Self-report by participants is one of the most common ways that researchers collect data, yet it is fraught with problems. Some worries for researchers are: “Will participants be honest or will they say what they think I want to hear?” “Will they understand the 
questions correctly?” “Will those who respond (as opposed to those who don’t respond) have unique ways of thinking so that my respondents do not represent everyone well?” and a BIG worry “Will they even fill out and return the questionnaire?”
One way to solve at least the latter 2 problems is to increase the response rate, and Edwards et al (2009 July 8) reviewed randomized trials to learn how to do just that!!
If you want to improve your questionnaire response rates, check it out! Here is Edwards et al.’s plain language summary as published in Cochrane Database of Systematic Reviews, where you can read the entire report.
Methods to increase response to postal and electronic questionnaires
Postal and electronic questionnaires are a relatively inexpensive way to collect information from people for research purposes. If people do not reply (so called ‘non-responders’), the research results will tend to be less accurate. This systematic review found several ways to increase response. People can be contacted before they are sent a postal questionnaire. Postal questionnaires can be sent by first class post or recorded delivery, and a stamped-return envelope can be provided. Questionnaires, letters and e-mails can be made more personal, and preferably kept short. Incentives can be offered, for example, a small amount of money with 
a postal questionnaire. One or more reminders can be sent with a copy of the questionnaire to people who do not reply.
Critical/reflective thinking: Imagine that you were asked to participate in a survey. Which of these strategies do you think would motivate or remind you to respond and why?
For more info read the full report: Methods to increase response to postal and electronic questionnaires
“Once you see Nightingale’s graph, the terrible picture is clear. The Russians were a minor enemy. The real enemies were cholera, typhus, and dysentery. Once the military looked at that eloquent graph, the modern army hospital system was inevitable. You and I are shown graphs every day. Some are honest; many are misleading….So you and I could use a Florence Nightingale today, as we drown in more undifferentiated data than anyone could’ve imagined during the Crimean War.” (Source: Leinhard, 1998-2002)
One source of rich word or narrative (qualitative) data for answering nursing questions is nurses’ stories. Dr. Pat Benner RN, author of Novice to Expert explains two things we can do to help nurses fully tell their stories so we can learn the most from their practice.
Quasi-experiments are a lot of work, yet don’t have the same scientific power to show cause and effect, as do randomized controlled trials (RCTs). An RCT would provide better support for any hypothesis that X causes Y. [As a quick review of what quasi-experimental versus RCT studies are, see 
and an experimental group. If the researcher wants to compare health outcomes of smokers with non-smokers, the researcher cannot assign some people to smoke and others not to smoke! Why? Because we already know that smoking has significant harmful effects. (Of course, in a dictatorship, by using the police a researcher could assign them to smoke or not smoke, but I don’t think we wanna go there.)
experimental groups. If the researcher wants to compare health outcomes of
to control & experimental groups. It costs $ & time to get a list of subjects and then assign them to control & experimental groups using random numbers table or drawing names from a hat.
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Herein lies a weak link in the cause-and-effect chain. Quasi- designs are NOT as strong as true experimental designs because something other than our treatment (in this case pet therapy) may have created any difference in outcomes (e.g., anxiety levels). Why? Here’s your answer.
In a quasi experimental design
