importance of hypothesis in nursing research

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StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

StatPearls [Internet].

Hypothesis testing, p values, confidence intervals, and significance.

Jacob Shreffler ; Martin R. Huecker .

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Last Update: March 13, 2023 .

• Definition/Introduction

Medical providers often rely on evidence-based medicine to guide decision-making in practice. Often a research hypothesis is tested with results provided, typically with p values, confidence intervals, or both. Additionally, statistical or research significance is estimated or determined by the investigators. Unfortunately, healthcare providers may have different comfort levels in interpreting these findings, which may affect the adequate application of the data.

• Issues of Concern

Without a foundational understanding of hypothesis testing, p values, confidence intervals, and the difference between statistical and clinical significance, it may affect healthcare providers' ability to make clinical decisions without relying purely on the research investigators deemed level of significance. Therefore, an overview of these concepts is provided to allow medical professionals to use their expertise to determine if results are reported sufficiently and if the study outcomes are clinically appropriate to be applied in healthcare practice.

Hypothesis Testing

Investigators conducting studies need research questions and hypotheses to guide analyses. Starting with broad research questions (RQs), investigators then identify a gap in current clinical practice or research. Any research problem or statement is grounded in a better understanding of relationships between two or more variables. For this article, we will use the following research question example:

Research Question: Is Drug 23 an effective treatment for Disease A?

Research questions do not directly imply specific guesses or predictions; we must formulate research hypotheses. A hypothesis is a predetermined declaration regarding the research question in which the investigator(s) makes a precise, educated guess about a study outcome. This is sometimes called the alternative hypothesis and ultimately allows the researcher to take a stance based on experience or insight from medical literature. An example of a hypothesis is below.

Research Hypothesis: Drug 23 will significantly reduce symptoms associated with Disease A compared to Drug 22.

The null hypothesis states that there is no statistical difference between groups based on the stated research hypothesis.

Researchers should be aware of journal recommendations when considering how to report p values, and manuscripts should remain internally consistent.

Regarding p values, as the number of individuals enrolled in a study (the sample size) increases, the likelihood of finding a statistically significant effect increases. With very large sample sizes, the p-value can be very low significant differences in the reduction of symptoms for Disease A between Drug 23 and Drug 22. The null hypothesis is deemed true until a study presents significant data to support rejecting the null hypothesis. Based on the results, the investigators will either reject the null hypothesis (if they found significant differences or associations) or fail to reject the null hypothesis (they could not provide proof that there were significant differences or associations).

To test a hypothesis, researchers obtain data on a representative sample to determine whether to reject or fail to reject a null hypothesis. In most research studies, it is not feasible to obtain data for an entire population. Using a sampling procedure allows for statistical inference, though this involves a certain possibility of error. [1]  When determining whether to reject or fail to reject the null hypothesis, mistakes can be made: Type I and Type II errors. Though it is impossible to ensure that these errors have not occurred, researchers should limit the possibilities of these faults. [2]

Significance

Significance is a term to describe the substantive importance of medical research. Statistical significance is the likelihood of results due to chance. [3]  Healthcare providers should always delineate statistical significance from clinical significance, a common error when reviewing biomedical research. [4]  When conceptualizing findings reported as either significant or not significant, healthcare providers should not simply accept researchers' results or conclusions without considering the clinical significance. Healthcare professionals should consider the clinical importance of findings and understand both p values and confidence intervals so they do not have to rely on the researchers to determine the level of significance. [5]  One criterion often used to determine statistical significance is the utilization of p values.

P values are used in research to determine whether the sample estimate is significantly different from a hypothesized value. The p-value is the probability that the observed effect within the study would have occurred by chance if, in reality, there was no true effect. Conventionally, data yielding a p<0.05 or p<0.01 is considered statistically significant. While some have debated that the 0.05 level should be lowered, it is still universally practiced. [6]  Hypothesis testing allows us to determine the size of the effect.

An example of findings reported with p values are below:

Statement: Drug 23 reduced patients' symptoms compared to Drug 22. Patients who received Drug 23 (n=100) were 2.1 times less likely than patients who received Drug 22 (n = 100) to experience symptoms of Disease A, p<0.05.

Statement:Individuals who were prescribed Drug 23 experienced fewer symptoms (M = 1.3, SD = 0.7) compared to individuals who were prescribed Drug 22 (M = 5.3, SD = 1.9). This finding was statistically significant, p= 0.02.

For either statement, if the threshold had been set at 0.05, the null hypothesis (that there was no relationship) should be rejected, and we should conclude significant differences. Noticeably, as can be seen in the two statements above, some researchers will report findings with < or > and others will provide an exact p-value (0.000001) but never zero [6] . When examining research, readers should understand how p values are reported. The best practice is to report all p values for all variables within a study design, rather than only providing p values for variables with significant findings. [7]  The inclusion of all p values provides evidence for study validity and limits suspicion for selective reporting/data mining.  

While researchers have historically used p values, experts who find p values problematic encourage the use of confidence intervals. [8] . P-values alone do not allow us to understand the size or the extent of the differences or associations. [3]  In March 2016, the American Statistical Association (ASA) released a statement on p values, noting that scientific decision-making and conclusions should not be based on a fixed p-value threshold (e.g., 0.05). They recommend focusing on the significance of results in the context of study design, quality of measurements, and validity of data. Ultimately, the ASA statement noted that in isolation, a p-value does not provide strong evidence. [9]

When conceptualizing clinical work, healthcare professionals should consider p values with a concurrent appraisal study design validity. For example, a p-value from a double-blinded randomized clinical trial (designed to minimize bias) should be weighted higher than one from a retrospective observational study [7] . The p-value debate has smoldered since the 1950s [10] , and replacement with confidence intervals has been suggested since the 1980s. [11]

Confidence Intervals

A confidence interval provides a range of values within given confidence (e.g., 95%), including the accurate value of the statistical constraint within a targeted population. [12]  Most research uses a 95% CI, but investigators can set any level (e.g., 90% CI, 99% CI). [13]  A CI provides a range with the lower bound and upper bound limits of a difference or association that would be plausible for a population. [14]  Therefore, a CI of 95% indicates that if a study were to be carried out 100 times, the range would contain the true value in 95, [15]  confidence intervals provide more evidence regarding the precision of an estimate compared to p-values. [6]

In consideration of the similar research example provided above, one could make the following statement with 95% CI:

Statement: Individuals who were prescribed Drug 23 had no symptoms after three days, which was significantly faster than those prescribed Drug 22; there was a mean difference between the two groups of days to the recovery of 4.2 days (95% CI: 1.9 – 7.8).

It is important to note that the width of the CI is affected by the standard error and the sample size; reducing a study sample number will result in less precision of the CI (increase the width). [14]  A larger width indicates a smaller sample size or a larger variability. [16]  A researcher would want to increase the precision of the CI. For example, a 95% CI of 1.43 – 1.47 is much more precise than the one provided in the example above. In research and clinical practice, CIs provide valuable information on whether the interval includes or excludes any clinically significant values. [14]

Null values are sometimes used for differences with CI (zero for differential comparisons and 1 for ratios). However, CIs provide more information than that. [15]  Consider this example: A hospital implements a new protocol that reduced wait time for patients in the emergency department by an average of 25 minutes (95% CI: -2.5 – 41 minutes). Because the range crosses zero, implementing this protocol in different populations could result in longer wait times; however, the range is much higher on the positive side. Thus, while the p-value used to detect statistical significance for this may result in "not significant" findings, individuals should examine this range, consider the study design, and weigh whether or not it is still worth piloting in their workplace.

Similarly to p-values, 95% CIs cannot control for researchers' errors (e.g., study bias or improper data analysis). [14]  In consideration of whether to report p-values or CIs, researchers should examine journal preferences. When in doubt, reporting both may be beneficial. [13]  An example is below:

Reporting both: Individuals who were prescribed Drug 23 had no symptoms after three days, which was significantly faster than those prescribed Drug 22, p = 0.009. There was a mean difference between the two groups of days to the recovery of 4.2 days (95% CI: 1.9 – 7.8).

• Clinical Significance

Recall that clinical significance and statistical significance are two different concepts. Healthcare providers should remember that a study with statistically significant differences and large sample size may be of no interest to clinicians, whereas a study with smaller sample size and statistically non-significant results could impact clinical practice. [14]  Additionally, as previously mentioned, a non-significant finding may reflect the study design itself rather than relationships between variables.

