Where and how to find data on safety: what do systematic reviews of complementary therapies tell us?

Background: Successfully identifying relevant data for systematic reviews with a focus on safety may require retrieving information from a wider range of sources than for ‘effectiveness’ systematic reviews. Searching for safety data continues to prove a major challenge. Objectives: To examine search methods used in systematic reviews of safety and to investigate indexing. Methods: Systematic reviews focusing on safety of complementary therapies and related interventions were retrieved from comprehensive searches of major databases. Data was extracted on search strategies, sources used and indexing in major databases. Safety related search terms were compared against index terms available on major databases. Data extraction by one researcher using a pre-prepared template was checked for accuracy by a second researcher. Results: Screening of 2563 records resulted in 88 systematic reviews being identified. Information sources used varied with the type of intervention being addressed. Comparison of search terms with available index terms revealed additional potentially relevant terms that could be used in constructing search strategies. Seventy-nine reviews were indexed on PubMed, 84 on EMBASE, 21 on CINAHL, 15 on AMED, 6 on PsycINFO, 2 on BNI and HMIC. The mean number of generic safety-related indexing terms on PubMed records was 2.6. For EMBASE the mean number was 4.8 with at least 61 unique terms being employed. Most frequently used indexing terms and subheadings were adverse effects, side effects, drug interactions and herb-drug interactions. Use of terms specifically referring to safety varied across databases. Conclusions: Investigation of search methods revealed the range of information sources used, a list of which may prove a valuable resource for those planning to conduct systematic reviews of safety. The findings also indicated that there is potential to improve safety-related search strategies. Finally, an insight is provided into indexing of and most effective terms for finding safety studies on major databases.

Uses of agent-based modeling for health communication: the TELL ME case study

Government communication is an important management tool during a public health crisis, but understanding its impact is difficult. Strategies may be adjusted in reaction to developments on the ground and it is challenging to evaluate the impact of communication separately from other crisis management activities. Agent-based modeling is a well-established research tool in social science to respond to similar challenges. However, there have been few such models in public health. We use the example of the TELL ME agent-based model to consider ways in which a non-predictive policy model can assist policy makers. This model concerns individuals’ protective behaviors in response to an epidemic, and the communication that influences such behavior. Drawing on findings from stakeholder workshops and the results of the model itself, we suggest such a model can be useful: (i) as a teaching tool, (ii) to test theory, and (iii) to inform data collection. We also plot a path for development of similar models that could assist with communication planning for epidemics.