DISCUSSION

An examination of Table 1 shows that there are 3 factors underlying the 16 drivers for ICT adoption. The data also shows that the highest priority given by the respondent GPs was to those drivers that loaded onto the medical and business efficiency factor (eigenvalue 7.567, % variance accounted for 47.295). An examination of Table 2 shows that 8 of the 16 drivers loaded onto the improved medical and business efficiency and effectiveness factor; 5 drivers loaded onto the pressure factor

Figure 5. Partial Least Squares Model of Drivers and Benefits (Females)

0.689* (1.65)

Drivers	Benefits
Improved Efficiency and Effectiveness
Improved Effectiveness
(1.064
0057
0.064	0.22-1
Improved Communications
0.287
Improved Efficiency
Improved Communications
*p<0.05

and 3 drivers loaded onto the improved commu­nications factor.

The first result of significance can be seen by comparing Tables 1 and 3. In Table 1 we see that contrary to the literature, when GPs were asked to consider drivers for ICT adoption they grouped improvement to efficiency and improvement to effectiveness together as a single group. However, when they were asked to consider the benefits of ICT adoption, improved efficiency and improved effectiveness were considered to be 2 unique and uncorrelated groups.

An examination of Table 3 shows, again, that there are 3 factors underlying the 17 benefits derived from ICT adoption. The data shows that respondents considered the most important ben­efits were those that loaded onto the improvement to communication factor (eigenvalue 9.335, % variance accounted for 54.912). An examination of Table 4 shows that there are 5 benefits loaded onto the communications factor, 5 benefits loaded onto the efficiency factor and 7 benefits loaded onto the effectiveness factor.

As indicated, a simple model (see Figure 3) was developed using the combined male and female data such that it provided for all possible associations between driving forces and benefits. This model was tested using male and female data to determine which associations were significant.

An examination of Figure 4 shows that male GPs who placed greater importance on improve­ment to efficiency and effectiveness through

ICT adoption, saw, as benefits, improvement to effectiveness (Beta = 1.296, t = 2.31), improve­ment to communications (Beta =.973, t = 1.79) and improvement to efficiency (Beta = 1.218, t = 2.50). The data showed that those that placed a greater importance on improvement to com­munications saw no significant difference in any of the three groups of benefits. It is interesting to note that those male respondents that felt
their primary reason for ICT adoption was the pressure placed upon them to adopt ICTs saw a negative ‘benefit’ (denoted by the negative Beta values -.697, -.726 and -.678 respectively). These results support similar findings in the small busi­ness community (MacGregor & Vrazalic 2007) and while not significant, suggest that pressure from governments, medical authorities or other medical practitioners appears to lead to a loss of efficiency, effectiveness and communications within the practice.

An examination of Figure 5 shows that fe­male GPs who placed a greater importance on improvement to effectiveness and efficiency saw no significant difference in and of the three groups ofbenefits. As with their male counterparts, female GPs who placed a greater importance on improvement to communications saw no sig­nificant difference in any of the three groups of benefits. Perhaps most surprising was the result for pressure to adopt ICTs. Unlike their male counterparts, female GPs reacted ‘positively’ to pressure being placed on them to adopt ICT in their practices. The results show that female GPs who placed greater importance on having adopted ICTs through pressure, saw, as benefits, improvement to effectiveness (Beta =.689, t = 1.65), improvement to communications (Beta =.703, t = 1.70) and improvement to efficiency (Beta =.793, t = 2.01).

There are a number of possibilities to explain the marked differences between the results in Fig­ures 4 and 5. One possibility is that those female GP respondents who placed greater emphasis on improvement to communications or improve­ment to effectiveness and efficiency expected far greater changes in their day-to-day activities than was forthcoming from the introduction of ICT. In other words, male GP respondents were far easier pleased with the changes brought about by ICT adoption (particularly if that adoption had been at their instigation) than were female GPs. If this was the case, only those female GPs who had been pressured, and presumably expected little positive outcome from the adoption, would have seen positive changes to their day-to-day activities.

An alternative explanation to the findings might be that male GPs tend to be more independent in their choices oftechnology than female GPs. Thus, males under pressure to adopt ICT would react negatively, compared to female GPs. It is interest­ing to note that a European study, comparing male and female GPs (Boerma & van den Brink-Muinen 2000) found that female GPs had less technology than males and that they undertook fewer technical procedures than their male counterparts. On the surface, the current study would tend to support those earlier findings.

The results of this study are significant in several ways. The analysis has shown that 16 of the most common driving forces to ICT adoption and 17 of the most common benefits can each be grouped in relation to 3 factors each. This gives researchers a powerful explanatory tool because it reduces the “noise” in the data. Instead of ac­counting for 16 drivers or 17 benefits, adoption can be explained in terms of3 factors. The Rotated Component Matrices also enable the prediction of the scores of each individual driver or benefit based on the score of the 3 factors. Whereas before researchers identified various drivers or benefits, this study shows that they are logically correlated to 3 factors. This makes it simpler not only to explain, but also predict ICT adoption in general practice.

Secondly, the results show that emphasis on certain driving forces for ICT adoption produces different perceived benefits, these differing mark­edly between male GPs and female GPs. While male GPs who emphasised improvement to ef­ficiency and effectiveness as the most important reason for adopting ICT perceived a significant improvement in all three groups of benefits, this was not the case for female GPs. Similarly as male GPs saw an erosion ofbenefits when adopting ICT under pressure, female GPs perceived a significant improvement in the perception of benefits.

Limitations of the Study

It should be noted that this study has several limi­tations. The data for the study was collected from several areas in Australia. Therefore, although conclusions can be drawn, the results may not be generalisable to other countries. Also, this is a quantitative study, and further qualitative research is required to gain a better understanding of the key issues.

CONCLUSION

The results show that ICT drivers and benefits can be grouped simplifying explanation. The results show that as GPs appear to separate effectiveness and efficiency in terms of benefits, they do not separate them as drivers for ICT adoption are concerned. The study has also shown that there is a significant and important link between driving forces for ICT adoption and perceived benefits of that adoption.

The results also show that there are differences between male and female GPs where it comes to ICT adoption and use. Clearly further studies need to be undertaken to determine why these differences do occur and to determine measures to minimise the effect of these differences.

Gender and Computing in
Cyberspace