Healthcare providers using evidence-based medicine to inform practice should use clinical judgment to determine the practical importance of studies through careful evaluation of the design, sample size, power, likelihood of type I and type II errors, data analysis, and reporting of statistical findings (p values, 95% CI or both). [4]  Interestingly, some experts have called for "statistically significant" or "not significant" to be excluded from work as statistical significance never has and will never be equivalent to clinical significance. [17]

The decision on what is clinically significant can be challenging, depending on the providers' experience and especially the severity of the disease. Providers should use their knowledge and experiences to determine the meaningfulness of study results and make inferences based not only on significant or insignificant results by researchers but through their understanding of study limitations and practical implications.

• Nursing, Allied Health, and Interprofessional Team Interventions

All physicians, nurses, pharmacists, and other healthcare professionals should strive to understand the concepts in this chapter. These individuals should maintain the ability to review and incorporate new literature for evidence-based and safe care. 

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Disclosure: Jacob Shreffler declares no relevant financial relationships with ineligible companies.

Disclosure: Martin Huecker declares no relevant financial relationships with ineligible companies.

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• Cite this Page Shreffler J, Huecker MR. Hypothesis Testing, P Values, Confidence Intervals, and Significance. [Updated 2023 Mar 13]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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The Research Hypothesis: Role and Construction

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A hypothesis is a logical construct, interposed between a problem and its solution, which represents a proposed answer to a research question. It gives direction to the investigator’s thinking about the problem and, therefore, facilitates a solution. There are three primary modes of inference by which hypotheses are developed: deduction (reasoning from a general propositions to specific instances), induction (reasoning from specific instances to a general proposition), and abduction (formulation/acceptance on probation of a hypothesis to explain a surprising observation).

A research hypothesis should reflect an inference about variables; be stated as a grammatically complete, declarative sentence; be expressed simply and unambiguously; provide an adequate answer to the research problem; and be testable. Hypotheses can be classified as conceptual versus operational, single versus bi- or multivariable, causal or not causal, mechanistic versus nonmechanistic, and null or alternative. Hypotheses most commonly entail statements about “variables” which, in turn, can be classified according to their level of measurement (scaling characteristics) or according to their role in the hypothesis (independent, dependent, moderator, control, or intervening).

A hypothesis is rendered operational when its broadly (conceptually) stated variables are replaced by operational definitions of those variables. Hypotheses stated in this manner are called operational hypotheses, specific hypotheses, or predictions and facilitate testing.

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Wrong hypotheses, rightly worked from, have produced more results than unguided observation

—Augustus De Morgan, 1872[ 1 ]—

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Supino, P.G. (2012). The Research Hypothesis: Role and Construction. In: Supino, P., Borer, J. (eds) Principles of Research Methodology. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3360-6_3

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Research Problems, Purposes, and Hypotheses

