Testability as a characteristic of a hypothesis

Testability The second characteristic of a hypothesis is its testability. This means that the variables of the study must lend themselves to observation, measurement, and analysis. The hypothesis is either supported or not supported after the data have been collected and analyzed. The predicted outcome proposed by the hypothesis will or will not be congruent with the actual outcome when the hypothesis is tested.

H E L P F U L H I N T When a hypothesis is complex (i.e., it contains more than one independent or dependent variable), it is difficult for the findings to indicate unequivocally that the hypothesis is supported or not supported. In such cases, the reader must infer which relationships are significant in the predicted direction from the findings or discussion section.

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Theory base The third characteristic is that the hypothesis is consistent with an existing body of theory and research findings. Whether a hypothesis is arrived at on the basis of a review of the literature or a clinical observation, it must be based on a sound scientific rationale. You should be able to identify the flow of ideas from the research idea to the literature review, to the theoretical framework, and through the research question(s) or hypotheses. Example: ➤ Nyamathi and colleagues (2015) (see Appendix A) investigated the effectiveness of a nursing case management intervention in comparison to a peer coaching intervention based on the comprehensive health-seeking and coping paradigm developed by Nyamathi in 1989, adapted from a coping model by Lazarus and Folkman (1984), and the health-seeking and coping paradigm by Schlotfeldt (1981), which is a useful theoretical framework for case management, peer coaching interventions, and vaccine completion outcomes.

Wording the hypothesis As you read the scientific literature and become more familiar with it, you will observe that there are a variety of ways to word a hypothesis that are described in Tables 2.4 and 2.5. Information about hypotheses may be further clarified in the instruments, sample, or methods sections of a research report (see Chapters 12 and 15).

TABLE 2.4 Examples of How Hypotheses are Worded


BP, Blood pressure; CRNA, Certified Nurse Anesthetists; DV, dependent variable; IV, independent variable; TM, telemonitoring; UC, usual care.

TABLE 2.5 Examples of Statistical Hypotheses

ANPs, Adult nurse practitioners; FNPs, family nurse practitioners; DV, dependent variable; IV, independent variable.

Statistical versus research hypotheses You may observe that a hypothesis is further categorized as either a research or a statistical hypothesis. A research hypothesis, also known as a scientific hypothesis, consists of a statement about the expected relationship of the variables. A research hypothesis indicates what the outcome of the study is expected to be. A research hypothesis is also either directional or nondirectional. If the researcher obtains statistically significant findings for a research hypothesis, the hypothesis is supported. The examples in Table 2.4 represent research hypotheses.

A statistical hypothesis, also known as a null hypothesis, states that there is no relationship between the independent and dependent variables. The examples in Table 2.5 illustrate statistical hypotheses. If, in the data analysis, a statistically significant relationship emerges between the variables at a specified level of significance, the null hypothesis is rejected. Rejection of the


statistical hypothesis is equivalent to acceptance of the research hypothesis.

Directional versus nondirectional hypotheses Hypotheses can be formulated directionally or nondirectionally. A directional hypothesis specifies the expected direction of the relationship between the independent and dependent variables. An example of a directional hypothesis is provided in a study by Parry and colleagues (2015) that investigated a novel noninvasive device to assess sympathetic nervous system functioning in patients with heart failure. The researchers hypothesized that participants with heart failure reduced ejection fraction (HFrEF), who have internal cardiac defibrillators or CRT pacemakers, will have a decrease in pre-ejection period (reflective of increased sympathetic nervous system activity) and decrease in left ventricular ejection time (reflective of an increased heart rate) with a postural change from sitting to standing.

In contrast, a nondirectional hypothesis indicates the existence of a relationship between the variables, but does not specify the anticipated direction of the relationship. Example: ➤ Rattanawiboon and colleagues (2016) evaluated the effectiveness of fluoride mouthwash delivery methods, swish, spray, or swab application, in raising salivary fluoride in comparison to conventional fluoride mouthwash, but did not predict which form of fluoride delivery would be most effective. Nurses who are learning to critically appraise research studies should be aware that both the directional and the nondirectional forms of hypothesis statements are acceptable.

Relationship between the hypothesis and the research design Regardless of whether the researcher uses a statistical or a research hypothesis, there is a suggested relationship between the hypothesis, the design of the study, and the level of evidence provided by the results of the study. The type of design, experimental or nonexperimental (see Chapters 9 and 10), will influence the wording of the hypothesis. Example: ➤ When an experimental design is used, you would expect to see hypotheses that reflect relationship statements, such as the following:

• X1 is more effective than X2 on Y.

• The effect of X1 on Y is greater than that of X2 on Y.

• The incidence of Y will not differ in subjects receiving X1 and X2 treatments.

• The incidence of Y will be greater in subjects after X1 than after X2.

  E V I D E N C E – B A S E D P R A C T I C E T I P Think about the relationship between the wording of the hypothesis, the type of research design suggested, and the level of evidence provided by the findings of a study using each kind of hypothesis. You may want to consider which type of hypothesis potentially will yield the strongest results applicable to practice.

Hypotheses reflecting experimental designs also test the effect of the experimental treatment (i.e., independent variable X) on the outcome (i.e., dependent variable Y). This suggests that the strength of the evidence provided by the results is Level II (experimental design) or Level III (quasi- experimental design).

In contrast, hypotheses related to nonexperimental designs reflect associative relationship statements, such as the following:

• X will be negatively related to Y.

• There will be a positive relationship between X and Y.

This suggests that the strength of the evidence provided by the results of a study that examined hypotheses with associative relationship statements would be at Level IV (nonexperimental design).

Table 2.6 provides an example of this concept. The Critical Thinking Decision Path will help you determine the type of hypothesis or research question presented in a study.


TABLE 2.6 Elements of a Clinical Question

CAUTIs, Catheter acquired urinary tract infections.

C R I T I C A L T H I N K I N G D E C I S I O N PAT H Determining the Use of a Hypothesis or Research Question

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