For this study, 200 students participated and the results are as follows.
Table 2
Individual characteristics of the participants
Variables | Items | Frequency (percentage) of student )n = 200) |
Age | < 20 year | 22(11%) |
20–30 year | 113(56.5%) |
30–40 year | 46(23%) |
> 40 year | 19(9.5%) |
Gender | Male | 126(63%) |
Female | 73(36.5%) |
Missing | 1(0.5%) |
Field of study | Medical Engineering | 70(35%) |
MI | 43(21.5%) |
HIT | 82(97.5%) |
missing | 5(2.5%) |
Degree | BA | 77(38.5%) |
MA | 73(36.5%) |
Professional doctorate | 43(21.5%) |
Missing | 7(3.5%)0 |
Prior field | HIT,HIM,Medical record | 55(27.5%) |
MI | 12(6%) |
C-E-M* | 33(16.5%) |
Work experience | 0 year | 87(43.5%) |
1–5 year | 62(31%) |
5–10 | 24(12%) |
> 10 | 27(13.5% |
Activity | Yes | 123(61.5%) |
No | 70(35%) |
Missing | 7(3.5%) |
Exposure | Yes | 81(40.5%) |
No | 109(54.5%) |
missing | 10(5%) |
*Computer,Electronic,Mathematic
Most students were between 20 and 30 years old. 63% of them were male and 43.5% had no work experience. Current and previous field of study of most of the students were HIT, HIM, and Medical Records. Most of the participants in this study were undergraduates. 61.5% were economically active. 54.5% were exposed to Big Data. The mean scores of participants in benefits, applications, and challenges section were 3.71, 3.68, and 3.71, respectively (saschallenge, sasadvantage and sasapplication). Examination of saschallenge, sasadvantage, and sasapplication by variables of age, gender, field of study, Prior field, work experience, with / without activity, exposure / non-exposure to Big Data can be seen below:
Table 3
Comparison of mean of saschallenge, sasadvantage and sasapplication across different age groups
| n | Mean ± SD(n) |
N | |
Questions | Age |
Advantages | 20 > year | 22 | .6986 ± .11620 |
20–30 year | 113 | .7522±..12519 |
30–40 year | 46 | .7574 ± .12829. |
> 40 year | 19 | .7252±..12159 |
Total | 200 | .7449±..12508 |
Applications | < 20 year | 22 | .6989±..12051 |
20–30 year | 113 | .7413±..13019 |
30–40 year | 46 | .7528 ± .11257. |
> 40 year | 19 | .7147±..12070 |
Total | 200 | .7368±..12462 |
Challenges | < 20 year | 22 | .6869±..15257 |
20–30 year | 113 | .7392±..16566 |
30–40 year | 46 | .7744±..15188 |
> 40 year | 19 | .6982±..18948 |
Total | 200 | .7377±..16466 |
One-way Anova test was used to compare mean of saschallenge, sasadvantage and sasapplication in different age groups with no significant difference in different age groups in these factors. Pvalue was 0.228, 0.317, 0.139 respectively.
Table 4
Comparison of mean of saschallenge, sasadvantage and sasapplication in different gender groups
| | N | Mean ± SD(n) |
Gender | N | |
Advantages | Male | 126 | .7454 ± .11719 |
Female | 73 | .7471 ± .13709 |
Applications | Male | 126 | .7329 ± .13281 |
Female | 73 | .7446 ± .11009 |
Challenges | Male | 126 | .7383 ± .17504 |
Female | 73 | .7370 ± .14741 |
Independent t-test was used to compare the mean of saschallenge, sasadvantage and sasapplication in different gender groups with no significant difference in different age groups in these factors.