Chapter 5 Research Problems, Purposes, and Hypotheses Chapter Overview What Are Research Problems and Purposes? Identifying the Problem and Purpose in Quantitative, Qualitative, and Outcomes Studies Problems and Purposes in Types of Quantitative Studies Problems and Purposes in Types of Qualitative Studies Problems and Purposes in Outcomes Research Determining the Significance of a Study Problem and Purpose Influences Nursing Practice Builds on Previous Research Promotes Theory Testing or Development Addresses Nursing Research Priorities Examining the Feasibility of a Problem and Purpose Researcher Expertise Money Commitment Availability of Subjects, Facilities, and Equipment Ethical Considerations Examining Research Objectives, Questions, and Hypotheses in Research Reports Research Objectives or Aims Research Questions Hypotheses Understanding Study Variables and Research Concepts Types of Variables in Quantitative Research Conceptual and Operational Definitions of Variables in Quantitative Research Research Concepts Investigated in Qualitative Research Demographic Variables Key Concepts References Learning Outcomes After completing this chapter, you should be able to: 1.  Identify research topics, problems, and purposes in published quantitative, qualitative, and outcomes studies. 2.  Critically appraise the research problems and purposes in studies. 3.  Critically appraise the feasibility of a study problem and purpose by examining the researcher’s expertise, money commitment, availability of subjects, facilities, and equipment, and the study’s ethical considerations. 4.  Differentiate among the types of hypotheses (simple versus complex, nondirectional versus directional, associative versus causal, and statistical versus research) in published studies. 5.  Critically appraise the quality of objectives, questions, and hypotheses presented in studies. 6.  Differentiate the types of variables in studies. 7.  Critically appraise the conceptual and operational definitions of variables in published studies. 8.  Critically appraise the demographic variables measured and the sample characteristics described in studies. Key Terms Associative hypothesis, p. 149 Background for a problem, p. 131 Causal hypothesis, p. 149 Complex hypothesis, p. 150 Conceptual definition, p. 155 Confounding variables, p. 155 Demographic variables, p. 157 Dependent (outcome) variable, p. 153 Directional hypothesis, p. 150 Environmental variables, p. 154 Extraneous variables, p. 154 Feasibility of a study, p. 143 Hypothesis, p. 149 Independent (treatment or intervention) variable, p. 153 Nondirectional hypothesis, p. 150 Null hypothesis (H 0 ), p. 151 Operational definition, p. 155 Problem statement, p. 131 Research concepts, p. 156 Research hypothesis, p. 151 Research objective or aim, p. 145 Research problem, p. 131 Research purpose, p. 131 Research question, p. 147 Research topic, p. 130 Research variables, p. 154 Sample characteristics, p. 157 Significance of a research problem, p. 131 Simple hypothesis, p. 150 Statistical hypothesis, p. 151 Testable hypothesis, p. 152 Variables, p. 153 We are constantly asking questions to gain a better understanding of ourselves and the world around us. This human ability to wonder and ask creative questions is the first step in the research process. By asking questions, clinical nurses and nurse researchers are able to identify significant research topics and problems to direct the generation of research evidence for use in practice. A research topic is a concept or broad issue that is important to nursing, such as acute pain, chronic pain management, coping with illness, or health promotion. Each topic contains numerous research problems that might be investigated through quantitative, qualitative, and outcomes studies. For example, chronic pain management is a research topic that includes research problems such as “What is it like to live with chronic pain?” and “What strategies are useful in coping with chronic pain?” Qualitative studies have been conducted to investigate these problems or areas of concern in nursing ( Munhall, 2012 ). Quantitative studies have been conducted to address problems such as “What is the most accurate way to assess chronic pain?” and “What interventions are effective in managing chronic pain?” Outcomes research methodologies have been used to examine patient outcomes and the cost-effectiveness of care provided in chronic pain management centers ( Doran, 2011 ). The problem provides the basis for developing the research purpose. The purpose is the goal or focus of a study that guides the development of the objectives, questions, or hypotheses in quantitative and outcomes studies. The objectives, questions, or hypotheses bridge the gap between the more abstractly stated problem and purpose and the detailed design for conducting the study. Objectives, questions, and hypotheses include the variables, relationships among the variables, and often the population to be studied. In qualitative research, the purpose and broadly stated research questions guide the study of selected research concepts. This chapter includes content that will assist you in identifying problems and purposes in a variety of quantitative, qualitative, and outcomes studies. Objectives, questions, and hypotheses are discussed, and the different types of study variables are introduced. Also presented are guidelines that will assist you in critically appraising the problems, purposes, objectives, questions, hypotheses, and variables or concepts in published quantitative, qualitative, and outcomes studies. What Are Research Problems and Purposes? A research problem is an area of concern in which there is a gap in the knowledge needed for nursing practice. Research is required to generate essential knowledge to address the practice concern, with the ultimate goal of providing evidence-based nursing care ( Brown, 2014 ; Craig & Smyth, 2012 ). In a study, the research problem (1) indicates the significance of the problem, (2) provides a background for the problem, and (3) includes a problem statement. The significance of a research problem indicates the importance of the problem to nursing and health care and to the health of individuals, families, and communities. The background for a problem briefly identifies what we know about the problem area, and the problem statement identifies the specific gap in the knowledge needed for practice. Not all published studies include a clearly expressed problem, but the problem usually can be identified in the first page of the report. The research purpose is a clear, concise statement of the specific goal or focus of a study. In quantitative and outcomes studies, the goal of a study might be to identify, describe, or examine relationships in a situation, examine the effectiveness of an intervention, or determine outcomes of health care. In qualitative studies, the purpose might be to explore perceptions of a phenomenon, describe elements of a culture, develop a theory of a health situation or issue, or describe historical trends and patterns. The purpose includes the variables or concepts, the population, and often the setting for the study. A clearly stated research purpose can capture the essence of a study in a single sentence and is essential for directing the remaining steps of the research process. The research problem and purpose from the study of Piamjariyakul, Smith, Russell, Werkowitch, and Elyachar (2013) of the effectiveness of a telephone coaching program on heart failure home management by family caregivers are presented as an example. This example is critically appraised using the following guidelines. Critical Appraisal Guidelines Problems and Purposes in Studies 1.  Is the problem clearly and concisely expressed early in the study? 2.  Does the problem include the significance, background, and problem statement? 3.  Does the purpose clearly express the goal or focus of the study? 4.  Is the purpose focused on the study problem statement? 5.  Are the study variables and population identified in the purpose? Research Example Problem and Purpose of a Quantitative Study Research Study Excerpt Problem Significance “Results of meta-analyses and American Heart Association (AHA) guidelines emphasize the critical importance of family caregivers’ involvement in home management of heart failure (HF). Family caregivers perform daily HF home management and provide essential support for patients in recognizing worsening symptoms (i.e., edema, shortness of breath; Riegel et al., 2009 ).” Piamjariyakul et al., 2013 , p. 32 Problem Background “Results of several studies have shown that HF rehospitalization is frequently precipitated by excess dietary sodium, inappropriate changes or reductions in taking prescribed medications, and respiratory infections, most of which family caregivers could help prevent if they were educated to be alert for these problems. . . . One intervention program found that a family partnership program on HF home care was helpful in adherence to diet with significant reductions in patients’ urine sodium ( Dunbar et al., 2005 ).” Piamjariyakul et al., 2013 , p. 32 Problem Statement “Yet, the few available studies on providing instruction for family caregivers are limited in content and lack guidance for implementing HF self-management strategies at home. . . . Also, in developing interventions that involve family caregivers, researchers need to measure caregiver outcomes (i.e., burden) to ensure that interventions do improve patient outcomes but do not have untoward negative impacts on the caregivers.” Piamjariyakul et al., 2013 , pp. 32-33 Research Purpose “The purpose of this study was to determine the feasibility and evaluate the helpfulness and costs of a coaching program for family caregiver HF home care management.” Piamjariyakul et al., 2013 , p. 33 Critical Appraisal Research Problem Piamjariyakul and colleagues (2013) presented a clear, concise research problem that had the relevant areas of (1) significance, (2) background, and (3) problem statement. HF is a significant, costly chronic illness to manage, and family caregivers are essential to the management process. A concise background of the problem was provided by discussing studies of the effects of caregivers on the outcomes of patients with HF. The discussion of the problem concluded with a concise problem statement that indicated the gap in the knowledge needed for practice and provided a basis for the study conducted by these researchers. Each problem provides the basis for generating a variety of research purposes and, in this study, the knowledge gap regarding the effectiveness of interventions on HF home management by family caregivers provides clear direction for the formulation of the research purpose. Research Purpose In a published study, the purpose frequently is reflected in the title of the study, stated in the study abstract, and restated after the literature review. Piamjariyakul and associates (2013) included the purpose of their study in all three places. The focus of this study was to examine the effectiveness of a telephone coaching program on HF home management (independent variable) on caregiving burden, confidence in providing HF care, preparedness, satisfaction, and program cost (dependent variables) for family caregivers (population). The purpose indicated the type of study conducted (quasi-experimental) and clearly identified the independent variable (telephone coaching program), population (patients with HF and their families), and setting (home). However, the dependent variables are not clearly identified in the study purpose but were discussed in the methods section of the study. The study purpose would have been strengthened by the inclusion of the dependent variables measured in this study. Implications for Practice The findings from the study by Piamjariyakul and co-workers (2013, p. 38) indicated that “The telephone coaching program was shown to reduce the caregiving burden and improve caregiver confidence and preparedness in HF home care management. . . . The cost for the program is considerably less than the cost for home healthcare providers ($120-160 per each visit), a single emergency department visit, or one inpatient hospitalization for HF due to poor HF home management.” This study has potential for use in practice to improve the quality of care provided to patients and families; however, the researchers did recognize the need for additional testing of the coaching program with a larger sample to determine its effectiveness. This type of study supports the Quality and Safety Education for Nurses ( QSEN, 2013 ; Sherwood & Barnsteiner, 2012 ) prelicensure competency to ensure safe, quality, and cost- effective health care that actively involves patients and families in this care process. Identifying the Problem and Purpose in Quantitative, Qualitative, and Outcomes Studies Quantitative, qualitative, and outcomes research approaches enable nurses to investigate a variety of research problems and purposes. Examples of research topics, problems, and purposes for different types of quantitative, qualitative, and outcomes studies are presented in this section. Problems and Purposes in Types of Quantitative