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Correlational methods

Limitations to Correlational Studies The study “ Influence of Maternal Health Literacy on Child Participation in Social Welfare Programs: The Philadelphia Experience” was a first of its kind study that tested for whether the extent to which new mothers were able to find and use health care information to take decisions that would benefit their new-born children and follow instructions for the child’s care and treatment had any relationship with the probability that the mother would enroll her child in programs for healthcare that they were eligible for. They found that there did seem to be a relationship between the health literacy of the mother and the self-reported participation in various social healthcare programs.
While a correlation between the variables may have been established, it is not possible to assume causation. Even in the event that we try to establish causation, there would be some confounding factors that could seriously affect the strength of the results. This stands true even though the data collected for this study could be considered a strong sample size. Some of these factors have to do with the data collection possibilities and processes.
Sampling Bias: The data collected came from individuals who chose to participate. It is likely that individuals with a particular attitude towards health literacy would be more likely to participate than others; and this would skew the results to favor those who share the same attitude.
Inaccurate reporting: Often, people report what they believe they are expected to say. Alternately, they may report the behavior that they would prefer to indulge in, as compared to the behaviors they do indulge in. this can happen without any deliberate intention to mis – represent facts; but it does affect the efficacy of data is there is no way to verify the reported data.
Non-generalisablity of cohort: The sample studied consists a majority of mothers belonging to a particular racial background and marital status. Also, all participants come from a single socio – geographical area. All these factors may have contributed to skewing the data towards the experiences and choices of a particular group as against those of the entire population. Such data tends to represent only part of the real picture.
Other concerns rise from the sociological factors that may be invisible, but playing a role nevertheless. These would include
The effort and resources required in availing the health care: There is no information collected of how difficult or easy the process of applying for health care for a child is. Nor is there a review of how accessible the services are even to those who are eligible for them. These may be factors that do affect the choices made.
Social campaigns and visibility: Often, coming across regular advertisement of resources available will induce people to apply, and vice versa. If any such campaigns have been run; or any negative publicity about the services has been visible to the participants, this would affect their decisions.
Social influence: People are more likely to commit an action if others around them have done the same. This factor also needs to be controlled for if we want to understand if the actions of the participants have been lead by their own choices, or have been influenced by the opinions and actions of others.
References:
Fielding, J. & Gilbert, N., ( 2006). Understanding Social Statistics (2 ed.). London : Sage.
Kalton, G., (1983). Introduction to Survey Sampling. London: Sage.

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