Table 5
Comparison of average of saschallenge, sasadvantage, and sasapplication across different fields of study
| n | Mean ± SD(n) |
N | |
| field |
advantages | Medical engineering | 70 | .7302 ± .13611 |
MI | 43 | .7760 ± .12040 |
HIT | 82 | .7488 ± .11194 |
Total | 195 | .7481 ± .12348 |
applications | Medical engineering | 70 | .7236 ± .11333 |
MI | 43 | .7778 ± .13359 |
HIT | 82 | .7337 ± .12527 |
Total | 195 | .7398 ± .12416 |
challenges | Medical engineering | 70 | .7140 ± .15265 |
MI | 43 | .8114 ± .16246 |
HIT | 82 | .7293 ± .16021 |
Total | 195 | .7419 ± .16167 |
One-way Anova test was used to compare the mean of saschallenge, sasadvantage and sasapplication in different fields, but the mean of sasapplication and sasadvantage were not significant.
The mean of saschallenge was significant in different disciplines. The mean of saschallenge in medical informatics was higher than other majors (Fig. 1).
Table 6
Comparison of the mean of saschallenge, sasadvantage, and sasapplication between different levels of study
| n | Mean ± SD(n) |
N | |
| Degree |
Advantages | BSC | 77 | .7270 ± .12249 |
MSC | 73 | .7521 ± .13956 |
PHD | 43 | .7718 ± 08582 |
Total | 193 | .7465 ± .12313 |
Applications | BSC | 77 | .7249 ± .13235 |
MSC | 73 | .7415 ± .12568 |
PHD | 43 | .7602 ± .09684 |
Total | 193 | .7390 ± .12285 |
Challenges | BSC | 77 | .6987 ± .16116 |
MSC | 73 | .7461 ± .17661 |
PHD | 43 | .7953 ± .12388 |
Total | 193 | .7382 ± .16345 |
One-way Anova test was used to compare the mean of saschallenge, sasadvantage, and sasapplication at different levels of study that the mean of sasapplication, sasadvantage, and saschallenge were not significant. Pvalues were 0.142, 0.313, 0.006 respectively.
Table 7
Comparison of the mean of saschallenge, sasadvantage, and sasapplication between previous fields of study
| n | Mean ± SD(n) |
N | |
| Perior field |
Advantages | HIT | 55 | .7678 ± .11516 |
MI | 12 | .7675 ± .06710 |
Engineering,electronic,math | 33 | .7652 ± .16349 |
Total | 100 | .7669 ± .12796 |
Applications | HIT | 55 | .7503 ± .11978 |
MI | 12 | .7893 ± .08649 |
Engineering,electronic,math | 33 | .7548 ± .12074 |
Total | 100 | .7564 ± .11628 |
Challenges | HIT | 55 | .7693 ± .16136 |
MI | 12 | .7889 ± .13283 |
Engineering,electronic,math | 33 | .7946 ± .16150 |
Total | 100 | .7800 ± .15728 |
The one-way Anova test was used to compare the mean of saschallenge, sasadvantage and sasapplication between the previous fields of study, but the mean of sasapplication, sasadvantage and saschallenge were not significant.
Table 8
Comparison of the mean of saschallenge, sasadvantage, and sasapplication between different work experiences
| n | Mean ± SD(n) |
| |
| Work experience |
Advantages | 0 year | 87 | .7459 ± .11910 |
1–5 year | 62 | .7620 ± .13001 |
5–10 | 24 | .7154 ± 14901 |
> 10 | 27 | .7290 ± .10848 |
Total | 200 | .7449 ± .12508 |
Applications | 0 year | 87 | .7426 ± .12193 |
1–5 year | 62 | .7441 ± .13534 |
5–10 | 24 | .7185 ± .10836 |
> 10 | 27 | .7176 ± .12415 |
Total | 200 | .7368 ± .12462 |
Challenges | 0 year | 87 | .7367 ± .16638 |
1–5 year | 62 | .7559 ± .15951 |
5–10 | 24 | .7167 ± .16671 |
> 10 | 27 | .7177 ± .17332 |
Total | 200 | .7377 ± .16466 |
One-way Anova test was used to compare the mean of saschallenge, sasadvantage and sasapplication between different work experiences that the mean of sasapplication, sasadvantage and saschallenge were not significant. Pvalues were 0.404, 0.673, 0.673 respectively.
