0.76 |
ALCS-B |
2.43 |
1.04 |
|
ALCS-C |
1.73 |
0.74 |
|
SEtHC |
2.01 |
0.69 |
|
Overall Cyberloafing Activity |
1.96 |
0.67 |
Visiting non-related work websites via computer or laptop (ALCS-A):
Table (4) shows that how far the nurse managers are engaging in cyberloafing behavior by visiting nonwork-related websites via computer or laptop during office hours. The overall nurse managers are engaging in cyberloafing is considered low (1.68±0.76). The overall mean score for the engagement in cyberloafing behavior, including the seventeen ways was calculated by combining the scores of all the items in the cyberloafing behavior and dividing the combined scores by the number of items.
Additionally, Table (4) reveals that the item with the highest average score was “Instant message/chat online” (2.35±1.70) followed by “Visit general news websites” (2.22 ± 1.50). While the least behavior in both healthcare sittings is “Visit adult oriented (sexually explicit) websites” (1.03±0.17).
Descriptive statistical analysis
Table 4. Frequency, percentage, Mean and standard division of Nurse Managers engagement in cyberloafing behaviors during office hours, how often they did each of the following through a DESKTOP COMPUTER or LAPTOP. (No.97)
No. |
Statement |
|
Constantly |
A few times a day |
Once a day |
A few times per week |
A few times per month |
Never |
X |
SD |
1. |
Visit nonjob related websites |
Frequency |
2 |
7 |
16 |
8 |
12 |
52 |
2.18 |
1.50 |
% |
2 % |
7% |
16% |
8% |
12% |
53% |
||||
2. |
Visit general news websites |
Frequency |
3 |
6 |
15 |
9 |
16 |
48 |
2.22 |
1.50 |
% |
3% |
6% |
15% |
9% |
16% |
49% |
||||
3. |
Visit entertainment websites |
Frequency |
0 |
3 |
17 |
7 |
14 |
56 |
1.94 |
1.28 |
% |
0% |
3% |
18% |
7% |
14% |
58% |
||||
4. |
Visit sports related websites |
Frequency |
0 |
3 |
7 |
3 |
9 |
75 |
1.49 |
1.06 |
% |
0% |
3% |
7% |
3% |
9% |
77% |
||||
5. |
Instant message/chat online |
Frequency |
5 |
11 |
14 |
4 |
12 |
51 |
2.35 |
1.70 |
% |
5% |
11% |
14% |
4% |
12% |
53% |
||||
6. |
Download non-work related information |
Frequency |
0 |
3 |
1 |
4 |
12 |
77 |
1.36 |
0.87 |
% |
0% |
3% |
1% |
4% |
12% |
79% |
||||
7. |
Look for employment |
Frequency |
0 |
4 |
2 |
7 |
7 |
77 |
1.44 |
1.01 |
% |
0% |
4% |
2% |
7% |
7% |
79% |
||||
8. |
Shop online |
Frequency |
1 |
1 |
5 |
4 |
9 |
77 |
1.42 |
0.99 |
% |
1% |
1% |
5% |
4% |
9% |
79% |
||||
9. |
Play online games |
Frequency |
0 |
1 |
1 |
1 |
9 |
85 |
1.19 |
0.60 |
% |
0% |
1% |
1% |
1% |
9% |
88% |
||||
10. |
Visit adult oriented (sexually explicit) websites |
Frequency |
0 |
0 |
0 |
0 |
3 |
94 |
1.03 |
0.17 |
% |
0% |
0% |
0% |
0% |
3% |
97% |
||||
11. |
Visit online discussion boards or forums |
Frequency |
0 |
0 |
1 |
5 |
10 |
81 |
1.24 |
0.59 |
% |
0% |
0% |
1% |
5% |
10% |
84% |
||||
12. |
Visit video sharing sites (Youtube, etc.) |
Frequency |
0 |
5 |
6 |
7 |
13 |
66 |
1.67 |
1.17 |
% |
0% |
5% |
6% |
7% |
13% |
68% |
||||
13. |
Visit social networking websites (Facebook, etc.) |
Frequency |
2 |
5 |
9 |
4 |
13 |
64 |
1.80 |
1.36 |
% |
2% |
5% |
9% |
4% |
13% |
66% |
||||
14. |
Visit investment or banking websites |
Frequency |
0 |
0 |
12 |
8 |
9 |
68 |
1.63 |
1.07 |
% |
0% |
0% |
12% |
8% |
9% |
70% |
||||
15. |
Check non-work related email |
Frequency |
1 |
5 |
11 |
7 |
9 |
64 |
1.84 |
1.34 |
% |
1% |
5% |
11% |
7% |
9% |
66% |
||||
16. |
Send non-work related email |
Frequency |
0 |
5 |
13 |
8 |
8 |
63 |
1.86 |
1.32 |
% |
0% |
5% |
13% |
8% |
8% |
65% |
||||
17. |
Receive non-work related email |
Frequency |
0 |
5 |
13 |
9 |
12 |
58 |
1.92 |
1.30 |
% |
0% |
5% |
13% |
9% |
12% |
60% |
||||
|
Mean |
|
1.68 |
0.76 |
Visiting non-related work websites via cellphone:
As showing in Table (5) how much engagement in cyberloafing behavior by visiting nonwork-related website via cellphones during office hours by nurse managers. The overall nurse managers are engaging in cyberloafing is considered slightly low (2.43±1.04). The overall mean score including the seven ways was calculated by combining the scores of all the items in the cyberloafing behavior and dividing the combined scores by the number of items.
Furthermore, the item with the highest average score that appears in Table (5) was “Send or receive text messages” (3.64±1.65) followed by “Make phone calls” (3.58 ± 1.65). While the least behavior in both healthcare sittings is “Play games” (1.33±0.90).
Table 5. Frequency, percentage, Mean and standard division of Nurse Managers engagement in cyberloafing behaviors during office hours, how often they did each of the following through a CELL PHONE. (No.97)
No. |
Statement |
|
Constantly |
A few times a day |
Once a day |
A few times per week |
A few times per month |
Never |
X |
SD |
1 |
Read/write nonwork email |
Frequency |
2 |
6 |
22 |
10 |
15 |
42 |
2.39 |
1.49 |
% |
2% |
6% |
23% |
10% |
15% |
43% |
||||
2 |
Visit nonjob related websites |
Frequency |
1 |
8 |
18 |
5 |
12 |
53 |
2.16 |
1.50 |
% |
1% |
8% |
19% |
5% |
12% |
55% |
||||
3 |
Visit social networking websites (Facebook, etc.) |
Frequency |
5 |
9 |
16 |
8 |
12 |
47 |
2.41 |
1.66 |
% |
5% |
9% |
16% |
8% |
12% |
48% |
||||
4 |
Shop online |
Frequency |
1 |
1 |
7 |
6 |
7 |
75 |
1.51 |
1.07 |
% |
1% |
1% |
7% |
6% |
7% |
77% |
||||
5 |
Make phone calls |
Frequency |
11 |
26 |
17 |
10 |
20 |
13 |
3.58 |
1.65 |
% |
11% |
27% |
18% |
10% |
21% |
13% |
||||
6 |
Send or receive text messages |
Frequency |
14 |
23 |
17 |
12 |
19 |
12 |
3.64 |
1.65 |
% |
14% |
24% |
18% |
12% |
20% |
12% |
||||
7 |
Play games |
Frequency |
1 |
1 |
3 |
3 |
8 |
81 |
1.33 |
0.90 |
% |
1% |
1% |
3% |
3% |
8% |
84% |
||||
|
Overall |
|
2.43 |
1.04 |
Taking break time to cyberloaf:
As showing in Table (6), how often the nurse managers are taking break to cyberloaf either by computer, laptop, or cellphones. In general, break time for cyberloafing engagement by nurse managers is considered low (1.73±0.74). The overall mean score for the breaks that including the four periods was calculated by combining the scores of all the items in the cyberloafing behavior and dividing the combined scores by the number of items.
