At the time of protocol development, the reviewers should provide some plan for the presentation of results – for example, a draft chart, figure or table (Lockwood et al. 2019). It is recommended that the authors do plan carefully how they intend to present the data extracted from the sources of evidence. Planning at this stage is very useful for an initial sense of what sorts of data might be identified and how best to present that data in relation to the scoping review’s objective and question/s. This may be further refined during the review process as the reviewers increase their awareness and consideration of the contents of all of their included sources.
The ultimate purpose of charting the data is to identify, characterize, and summarize research evidence on a topic, including identification of research gaps (Nyanchoka et al. 2019).The results of a scoping review may be presented as a map of the data extracted from the included papers in a diagrammatic or tabular form, and/or in a descriptive format that aligns with the objective/s and scope of the review. The elements of the PCC inclusion criteria may be useful to guide how the data should be mapped most appropriately. In the scoping review example described above, because the objective was to map quality of life questionnaires used for pediatric patients following tonsillectomies with or without adenoidectomies for chronic infection or sleep-disordered breathing, the data may be usefully mapped by a tabular presentation of how the different components of the PCC includes as shown below. Other examples of presenting data from a scoping review can be found below (Table 11.3).
Table 11.3: Example tabular presentation of data for a scoping review
Numbers of publications
Types of studies
Quality of life domains
Format/ number of items
The tables and charts may also show results as: distribution of sources of evidence by year or period of publication (depends on each case), countries of origin, area of intervention (clinical, policy, educational, etc.) and research methods. A descriptive summary should accompany the tabulated and/or charted results and should describe how the results relate to the review objective/s and question/s.
The results can also be classified under main conceptual categories, such as: “intervention type”, “population” (and sample size, if it is the case), “duration of intervention”, “aims”, “methodology adopted”, “key findings” (evidence established), and “gaps in the research”. For each category reported, a clear explanation should be provided.
The examples below show various formats of charting the evidence depending on the scoping review question. In the first example (Figure 11.1), the authors aimed to clarify if intense sweeteners are effective tools to lower sugar consumption and maintain a healthy weight or, on the contrary, if these compounds promote weight gain (Mosdøl et al. 2018). This will result in identifying gaps where new systematic reviews or primary research are needed, including which hypotheses, types of intense sweeteners and outcomes that need further assessment.
In the second example (Figure 11.2), the authors were interested to map the types of family involvements in intensive care units and identify their level of involvement from passive to active (Olding et al. 2016. In this case, the authors used conventional content analysis to develop codes inductively through immersion with the text, deriving codes from the data itself rather than coding with preconceived categories.
In the third example (Figure 11.3), the authors used relational analysis to present their results. With this technique, all data from eligible sources were used to identify examples of an Integrated Knowledge Translation (IKT) approach or strategy, enabler, barrier, and outcome. This approach allowed gaps in the IKT literature to be identified (Gagliardi et al. 2015). These data were added to the IKT approaches or strategies, enablers, barriers, and outcomes identified in sources referenced in the background of this manuscript and then compiled in a summary of IKT conditions, influencing factors, and outcomes. This approach made clear what was known and not known about IKT interventions. To further understand knowledge gaps, the authors identified relationships between the characteristics of IKT strategies, contextual factors, and outcomes by categorizing IKT as used in eligible sources of evidence.
The fourth example (Figure 11.4) is derived from a scoping review by Pham et al. 2014. The authors provided an example of a bubble chart for results presentation. This method is frequently used in the engineering sector but could also be employed in many other disciplines. The size of each ‘bubble’ is representative of the number of sources of evidence published in each year.
Figure 11.1: Example of data presentation (artificial sweeteners and weight loss/ gain). (Mosdøl et al. 2018)
Figure 11:2: Example of data presentation (types of family involvements in intensive care units and level of involvement from passive to active). (Olding et al. 2016)
Figure 11.3: Example of data presentation (IKT approaches or strategies, enablers, barriers, and outcomes). (Gagliardi et al. 2015)
Figure 11:4: Example of data presentation (sources of evidence published by year) (Pham et al 2014)