Article type
Year
Abstract
Background:
Public health interventions include organized measures to prevent disease, promote health, and prolong life among the population as a whole. Public health interventions are usually prefixed with the word 'complex'. The innate characteristics of these interventions to cater to an outstretched population, encompass a bundle of activities, and contextual confinement entrusts complexity.
Objective:
To develop a mechanism to quantify complexity and classify the studies based on their complexity status.
Methodology:
We developed a tool to measure complexity in public health interventions consisting of four domains. We derived items of the tool from three different sources:
1) theories deduced from qualitative study;
2) meticulous examination of published public health interventions; and
3) expert opinion.
The tool was validated by collecting the feedback from seven public health experts. The tool provides four domain-specific complexity scores (obtained by adding scores of all items of the domain) and one total complexity score (obtained by adding four domain-specific complexity scores). As the number of items in each of the four domains is not same, it is important to take into account the relative contribution of domains towards the total complexity score for ranking the studies according to their complexity status. This was achieved by the method of composite dynamic index which is a weighted linear combination of complexity scores of four domains, where the weightage for each domain is assigned inversely proportional to standard deviation of its values. Further beta distribution was fitted to the developed composite index and studies were classified into four classes of complexity namely very highly complex, highly complex, moderately complex and least complex for the purpose of interpretation of complexity score. We applied the tool to assess the complexity of 259 studies collected from 30 public health systematic reviews, constructed a composite dynamic index, and classified studies into four classes of complexity.
Results:
The tool consists of four domains, namely, population, intervention, context and outcome. The context domain received the least weightage in the composite dynamic index, indicating that it is most variable than other domains
Patient or healthcare consumer involvement:
None.
Public health interventions include organized measures to prevent disease, promote health, and prolong life among the population as a whole. Public health interventions are usually prefixed with the word 'complex'. The innate characteristics of these interventions to cater to an outstretched population, encompass a bundle of activities, and contextual confinement entrusts complexity.
Objective:
To develop a mechanism to quantify complexity and classify the studies based on their complexity status.
Methodology:
We developed a tool to measure complexity in public health interventions consisting of four domains. We derived items of the tool from three different sources:
1) theories deduced from qualitative study;
2) meticulous examination of published public health interventions; and
3) expert opinion.
The tool was validated by collecting the feedback from seven public health experts. The tool provides four domain-specific complexity scores (obtained by adding scores of all items of the domain) and one total complexity score (obtained by adding four domain-specific complexity scores). As the number of items in each of the four domains is not same, it is important to take into account the relative contribution of domains towards the total complexity score for ranking the studies according to their complexity status. This was achieved by the method of composite dynamic index which is a weighted linear combination of complexity scores of four domains, where the weightage for each domain is assigned inversely proportional to standard deviation of its values. Further beta distribution was fitted to the developed composite index and studies were classified into four classes of complexity namely very highly complex, highly complex, moderately complex and least complex for the purpose of interpretation of complexity score. We applied the tool to assess the complexity of 259 studies collected from 30 public health systematic reviews, constructed a composite dynamic index, and classified studies into four classes of complexity.
Results:
The tool consists of four domains, namely, population, intervention, context and outcome. The context domain received the least weightage in the composite dynamic index, indicating that it is most variable than other domains
Patient or healthcare consumer involvement:
None.