Moreover, Table (6) revealing the item with the highest average score which is “Take a quick break using a cell phone” (2.35±1.02) followed by “Take a quick break using a computer” (1.71±0.91). Hence, the least break is “Take a long break using a computer” (1.35±0.83).
Table 6. Frequency, percentage, Mean and standard division of Nurse Managers engagement in cyberloafing behaviors on a typical workday, how often they did each of the following. (No.97)
No. |
Statement |
|
Five or more times a day |
Three to four times a day |
Once or twice a day |
Less than once a day |
Never do this |
X |
SD |
1 |
Take a quick break using a computer |
Frequency |
1 |
6 |
6 |
35 |
49 |
1.71 |
0.91 |
% |
1% |
6% |
6% |
36% |
51% |
||||
2 |
Take a quick break using a cell phone |
Frequency |
4 |
9 |
22 |
44 |
18 |
2.35 |
1.02 |
% |
4% |
9% |
23% |
45% |
19% |
||||
3 |
Take a long break using a computer |
Frequency |
2 |
2 |
4 |
12 |
77 |
1.35 |
0.83 |
% |
2% |
2% |
4% |
12% |
79% |
||||
4 |
Take a long break using a cell phone |
Frequency |
4 |
3 |
2 |
20 |
68 |
1.51 |
0.99 |
% |
4% |
3% |
2% |
21% |
70% |
||||
|
Oveall |
|
1.73 |
0.74 |
Self-Efficacy to Hide Cyberloafing (SEtHC):
As participants were asked for their ability to hide cyberloafing from their co-workers and supervisors and not being caught, so, the results of their answers are revealing in Table (7).
The overall self-efficacy to hide cyberloafing from co-workers is considered slightly low (2.01±0.69). The overall mean score for their ability to hide cyberloafing behavior, including the two items was calculated by combining the scores of all the items in the self-efficacy to hide cyberloafing behavior and dividing the combined scores by the number of items. The item “I COULD hide my computer activity if I wanted to” score is (2.20±1.70) which considered the highest average score. While is “I COULD pretend to be working on my computer and people would never know” recorded as the lowest (1.82±1.39) in both healthcare settings.
Table 7. Frequency, percentage, Mean and standard division of Nurse Managers engagement in cyberloafing behaviors during office hours, how often they could Hide Cyberloafing (Self-Efficacy to Hide Cyberloafing Scale). (No.97)
No. |
Statement |
|
Agree very much |
Agree moderately |
Agree slightly |
Disagree slightly |
Disagree moderately |
Disagree very much |
X |
SD |
1 |
I COULD pretend to be working on my computer and people would never know |
Frequency |
4 |
3 |
6 |
9 |
12 |
63 |
1.82 |
1.39 |
% |
4% |
3% |
6% |
9% |
12% |
65% |
||||
2 |
I COULD hide my computer activity if I wanted to |
Frequency |
10 |
4 |
6 |
8 |
16 |
53 |
2.20 |
1.70 |
% |
10% |
4% |
6% |
8% |
16% |
55% |
||||
|
Overall |
|
2.01 |
0.69 |
Research Question 3
What is the ‘nurse managers’ attitude and behavior towards work performance and their productivity?
From descriptive statistics of independent variable in Table (8) we can answer question three of research questions regarding attitude and behavior of nurse managers towards work performance and productivity. Herein, the findings of EWPS questionnaire in respect to certain questions related to nurse managers’ behavior.
Table 8. Nurse managers’ attitude and behavior towards work performance and their productivity
Almost Always |
Often |
Sometimes |
Rarely |
Never |
X |
SD |
||
During the past week, how frequently did you Arrive at work late or leave work early? |
Frequency |
1 |
3 |
19 |
26 |
48 |
1.79 |
0.94 |
% |
1% |
3% |
20% |
27% |
49% |
|||
Take longer lunch hours or coffee breaks? |
Frequency |
4 |
1 |
12 |
26 |
54 |
1.71 |
1.01 |
% |
4% |
1% |
12% |
27% |
56% |
|||
Just do no work at times when you would be expected to be working? |
Frequency |
1 |
4 |
21 |
28 |
43 |
1.89 |
0.96 |
% |
1% |
4% |
22% |
29% |
44% |
|||
Find yourself daydreaming, worrying, or staring into space when you should be working? |
Frequency |
0 |
2 |
25 |
27 |
43 |
1.86 |
0.88 |
% |
0% |
2% |
26% |
28% |
44% |
|||
Have to do a job over because you made a mistake or your supervisor told you to do a job over? |
Frequency |
1 |
3 |
23 |
28 |
42 |
1.90 |
0.94 |
% |
1% |
3% |
24% |
29% |
43% |
|||
Waste time looking for misplaced supplies, materials, papers, phone numbers, etc.? |
Frequency |
5 |
9 |
22 |
35 |
26 |
2.30 |
1.12 |
% |
5% |
9% |
23% |
36% |
27% |
|||
Find you have forgotten to call someone? |
Frequency |
2 |
6 |
25 |
43 |
21 |
2.23 |
0.93 |
% |
2% |
6% |
26% |
44% |
22% |
|||
Find you have forgotten to respond to a request? |
Frequency |
0 |
3 |
25 |
50 |
19 |
2.12 |
0.75 |
% |
0% |
3% |
26% |
52% |
20% |
|||
Become annoyed with or irritated by coworkers, boss/supervisor, client/customers/ vendors, or others? |
Frequency |
3 |
4 |
37 |
32 |
21 |
2.34 |
0.97 |
% |
3% |
4% |
38% |
33% |
22% |
|||
Become impatient with others at work? |
Frequency |
5 |
7 |
24 |
36 |
25 |
2.29 |
1.09 |
% |
5% |
7% |
25% |
37% |
26% |
|||
Avoid attending meetings? |
Frequency |
3 |
1 |
10 |
27 |
56 |
1.64 |
0.94 |
% |
3% |
1% |
10% |
28% |
58% |
|||
Avoid interaction with coworkers, clients, vendors, or supervisors? |
Frequency |
0 |
1 |
11 |
26 |
59 |
1.53 |
0.74 |
% |
0% |
1% |
11% |
27% |
61% |
|||
Have a coworker redo something you had completed? |
Frequency |
1 |
2 |
20 |
31 |
43 |
1.84 |
0.90 |
% |
1% |
2% |
21% |
32% |
44% |
|||
Find it difficult to concentrate on the task at hand? |
Frequency |
2 |
0 |
31 |
33 |
31 |
2.06 |
0.91 |
% |
2% |
0% |
32% |
34% |
32% |
|||
Fall asleep unexpectedly or become very sleepy while at work? |
Frequency |
0 |
0 |
16 |
35 |
46 |
1.69 |
0.74 |
% |
0% |
0% |
16% |
36% |
47% |
|||
Become restless while at work? |
Frequency |
2 |
5 |
19 |
27 |
44 |
1.91 |
1.02 |
% |
2% |
5% |
20% |
28% |
45% |
|||
Notice that your productivity for the time spent is lower than expected? |
Frequency |
2 |
0 |
22 |
44 |
29 |
1.99 |
0.85 |
% |
2% |
0% |
23% |
45% |
30% |
|||
Notice that your efficiency for the same spent is lower than expected? |
Frequency |
0 |
3 |
28 |
41 |
25 |
2.09 |
0.82 |
% |
0% |
3% |
29% |
42% |
26% |
|||
Lose interest or become board with your work? |
Frequency |
3 |
7 |
32 |
29 |
26 |
2.30 |
1.04 |
% |
3% |
7% |
33% |
30% |
27% |
|||
Work more slowly or take longer to complete tasks than expected? |
Frequency |
0 |
5 |
23 |
27 |
42 |
1.91 |
0.94 |
% |
0% |
5% |
24% |
28% |
43% |
|||
Have your boss/ coworkers remind you to do things? |
Frequency |
2 |
3 |
39 |
40 |
13 |
2.39 |
0.84 |
% |
2% |
3% |
40% |
41% |
13% |
|||
Not want to return phone calls or put off returning calls? |
Frequency |
0 |
4 |
26 |
26 |
41 |
1.93 |
0.93 |
% |
0% |
4% |
27% |
27% |
42% |
|||
Have trouble organizing work or sitting priorities? |
Frequency |
1 |
5 |
29 |
36 |
26 |
2.16 |
0.92 |
% |
1% |
5% |
30% |
37% |
27% |
|||
Fail to finish assigned tasks? |
Frequency |
0 |
0 |
25 |
39 |
33 |
1.92 |
0.77 |
% |
0% |
0% |
26% |
40% |
34% |
|||
Feel too exhausted to do your work? |
Frequency |
3 |
4 |
39 |
32 |
19 |
2.38 |
0.95 |
% |
3% |
4% |
40% |
33% |
20% |
|||
Overall |
2.01 |
0.54 |
Frequency of late arrival to work or early leave from work
All the items of the cyberloafing scale were analyzed to determine any patterns and behavior of nurses towards cyberloafing within the clinical setting.