Table 9
Comparison of the mean of saschallenge, sasadvantage, and sasapplication in groups with / without economic activity
| Activity | N | Mean ± SD(n) |
Advantages | Yes | 123 | .7521 ± .12231. |
No | 70 | .7403 ± .13160. |
Applications | Yes | 123 | .7454 ± .12092. |
No | 70 | .7185 ± .13357. |
Challenges | Yes | 123 | .7478±..17636 |
No | 70 | .7251 ± .14521. |
Independent t-test was used to compare the mean of saschallenge, sasadvantage and sasapplication in the groups with / without economic activity in these factors. Pvalues were 0.532, 0.155, 0.361 respectively.
Table 10
Comparison of the mean of saschallenge, sasadvantage, and sasapplication in groups with / without exposure to Big Data
| | n | Mean ± SD(n) |
Exposure | N | |
Advantages | Yes | 81 | .7619 ± .11752 |
No | 109 | .7359 ± .13009 |
Applications | Yes | 81 | .7561 ± .11112 |
No | 109 | .7239 ± .13370 |
Challenges | Yes | 81 | .7627 ± .15108 |
No | 109 | .7252 ± .16977 |
Independent t-test was used to compare the mean of rasadvantage, saschallenge and sasapplication in the groups with / without exposure to Big Data that there is no significant difference between the groups with / without exposure to Big Data in these factors. Pvalues were 0.157, 0.08, 0.116 respectively.
In order to examine the sasadvantage, saschallenge and sasapplication sub-domains, the previous analyzes of each sub-domain are repeated in terms of variables such as age, gender, field of study, degree, and so on.
Table 11
Comparison of the mean of sasadvantage, saschallenge and sasapplication domains by age
| n | |
N | Mean ± SD(n) |
| Age |
Information | < 20 year | 22 | .7491 ± .14458 |
20–30 year | 113 | .7692 ± .17013 |
30–40 year | 46 | .7843 ± .15966 |
> 40 year | 19 | .7789 ± .12534 |
Total | 200 | .7714 ± .16057 |
Modeling | < 20 year | 22 | .7364 ± .15324 |
20–30 year | 113 | .7611 ± .18425 |
30–40 year | 46 | .7754 ± .18979 |
> 40 year | 19 | .7719 ± .16226 |
Total | 200 | .7627 ± .17954 |
Data | < 20 year | 22 | .6545 ± .14790 |
20–30 year | 113 | .7384 ± .15538 |
30–40 year | 46 | .7252 ± .14910 |
> 40 year | 19 | .7137 ± .17802 |
Total | 200 | .7238 ± .15637 |
Process_Managment | < 20 year | 22 | .6742 ± .17516 |
20–30 year | 113 | .7451 ± .14399 |
30–40 year | 46 | .7529 ± .14633 |
> 40 year | 19 | .6667 ± .20458 |
Total | 200 | .7317 ± .15655 |
Health_Sevice_Delivery | < 20 year | 22 | .6786 ± .13032 |
20–30 year | 113 | .7358 ± .14164 |
30–40 year | 46 | .7453 ± .11181 |
> 40 year | 19 | .7009 ± .11773 |
Total | 200 | .7284 ± .13269 |
Research | < 20 year | 22 | .6909 ± 19557 |
20–30 year | 113 | .7996 ± 19451 |
30–40 year | 46 | .8087 ± .20718 |
> 40 year | 19 | .7421 ± .20430 |
Total | 200 | .7843 ± .20054 |
Health_Information | < 20 year | 22 | .7182 ± .13040 |
20–30 year | 113 | .7357 ± .15005 |
30–40 year | 46 | .7405 ± .13875 |
> 40 year | 19 | .7092 ± .16398 |
Total | 200 | .7324 ± .14611 |
Essential_Medicines | < 20 year | 22 | .6982 ± .11377 |
20–30 year | 113 | .7371 ± .15626 |
30–40 year | 46 | .7591 ± .13224 |
> 40 year | 19 | .7039 ± .13988 |
Total | 200 | .7347 ± .14565 |
Health_Financing | < 20 year | 22 | .7091 ± .24477 |
20–30 year | 113 | .7469 ± .21384 |
30–40 year | 46 | .7478 ± .20842 |
> 40 year | 19 | .7789 ± .22992 |
Total | 200 | .7460 ± .21661 |
Leadership_Governance | < 20 year | 22 | .7106 ± .13584 |
20–30 year | 113 | .7428 ± .16770 |
30–40 year | 46 | .7551 ± .16810 |
> 40 year | 19 | .7667 ± .14741 |
Total | 200 | .7443 ± .16227 |
One-way Anova test was used to compare the mean of sasadvantage, saschallenge and sasapplication domains by age groups that process management became significant. Pvalues were 0.855, 0.861, 0.145, 0.046, 0.172, 0.072, 0.831, 0.315, 0.784, 0.680, respectively.
