Each intervention is represented by a circle; the size of the circle is proportional to the number of participants undertaking that intervention.
In a treatment simulation, an intervention is represented through higher probabilities of preventing this binding taking place.
That is, the intervention is represented by the actual dose received (number of home visits and case conferences).
In a control simulation the lack of intervention is represented with an efficacy of 0% (i.e., with zero probability of peptide‐to‐MHC binding prevention).
The effect of the intervention is represented in the model by T I - T C, which is the difference between study group means at follow-up adjusted for baseline differences.
Prevention sciences encompassing etiology, epidemiology and intervention are represented through peer-reviewed original research articles on a variety of health and social problems, including but not limited to substance abuse, mental health, HIV/AIDS, violence, accidents, teenage pregnancy, suicide, delinquency, STD's, obesity, diet/nutrition, exercise, and chronic illness.
All of our target groups for the future communications intervention were represented in this list: researchers, program managers, policymakers, donors, advocates, and other public figures.
Within the Harvest Plot, each intervention was represented as a single bar in one of three categories: those that were more effective in more disadvantaged groups (reduce), had the same effect in all groups (no preferential impact by SEP), or were less effective in disadvantaged groups (widen).
29 The months preceding and following the intervention were represented by a five-level term: (1) the 2 months preceding the change (August September, 'pre-plain packs (PP)'); (2) the 2 months of 'phase-in' (October November); (3) the 2 months 'immediate post-PP' (December January); (4) '3–4 months post-PP' (February March); and (5) '5–6 months post-PP' (April-May).
Note that the first of these two interventions is represented through states in our multi-state model in Fig. 1, while the latter is represented as an additional covariate as shown in Table 2.
An interesting target population for preconception preventative interventions is represented by women of childbearing age who are engaged on the web: a large proportion of this group of women frequently search for health information online [ 11].