Late arrival at work and early leave was reported to occur by a minority of respondent where only 1% reported that they ‘almost always’ arrive late or leave early. On the other hand, about half of the participants (49%) never have been later for work and never left work early before the end of their duty hours.
Prolonged lunch hours and coffee breaks
In terms of long lunch hours and coffee breaks, more than the half of nurse (56%) reported never taking too long during lunch hours or lengthen coffee breaks. On the other hand, 4% (4 nurse managers) almost always had longer lunch hours and/or coffee breaks. This could reflect their need to take some time off during stressful work.
No work at times when work is being expected
In terms of doing nothing related to work during duty hours, about half of study respondents (44%) reported never being lazy to do the job during their duty hours. However, only one nurse manager reported doing noting at times when she was expected to be working.
Annoyance and Irritation by co-workers, supervisors, clients, and others
Forty-three percent of respondents reported never doing a job just because the supervisor instructed them to do so. However, only a single nurse manager reported that almost always her supervisor was instructing her to do the job, otherwise she would not have done it. Surprisingly, (38%) of nurse managers reported being ‘sometimes’ irritated by co-workers, supervisors, clients or others, whereas, 7% of nurses were ‘often’ to ‘almost always’ being irritated by colleagues, bosses, or clients.
Being impatient with others at work
Noteworthy, 5% of study participants reported being ‘almost always’ impatient with other in the workplace. On the other hand, 25% of respondents were ‘sometimes’ impatient, while 26% of nurse managers are ‘never’ impatient with others.
Falling asleep or becoming very sleepy during work hours
As regards falling asleep unexpectedly or feeling sleeping during duty hours, 16% reported being ‘sometimes’ sleepy in the workplace, however, none of them were ‘almost always or often’ falling asleep during work. This could simply be contributable to the hard work environment they are placed in. As most nurses are at the front line by the patients’ bed 24/7, they are expected to feel exhausted and sleepy at times.
Self-assessment of expectations of work productivity and efficiency
As for the self-assessment of productivity during work among nurse managers, only 2% of respondents reported perceiving their productivity at work as ‘almost always’ lower than expected. On the other hand, about half of participants (45%) reported acknowledging their productivity at the clinical setting as ‘rarely less than expected. In terms of efficiency of work in the clinical setting, none of the respondents reported efficiency of their work as “almost always’ less than expected. Furthermore, 42% of the study participants reported their efficiency as ‘rarely’ lower than expected.
Loss of interest or becoming bored with work
Surprisingly, a total of 10% of nurse managers in the current study reported losing interest or becoming bored with work “often to almost always”. Moreover, 33% of respondents reported ‘sometimes’ losing interest in work. These findings point out the extra load put on nurses in patient care. As most nurses are expected and instructed to do nothing less than perfect as regards patient care, they may often get the feeling of being burnt out, which could manifest as losing interest in the job or being bored at the same time.
Feeling exhausted to do work
Consistently, 7% of participating nurse managers reported that ‘often’ to ‘almost always’ they feeling exhausted during duty hours. Furthermore, about 40% of nurse managers reported being ‘sometimes’ exhausted.
Failure to finish assigned tasks
That being said, about half of nurse managers (40%) reported that they ‘rarely’ fail to finish their assigned tasks, as they are expected to do nothing less than perfect during work. Moreover, none of them reported being ‘almost always’ or ‘sometimes’ unable to finish the tasks. This finding also makes it clear that the intention of nurse managers to prove compliant to difficult tasks makes them exhausted and subsequently feeling lack of interest in work.
Putting off returning calls
Of note, none of the nurse managers in the current study reported ‘almost always’ putting off on returning calls, whereas only (42%) would return calls.
Research Question 4
What is the bivariate relationship between cyberloafing and productivity?
CORRELATION BETWEEN CYBERLOAFING AND PRODUCTIVITY
Two correlations were tested to answer this research question, and the results are presented in Table (9). The results indicated that there was a correlation between internet surfing and employee productivity, r (97) = - 0.550. Although a negative relationship existed between internet surfing and employee productivity, (p-value = 0.000). So, there is significant relationship between internet surfing and employee productivity.
Upon investigating the correlation between internet surfing (cyberloafing) activity and employee productivity among nurse managers, the statistical analysis revealed a significant negative relationship between both factors (P <0.0005). Therefore, we suggest that our findings support the existing literature in regards to the negative correlation between the act of cyberloafing within the clinical setting and its impact on the employee’s productivity. Such association could be explained by the negative effect of escaping from work in the clinical setting by acting through cyberloafing on performing job-related tasks effectively and on time which means it leads to decrease productivity.
Table 9. Pearson Correlation Coefficient
|
ALCS |
|
EWPS |
Pearson Correlation |
- 0.550** |
Sig. (2-tailed) |
0.000 |
|
N |
97 |
** Correlation is significant at the 00.010.
Linear Regression Analysis Findings
We performed linear regression analysis between the dependent variable (employee’s productivity) and a group of independent variables including some of the basic demographic characteristics of study participants.
As shown in Table (10), we found that age, nationality, and marital status to be significantly correlated with nurse managers' productivity. That being said, age was negatively correlated with nurse managers’ productivity, as an increase in age would reflect a reduction in the outcome of productivity (P =0.002). As for marital status, we found that being single is positively correlated with better productivity outcome (P =0.004) while being married was negatively associated with productivity (P =0.01). However, that finding requires further confirmation by further studies to control any confounding variable.
Table 10. linear regression Analysis for cyberloafing behaviour in relation with employees' productivity
Pearson Correlation |
||
EWPS 1to25 |
||
EWPS 1to25 |
1.000 |
|
ALCS |
.550 |
.000 |
Group |
.143 |
.081 |
Sex |
-.135 |
.094 |
education |
.110 |
.141 |
Age |
-.285 |
.002 |
nationality |
.294 |
.002 |
organization |
-.153 |
.067 |
Level |
.143 |
.081 |
experience |
-.113 |
.134 |
Single |
.268 |
.004 |
Married |
-.235 |
.010 |
Divorced |
.111 |
.139 |
Widow |
-.140 |
.086 |
Research Question 5
Is there a difference among nurse managers' cyberloafing behavior and their productivity in the Two study settings?
As showing in Table (11), it was observed that the EWPS is sig=0.135 > 0.05 which demonstrate no Significance level for average Sample answers by participant in each organization. Moreover, in the ALCS and its sub-axes the sig is (0.794) > 0.05 showing that there is no Significance level for average sample answers by participant in each organization. So, there was no significant difference among nurse managers' cyberloafing behavior in the two study settings (p>0.05).