Studies Example research topics, problems, and purposes for the different types of quantitative research (descriptive, correlational, quasi-experimental, and experimental) are presented in Table 5-1 . If little is known about a topic, researchers usually start with descriptive and correlational studies and progress to quasi-experimental and experimental studies as knowledge expands in an area. An examination of the problems and purposes in Table 5-1 will reveal the differences and similarities among the types of quantitative research. The research purpose usually reflects the type of study that was conducted ( Grove, Burns, & Gray, 2013 ). The purpose of descriptive research is to identify and describe concepts or variables, identify possible relationships among variables, and delineate differences between or among existing groups, such as males and females or different ethnic groups. Table 5-1 Quantitative Research Topics, Problems, and Purposes Type of Research Research Topic Research Problem and Purpose Descriptive research Hand hygiene (HH), HH opportunities, HH adherence, infection control, pediatric extended care facilities (ECFs), clinical and nonclinical caregivers Title of study: “Hand hygiene opportunities in pediatric extended care facilities” ( Buet et al., 2013, p. 72 ). Problem: “The population in pediatric ECFs [extended care facilities] is increasingly complex, and such children are at high risk of healthcare-associated infections (HAIs), which are associated with increased morbidity, mortality, resources use, and cost ( Burns et al., 2010 ) [problem significance]. . . . The Centers for Disease Control and Prevention (CDC) … and the World Health Organization ( WHO, 2009 ) have published evidence-based guidelines confirming the causal relationship between poor infection control practices, particularly hand hygiene (HH), and increased risk of HAIs [problem background]. However, most of the HH research has been focused in adult long term care facilities and acute care settings and findings from such studies are unlikely to be applicable to HH in pediatric ECFs given the different care patterns, including the relative distribution of different devices” [problem statement] ( Buet et al., 2013 , pp. 72-73). Purpose: “The purpose of this observational study was to assess the frequency and type of HH opportunities initiated by clinical (e.g., physicians and nurses) and non-clinical (e.g., parents and teachers) care givers, as well as evaluate HH adherence using the WHO’s ‘5 Moments for HH’ observation tool” ( Buet et al., 2013, p. 73 ). Correlational research Insulin resistance; anthropometric measurements (height, weight, body mass index [BMI], and waist circumference); systolic and diastolic blood pressure; laboratory values of lipids and triglycerides; and inflammatory marker high-sensitivity C-reactive protein (hsCRP) Title of study: “Biological correlates and predictors of insulin resistance among early adolescents” ( Bindler et al., 2013, p. 20 ). Problem: “Prevalence of obesity is at historic high levels among youth; for example, worldwide, obesity has doubled, and in developed countries, the numbers of youth who are overweight or obese have tripled in the last three decades ( WHO, 2011 ) [problem significance]. . . . Youth with obesity and insulin resistance (IR) are at increased risk of associated chronic conditions in adulthood, such as elevated blood pressure (BP), cardiovascular disease (CVD), type 2 diabetes, and several types of cancer ( Li et al., 2009 ) [problem background]. Despite the known relationships between IR and cardiometabolic factors, no study has yet examined the independent effects of these factors on a predictive model of IR among early adolescents” [problem statement] ( Bindler et al., 2013, pp. 20-21 ). Purpose: “Therefore, the purposes of this study among a group of early adolescents participating in the Teen Eating and Activity Mentoring in Schools (TEAMS) study were to describe the anthropometric and laboratory markers of the participants and to test the ability of these markers to predict risk of exhibiting IR” ( Bindler et al., 2013, p. 21 ). Quasi-experimental research Nurse-case-managed intervention, hepatitis A and B vaccine completion, sociodemographic factors, risk behaviors, and homeless adults Title of study: “Effects of a nurse-managed program on hepatitis A and B vaccine completion among homeless adults” ( Nyamathi et al., 2009, p. 13 ). Problem: “Hepatitis B virus (HBV) infection poses a serious threat to public health in the United States. Recent estimates place the true prevalence of chronic HBV in the United States at approximately 1.6 cases per 100,000 persons ( CDC, 2008 ). It is estimated that there were 51,000 new cases of HBV infection in 2005 ( Wasley et al., 2007 ), a financial burden reaching $1 billion annually. . . . Homeless populations are at particularly high risk of HBV infection due to high rates of unprotected sexual behavior and sharing of needles and other IDU [injection drug user] paraphernalia. Previous studies have reported that HBV infection rates among homeless populations range from 17% to 31% (i.e., from 17,000 to 31,000 per 100,000) compared with 2.1 per 100,000 in the general United States population [problem significance]. . . . Vaccination is the most effective way to prevent HBV infection ( CDC, 2006 ). . . . Improving vaccination adherence rates among homeless persons is an important step toward reducing the high prevalence of HBV infection in this population [problem background]. … Thus, little is known about adherence to HBV vaccination among community samples of urban homeless person[s] or about the effect of stronger interventions to incorporate additional strategies, such as nurse case management and targeted HBV education along with client tracking [problem statement]” ( Nyamathi et al., 2009, pp. 13-14 ). Purpose: The purpose of this study was to determine the “effectiveness of a nurse-case-managed intervention compared with that of two standard programs on completion of the combined hepatitis A virus (HAV) and HBV vaccine series among homeless adults and to assess sociodemographic factors and risk behaviors related to the vaccine completion” ( Nyamathi et al., 2009, p. 13 ). Experimental research Chronic widespread pain, aerobic exercise, analgesia, neurotrophin-3 synthesis, pain management, animal model Title of study: “Aerobic exercise alters analgesia and neurotrophin-3 [NT-3] synthesis in an animal model of chronic widespread pain” ( Sharma et al., 2010, p. 714 ). Problem: “Chronic widespread pain is complex and poorly understood and affects about 12% of the adult population in developed countries ( Rohrbeck et al., 2007 ) [problem significance]. . . . Management of chronic pain syndromes poses challenges for healthcare practitioners, and pharmacological interventions offer limited efficacy. . . . Exercise training has been long suggested to reduce pain and improve functional outcomes ( Whiteside et al., 2004 ) [problem background]. . . . Surprisingly, the current literature is mainly limited to human studies where the molecular basis for exercise training cannot be easily determined. Relatively few animal studies have addressed the effects and mechanisms of exercise on sensory modulation of chronic pain” [problem statement] ( Sharma et al., 2010, p. 715 ). Purpose: “The purpose of the present study was to examine the effects of moderate-intensity aerobic exercise on pain-like behavior and NT-3 in an animal model of widespread pain” ( Sharma et al., 2010, p. 714 ). Buet and co-workers (2013) conducted a descriptive study to identify the hand hygiene (HH) opportunities and adherence among clinical and nonclinical caregivers in extended pediatric care facilities. These researchers followed the World Health Organization “5 Moments for Hand Hygiene” ( WHO, 2009 ): before touching a patient, before clean or aseptic procedures, after body fluid exposure or risk, after touching a patient, and after touching patient surroundings. Researchers found that HH opportunities were numerous for clinical and nonclinical caregivers, but adherence to HH was low, especially for nonclinical individuals. This study supports the importance of HH in the delivery of quality, safe care based on current evidence-based guidelines ( Melnyk & Fineout-Overholt, 2011 ; QSEN, 2013 ). The purpose of correlational research is to examine the type (positive or negative) and strength of relationships among variables. In their correlational study, Bindler, Bindler, and Daratha (2013) examined the prediction of insulin resistance (IR) in adolescents using anthropometric measurements (height, weight, body mass index [BMI], and waist circumference), systolic and diastolic blood pressure, laboratory values [lipid and triglyceride levels], and the inflammatory marker of high-sensitivity, C-reactive protein (see Table 5-1 ). The researchers found that waist circumference and triglycerides were the strongest predictors of IR in adolescents. The findings from this study stressed the importance of nurses measuring waist circumference, height, and weight; calculating BMI; and examining lipid levels to identify youths at risk for IR. Quasi-experimental studies are conducted to determine the effect of a treatment or independent variable on designated dependent or outcome variables ( Shadish, Cook, & Campbell, 2002 ). Nyamathi and colleagues (2009) conducted a quasi-experimental study to examine the effectiveness of a nurse case-managed intervention on hepatitis A and B vaccine completion among homeless adults. The research topics, problem, and purpose for this study are presented in Table 5-1 . The findings from this study “revealed that a culturally sensitive comprehensive program, which included nurse case management plus targeted hepatitis education, incentives, and client tracking, performed significantly better than did a usual care program” ( Nyamathi et al., 2009 , p. 21). Thus the researchers recommended that public health program planners and funders use this type of program to promote increased completion of hepatitis A and B vaccinations for high-risk groups. Experimental studies are conducted in highly controlled settings, using a highly structured design to determine the effect of one or more independent variables on one or more dependent variables ( Grove et al., 2013 ). Sharma, Ryals, Gajewski, and Wright (2010) conducted an experimental study to determine the effects of an aerobic exercise program on pain like behaviors and neurotrophin-3 synthesis in mice with chronic widespread pain (see Table 5-1 ). These researchers found that moderate-intensity aerobic exercise had the effect of deep tissue mechanical hyperalgesia on chronic pain in mice. This finding provides a possible molecular basis for aerobic exercise training in reducing muscular pain in fibromyalgia patients. Problems and Purposes in Types of Qualitative Studies The problems formulated for qualitative research identify areas of concern that require investigation to gain new insights, expand understanding, and improve comprehension of the whole ( Munhall, 2012 ). The purpose of a qualitative study indicates the focus of the study, which may be a concept such as pain, an event such as loss of a child, or a facet of a culture such as the healing practices of a specific Native American tribe. In addition, the purpose often indicates the qualitative approach used to conduct the study. The basic assumptions for this approach are discussed in the research report ( Creswell, 2014 ). Examples of research topics, problems, and purposes for the types of qualitative research—phenomenological, grounded theory, ethnographic, exploratory-descriptive, and historical—commonly found in nursing are presented in Table 5-2 . Table 5-2 Qualitative Research Topics, Problems, and Purposes Type of Research Research Topic Research Problem and Purpose Phenomenological research Lived experience of children, asthma, health promotion, child health, chronic illness, fears of exacerbations, fears of being ostracized Title of study: “Children’s experiences of living with asthma: Fear of exacerbations and being ostracized” ( Trollvik et al., 2011, p. 295 ). Problem: “Asthma is the most common childhood disease and long-term medical condition affecting children ( Masoli et al., 2004 ). The prevalence of asthma is increasing, and atopic diseases are considered to be a worldwide health problem and an agent of morbidity in children significance]. . . . Studies show that children with asthma have more emotional/behavioral problems than healthy children… It has also been found that asthma control in children is poor and that healthcare professionals (HCPs) and children focus on different aspects of having asthma ( Price et al., 2002 ) [problem background]. . . . Few studies have considered very young children’s, 7-10 years old, perspectives; this study might contribute to new insights into their lifeworld experiences” [problem statement] ( Trollvik et al., 2011, pp. 295-296 ). Purpose: “The aim of this study was to explore and describe children’s everyday experiences of living with asthma to tailor an Asthma Education Program based on their perspectives. . . . In this