Table 2

Example data extraction items

Examples of data extraction items
Study characteristicsAuthor name; year of publication; rationale for using an ITS design; type and description of the intervention.
DesignTime interval (eg, monthly); total number of observations; total number of time intervals and number of segments; number of time intervals per segment; average number of observations per time interval; and whether there is a comparison group.
OutcomeDescription (eg, vehicle occupant injury) and classification (eg, count) of the outcome at the individual observation level; description of the aggregate level outcome (eg, rate per population of motor vehicle occupant injuries).
ModelModel shape (eg, level change or slope change, or both, and whether this shape is prespecified or not); number of segments; model type (eg, autoregressive integrated moving average (ARIMA), segmented regression, other regression, pre–post); modelling approach for any transition period; and, if there was a comparison group, how it was incorporated in the analysis.
Statistical methodsStatistical estimation method (eg, logistic, Poisson, overdispersed Poisson, generalised estimating equation (GEE); whether autocorrelation, seasonality and outliers were investigated; and, how they were handled in the analysis; whether and how non-stationarity was tested for.
Effect measuresReported effect measures (eg, change in level, change in slope); whether an absolute or relative measure; effect estimates and statistics associated with the effect measure (eg, p values, CIs); details on any forecasting (eg, projecting from one segment to a specified time point in another segment) and whether there was mention of any ceiling or floor effects.
  • ITS, interrupted time series.