Table 11. Significance level for average Sample answers in the two settings (T-test)
|
Hospital |
NO. |
X |
SD |
t |
Df |
Sig |
|
|
Employee productivity (EWPS) 1to25 |
King Fahad Hospital |
58 |
1.9386 |
0.5715 |
-1.509 |
95 |
0.135 |
no Significance |
|
King Abdulaziz Hospital |
39 |
2.1067 |
0.4831 |
||||||
Cyberloafing (ALCS)
|
ALCS-A 1to17 |
King Fahad Hospital |
58 |
1.6440 |
0.7688 |
-0.570 |
95 |
0.570 |
no Significance |
King Abdulaziz Hospital |
39 |
1.7345 |
0.7628 |
||||||
ALCS-B 1to7 |
King Fahad Hospital |
58 |
2.4483 |
0.9698 |
0.192 |
95 |
0.848 |
no Significance |
|
King Abdulaziz Hospital |
39 |
2.4066 |
1.1553 |
||||||
ALCS-C 1to4 |
King Fahad Hospital |
58 |
1.7112 |
0.7777 |
-0.293 |
95 |
0.770 |
no Significance |
|
King Abdulaziz Hospital |
39 |
1.7564 |
0.6942 |
||||||
SETHC 1to2 |
King Fahad Hospital |
58 |
2.0776 |
1.4624 |
0.578 |
95 |
0.565 |
no Significance |
|
King Abdulaziz Hospital |
39 |
1.9103 |
1.2971 |
||||||
Overall of (ALCS)
|
King Fahad Hospital |
58 |
1.8695 |
0.6771 |
-0.261 |
95 |
0.794 |
no Significance |
|
King Abdulaziz Hospital |
39 |
1.9060 |
0.6674 |
P value 0.794 > 0.05
Research Question 6
Is there an association between nurse managers' demographic characteristics and their cyberloafing behavior and productivity in the Two study settings?
The answer for this question is showing in Table (12) to Table (15).
- Level:
Table (12) presents a result of descriptive statistics of nurse mangers' and cyberloafing behavior in the two study settings, and presenting Two-way ANOVA test as related to their level.
The results as showing in Table (12), in the association between Nurse managers' level and their cyberloafing behavior in the two study settings the result revealed that, there is no evidence to assume that if there is any association (0.109>0.05).
Table 12. Frequency, Mean and standard division of Nurse Managers and their productivity and the association between them in the Two study settings as related to their level group
Hospital |
X |
SD |
N |
Hospital * level |
||
F |
Sig |
|||||
king fahad hospital |
Head nurse |
1.9274 |
.60197 |
38 |
|
|
nursing supervisor |
1.9600 |
.52283 |
20 |
|||
Total |
1.9386 |
.57147 |
58 |
|||
king abdulaziz hospital |
Head nurse |
1.9886 |
.42845 |
28 |
||
nursing supervisor |
2.4073 |
.50273 |
11 |
|||
Total |
2.1067 |
.48309 |
39 |
|||
Total |
Head nurse |
1.9533 |
.53240 |
66 |
||
nursing supervisor |
2.1187 |
.55199 |
31 |
|||
Total |
2.0062 |
.54143 |
97 |
2.619 |
0.109 |
Table (13) is presenting a result of descriptive statistics of nurse mangers' and their cyberloafing in the two study settings, and Two-way ANOVA test as related to their level.
Table (13) is showing, the result revealed than there is no evidence to assume that if there is association between Nurse managers' level either head nurse or nursing supervisor and their cyberloafing behavior in the Two study settings sig = 0.087>0.05.
Table 13. Frequency, Mean and standard division of Nurse Managers and their cyberloafing behavior and the association between them in the Two study settings as related to their level group
Hospital |
X |
SD |
N |
Hospital * level |
||
F |
Sig |
|||||
king fahad hospital |
Head nurse |
1.7632 |
.66850 |
38 |
|
|
nursing supervisor |
2.0717 |
.66300 |
20 |
|||
Total |
1.8695 |
.67712 |
58 |
|||
king abdulaziz hospital |
Head nurse |
1.6810 |
.50041 |
28 |
||
nursing supervisor |
2.4788 |
.71683 |
11 |
|||
Total |
1.9060 |
.66741 |
39 |
|||
Total |
Head nurse |
1.7283 |
.60006 |
66 |
||
nursing supervisor |
2.2161 |
.69920 |
31 |
|||
Total |
1.8842 |
.66998 |
97 |
2.983 |
0.087 |
- Education:
By performing Two-Way ANOVA test to determine the association between nurse managers' cyberloafing behavior and productivity in related to Nursing education level, the result in Table (14) and (15) revealed that there is no significant difference between Nurse's education level and their cyberloafing behavior and productivity (p>0.05)
Table 14. Frequency, Mean and standard division of Nurse Managers and their productivity and the association between them in the Two study settings as related to their education group
Hospital |
X |
SD |
N |
Hospital * education |
||
F |
Sig |
|||||
king fahad hospital |
bachelor degree |
1.9902 |
.51682 |
41 |
|
|
Diploma |
1.8141 |
.68731 |
17 |
|||
Total |
1.9386 |
.57147 |
58 |
|||
king abdulaziz hospital |
bachelor degree |
2.1229 |
.44912 |
28 |
||
Diploma |
2.0655 |
.58276 |
11 |
|||
Total |
2.1067 |
.48309 |
39 |
|||
Total |
bachelor degree |
2.0441 |
.49144 |
69 |
||
Diploma |
1.9129 |
.64911 |
28 |
|||
Total |
2.0062 |
.54143 |
97 |
0.231 |
0.632 |
Table 15. Frequency, Mean and standard division of nurse managers and their cyberloafing behavior and the association between them in the Two study settings as related to their education group
Hospital |
X |
SD |
N |
Hospital * education |
||
F |
Sig |
|||||
king fahad hospital |
bachelor degree |
1.8911 |
.63670 |
41 |
|
|
diploma |
1.8176 |
.78476 |
17 |
|||
Total |
1.8695 |
.67712 |
58 |
|||
king abdulaziz hospital |
bachelor degree |
1.9321 |
.73184 |
28 |
||
diploma |
1.8394 |
.48963 |
11 |
|||
Total |
1.9060 |
.66741 |
39 |
|||
Total |
bachelor degree |
1.9077 |
.67197 |
69 |
||
diploma |
1.8262 |
.67369 |
28 |
|||
Total |
1.8842 |
.66998 |
97 |
0.004 |
0.951 |
- Gender:
As a result of classifying participants according to their gender, table (16) and (17) shows Two-way ANOVA test for no differences between either male or female in their engagement in cyberloafing and level of productivity in the two study settings (p > .05).
Table 16. Frequency, Mean and standard division of Nurse Managers and their productivity and the association between them in the Two study settings as related to their gender group
Hospital |
X |
SD |
N |
Hospital * Gender |
||
F |
Sig |
|||||
King Fahad Hospital |
Male |
2.1771 |
.62646 |
7 |
|
|
Female |
1.9059 |
.56227 |
51 |
|||
Total |
1.9386 |
.57147 |
58 |
|||
King Abdulaziz Hospital |
Male |
2.1886 |
.48920 |
7 |
||
Female |
2.0888 |
.48776 |
32 |
|||
Total |
2.1067 |
.48309 |
39 |
|||
Total |
Male |
2.1829 |
.54002 |
14 |
||
Female |
1.9764 |
.53920 |
83 |
|||
Total |
2.0062 |
.54143 |
97 |
0.301 |
0.585 |
Table 17. Frequency, Mean and standard division of Nurse Managers and their cyberloafing behavior and the association between them in the Two study settings as related to their gender group
Hospital |
X |
SD |
N |
Hospital * Gender |
||
F |
Sig |
|||||
King Fahad Hospital |
Male |
2.3524 |
1.09829 |
7 |
|
|
Female |
1.8033 |
.58379 |
51 |
|||
Total |
1.8695 |
.67712 |
58 |
|||
King Abdulaziz Hospital |
Male |
2.0714 |
.54414 |
7 |
||
Female |
1.8698 |
.69367 |
32 |
|||
Total |
1.9060 |
.66741 |
39 |
|||
Total |
Male |
2.2119 |
.84536 |
14 |
||
Female |
1.8289 |
.62512 |
83 |
|||
Total |
1.8842 |
.66998 |
97 |
0.814 |
0.369 |
- Marital status:
As a result of classifying participants according to their marital status, table (18) and (19) are showing the descriptive statistics of participants' marital status, and presenting Two-Way ANOVA test which shows there is no association between nurse manager marital status and productivity and cyberloafing behavior in the two study settings (p > 0.05).