study, a phenomenological and hermaneutical approach was used to gain an understanding of the children’s lifeworld” ( Trollvik et al., 2011 , p. 296). Grounded theory research Foster care, pregnancy prevention, prevention of sexually transmitted infections, patient-provider relationship Title of study: “Where do youth in foster care receive information about preventing unplanned pregnancy and sexually transmitted infections [STIs]” ( Hudson, 2012, p. 443 ). Problem: “Within the United States, approximately 460,000 children live in foster care, and adolescents comprise half of this population. . . . Children enter the foster care system as a result of sexual abuse, physical abuse, or physical neglect and abandonment ( Child Welfare League of America, 2007 ) [problem significance]. . . . With limited access to health promotion information and education about high-risk sexual behavior, it is not surprising that these young people have a high incidence of unplanned pregnancy and STIs compared with youth not in foster care [problem background]. Little research exists on the extent to which foster youth receive information about sexual activity from healthcare providers” [problem statement] ( Hudson, 2012, p. 443-444 ). Purpose: A grounded theory study was conducted to “describe how and where foster youth receive reproductive health and risk reduction information to prevent pregnancy and sexually transmitted infections. Participants also were asked to describe their relationship with their primary healthcare provider while they were in foster care” ( Hudson, 2012, p. 443 ). Ethnographic research Critical illness, mechanical ventilation, weaning, family presence, surveillance Title of study: “Family presence and surveillance during weaning from prolonged mechanical ventilation” ( Happ et al., 2007, p. 47 ). Problem: “During critical illness, mechanical ventilation imposes physical and communication barriers between family members and their critically ill loved ones [problem signicance]. . . . Most studies of family members in the intensive care unit (ICU) have focused on families’ needs for information, access to the patient, and participation in decisions to withdraw or withhold life-sustaining treatment. … Although numerous studies have been conducted of patient experiences with short- and long-term mechanical ventilation (LTMV), research has not focused on family interactions with patients during weaning from mechanical ventilation [problem background]. Moreover, the importance of family members’ bedside presence and clinicians’ interpretation of family behaviors at the bedside have not been critically examined” [problem statement] ( Happ et al., 2007, pp. 47-48 ). Purpose: “With the use of data from an ethnographic study of the care and communication processes during weaning from LTMV, we sought to describe how family members interact with the patients and respond to the ventilator and associated ICU bedside equipment during LTMV weaning” ( Happ et al., 2007, p. 48 ). Exploratory-descriptive qualitative research Intimate partner violence, abuse of spouse, supporting mothering, parent-child relationships, family health, providers’ perspective, social support Title of study: “Supporting mothering: Service providers’ perspectives of mothers and young children affected by intimate partner violence” ( Letourneau et al., 2011, p. 192 ). Problem: “Estimates of the percent of women with exposure to intimate partner violence (IPV) over their lifetimes by husbands, partners, or boyfriends range between 8% and 66%. . . . The high concentration of preschool-age children in households where women experience IPV… is a major concern [problem significance]. . . . Indeed, preschool-age children exposed to IPV may share many of the adjustment difficulties experienced by victims of direct physical and psychological abuse ( Litrownik et al., 2003 ) [problem background]. The degree to which children from birth to 36 months of age are affected by IPV, however, is not well understood. Even less is known of effective services and supports that target mothers and their young children exposed to IPV” [problem statement] ( Letourneau et al., 2011, p. 193 ). Purpose: “We conducted a qualitative descriptive study of service providers’ understandings of the impact of IPV on mothers, young children (birth to 36 months), and mother-infant/child relationships, and of the support needs of these mothers and young children” ( Letourneau et al., 2011, p. 192 ). Historical research Health disparities, childhood obesity, historical exemplar, prevention of infant mortality, public health nurses’ role Title of study: “Nurses’ role in the prevention of infant mortality in 1884-1925: Health disparities then and now ( Thompson & Keeling, 2012, p. 471 ). Problem: “Over the past several years, health policy makers have directed increased attention to issues of health disparities, an issue that has concerned the nursing profession for over a century[problem significance]. . . . Reutter and Kushner (2010) advocate that addressing health inequities are well within the nursing mandate and yet is an underutilized role [problem background]. . . . Nursing historical research lends insight into the complex health issues that nurses face today and may guide policy and nursing practice [problem statement]” ( Thompson & Keeling, 2012, p. 471 ). Purpose: The purpose of this historical study “was to evaluate the public health nurses’ (PHNs’) role with infant mortality during 1884-1925, specifically how nursing care impacted on conditions of poverty, poor nutrition, poor living conditions, lack of education, and lack of governmental policies that contributed to the poor health of infants a century ago” ( Thompson, & Keeling, 2012, p. 471 ). Phenomenological research is conducted to promote a deeper understanding of complex human experiences as they have been lived by the study participants ( Munhall, 2012 ). Trollvik, Nordbach, Silen, and Ringsberg (2011) conducted a phenomenological study to describe children’s experiences of living with asthma. The research topics, problem, and purpose for this study are presented in Table 5-2 . Findings from this study described two themes with five subthemes (identified in parentheses): fear of exacerbation (body sensations, frightening experiences, and loss of control) and fear of being ostracized (experiences of being excluded and dilemma of keeping the asthma secret or being open about it). The findings from this study emphasize that asthma management is not only a major issue for the children involved but also for their parents, teachers, and healthcare providers. Asthma educational programs need to be tailored to the individual child based on her or his perspectives and needs. This type of knowledge provides direction for accomplishing the QSEN (2013) competencies of providing patient-centered care. In grounded theory research, the problem identifies the area of concern and the purpose indicates the focus of the theory to be developed to account for a pattern of behavior of those involved in the study ( Wuest, 2012 ). For example, Hudson (2012, p. 443) conducted a grounded theory study to “describe how and where foster youth receive reproductive health and risk reduction information to prevent pregnancy and sexually transmitted infections (STIs)” (see Table 5-2 ). The following three thematic categories emerged from this study: “(a) discomfort visiting and disclosing, (b) receiving and not receiving the bare essentials, and (c) learning from community others” ( Hudson, 2012 , p. 445). The implications for practice were that primary care providers needed to provide time and confidential space for foster youths to disclose their sexual activities, and they (foster youths) need to receive more reproductive and risk prevention information from their school settings. In ethnographic research, the problem and purpose identify the culture and specific attributes of the culture that are to be examined, described, analyzed, and interpreted to reveal the social actions, beliefs, values, and norms of the culture ( Wolf, 2012 ). Happ, Swigart, Tate, Arnold, Sereika, and Hoffman (2007) conducted an ethnographic study of family presence and surveillance during weaning of their family member from a ventilator. Table 5-2 includes the research topics, problem, and purpose of this study. They concluded that “this study provided a potentially useful conceptual framework of family behaviors with long-term critically ill patients that could enhance the dialogue about family-centered care and guide future research on family presence in the intensive care unit” ( Happ et al., 2007 , p. 47). Exploratory-descriptive qualitative research is being conducted by several qualitative researchers to describe unique issues, health problems, or situations that lack clear description or definition. This type of research often provides the basis for future qualitative and quantitative research ( Creswell, 2014 ; Grove et al., 2013 ). Letourneau, Young, Secco, Stewart, Hughes, and Critchley (2011) conducted an exploratory-descriptive qualitative study of service providers’ understandings of the impact of intimate partner violence (IPV) on mothers and their young children to determine their needs for support (see Table 5-2 ). They found that these mothers and their children require more support than is currently available. In addition, the service providers had difficulty identifying interventions to promote and protect them and their children. The problem and purpose in historical research focus on a specific individual, characteristic of society, event, or situation in the past and usually identify the time period in the past that was examined by the study ( Lundy, 2012 ). For example, Thompson and Keeling (2012) examined the role of the public health nurse (PHN) in the prevention of infant mortality from 1884 to 1925 (see Table 5-2 ). They emphasized that studying the past role of PHNs and the health disparities then and now would increase our understanding of current nursing practice with regard to childhood health issues. They provided the following suggestions for nursing practice: “focus on health disparities in childhood obesity, in areas of environmental and policy change, and the development of social programs and education for families to support healthier living” ( Thompson & Keeling, 2012 , p. 471). Problems and Purposes in Outcomes Research Outcomes research is conducted to examine the end results of care ( Doran, 2011 ). This is a growing area of research in nursing to examine the relationships between the nursing process of care and patient outcomes. Table 5-3 includes the topics, problem, and purpose from an outcomes study by Ausserhofer and associates (2013) , who explored the relationship between patient safety climate (PSC) and selected patient outcomes in Swiss acute care hospitals. The adverse events or outcomes examined were medication errors, patient falls, pressure ulcers, and healthcare-associated infections that are common problems in U.S. hospitals ( Institute of Medicine, 2004 ). This study was guided by a common outcomes framework that focused on structure or work system, process of care, and patient outcomes (see Chapter 14 ). These researchers did not find a significant relationship of PSC to the selected patient outcomes. However, they stressed the need for additional research in this area and for selecting more reliable outcome measures. Table 5-3 Outcomes Research Topics, Problem, and Purpose Type of Research Research Topic Research Problem and Purpose Outcomes research Work system of patient safety climate (PSC) Process of care of nurses, workload work, and patient needs Outcomes of adverse events and patient satisfaction Title of study: “The association of patient safety climate and nurse-related organizational factors with selected patient outcomes: A cross-sectional survey” Ausserhofer et al., 2013, p. 240 ). Problem: “Today’s patient care in healthcare organizations is anything but safe, as between 2.9% and 16.6% of hospitalized patients are affected by adverse events such as medication errors, healthcare-associated infection, or patient falls. More than one-third of adverse events lead to temporary (34%) or permanent disability (6-9%) and between 3% and 20.8% of the patients experiencing an adverse event die [problem significance]. . . . As 37-70% of all adverse events are considered preventable, . . . harmful impacts on patients, such as psychological trauma, impaired functionality or loss of trust in the healthcare system as well as socio-economic costs, could be avoided ( Institute of Medicine, 2004 ). . . . Patient safety climate (PSC) is an important work environment factor determining patient safety and quality of care in healthcare organizations [problem background]. Few studies have investigated the relationship between PSC and patient outcomes, considering possible confounding effects of other nurse-related organizational factors [problem statement]” ( Ausserhofer et al., 2013, pp. 240-241 ). Purpose: “The purpose of this study was to explore the relationship between PSC and selected patients outcomes in Swiss acute care hospitals” ( Ausserhofer et al., 2013, p. 242 ).