Table 12
Mean comparison of sasadvantage, saschallenge and sasapplication domains by gender
| | n | Mean ± SD(n) |
Gender | N | |
Information | Male | 126 | .7679 ± .15380 |
Female | 73 | .7759 ± .17317 |
Modeling | Male | 126 | .7566 ± .17391 |
Female | 73 | .7735 ± .19076 |
Data | Male | 126 | .7168 ± .15714 |
Female | 73 | .7370 ± .15605 |
process_managment | Male | 126 | .7447 ± .14168 |
Female | 73 | .7183 ± .16207 |
health_sevice_delivery | Male | 126 | .7252 ± .13799 |
Female | 73 | .7357 ± .12353 |
Research | Male | 126 | .7794 ± .21441 |
Female | 73 | .7932 ± .17664 |
Health_information | Male | 126 | .7268 ± .15116 |
Female | 73 | .7426 ± .13836 |
Essential_medicines | Male | 126 | .7328 ± .15952 |
Female | 73 | .7394 ± .15952 |
Health_financing | Male | 126 | .7317 ± .22650 |
Female | 73 | .7699 ± .19908 |
Leadership_governance | Male | 126 | .7405 ± .16874 |
Female | 73 | .7516 ± .15245 |
Independent t-test was used to compare the mean of sasadvantage, saschallenge and sasapplication in gender groups with no significant difference in gender in these factors. Pvalues were 0.738, 0.525, 0.383, 0.230, 0.592, 0.642, 0.463, 0.761, 0.234, respectively.
Table 13
Mean comparison of sasadvantage, saschallenge and sasapplication domains by different fields of study
| n | Mean ± SD(n) |
N | |
| Field of study |
Information | Medical engineering | 70 | .7354 ± .18137 |
MI | 43 | .8242 ± .14688 |
HIT | 82 | .7780 ± .14113 |
Total | 195 | .7729 ± .16058 |
Modeling | Medical engineering | 70 | .7238 ± .20968 |
MI | 43 | .8124 ± .15753 |
HIT | 82 | .7715 ± .15539 |
Total | 195 | .7634 ± .17949 |
Data | Medical engineering | 70 | .7211 ± .15692 |
MI | 43 | .7433 ± .13972 |
HIT | 82 | .7224 ± .16066 |
Total | 195 | .7266 ± .15441 |
Process_Managment | Medical engineering | 70 | .7367 ± .15739 |
MI | 43 | .7450 ± .15514 |
HIT | 82 | .7350 ± .13465 |
Total | 195 | .7378 ± .14699 |
Health_Sevice_Delivery | Medical engineering | 70 | .7227 ± .12854 |
MI | 43 | .7502 ± .13100 |
HIT | 82 | .7261 ± .13873 |
Total | 195 | .7302 ± .13320 |
Research | Medical engineering | 70 | .7321 ± .17796 |
MI | 43 | .8802 ± .16873 |
HIT | 82 | .7854 ± .21907 |
Total | 195 | .7872 ± .20119 |
Health_Information | Medical engineering | 70 | .7212 ± .13062 |
MI | 43 | .7887 ± .14366 |
HIT | 82 | .7216 ± .14812 |
Total | 195 | .7363 ± .14310 |
Essential_Medicines | Medical engineering | 70 | .7181 ± .13169 |
MI | 43 | .7758 ± .14452 |
HIT | 82 | .7379 ± .15266 |
Total | 195 | .7391 ± .14449 |
Health_Financing | Medical engineering | 70 | .7457 ± 19537 |
MI | 43 | .7349 ± .22560 |
HIT | 82 | .7512 ± .22566 |
Total | 195 | .7456 ± .21423 |
Leadership_Governance | Medical engineering | 70 | .7367 ± .14625 |
MI | 43 | .7713 ± .19032 |
HIT | 82 | .7394±..16188 |
Total | 195 | .7455 ± .16304 |
One-way Anova test was used to compare the mean of sasadvantage, saschallenge, and sasapplication domains by field of study, that the mean of sasadvantage, saschallenge, and saschallenge in information, modeling, research, and health informatics were significant. Pvalues were 0.015, 0.033, 0.726, 0.935, 0.532, 0.001, 0.024, 0.119, 0.922 and 0.500 respectively (Fig. 2 and Fig. 3).