Table 18. Frequency, Mean and standard division of Nurse Managers and their productivity and the association between them in the Two study settings as related to their marital status group
Hospital |
X |
SD |
N |
Hospital * status |
||
F |
Sig |
|||||
King Fahad Hospital
|
Single |
2.2244 |
.43259 |
18 |
|
|
Married |
1.7937 |
.58059 |
38 |
|||
Divorced |
2.6800 |
|
1 |
|||
Widow |
1.5600 |
|
1 |
|||
Total |
1.9386 |
.57147 |
58 |
|||
King Abdulaziz Hospital |
Single |
2.2327 |
.57238 |
11 |
||
Married |
2.1178 |
.49267 |
18 |
|||
Divorced |
2.1520 |
.32422 |
5 |
|||
Widow |
1.7440 |
.22379 |
5 |
|||
Total |
2.1067 |
.48309 |
39 |
|||
Total |
Single |
2.2276 |
.48025 |
29 |
||
Married |
1.8979 |
.57019 |
56 |
|||
Divorced |
2.2400 |
.36133 |
6 |
|||
Widow |
1.7133 |
.21379 |
6 |
|||
Total |
2.0062 |
.54143 |
97 |
1.093 |
0.356 |
Table 19. Frequency, Mean and standard division of Nurse Managers and their cyberloafing behavior and the association between them in the Two study settings as related to their marital status group
Hospital |
X |
SD |
N |
Hospital * status |
||
F |
Sig |
|||||
King Fahad Hospital |
Single |
2.0926 |
.61735 |
18 |
|
|
Married |
1.7632 |
.70356 |
38 |
|||
Divorced |
1.9667 |
|
1 |
|||
Widow |
1.8000 |
|
1 |
|||
Total |
1.8695 |
.67712 |
58 |
|||
King Abdulaziz Hospital |
Single |
2.1030 |
.52841 |
11 |
||
Married |
1.9185 |
.83636 |
18 |
|||
Divorced |
1.8133 |
.41001 |
5 |
|||
Widow |
1.5200 |
.29684 |
5 |
|||
Total |
1.9060 |
.66741 |
39 |
|||
Total |
Single |
2.0966 |
.57545 |
29 |
||
Married |
1.8131 |
.74470 |
56 |
|||
Divorced |
1.8389 |
.37203 |
6 |
|||
Widow |
1.5667 |
.28906 |
6 |
|||
Total |
1.8842 |
.66998 |
97 |
0.187 |
0.905 |
- Age:
Table (20) and (21) present results of descriptive statistics and Two-way ANOVA test for analyzing the association between nurse managers and their cyberloafing behavior and productivity in the age group. The result revealed that there is no evidence to assume if there is an association between Nurse managers and the two study variables (p>0.05).
Table 20. Frequency, Mean and standard division of Nurse Managers and their productivity and the association between them in the Two study settings as related to their age group
Hospital |
X |
SD |
N |
Hospital* age |
||
F |
Sig |
|||||
King Fahad Hospital |
less than 30 |
2.1771 |
.73787 |
7 |
|
|
30-35 |
2.0229 |
.50858 |
28 |
|||
36-40 |
2.1200 |
.56631 |
10 |
|||
41-45 |
1.6089 |
.41026 |
9 |
|||
greater than 45 |
1.2200 |
.23209 |
4 |
|||
Total |
1.9386 |
.57147 |
58 |
|||
King Abdulaziz Hospital |
less than 30 |
2.2800 |
.47917 |
5 |
||
30-35 |
1.9788 |
.53406 |
17 |
|||
36-40 |
2.3200 |
.29814 |
10 |
|||
41-45 |
2.2600 |
.53914 |
4 |
|||
greater than 45 |
1.6267 |
.15144 |
3 |
|||
Total |
2.1067 |
.48309 |
39 |
|||
|
30-35 |
2.0062 |
.51274 |
45 |
||
36-40 |
2.2200 |
.45227 |
20 |
|||
41-45 |
1.8092 |
.53170 |
13 |
|||
greater than 45 |
1.3943 |
.28606 |
7 |
|||
Total |
2.0062 |
.54143 |
97 |
1.220 |
0.308 |
Table 21. Frequency, Mean and standard division of Nurse Managers and their cyberloafing behavior and the association between them in the Two study settings as related to their age group
Hospital |
X |
SD |
N |
Hospital * age |
||
F |
Sig |
|||||
king fahad hospital |
less than 30 |
1.9381 |
.90522 |
7 |
|
|
30-35 |
2.0143 |
.67558 |
28 |
|||
36-40 |
1.9100 |
.43887 |
10 |
|||
41-45 |
1.5370 |
.72981 |
9 |
|||
greater than 45 |
1.3833 |
.32830 |
4 |
|||
Total |
1.8695 |
.67712 |
58 |
|||
king abdulaziz hospital |
less than 30 |
1.7600 |
.49126 |
5 |
||
30-35 |
1.6725 |
.54253 |
17 |
|||
36-40 |
2.2800 |
.79009 |
10 |
|||
41-45 |
2.2750 |
.72998 |
4 |
|||
greater than 45 |
1.7333 |
.69602 |
3 |
|||
Total |
1.9060 |
.66741 |
39 |
|||
|
30-35 |
1.8852 |
.64434 |
45 |
||
36-40 |
2.0950 |
.65035 |
20 |
|||
41-45 |
1.7641 |
.78357 |
13 |
|||
greater than 45 |
1.5333 |
.50037 |
7 |
|||
Total |
1.8842 |
.66998 |
97 |
1.294 |
0.259 |
- Years of experience:
Tables (22) and (23) are showing no significant association between years of experience of the participants in regard to cyberloafing behavior and productivity. (p>0.05)
Table 22. Frequency, Mean and standard division of Nurse Managers and their productivity and the association between them in the Two study settings as related to their years of experience group
Hospital |
experience |
X |
SD |
N |
Hospital * experience |
|
F |
Sig |
|||||
King Fahad Hospital |
0-3 |
2.0576 |
.59756 |
25 |
|
|
4-6 |
1.7929 |
.53315 |
17 |
|
|
|
7-9 |
2.0711 |
.52603 |
9 |
|
|
|
10-12 |
1.7867 |
.67686 |
3 |
|
|
|
13+ |
1.6300 |
.59003 |
4 |
|
|
|
Total |
1.9386 |
.57147 |
58 |
|
|
|
King Abdulaziz Hospital |
0-3 |
2.1200 |
.48841 |
12 |
|
|
4-6 |
2.0873 |
.61157 |
11 |
|
|
|
7-9 |
2.2178 |
.46994 |
9 |
|
|
|
10-12 |
2.0467 |
.22545 |
6 |
|
|
|
13+ |
1.5200 |
. |
1 |
|
|
|
Total |
2.1067 |
.48309 |
39 |
|
|
|
Total |
0-3 |
2.0778 |
.55841 |
37 |
|
|
4-6 |
1.9086 |
.57306 |
28 |
|
|
|
7-9 |
2.1444 |
.48973 |
18 |
|
|
|
10-12 |
1.9600 |
.40398 |
9 |
|
|
|
13+ |
1.6080 |
.51334 |
5 |
|
|
|
Total |
2.0062 |
.54143 |
97 |
0.234 |
0.918 |
Table 23. Frequency, Mean and standard division of Nurse Managers and their cyberloafing behavior and the association between them in the Two study settings as related to their years of experience group
Hospital |
X |
SD |
N |
Hospital * experience |
||
F |
Sig |
|||||
King Fahad Hospital |
0-3 |
1.9853 |
.69762 |
25 |
|
|
4-6 |
1.5569 |
.50645 |
17 |
|||
7-9 |
2.0556 |
.61531 |
9 |
|||
10-12 |
2.2111 |
1.30909 |
3 |
|||
13+ |
1.8000 |
.63654 |
4 |
|||
Total |
1.8695 |
.67712 |
58 |
|||
King Abdulaziz Hospital |
0-3 |
1.8056 |
.60550 |
12 |
||
4-6 |
1.6394 |
.47348 |
11 |
|||
7-9 |
2.2889 |
.88081 |
9 |
|||
10-12 |
2.1056 |
.58781 |
6 |
|||
13+ |
1.4000 |
|
1 |
|||
Total |
1.9060 |
.66741 |
39 |
|||
|
4-6 |
1.5893 |
.48653 |
28 |
||
7-9 |
2.1722 |
.74678 |
18 |
|||
10-12 |
2.1407 |
.80446 |
9 |
|||
13+ |
1.7200 |
.57956 |
5 |
|||
Total |
1.8842 |
.66998 |
97 |
0.402 |
0.807 |
Hence, there is no association between nurse managers' demographic characteristics and their cyberloafing behavior and productivity in the two study sittings (p > 0.05).