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The Craft of Writing a Strong Hypothesis

Table of Contents

Writing a hypothesis is one of the essential elements of a scientific research paper. It needs to be to the point, clearly communicating what your research is trying to accomplish. A blurry, drawn-out, or complexly-structured hypothesis can confuse your readers. Or worse, the editor and peer reviewers.

A captivating hypothesis is not too intricate. This blog will take you through the process so that, by the end of it, you have a better idea of how to convey your research paper's intent in just one sentence.

What is a Hypothesis?

The first step in your scientific endeavor, a hypothesis, is a strong, concise statement that forms the basis of your research. It is not the same as a thesis statement , which is a brief summary of your research paper .

The sole purpose of a hypothesis is to predict your paper's findings, data, and conclusion. It comes from a place of curiosity and intuition . When you write a hypothesis, you're essentially making an educated guess based on scientific prejudices and evidence, which is further proven or disproven through the scientific method.

The reason for undertaking research is to observe a specific phenomenon. A hypothesis, therefore, lays out what the said phenomenon is. And it does so through two variables, an independent and dependent variable.

The independent variable is the cause behind the observation, while the dependent variable is the effect of the cause. A good example of this is “mixing red and blue forms purple.” In this hypothesis, mixing red and blue is the independent variable as you're combining the two colors at your own will. The formation of purple is the dependent variable as, in this case, it is conditional to the independent variable.

Different Types of Hypotheses‌

Types of hypotheses

Some would stand by the notion that there are only two types of hypotheses: a Null hypothesis and an Alternative hypothesis. While that may have some truth to it, it would be better to fully distinguish the most common forms as these terms come up so often, which might leave you out of context.

Apart from Null and Alternative, there are Complex, Simple, Directional, Non-Directional, Statistical, and Associative and casual hypotheses. They don't necessarily have to be exclusive, as one hypothesis can tick many boxes, but knowing the distinctions between them will make it easier for you to construct your own.

1. Null hypothesis

A null hypothesis proposes no relationship between two variables. Denoted by H 0 , it is a negative statement like “Attending physiotherapy sessions does not affect athletes' on-field performance.” Here, the author claims physiotherapy sessions have no effect on on-field performances. Even if there is, it's only a coincidence.

2. Alternative hypothesis

Considered to be the opposite of a null hypothesis, an alternative hypothesis is donated as H1 or Ha. It explicitly states that the dependent variable affects the independent variable. A good  alternative hypothesis example is “Attending physiotherapy sessions improves athletes' on-field performance.” or “Water evaporates at 100 °C. ” The alternative hypothesis further branches into directional and non-directional.

• Directional hypothesis: A hypothesis that states the result would be either positive or negative is called directional hypothesis. It accompanies H1 with either the ‘<' or ‘>' sign.
• Non-directional hypothesis: A non-directional hypothesis only claims an effect on the dependent variable. It does not clarify whether the result would be positive or negative. The sign for a non-directional hypothesis is ‘≠.'

3. Simple hypothesis

A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, “Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking.

4. Complex hypothesis

In contrast to a simple hypothesis, a complex hypothesis implies the relationship between multiple independent and dependent variables. For instance, “Individuals who eat more fruits tend to have higher immunity, lesser cholesterol, and high metabolism.” The independent variable is eating more fruits, while the dependent variables are higher immunity, lesser cholesterol, and high metabolism.

5. Associative and casual hypothesis

Associative and casual hypotheses don't exhibit how many variables there will be. They define the relationship between the variables. In an associative hypothesis, changing any one variable, dependent or independent, affects others. In a casual hypothesis, the independent variable directly affects the dependent.

6. Empirical hypothesis

Also referred to as the working hypothesis, an empirical hypothesis claims a theory's validation via experiments and observation. This way, the statement appears justifiable and different from a wild guess.

Say, the hypothesis is “Women who take iron tablets face a lesser risk of anemia than those who take vitamin B12.” This is an example of an empirical hypothesis where the researcher  the statement after assessing a group of women who take iron tablets and charting the findings.

7. Statistical hypothesis

The point of a statistical hypothesis is to test an already existing hypothesis by studying a population sample. Hypothesis like “44% of the Indian population belong in the age group of 22-27.” leverage evidence to prove or disprove a particular statement.

Characteristics of a Good Hypothesis

Writing a hypothesis is essential as it can make or break your research for you. That includes your chances of getting published in a journal. So when you're designing one, keep an eye out for these pointers:

• A research hypothesis has to be simple yet clear to look justifiable enough.
• It has to be testable — your research would be rendered pointless if too far-fetched into reality or limited by technology.
• It has to be precise about the results —what you are trying to do and achieve through it should come out in your hypothesis.
• A research hypothesis should be self-explanatory, leaving no doubt in the reader's mind.
• If you are developing a relational hypothesis, you need to include the variables and establish an appropriate relationship among them.
• A hypothesis must keep and reflect the scope for further investigations and experiments.

Separating a Hypothesis from a Prediction

Outside of academia, hypothesis and prediction are often used interchangeably. In research writing, this is not only confusing but also incorrect. And although a hypothesis and prediction are guesses at their core, there are many differences between them.

A hypothesis is an educated guess or even a testable prediction validated through research. It aims to analyze the gathered evidence and facts to define a relationship between variables and put forth a logical explanation behind the nature of events.

Predictions are assumptions or expected outcomes made without any backing evidence. They are more fictionally inclined regardless of where they originate from.

For this reason, a hypothesis holds much more weight than a prediction. It sticks to the scientific method rather than pure guesswork. "Planets revolve around the Sun." is an example of a hypothesis as it is previous knowledge and observed trends. Additionally, we can test it through the scientific method.

Whereas "COVID-19 will be eradicated by 2030." is a prediction. Even though it results from past trends, we can't prove or disprove it. So, the only way this gets validated is to wait and watch if COVID-19 cases end by 2030.

Finally, How to Write a Hypothesis

Quick tips on writing a hypothesis

1.  Be clear about your research question

A hypothesis should instantly address the research question or the problem statement. To do so, you need to ask a question. Understand the constraints of your undertaken research topic and then formulate a simple and topic-centric problem. Only after that can you develop a hypothesis and further test for evidence.

2. Carry out a recce

Once you have your research's foundation laid out, it would be best to conduct preliminary research. Go through previous theories, academic papers, data, and experiments before you start curating your research hypothesis. It will give you an idea of your hypothesis's viability or originality.

Making use of references from relevant research papers helps draft a good research hypothesis. SciSpace Discover offers a repository of over 270 million research papers to browse through and gain a deeper understanding of related studies on a particular topic. Additionally, you can use SciSpace Copilot , your AI research assistant, for reading any lengthy research paper and getting a more summarized context of it. A hypothesis can be formed after evaluating many such summarized research papers. Copilot also offers explanations for theories and equations, explains paper in simplified version, allows you to highlight any text in the paper or clip math equations and tables and provides a deeper, clear understanding of what is being said. This can improve the hypothesis by helping you identify potential research gaps.

3. Create a 3-dimensional hypothesis

Variables are an essential part of any reasonable hypothesis. So, identify your independent and dependent variable(s) and form a correlation between them. The ideal way to do this is to write the hypothetical assumption in the ‘if-then' form. If you use this form, make sure that you state the predefined relationship between the variables.

In another way, you can choose to present your hypothesis as a comparison between two variables. Here, you must specify the difference you expect to observe in the results.

4. Write the first draft

Now that everything is in place, it's time to write your hypothesis. For starters, create the first draft. In this version, write what you expect to find from your research.

Clearly separate your independent and dependent variables and the link between them. Don't fixate on syntax at this stage. The goal is to ensure your hypothesis addresses the issue.

5. Proof your hypothesis

After preparing the first draft of your hypothesis, you need to inspect it thoroughly. It should tick all the boxes, like being concise, straightforward, relevant, and accurate. Your final hypothesis has to be well-structured as well.

Research projects are an exciting and crucial part of being a scholar. And once you have your research question, you need a great hypothesis to begin conducting research. Thus, knowing how to write a hypothesis is very important.

Now that you have a firmer grasp on what a good hypothesis constitutes, the different kinds there are, and what process to follow, you will find it much easier to write your hypothesis, which ultimately helps your research.

Now it's easier than ever to streamline your research workflow with SciSpace Discover . Its integrated, comprehensive end-to-end platform for research allows scholars to easily discover, write and publish their research and fosters collaboration.

It includes everything you need, including a repository of over 270 million research papers across disciplines, SEO-optimized summaries and public profiles to show your expertise and experience.

If you found these tips on writing a research hypothesis useful, head over to our blog on Statistical Hypothesis Testing to learn about the top researchers, papers, and institutions in this domain.

Frequently Asked Questions (FAQs)

1. what is the definition of hypothesis.

According to the Oxford dictionary, a hypothesis is defined as “An idea or explanation of something that is based on a few known facts, but that has not yet been proved to be true or correct”.