Table 14
Mean comparison of sasadvantage, saschallenge and sasapplication domains by different levels of study
| n | Mean ± SD(n) |
N | |
Information | BSC | 77 | .7356 ± .17902 |
MSC | 73 | .7863 ± .15581 |
PHD | 43 | .8047 ± .12443 |
Total | 193 | .7702 ± .16131 |
Modeling | BSC | 77 | .7359 ± .18589 |
MSC | 73 | .7553 ± .19470 |
PHD | 43 | .8155 ± 13161 |
Total | 193 | .7610 ± 18059 |
Data | BSC | 77 | .7122 ± .16066 |
MSC | 73 | .7332 ± .16547 |
PHD | 43 | .7386 ± .11787 |
Total | 193 | .7260 ± .15380 |
Process_Managment | BSC | 77 | .7277 ± .13050 |
MSC | 73 | .7379 ± .18116 |
PHD | 43 | .7504 ± .10193 |
Total | 193 | .7366 ± .14627 |
Health_Sevice_Delivery | BSC | 77 | .7178 ± .13130 |
MSC | 73 | .7289 ± .14290 |
PHD | 43 | .7505 ± .10839 |
Total | 193 | .7293 ± .13117 |
Research | BSC | 77 | .7487 ± .20822 |
MSC | 73 | .7849 ± .21192 |
PHD | 43 | .8558 ± .14809 |
Total | 193 | .7863 ± .20112 |
Health_Information | BSC | 77 | .7237 ± .15430 |
MSC | 73 | .7408 ± 14471 |
PHD | 43 | .7462 ± .12148 |
Total | 193 | .7352 ± .14352 |
Essential_Medicines | BSC | 77 | .7186 ± .15838 |
MSC | 73 | .7450 ± .14472 |
PHD | 43 | .7606 ± .11002 |
Total | 193 | .7380 ± .14393 |
Health_Financing | BSC | 77 | .7377 ± .22771 |
MSC | 73 | .7479 ± .22367 |
PHD | 43 | .7581 ± .17759 |
Total | 193 | .7461 ± .21505 |
Leadership_Governance | BSC | 77 | .7455 ± .15284 |
MSC | 73 | .7406 ± .17080 |
PHD | 43 | .7605 ± .15106 |
Total | 193 | .7470 ± .15886 |
Table 15
Mean comparison of sasadvantage, saschallenge and sasapplication domains by different previous fields of study
| n | Mean ± SD(n) |
N | |
Information | HIT | 55 | .8196 ± .12290 |
MI | 12 | .8033 ± .13694 |
C-E-M | 33 | .7600 ± .19183 |
Total | 100 | .7980 ± .15153 |
Modeling | HIT | 55 | .7782 ± .16079 |
MI | 12 | .8444 ± .12818 |
C-E-M | 33 | .7980 ± .19825 |
Total | 100 | .7927 ± .17053 |
Data | HIT | 55 | .7484 ± .13612 |
MI | 12 | .7133 ± .12630 |
C-E-M | 33 | .7442 ± .18599 |
Total | 100 | .7428 ± .15226 |
Process_Managment | HIT | 55 | .7358 ± .15567 |
MI | 12 | .7444 ± .10856 |
C-E-M | 33 | .7707 ± .18004 |
Total | 100 | .7483 ± .15894 |
Health_Sevice_Delivery | HIT | 55 | .7435 ± .12499 |
MI | 12 | .7578 ± .11098 |
C-E-M | 33 | .7390 ± .15264 |
Total | 100 | .7438 ± .13211 |
Research | HIT | 55 | .8091 ± .21860 |
MI | 12 | .9333 ± .07177 |
C-E-M | 33 | .8167 ± .16802 |
Total | 100 | .8265 ± .19325 |
Health_Information | HIT | 55 | .7389 ± .14249 |
MI | 12 | .7885 ± .10091 |
C-E-M | 33 | .7583 ± .14340 |
Total | 100 | .7512 ± .13829 |
Essential_Medicines | HIT | 55 | .7556 ± .13039 |
MI | 12 | .7978 ± .10511 |
C-E-M | 33 | .7503 ± .13676 |
Total | 100 | .7589 ± .12946 |
Health_Financing | HIT | 55 | .7964 ± .19048 |
MI | 12 | .7333 ± .19695 |
C-E-M | 33 | .7455 ± .23061 |