Summary
This chapter reported the findings of the current study, 97 nurse managers participated in this study, and most of the participants were female. Nurses perceived highly to OCB
(5.78±1.43). In order to reduce the risk of a Type Ⅲ error, Two-way ANOVA test was computed to check for homogeneity of variance. There were no association among the participants' demographic characteristics and CB and productivity. There is a significant relationship between nurse managers' cyberloafing behavior and productivity.
The purpose of the current study was to determine the impact of cyber loafing on nurse managers' productivity. To reach this aim six research questions were stated and investigated. The results chapter showed the answer for each question, tabulated and presented statistically through descriptive and inferential statistical work. This chapter discusses the findings and relates them to other studies that have been conducted related to cyberloafing.
In respect to the first research question about demographic profile of the nurse managers, (Yilmaz, 2013) indicates that a good research study is one that groups the participants considering certain demographics like age, sex, marital status and education status. Doing this helps to ensure that the data collected is not biased and that it is well distributed thus helping achieve the best results. The majority of the study surveyed population was female nurses which supports the argument that nursing is a female dominant profession worldwide. Following this criteria, this study divided respondents in the survey study into various age groups: less than 30 years old; 30 to 35 years old; 36 to 40 years old; 41 to 45 years old; greater than 45 years to help define the extensiveness of cyberloafing in regard to age. Based on the marital status of our study participants, twenty-nine nurses were single; 56 were married; 6 were divorced; 6 were widows. Furthermore, according to the highest educational level received, sixty-nine of the study participants reported receiving bachelor degree, whereas 28 nurse managers received diploma as their highest degree of education.
On the second research question about the extent to which nurse managers engaging in cyberloafing, computer and internet based functioning is something that has greatly grown in many sectors over the years, most especially in the health care sectors. Using the internet helps to reduce costs and it helps to shorten the time taken in providing health services (Henle & Blanchard, 2008). This has also provided a considerable problem for the management that now has to deal with the issue of the employees engaging in non-work related activities for instance sending and receiving personal emails, playing online games, online shopping and engaging in social connections that affect the overall services provided within organizations (Weiser, 2000). In the health care system where the use of pen and paper has become obsolete, it is difficult for the nurses to avoid using the internet while on duty at the hospital. Many nurses are involved in cyberloafing which affects their work because they are always distracted while on duty (Henle & Blanchard, 2008). This study however disagree with this concept showing that the number of nurse managers that are engaged in cyberloafing is relatively low, with the highest non-work related activity being making phone calls where 27% of the nurses indicate that they did this a few times in a day, followed by sending and receiving of messages where 24% of the nurses indicated that they are victims to this and the least behavior being playing of internet games with only 1% of the nurses admitting that they engage in this while at work.
Other activities like visiting social networks like Facebook and shopping online also happen but they are not frequent and only 9% of the nurses admitted to engaging in such activities while at work. Most of the nurse managers indicated that they are ready to hide their cyberloafing activities from their supervisors in case they are caught which indicates that they are aware that cyberloafing is not acceptable at work. Most of the times employees engage in cyber loafing to take some time off the stressful work setting in their various organizations (Zoghbi, 2012). Taking those few minutes to go through one’s social media changes one’s attitude helping them to relax and lighten up which helps them have more motivation once they get back to work (Zoghbi, 2012). This concept has been illustrated in this study where upon investigating the correlation between internet surfing (cyberloafing) activity and employee productivity in our population, there is significant positive relationship between both factors (P <0.0005). Consequently, the conclusion that any act of cyberloafing during working hours within the healthcare setting has a positive effect on employee’s productivity within the workplace, most probably secondary to the relief of the stressful environment the nurses work at as well as its effect in helping the nurses ability to cope with the demanding tasks and stress within the working place as they are in continuous work by the patients’ bedside 24/7.
The internet is in most cases used by staff as an educational tool where they look up various strategies to help improve their output while at work (Fox, 2007). A nurse manager could for instance look up the internet for best way to deal with an irritable patient while on duty which will in the overall help him or her conduct her duties appropriately. In regard to loosing work interest, a total of 10% of nurse managers in our study reported losing interest or becoming bored with work “often to almost always”. Moreover, 33% of respondents reported losing interest in work ‘sometimes’. These findings point out the extra load put on nurses in patient care. As most nurses are expected and instructed to do nothing less than perfect as regards patient care, they may often get the feeling of being burnt out, which could manifest as losing interest in the job or being bored at the same time and hence choosing to use the internet while on duty(Fox, 2007). Consistently, in our study, 7% reported feeling exhausted during duty hours from ‘often’ to ‘almost always’. Furthermore, the majority of nurse managers in our population reported being exhausted ‘sometimes’, accounting for 40% from the total population surveyed. The majority of nurses in our population ‘rarely’ fail to finish their assigned tasks, as they are expected to do nothing less than perfect during work. Moreover, none of the nurses reported being unable to finish the task either ‘almost always’ or ‘sometimes’. This finding also makes it clear that the intention of nurse managers to prove compliant to difficult tasks makes them exhausted and subsequently feeling lack of interest in work.
On the third research question about attitude and behaviors, Carmeli et al., (2008) establishes that nurses are just basically positively motivated to attend to their patients in the right manner and be at work at the right time and not letting the irritation that they get from other people affect their output, because this is how they are trained to function. This study shows that the attitudes of the nurse managers towards job performance are just naturally positive without them having to be pushed around by their supervisors to perform their duties. 43% of respondents reported never doing a job just because the supervisor instructed them to do so. However, only a single nurse manager reported that almost always her supervisor was instructing her to do the job, otherwise she would not have done it. Surprisingly, the majority of nurses reported being ‘sometimes’ irritated by co-workers, supervisors, clients or others, whereas, 7% of nurses were ‘often’ to ‘almost always’ being irritated by colleagues, bosses, or clients. A nursing career is not for people who are dedicated; it is for people who understand the concept of being self-disciplined and selfless (Carmeli et al., 2008). These are people that do not need to be pushed around to attend to patients and be at the right place at the right time (Carmeli et al., 2008). Nurses have to be time conscious ensuring that they are not wasting time taking long breaks and chatting with their colleagues while patients are suffering in their wards. In terms of long lunch hours and coffee breaks, the majority of nurse managers in our study (56%) reported never taking too long during lunch hours or lengthens coffee breaks. On the other hand, 4% (4 nurse managers) almost always had longer lunch hours and/or coffee breaks. This could reflect their need to take some time off during stressful work. In terms of doing nothing related to work during duty hours, the majority of study respondents (44%) reported never being lazy to do the job during their duty hours. However, only one nurse manager reported doing nothing at times when she was expected to be working.
