Reduced Coping Strategy Index (rCSI)

Impact

mean and median of the Reduced Coping Strategies Index (rCSI)

The Reduced Coping Strategies Index (rCSI) is a proxy indicator of household food insecurity. It considers both the frequency and severity of five pre-selected coping strategies that the household used in the seven days prior to the survey. It is a simplified version of the full Coping Strategies Index indicator.

Determine the indicator's value by using the following methodology:

 

1) Conduct individual interviews with a representative sample of the target group members, asking them how many days in the previous 7 days they had to use the coping strategies listed below. Use the questions provided in the left column below. Record the frequency by entering the relevant number (e.g. 0 – did not have to use the coping strategy; 2 – had to use it two days; 7 – had to use it every day in the past 7 days).

 

2) During the data analysis, for each coping strategy, multiply the ‘frequency’ by the assigned ‘severity weight’, thereby getting a ‘weighted score’ per each strategy.

 

3) Add up the scores of all assessed strategies to receive the household’s rCSI score. A high score means an extensive use of negative coping strategies and hence increased food insecurity (the maximum score for the rCSI is 56; this would happen if a household used all five strategies every day for the last 7 days).

 

4) To calculate the indicator’s values:

• to calculate the mean value of rCSI, add the rCSI scores of all the surveyed households and divide this by the total number of surveyed households

• to calculate the median value of rCSI, arrange all household rCSI scores in ascending order and identify the middle value (or average the two middle values if there is an even number of households)

Disaggregate the data by wealth, location and other vulnerability criteria.

1) rCSI is prone to significant seasonal differences. Do your best to collect baseline and endline data at the same time of a year; otherwise, it is very likely that they will not be comparable.

 

2) It is recommended to calculate both the mean and the median because they show different things about the data. The mean is the average of all values but can be affected by very high or very low numbers. The median is the middle value and is not affected by extreme values. When both are shown, it helps to understand if most people’s situations are typical or if some extreme cases are changing the average. This makes it easier to get a clearer picture of the overall situation.