Total | 100 | .7720 ± .20503 |
Leadership_Governance | HIT | 55 | .7394 ± .16840 |
MI | 12 | .7722 ± .11962 |
C-E-M | 33 | .7616 ± .18373 |
Total | 100 | .7507 ± .16774 |
One-way Anova test was used to compare the mean of sasadvantage, saschallenge and sasapplication domains by different previous fields of study that the mean of sasadvantage, saschallenge and sasapplication was not significant. Pvalues were 0.202, 0.469, 0.772, 0.610, 0.916, 0.122, 0.501, 0.537, 0.420 and 0.749 respectively.
Table 16
Mean comparison of sasadvantage, saschallenge and sasapplication domains by experience
| n | Mean ± SD(n) |
N | |
| Workexperience |
Information | 0 year | 87 | .7674 ± .15341 |
1–5 year | 62 | .7923 ± .17650 |
5–10 year | 24 | .7283 ± .15999 |
> 10 year | 27 | .7748 ± .14471 |
Total | 200 | .7714 ± .16057 |
Modeling | 0 year | 87 | .7678 ± .16824 |
1–5 year | 62 | .7785 ± .18098 |
5–10 year | 24 | .6944 ± .23003 |
> 10 year | 27 | .7704 ± .15616 |
Total | 200 | .7627 ± .17954 |
Data | 0 year | 87 | .7223 ± .15424 |
1–5 year | 62 | .7497 ± .14771 |
5–10 year | 24 | .6917 ± .18062 |
> 10 year | 27 | .6978 ± .15858 |
Total | 200 | .7238 ± .15637 |
Process_managment | 0 year | 87 | .7368 ± .15668 |
1–5 year | 62 | .7387 ± .14897 |
5–10 year | 24 | .7347 ± .14955 |
> 10 year | 27 | .6963 ± .18171 |
Total | 200 | .7317 ± .15655 |
Health_sevice_delivery | 0 year | 87 | .7348 ± .14072 |
1–5 year | 62 | .7454 ± .13775 |
5–10 year | 24 | .7049 ± .11289 |
> 10 year | 27 | .6893 ± .10273 |
Total | 200 | .7284 ± .13269 |
Research | 0 year | 87 | .7810 ± .19681 |
1–5 year | 62 | .8081 ± .19210 |
5–10 year | 24 | .7437 ± .22904 |
> 10 year | 27 | .7759 ± .20911 |
Total | 200 | .7843 ± .20054 |
Health_information | 0 year | 87 | .7385 ± .14954 |
1–5 year | 62 | .7403 ± .14303 |
5–10 year | 24 | .7156 ± .13054 |
> 10 year | 27 | .7093 ± .15893 |
Total | 200 | .7324 ± .14611 |
Essential_medicines | 0 year | 87 | .7352 ± .14816 |
1–5 year | 62 | .7452 ± .14842 |
5–10 year | 24 | .7206 ± .13025 |
> 10 year | 27 | .7220 ± .14984 |
Total | 200 | .7347 ± .14565 |
Health_financing | 0 year | 87 | .7770 ± .19630 |
1–5 year | 62 | .6968 ± .22830 |
5–10 year | 24 | .7583 ± .26361 |
> 10 year | 27 | .7481 ± .19684 |
Total | 200 | .7460 ± .21661 |
Leadership_governance | 0 year | 87 | .7625 ± .13826 |
1–5 year | 62 | .7129 ± .18782 |
5–10 year | 24 | .7361 ± .16794 |
> 10 year | 27 | .7654 ± .16316 |
Total | 200 | .7443 ± .16227 |
One-way Anova test was used to compare the mean of sasadvantage, saschallenge and sasapplication domains by experience that the mean of sasapplication, sasadvantage, and saschallenge were not significant. Pvalues were 0.419, 0.255, 0.327, 0.661, 0.231, 0.592, 0.725, 0.863, 0.167, 0.270 respectively.
