It takes 2 people to dance the tango, and 2 types of data to answer research questions.
Researchers answer hypotheses and research questions by collecting and analyzing data. The collected data often are numbers (AKA quantitative data) that are analyzed with statistical tests.
In contrast, some researchers may collect word data to answer the research question. The word data are usually subjects’ descriptive answers to open-ended interview questions. Researchers analyze the word data (AKA qualitative data) by looking for patterns in subjects’ descriptions.
A researcher may also choose to collect and analyze both numbers (quantitative) data AND word (qualitative) data to answer a research question more completely. This is similar to what an RN might do when the RN asks the patient to rate pain from 0 to 10 (number data) and also to describe the character, location, & severity of the pain (word data). You can see that having both types of data can give a more complete picture clinically. The same is true in research. (Using both quantitative & qualitative data is called mixed methods.)
Many nurses associate research only with numbers data and statistical analysis. Here is an excerpt of how analysis of numbers/quantitative data may look. “The majority of patients were female (58.5%), the mean age was 59.5 years, 53.1% of the patients had cancer, and 55.5% had undergone surgery….The majority of patients (56.6%) reported pain in the abdominal region. The mean duration of pain in patients with chronic pain was 4.8 years (SD =10.8), and for patients with acute pain 5.9 days (SD =5.9).” (de Rond et al, 2000, p.429) Notice the statistical calculation of percents, means (averages), and standard deviations (SD).*
In contrast, sometimes word data and analysis is the only way to answer a research question! Here is an example of how such qualitative data analysis was used to answer the question of what social processes were blocking the comforting of hospice patients: “Open coding initially generated five [barriers to appropriate opioid use to manage pain among hospice patients]…: within the patient, within the physician, within the family, within the nurse, and within the healthcare system….Two basic psychosocial processes became apparent as the foundation of these barriers: fear and avoidance behaviors.” (Zerwekh et al, 2002, p.85) Notice that the researchers identified 5 barriers and 2 processes by analyzing nurses’ descriptions.
At other times researchers may collect and analyze BOTH numbers (quantitative) data and word (qualitative) data, as in this excerpt: “[In response to the question of] ‘Who asked me about my pain and how did they do this?’ Seven of the eight children interviewed indicated they had been asked about their pain. …Some children did provide evidence of areas where they felt improvements could be made. One child indicated she would like nurses: to check on me more often (Case 1). However, another child (Case 3) indicated that nurses asked her about her pain too often and that this was particularly annoying if it meant they woke her up.” (Twycross & Finley, 2013, p.3100) Notice in this mixed methods case that 70% (7 of 10) said they had been asked about pain, and that several gave descriptions suggesting improvements.
CRITICAL THINKING: Read this excerpt and identify whether the researcher collected and analyzed quantitative or quantitative data or used mixed methods:“Approximately 82% of all patients received pain medications in the hospital, doctor’s office, outpatient clinic, or surgery center. The most commonly administered medications were morphine (33%) and meperidine (27%) for inpatients and acetaminophen with codeine (23%) and ibuprofen (15%) for outpatients. Overall, one third of patients requested their first one to two doses of pain medication while in the surgical setting. Of these, 37% were inpatients and 25% were outpatients. After discharge, 76% of all patients received pain medications.” (Source: Apfelbaum, Chen, Mehta, & Gan, 2003, DOI: 10.1213/01.ANE.0000068822.10113.9E)
*Standard deviations (SD) are how the data spread out while means (averages) are how the data clump together.