On the fourth research question about bivariate relationship between, the study by Fox, (2007) indicates that it is often common for employees to lose interest with work especially because this is something that they do day in day out. The work environment and roles can become monotonous leading workers to feel bored and this is one of the things that prompt them to cyberloaf. This concepts have been supported by this study where the linear regression analysis performed between the dependent variable (employee’s productivity) and a group of independent variables including some of the basic demographic characteristics of study participants; indicates that age and marital status to be significantly correlated with nurse managers' productivity. The study shows that age is negatively correlated with nurse managers’ productivity, as an increase in age would reflect a reduction in the outcome of productivity (P =0.002). Being married and having a family also negatively affects productivity, where nurses married have divided attention for work and family. Late arrival at work and early leave was reported to occur by a minority of respondent where only 1% reported that they ‘almost always’ arrive late or leave early and this is dependent on their marital status where the married ones always come late and leave early because they have other responsibilities as parents while the single ones always come in early and leave late which can be attributed to the fact that they do not have much responsibilities. On the other hand, the majority (49%) never have been later for work and never left work early before the end of their duty hours.
On the fifth research question about difference among nurse managers' cyberloafing behavior and their productivity in the Two study settings, the study by Henle et al., (2010) indicates that nurses are people expected to offer quality health care to patients without any form of bias. They often have to deal with stress as they attend to different types of patients who at times treat them in an inhumane manner which can greatly affect their productive. However the use of the internet for them, acts as an escape from these stress which helps them to rejuvenate and always perform their best (Weiser, 2000). This study in regard to self-assessment of productivity during work in the survey nurse managers, indicates that only 2% of respondents reported receiving their productivity at work as ‘almost always’ lower than expected meaning that their productivity is always above average. On the other hand, the majority of participants reported acknowledging their productivity at the clinical setting as ‘rarely less than expected (45%). In terms of efficiency of work in the clinical setting, none of the responded reported their efficiency of work as “almost always’ less than expected. Furthermore, 42% of the study population reported their efficiency as ‘rarely’ lower than expected. Employees use the internet as a way to help ease boredom and monotony at work (Weiser, 2000). This argument is supported by the findings from this study where the few nurse managers that engage in cyberloafing cite it as an effect of boredom while at work, which cause them to feel sleepy where 16% of them reported that they often feel sleepy wile at work. The nurses just like many other employees out there opt to cyberloaf as a way of keeping their minds engaged which in turn helps them to stay sharp and motivated at work (Weiser, 2000). It is important to note that none of the nurse managers in our study reported ‘almost always’ putting off on returning calls, whereas the majority (42%) would return calls. This shows that even though the nurses understand their responsibilities while at work, they are still attached to other activities outside of work that they do not feel restricted to attend to while still at work.
On the sixth research question on whether there is an association between nurse managers' demographic characteristics and their cyberloafing behavior and productivity in the Two study settings the study by Zoghbi-Manrique-de-Lara, & Olivares-Mesa, (2010), there are many factors that affect the productivity of employees and this range from the age of the employee to their responsibilities away from work. When it comes to age, the young people tend to be more energetic as compared to the older generation which allows them to perform more work and hence making them more productive (Young, 2001). In the study, most of the nurse managers that are in the age gap of 30 and below tend to use the internet while at work much more as compared to the nurse managers that are between the ages of 45 and above. Cyberloafing differs according to generations and hence the age factor. The baby boomers have a preference to balance work and family and they therefore are not frequently engaged in cyber loafing because they disconnect their smartphones while working (De Lara, 2009). The generation X on the other hand demands a balance between work, family and friends and they are often willing to switch between work and personal life while at work. The generation Y on the other hand believes in fun at all times even while working and so they are often in both professional and personal modes concurrently meaning hat hey engage in cyberloafing the most (De Lara, 2009). Most of the employees that have families have divided attention where they are constantly concerned about their families, even while at work which affects their productivity as compared to the people that are single (Zoghbi-Manrique-de-Lara, & Olivares-Mesa, 2010). This study shows that in regard to marital status, being single is positively correlated with better productivity outcome (P =0.004) while being married was negatively associated with productivity (P =0.01). `
Summary
This discussed the findings were discussed in accordance to the past studies on cyberloafing. It basically included discussions on the nurse managers that were included in the study and the overall representation of their standing on cyberloafing. This discussion has established that cyberloafing is something that cannot really be eradicated in healthcare especially with the increased development of technology that requires all health care facilities to be internet connected. The findings show that though cyberloafing interrupts with the workflow of a nurse, it does not really affect his or her output in the overall. This study and many others that have been cited indicate that even though nurse managers engage in cyberloafing, it is minimal and it is through engagement of minor activities like phone calls and text messages a few times a day. This helps to reduce the stressing impacts of their work as they chat and talk with their loved ones which help motivate them to work extra harder and hence better work performance. This study shows that cyberloafing does not negatively impact the healthcare sector and the overall productivity of the nurses.
Chapter ⅥConclusion/Recommendations
The current study findings reveal that the majority of our nursing managers reported returning phone calls during work; however, this does not affect their work productivity and efficiency. Most nurse managers achieve tend to deliver work with high productivity and efficiency, while aiming for finishing assigned tasks on time with no delay. However, Result shows some negative outcomes on their personality, many of them reported to feel sleepy during work hours and a considerable percentage of them reported losing the interest to work. Moreover, cyberloafing behavior has been shown to be positively associated with employee’s productivity in the workplace.
Based on the findings of our study which prove that cyberloafing activity is associated positively with employee’s productivity in the workplace, the researcher recommends the following:
- Nursing Education: Nursing personnel can manipulate the thinking of adults regarding the harmful effects of internet usage for personally-centered purposes in the healthcare setting in order to decrease the frequency of cyberloafing, if it harmfully affects employee’s productivity, and to improve physical and psychological health of the nursing staff
- Nursing administrator can provide facilities and promote education to junior nurses and the nursing staff regarding the internet usage and internet addiction (cyberloafing).
- Nurse administrator should ensure for the availability of the material like pamphlets, posters, charts, modules, guidelines related to prevention of internet addiction (cyberloafing), if it harmfully affects employee’s productivity.
- There should be policy for supervision of staffs and adequate supply of the equipment to reduce addiction
- Cyberloafing would be permitted under certain circumstances, in order to prevent burnout among the nursing staff and to allow nurses to get a way to escape the stressful work environment to better cope with their work for better patients’ outcomes.
- Nurse managers should appropriately address cyberloafing behavior and identify whether or not it negatively impacts employee’s productivity and subsequently patients’ outcomes.
- Nursing Research: Further research should be conducted in order to investigate this phenomenon and examine its impact on the productivity and efficiency of work of registered nurses in the workplace.
- Nurses can take initiative to conduct more research regarding the internet usage, mobile usage, and other personal gadget usage in the workplace for non-work-related purposes.
- Further research investigating the effect of cyberloafing/slacking on nurses’ productivity still warrants further investigation.
Given the fact that the study questionnaire is self-reported, this highlights the risk of recall bias in our study. Worthy to mention, the small sample size of our study would affect the interpretation of our findings and limits the generalizability of our results. Therefore, much larger sample sizes are required in order to detect a real significant correlation. Moreover, we did not gather any information as related to nurse managers’ use of internet during duty hours or their behavior in their daily working hours.
SummaryThe act of using internet access for personal, non-work-related purposes, in the workplace, intimately called “cyberloafing or cyberslacking” is thought to be of major impact on employee’s productivity as well as the efficiency of work delivered.
Nurses, being at the patients’ bedside 24/7, have the highest liability of being intimidated by work stresses and then try to escape that by cyberloafing, and eventually affecting patients’ outcomes.
We conducted this survey study at the level of two nursing settings in KSA to investigate the extent of cyberloafing in these settings and to determine the association between both factors: cyberloafing and productivity. We used pre-validated questionnaires from previous studies to assess the extent and pattern of cyberloafing as well as employee’s productivity. Our survey was based on the responses of nurse managers “supervisors and head nurses” only and did not incorporate registered nurses.