Table 17
Mean comparison of sasadvantage, saschallenge and sasapplication domains by economical activity
| Activity | N | Mean ± SD(n) |
Information | yes | 123 | .7776 ± .16034 |
no | 70 | .7657 ± .16447 |
Modeling | yes | 123 | .7691 ± .17850 |
no | 70 | .7533 ± .18970 |
Data | yes | 123 | .7389 ± .15444 |
no | 70 | .7091 ± .15941 |
Process_managment | yes | 123 | .7333 ± .15611 |
no | 70 | .7386 ± .14319 |
Health_sevice_delivery | yes | 123 | .7296 ± .13578 |
no | 70 | .7217 ± .13088 |
Research | yes | 123 | .8089 ± .19110 |
no | 70 | .7364 ± .21752 |
Health_information | yes | 123 | .7419 ± .14312 |
no | 70 | .7112 ± .15432 |
Essential_medicines | yes | 123 | .7457 ± .13364 |
no | 70 | .7168 ± .16645 |
Health_financing | yes | 123 | .7463 ± .22914 |
no | 70 | .7314 ± .19821 |
Leadership_governance | yes | 123 | .7561 ± .15770 |
no | 70 | .7195 ± .17450 |
Independent t-test was used to compare the mean of sasadvantage, saschallenge and sasapplication by economical activity that there was a significant difference in different groups in research. Pvalues were 0.625, 0.565, 0.205, 0.693, 0.818, 0.017, 0.167, 0.761, 0.188, 0.649 and 0.133. respectively.
Table 18
Mean comparison of sasadvantage, saschallenge and sasapplication domains by exposure / non-exposure to Big Data
| Exposure | N | Mean ± SD(n) |
Information | yes | 81 | .7970 ± .14571 |
no | 109 | .7545 ± .16905 |
Modeling | yes | 81 | .7835 ± .17177 |
no | 109 | .7468 ± .18851 |
Data | yes | 81 | .7358 ± .15135 |
no | 109 | .7196 ± .16271 |
Process_managment | yes | 81 | .7436 ± .15755 |
no | 109 | .7284 ± .14613 |
Health_sevice_delivery | yes | 81 | .7413 ± .13150 |
no | 109 | .7182 ± .13423 |
Research | yes | 81 | .8142 ± .19577 |
no | 109 | .7624 ± .20940 |
Health_information | yes | 81 | .7475 ± .13899 |
no | 109 | .7218 ± .15380 |
Essential_medicines | yes | 81 | .7567 ± .12935 |
no | 109 | .7231 ± .15477 |
Health_financing | yes | 81 | .7704 ± .20028 |
no | 109 | .7248 ± .23060 |
Leadership_governance | yes | 81 | .7778 ± .15330 |
no | 109 | .7217 ± .16957 |
Independent t-test was used to compare the mean sasadvantage, saschallenge and sasapplication by exposure / non-exposure to the Big Data that there was a significant difference in groups in information. Pvalues were 0.071, 0.169,0.486, 0.085, 0.494, 0.236, 0.114, 0.156, 0.020, 0.761, 0.188, 0.649, 0.133 respectively. The mean of sasinformation was higher among those exposed to the Big Data than those not exposed to the Big Data.