Divorce, deployment and statistics

December 31, 2008 By Claire
Posted in Spouse and Family

I had mentioned that I wanted to do a follow up “piggyback” write up to an earlier post by CJ on Divorce and the Military.

There are really two topics in that post and I wanted to address each one separately. The first issue has to do with statistics and the media, and the second has to do with research around divorce and current theories in the field of marital counseling. I will do a quick overview of the statistical issues today and refer you to a very well written, succinct guide to scrutinizing the use of statistics. Next week I will write up some of the more recent findings in marital counseling — focusing on what builds a strong marriage instead of telling you how to avoid a divorce.

My background is quite diverse in regard to the different populations I have worked with. I have worked in the poorest regions of Appalachia, and I have worked with violent and assaultive youth, pediatric brain tumor patients and their families, and my last job placed me in various client settings evaluating program effectiveness and developing tools to measure outcomes as a research associate.

One common thread through all of my work has been research. Every program I have worked in over the years has either used research to inform its practice, or was actively conducting research in the field. There are two things I learned along the way: research is necessary to guide practice, and the information we gain from social research is often more limited than researchers want to admit.

CJ had pulled the following quote from the media in regards the latest statistics available on the divorce rate in the military:

The divorce rate among soldiers and Marines increased last year as military marriages suffered continuing stress from America’s two ongoing wars. There were an estimated 10,200 failed marriages in the active duty Army and 3,077 among Marines, according to figures obtained by The Associated Press for the budget year ended Sept. 30.

That’s a divorce rate of 3.5 percent among more than 287,000 married troops in the Army, up from 3.3 percent in the previous fiscal year, according to Defense Department figures.

The highlighted part of the quote is what I really wanted to focus on for the moment. The author of this article very cleverly links the “continuing stress of deployment” with the increase in divorce among Soldiers and Marines. The way the article is worded makes it appear as if some in depth, longitudinal, scientific study has been done that actually points to a cause and effect relationship between divorce and deployments. That most certainly is not the case. The author links the two ideas without really saying that research supports the idea.

The fact of the matter is statistics are way too limited to make a cause and effect statement. Statistics can illuminate areas where further research is warranted, and they are often used to justify the development of programs. Statistics in and of themselves, however, can not offer alternative explanations nor can they account for other inter-complexities in studying human nature and human institutions. Relying on statistics to draw conclusions can be messy business.

Last year the Army released a study which asserted that deployment increased the likelihood of child abuse. I was not able to get an entire copy of the research that was done, but when I saw the sample population that was used to draw the conclusionsI was astounded at the conclusions!

The conclusion that deployment increased the rate of child abuse was drawn off of a very limited sample population of Army families who (get this) already had a substantiated case of child abuse or neglect! In reality the research was saying that families who already have abused or neglected their children are more likely to do so again when deployment (and the related stress) occurs. That’s not new information people.

There is a huge body of research that addresses the propensity for abuse and neglect and the recurrence within families who already have substantiated charges. The thing that sent me through the roof is the fact that they were using these very, very, very limited statistics to make huge, sweeping, general statements against Army wives. The journal write up said that Army wives were at risk for child abuse! How dare they slander the entire community of Army wives based on such limited data? When I started researching the names linked to the research I did find a name that is also closely linked with the anti-war crowd. Red flags were flapping everywhere on that one!

Statistics can be used to point the finger at a given villain. Deployment is the villain here and statistics are being used to pin the blame of failed marriages and other domestic issues on it. The stresses of deployment and the long term effects on military families should be studied, but more so to highlight what does work for military marriages and how those strengths can be used to help couples who are struggling.

So, here are a few things to always consider when you are faced with an article in the media or really any source that has a vested interest in the outcome and interpretation of the data:

Excerpts taken from a fact sheet from the National Association of Child Advocates (link to PDF at bottom):

Consider the source.
It is important to evaluate the credibility of the individual(s) and the organization that produced the research. Research produced by respected researchers and institutions is more likely to be trustworthy. Also, research produced or funded by groups with a strong political or commercial agenda (e.g., partisan groups, or the company which manufactured the product being studied) is less trustworthy, since these groups have a vested
interest in the study’s findings supporting their viewpoint.

Media is also a source to be evaluated. [emphasis mine]
If you are learning about research through the media, keep in mind that the media coverage may not fully or accurately summarize the original research. Because research can be technical and complex, and because media coverage often seeks to be attention-grabbing and succinct, media reporting of research sometimes oversimplifies the research, leading to misinterpretation. Don’t assume that media’s report of the research is necessarily what the actual study says, particularly if the media coverage is very brief or provocative. Do follow up by trying to get a copy of the original research article, or by getting more information from additional sources.

Research results are really about the topic AS MEASURED, not as we may think of it.
In any research study, the topic studied is measured in some specific way. Knowing how the topic was measured helps you to understand what the research was really about.

Different types of research have different strengths.
Another indicator of the quality of a research study, and the claims that can be made based on it, is the study’s research design. The research design is the way the study is structured to answer a question. There are two broader categories of research: quantitative research, and qualitative research . Quantitative research uses numbers, and analyzes and reports data in numeric form. Qualitative research typically reports results through story-like descriptions rather than numbers.
[note: The article linked below offers a great quick overview of the different types of research.]

Sampling is more important than sample size.
As many advocates know, the study’s sample size is important. The minimum sample size needed in quantitative research depends on how big the effects being studied are, so there is no rule, but a general guideline for a minimum sample size might be 30 to 50 people. The larger the sample, the smaller the difference
needed between groups to attain statistical significance.

Statistical significance explained.
One of the things advocates value most about research is getting “ hard data” – numbers – about the effects of a policy on children. A study reports a statistically significant difference between those who received a program and those who didn’t. But what does statistical significance mean, and what can we conclude from it? A statistically significant result is one that is unlikely to be due to chance. Researchers use statistics to test whether the results they found are likely to be due to the effect of the program being studied, and not to other unrelated factors

… snip …

Statistical significance is different than the substantive significance, or meaningfulness, of a finding. A result may be statistically significant but unimportant (sample size is crucial here , because a very small difference will be statistically significant if group sizes are large). Conversely, a result may not be statistically significant, perhaps because the sample size was too small, but it may be meaningful nonetheless because it suggests an important change in an outcome.

Research findings are about groups.
Research results are usually based on comparisons between groups of people. For example, a study may find that children in program X have higher reading scores than children in program Y. That research findings are based on groups of people makes them particularly relevant for policy decisions, since policies affect groups of people, but less relevant for individual case decisions.

Any one study is not the whole story.
Although we usually come across re s e a rch one study at a time, from the news or a new report, research is most valuable when many specific studies are taken together to tell the whole story of what we know on a given topic. Research, as a tool for scientific discovery, is designed to work this way. Science is about the aggregation of specific studies, one building on another to increase our knowledge base

The points above are not complete and were taken from THIS article. Please print out the article and keep it on hand. It’s a great reference and very well written.

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