2. What is an example of hypothesis?

The hypothesis is a statement that proposes a relationship between two or more variables. An example: "If we increase the number of new users who join our platform by 25%, then we will see an increase in revenue."

3. What is an example of null hypothesis?

A null hypothesis is a statement that there is no relationship between two variables. The null hypothesis is written as H0. The null hypothesis states that there is no effect. For example, if you're studying whether or not a particular type of exercise increases strength, your null hypothesis will be "there is no difference in strength between people who exercise and people who don't."

4. What are the types of research?

• Fundamental research

• Applied research

• Qualitative research

• Quantitative research

• Mixed research

• Exploratory research

• Longitudinal research

• Cross-sectional research

• Field research

• Laboratory research

• Fixed research

• Flexible research

• Action research

• Policy research

• Classification research

• Comparative research

• Causal research

• Inductive research

• Deductive research

5. How to write a hypothesis?

• Your hypothesis should be able to predict the relationship and outcome.

• Avoid wordiness by keeping it simple and brief.

• Your hypothesis should contain observable and testable outcomes.

• Your hypothesis should be relevant to the research question.

6. What are the 2 types of hypothesis?

• Null hypotheses are used to test the claim that "there is no difference between two groups of data".

• Alternative hypotheses test the claim that "there is a difference between two data groups".

7. Difference between research question and research hypothesis?

A research question is a broad, open-ended question you will try to answer through your research. A hypothesis is a statement based on prior research or theory that you expect to be true due to your study. Example - Research question: What are the factors that influence the adoption of the new technology? Research hypothesis: There is a positive relationship between age, education and income level with the adoption of the new technology.

8. What is plural for hypothesis?

The plural of hypothesis is hypotheses. Here's an example of how it would be used in a statement, "Numerous well-considered hypotheses are presented in this part, and they are supported by tables and figures that are well-illustrated."

9. What is the red queen hypothesis?

The red queen hypothesis in evolutionary biology states that species must constantly evolve to avoid extinction because if they don't, they will be outcompeted by other species that are evolving. Leigh Van Valen first proposed it in 1973; since then, it has been tested and substantiated many times.

10. Who is known as the father of null hypothesis?

The father of the null hypothesis is Sir Ronald Fisher. He published a paper in 1925 that introduced the concept of null hypothesis testing, and he was also the first to use the term itself.

11. When to reject null hypothesis?

You need to find a significant difference between your two populations to reject the null hypothesis. You can determine that by running statistical tests such as an independent sample t-test or a dependent sample t-test. You should reject the null hypothesis if the p-value is less than 0.05.

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Understanding the importance of a research hypothesis

A research hypothesis is a specification of a testable prediction about what a researcher expects as the outcome of the study. It comprises certain aspects such as the population, variables, and the relationship between the variables. It states the specific role of the position of individual elements through empirical verification. When conducting research, there are certain assumptions that are made by the researcher. According to the available information, the goal is to present the expected outcome after testing them.

A hypothesis should be precise and accurate

A hypothesis is a clear statement of the information that the researcher intends to investigate. It is thus a clear statement that is essential before conducting research.

Based on this aspect, the features of the hypothesis are listed below:

1. Conceptual

The statement of the hypothesis is based on a certain concept i.e. it could be either related to the theory or the pre-assumption of the researcher about certain variables i.e. educated guess. This leads to linking the research questions of the study. It helps the collection of data and conducting analysis as per the stated concept.

People who shop at speciality stores tend to spend more on luxury brands as compared to those who shop at a department store.

2. Verbal statement

The research hypothesis represents a verbal statement in declarative form. The hypothesis is often stated in mathematical form. However, it brings in the possibility of representing the idea, assumption, or concept of the researcher in the form of words that could be tested.

The capability of students who are undergoing vocational training programs is not different from the students undergoing regular studies.

3. Empirical reference

By building a tentative relationship among concepts, hypothesis testing provides an empirical verification of a study. It helps validate the assumption of the researcher.

The quality of nursing education affects the quality of nursing practice skills.

4. Tentative relationship

It links the variables as per assumption and builds a tentative relationship. A hypothesis is initially unverified, therefore the relationship between variables is uncertain. Thus a predictable relationship is specified.

Sleep deprivation affects the productivity of an individual.

5. Tool of knowledge advancement

With help of a hypothesis statement, the researcher has the opportunity of verifying the available knowledge and having further enquiry about a concept. Thus, it helps the advancement of knowledge.

The effectiveness of social awareness programs influences the living standards of people.

The hypothesis statement provides the benefit of assessing the available information and making the appropriate prediction about the future. With the possibility of verifiability and identifying falsifiable information, researchers assess their assumptions and determine accurate conclusions.

People who are exposed to a high level of ultraviolet light tend to have a higher incidence of cancer.

7. Not moral

The hypothesis statement is not based on the consideration of moral values or ethics. It is as per the beliefs or assumptions of the researcher. However, testing and prediction are not entirely based on individual moral beliefs. For example, people having sample moral values would take the same strategy for business management. In this case, it is not the desired objective to study the business management strategy.

Neither too specific nor too general

A hypothesis should not be too general or too specific.

‘Actions of an individual would impact the health’ is too general, and ‘running would improve your health’ is too specific. Thus, the hypothesis for the above study is exercise does have an impact on the health of people.

Prediction of consequences

The hypothesis is the statement of the researcher’s assumption. Thus, it helps in predicting the ultimate outcome of the thesis.

Experience leads to better air traffic control management.

Even if the assumption of the researcher is proven false in testing, the result derived from the examination is valuable. With the presence of null and alternative hypotheses, each assessment of the hypothesis yields a valuable conclusion.

Separating irrelevant information from relevant information

 A hypothesis plays a significant role ineffectiveness of a study. It not only navigates the researcher but also prevents the researcher from building an inconclusive study. By guiding as light in the entire thesis, the hypothesis contributes to suggesting and testing the theories along with describing the legal or social phenomenon.

Navigate research

A hypothesis helps in identifying the areas that should be focused on for solving the research problem. It helps frame the concepts of study in a meaningful and effective manner. It also helps the researcher arrive at a conclusion for the study based on organized empirical data examination.

Prevents blind research

A hypothesis guides the researcher in the processes that need to be followed throughout the study. It prevents the researcher from collecting massive data and doing blind research which would prove irrelevant.

A platform for investigating activities

By examining conceptual and factual elements related to the problem of a thesis, the hypothesis provides a framework for drawing effective conclusions. It also helps stimulate further studies.

Describes a phenomenon

Each time a hypothesis is tested, more information about the concerned phenomenon is made available. Empirical support via hypothesis testing helps analyse aspects that were unexplored earlier.

Framing accurate research hypothesis statements

For the deduction of accurate and reliable outcomes from the analysis, belong stated things should be noted:

• Should never be formulated in the form of a question.
• Empirical testability of the hypothesis should be possible.
• A precise and specific statement of concept should be present.
• The hypothesis should not be contradictory to the identified concept and linkage between the variables.
• A clear specification of all the variables which are used for building relationships in the hypothesis should be present.
• The focus of a single hypothesis should only be on one issue. No multi-issue consideration should be taken while building the hypothesis i.e. could only be either relational or descriptive.
• The hypothesis should not be conflicting with the defined law of nature which is already specified as true.
• Effective tools and techniques need to be used for the verification of the hypothesis.
• The form of the hypothesis statement should be simple and understandable. Complex or conflicting statement reduces the applicability and reliability of the thesis results.
• The hypothesis should be amendable in the form that testing could be completed within a specified reasonable time.
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• Volume 27, Issue 1
• Induction, deduction and abduction
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• http://orcid.org/0000-0003-4308-4219 David Barrett 1 ,
• http://orcid.org/0000-0003-0157-5319 Ahtisham Younas 2 , 3
• 1 Department of Health Sciences , University of York , York , UK
• 2 Memorial University of Newfoundland , St. John's , Newfoundland , Canada
• 3 Swat College of Nursing , Pakistan
• Correspondence to Professor David Barrett, Department of Health Sciences, University of York, York, UK; david.i.barrett{at}york.ac.uk

https://doi.org/10.1136/ebnurs-2023-103873

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• Nursing Research

Researchers often refer to the type of ‘reasoning’ that they have used to support their analysis and reach conclusions within their study. For example, Krick and colleagues completed a study that supported the development of an outcome framework for measuring the effectiveness of digital nursing technologies. 1 They reported completing the analysis through combining ‘an inductive and deductive approach’ (p1), but what do these terms mean? How can these methods of reasoning support nursing practice, and guide the development and appraisal of research evidence?

This article will explore inductive and deductive reasoning and their place in nursing research. We will also explore a third approach to reasoning—abductive reasoning—which is arguably less well-known than induction and deduction, but just as prevalent and important in nursing practice and nursing research.