We re-tested the validity of both questionnaires and both were shown to be highly valid. Our analysis revealed that most nurses did their best in order to deliver their work at time, where most reported ‘never’ failing to deliver work assignments. Also, most of them were deemed to deliver high productivity and work efficiency. As a consequence, we think that this in some way affected their sleep, where most of nurse managers reported ‘sometimes’ falling asleep or feeling sleepy during duty hours. Subsequently, this would have impacted their interest in work, as most nurses reported ‘sometimes’ losing interest in work. Furthermore, we investigated the association between cyberloafing in the clinical setting and nurse managers’ productivity and we found a significantly positive association between both factors. So, we can propose that the positive relationship between cyberloafing and productivity is a result of the nurses trying to find a ‘way’ to escape work stress in order to be able to deliver work efficiently.
Based on the rigorous and thorough literature review, there are very scarce reported investigating the effect of cyberloafing in the clinical setting on health care workers’ productivity. Therefore, we recommend conducting further research with high sample sizes in order to detect the actual and significant association between cyberloafing behavior in the work place and employees’ productivity. Also, usage of internet in clinical practice should be assessed in further work.
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APPENDICES
Appendix I – Tables
Table 1. Scales Reliability; Cronbach’s Alpha (α)
Cronbach's Alpha |
N of Items |
Axis |
|
0.921 |
25 |
|
EWPS |
0.916 |
17 |
ALCS-A |
ALCS |
0.847 |
7 |
ALCS-B |
|
0.797 |
4 |
ALCS-C |
|
0.763 |
2 |
SEtHC |
|
0.916 |
30 |
All |
|
0.941 |
55 |
Cronbach's Alpha all |
Appendix Ⅱ – Cyberloafing Scale by Askew and Lim
- Are you currently employed?
- No Yes
- At work, do you have access to the internet? Access can be through a computer, smartphone, or both.
- No Yes
- DEMOGRAPHICS
The following will enable me to identify trends among different people responding, so please provide me with answer to some basic questions about you
- Age: __________
- Nationality: _______________
- What organization do you work in? __________________________________
- Years of experience:
- 1-3 4-6 3. 7-9 4. 10-12 5. 13+
- Which of the following best describes your current level in the organization?
- Staff Head nurse 3. Supervisor 4. Other ______________
- How many hours per week do you work?
0-10 2. 11-20 3. 21-30 4. 31-40 5. 41-50 6. 51+
- During office hours, how often do you do each of the following through a
DESKTOP COMPUTER or LAPTOP?
1 |
2 |
3 |
4 |
5 |
6 |
Never |
A few times per month |
A few times per week |
Once a day |
A few times a day |
Constantly |
_________ 1. Visit nonjob related websites
_________2. Visit general news websites
_________3. Visit entertainment websites
_________4. Visit sports related websites
_________5. Instant message/chat online
_________6. Download non-work related information
_________7. Look for employment
_________8. Shop online
_________9. Play online games
_________10. Visit adult oriented (sexually explicit) websites
_________11. Visit online discussion boards or forums
_________12. Visit video sharing sites (Youtube, etc.)
_________13. Visit social networking websites (Facebook, etc.)
_________14. Visit investment or banking websites
_________15. Check non-work related email
_________16. Send non-work related email
_________17. Receive non-work related email
Appendix Ⅲ
- During office hours, how often do you do each of the following though a CELL
PHONE?
1 |
2 |
3 |
4 |
5 |
6 |
Never |
A few times per month |
A few times per week |
Once a day |
A few times a day |
Constantly |
_________1. Read/write nonwork email
_________2. Visit nonjob related websites
_________3. Visit social networking websites (Facebook, etc.)
_________4. Shop online
_________5. Make phone calls
_________6. Send or receive text messages
_________7. Play games
- On a typical workday, how often do you do
1 |
2 |
3 |
4 |
5 |
Never do this |
Less than once a day |
Once or twice a day |
Three to four times a day |
Five or more times a day |
_________1. Take a quick break using a computer
_________2. Take a quick break using a cell phone
_________3. Take a long break using a computer
_________4. Take a long break using a cell phone
Appendix Ⅳ- Self Efficacy to Hide Cyberloafing Scale
The Ability to Hide Cyberloafing (AtHC) refers to how well an employee can hide his or
her computer activity from coworkers and supervisors. Below is the AtHC scale
developed by Askew and his colleagues (Askew, Coovert, Vandello, Ilie, & Tang, 2010).
The scale has shown good reliability and criterion-related validity (Askew, 2010a, Askew
et al., 2010, Askew et al., 2012).
Rate your agreement with the following statements. Please respond to the statements with
respect to your present job.
1 |
2 |
3 |
4 |
5 |
6 |
Disagree very much |
Disagree moderately |
Disagree slightly |
Agree slightly |
Agree moderately |
Agree very much |
______ 1. I COULD pretend to be working on my computer and people would never know.
______ 2. I COULD hide my computer activity if I wanted to.
Appendix Ⅴ – Endicott Work Productivity Scale (EWPS)
This questionnaire is designed to help assess work activities during the past week.
Date __ __/__ __/__ __ Group # _______ Sex: 1 - Male 2 - Female Marital status ____________
Occupation: ____________________________ Education: ____________________________
Do you receive pay or other money for any type of work? 1. No 2. Yes
Do you do volunteer work? 1. No 2. Yes
If you do not receive money for your work and do not do volunteer work, please indicate why you do not:
___ I am physically ill
___ I am too upset, depressed, or nervous
___ I can't find work
___ Other (Please describe)
If you receive money for your work or do volunteer work, please complete the questionnaire, otherwise stop here.
Please describe the characteristics of your work setting by completing the following items:
I am self-employed. |
1. No |
2. Yes |
I work for someone else. |
1. No |
2. Yes |
I have a boss/supervisor. |
1. No |
2. Yes |
I have co-workers with whom I must work. |
1. No |
2. Yes |
I supervise others at work. |
1. No |
2. Yes |
I deal with clients/customers/vendors. |
1. No |
2. Yes |
How many hours do you usually work or would you usually be expected to work?____ hours per week
How many hours did you work last week? _____ hours per week
If you missed time at work last week, please note all the reasons why:
____ I had a day off (Holiday/vacation)
____ I was physically ill
____ Too upset, depressed, or nervous
Other_____________________________
(Please describe)
(PLEASE COMPLETE PAGE 2 OF THE QUESTIONNAIRE)
E W P S
0 |
1 |
2 |
3 |
4 |
Never |
Rarely |
Sometimes |
Often |
Almost Always |
_________1. During the past week, how frequently did you Arrive at work late or leave work early?
_________2. Take longer lunch hours or coffee breaks?
_________3. Just do no work at times when you would be expected to be working?
_________4. Find yourself daydreaming, worrying, or staring into space when you should be working?
_________5. Have to do a job over because you made a mistake or your supervisor told you to do a job over?
_________6. Waste time looking for misplaced supplies, materials, papers, phone numbers, etc.?
_________7. Find you have forgotten to call someone?
_________8. Find you have forgotten to respond to a request?
_________9. Become annoyed with or irritated by coworkers, boss/supervisor, client/customers/ vendors, or others?
_________10. Become impatient with others at work?
_________11. Avoid attending meetings?
_________12. Avoid interaction with coworkers, clients, vendors, or supervisors?
_________13. Have a coworker redo something you had completed?
_________14. Find it difficult to concentrate on the task at hand?
_________15. Fall asleep unexpectedly or become very sleepy while at work?
_________16. Become restless while at work?
_________17. Notice that your productivity for the time spent is lower than expected?
_________18. Notice that your efficiency for the same spent is lower than expected?
_________19. Lose interest or become board with your work?
_________20. Work more slowly or take longer to complete tasks than expected?
_________21. Have your boss/ coworkers remind you to do things?
_________22. Not want to return phone calls or put off returning calls?
_________23. Have trouble organizing work or sitting priorities?
_________24. Fail to finish assigned tasks?
_________25. Feel too exhausted to do your work?