In many areas where we predicted advancement for Aboriginal and Torres Strait Islander people, positive outcomes have indeed been achieved.
The proposed framework highlighted the importance of conceptualizing e-health "use" and "adoption" as dynamic, continuous, longitudinal processes occurring in different stages, influenced by different factors to predict advancement to the next stage.
For the purpose of this paper, we conceptualized different "stages of use" (consideration to use, intention to use, utilization with attrition or continuation, and outcome stage; see description under "Methods"), realizing that in each stage, different factors may play different roles and become less or more important to predict advancement to the next stage.
Sun et al (2001) recently revealed that the effect of HPV infection on SIL development is dominated by the viral load, thus highlighting a potential application of viral load testing in predicting the advancement of cervical intraepithelial lesions.
In addition, a decrease in the use of Nonproductive coping strategies and an increase in the use of Productive ones predicted individuals' advancement toward making a career decision.
The "hot jobs" referenced here are simply defined as the "mission critical roles and highly visible projects" that exist in any given corporation, and importantly, they often predict career advancement.
Depending on whether first or last males sperm precedence is applicable, one may predict an advancement of the mating activity on the population level.
Orwell's genius is not reserved for technological predictions though, as he also correctly predicted future advancements in aesthetics.
Using a three-wave longitudinal design we found that mentoring added value, above and beyond the other forms of career capital, in predicting promotions and advancement expectations.
Rather than the ever-accelerating advancement predicted by Kurzweil, we believe that progress toward this understanding is fundamentally slowed by the complexity brake.
A number of challenges in collaborative model building include definition of data standards, agreement on approval processes, and life-cycle management of the model and knowledge; however, the opportunity lies in the advancements in predicting drug safety and efficacy.