Inductive reasoning

Induction, or inductive reasoning, involves the identification of cues and the collection of data to develop general theories or hypotheses. For this reason, inductive reasoning is often described as being ‘bottom-up’ reasoning. In the paper by Krick and colleagues mentioned previously, the inductive element of their work was taking findings from individual studies in a scoping review and using these to ‘inductively derive’ a first draft of their digital nursing outcomes framework. 1

It is easy to see how this study—and many other qualitative pieces of nursing research—frame themselves as having used inductive reasoning, with data from individuals building piece-by-piece into a general theory or overview of a phenomenon. However, the inductive nature of qualitative research is not universally accepted. Bergdahl and Berterö, discuss the ‘myth’ of inductive reasoning in qualitative research. 4 Though they agree that inductive methods require using direct observations or experiments to develop a general theory, they suggest that this is not what qualitative researchers do. Instead, they argue that the codes and themes developed during qualitative research are not tested scientifically, so do not represent true inductive reasoning. Instead, the generation of theory in qualitative research—they argue—requires a ‘creative leap’ which is well beyond the scope of an inductive approach. 4

Deductive reasoning

In their critique of induction in qualitative research, Bergdahl and Berterö argue that qualitative researchers should be more open to a deductive approach. 4 At a superficial level, deductive reasoning can be viewed as the opposite to induction, with specific conclusions drawn from general theories. So, with inductive reasoning often conceptualised as ‘bottom-up’, deductive reasoning can be viewed as ‘top-down’.

Some researchers have applied deductive reasoning within qualitative research as advocated by Bergdahl and Berterö, often by analysing qualitative data in the context of existing theory. A 2022 study by Andersson and colleagues explored critical care nurses’ experiences of working during the first phase of the COVID-19 pandemic. However, rather than starting their analysis of qualitative interviews with a ‘blank canvas’ (as would be the case in a study using inductive reasoning), the authors applied an existing person-centred practice framework as a lens through which the data could be better understood and interpreted. 5

Often, we see deductive reasoning linked to the hypothesis-testing nature of quantitative nursing research. A typical example is from Chang and colleagues, who completed a randomised controlled trial (RCT) in which the impact of a simulation-based mobile app on student learning was evaluated. 6 The authors developed a set of hypotheses (the ‘general theory’ that forms the foundation of deductive reasoning) related to student learning and satisfaction and then tested whether these were supported through analysis of outcomes in the intervention (mobile app) and control (usual paper-based learning) groups. Through analysis of findings, the authors demonstrated the use of a deductive approach to confirm a theory-based hypothesis. 6

Abductive reasoning

The two approaches discussed so far—induction and deduction—would seem to provide the foundation for much of what nurse researchers seek to do. Induction allows us to build theory from data, and deduction allows us to test theory and hypotheses. However, there is a third approach to reasoning — abduction—which is under-represented in the nursing evidence base, despite its importance to both research and practice. 7

With abduction, we generate new ideas from, and recognise meaning in, the information that is available to us. 8 The key point here is that we ‘generate’ new ideas, rather than test or verify them in the way that we should when using inductive or deductive reasoning. Abductive reasoning therefore plays an important part in both quantitative and qualitative research.

From a quantitative perspective, it is often abductive reasoning that we use to first develop the hypothesis or theory that we can then test deductively. A set of observations about an element of nursing practice may lead us—through abductive reasoning—to develop a hypothesis that best explains what we have seen. We can then apply the hypothetico-deductive approach to test this, as with the RCT by Chang and colleagues described earlier.

In qualitative research, abduction may offer the solution to the ‘myth’ of inductive reasoning proposed by Bergdahl and Berterö. The ‘creative leap’ that they state qualitative researchers must make to turn their data into general theories, 4 aligns well with the moment of discovery often associated with abductive reasoning.

Though abductive reasoning is a critical part of nursing practice and research, there is ongoing discussion about how effective it is when used as the only form of reasoning. Given the importance of producing research that supports evidence-based nursing care, it could be argued that suppositions based on abduction alone require testing by inductive and deductive methods before they can be generalised and implemented with confidence. 7

This will depend to an extent on what we look to do with the insights provided by abductive reasoning: we would not, for example, introduce a new nursing intervention based only on the ‘best fit’ hypothesis of abduction. We would want to robustly test this hypothesis through deductive and inductive methods to ensure that practice was evidence-based. However, where abduction leads us towards understanding the experiences of those in our care, or of nurses themselves, it may be that—even without inductive or deductive substantiation—these insights can offer valuable guidance.

In this paper, we have explored three approaches to reasoning—inductive, deductive and abductive—and how they can be applied in nursing research. The main characteristics of these approaches are summarised in table 1 . The key message for nurse researchers is that each approach has an important part to play in the generation, testing and implementation of new knowledge. In many cases, the research process will require nurses to deploy all three approaches, so an understanding of each is an important part of any nurse’s knowledge base.

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Summary of inductive, deductive and abductive reasoning

• Seibert K , et al
• Alteren J ,
• Hermstad M ,
• Nerdal L , et al
• Bergdahl E ,
• Andersson M ,
• Chang H-Y ,
• Chang Y-C , et al
• Karlsen B ,
• Hillestad TM ,

Twitter @barrett1972, @@Ahtisham04

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Provenance and peer review Not commissioned; internally peer reviewed.

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New Research First to Test 60-Year-Old Theory on Autism

By Emily Leclerc | Waisman Science Writer

*Note: The Travers lab has chosen to use identity first language in response to the growing preference for this type of language in the autism community. The language in this story reflects that choice.*

Autism is often associated with complex tasks like social processing and language and the later-developing brain regions that control them. But what if autism is more rooted in the earliest developing and most reflex-like part of the brain – the brainstem? This brainstem focused hypothesis about autism was put forth nearly 60 years ago by scientists but was left virtually untested due to the challenges of imaging the area in living individuals.

This new research by Brittany Travers, PhD , Waisman investigator and associate professor of kinesiology, is the first to officially test this hypothesis in children thanks to the advancements in brain imaging techniques. Her work reveals that the brainstem may indeed be central to core autism features. “It is a pivotal brain structure and deserves some attention, particularly in autism,” Travers says.

A stalk-like structure located at the base of the brain, the brainstem controls the body’s involuntary and automatic processes such as heart rate, blood pressure, breathing, digestion, and swallowing, among other functions. Even though we may not be aware of it, this autonomic nervous system – the name given to the specific bundle of nerves in the brainstem that regulate those processes – is in a constant state of responding to external and internal information.

The brainstem has reactions and sets of reactions to a variety of stimuli to try to keep our body in a state of balance, or homeostasis. Increase heart rate when this happens. Lower blood pressure when that happens. Disrupt digestion to reallocate energy when this happens. In turn, our behavior may be subtly or not so subtly affected by the underlying autonomic nervous system processing, even if we are not aware of it. So, what happens when this system is acting differently in a person?

“The brainstem is one of the earliest developing parts of the brain. So, it makes sense, in a neurodevelopmental condition like autism, that there would be differences that are happening in the brainstem that help explain the individual differences in autism,” Travers says.

Travers’ recent paper, “ Role of autonomic, nociceptive, and limbic brainstem nuclei in core autism features ” published in the journal Autism Research , shows that several core autism features, such as social communication differences and restrictive or repetitive behavior, may be directly related to the areas of the brainstem involved in autonomic functions, which may lead autistic individuals to experience or interpret the world’s stimuli in different ways.

Travers and her team utilized diffusion tensor imaging (DTI), a type of magnetic resonance imaging (MRI) that specifically measures how water diffuses through different tissue types, to look at the brainstem’s structure in autistic individuals and non-autistic individuals. Traditionally, the brainstem is a hard structure to image due to its location and the similarities in its tissue composition. DTI makes it possible to visualize the brainstem’s unique structure and tissue composition. Travers found differences in the autonomic nervous system’s structure between the two groups of participants that correlated with social communication differences and more restrictive or repetitive behavior.

DTI allowed Travers to focus specifically on the nuclei in the brainstem that are involved in our autonomic functions, pain systems, and the limbic system – which handles memory, emotion, and stress responses. “The autonomic nervous system is very much tied to the pain network and also to emotional structures. The original theories were also in line with these parts of the brainstem,” Travers says. “So, we chose to look at this particular grouping of brainstem structures.”

In particular, Travers found two nuclei in the brainstem that showed microstructural differences in autistic individuals and significant association with core autism features. The first nucleus, LPB, is involved in the pain processing system for internal organs and showed a significant relationship with an increase in repetitive behaviors. The second nucleus, PCRtA, is involved in digestion, swallowing, eating, and cardio-respiration and showed a meaningful relationship with more pronounced social communication challenges. Travers hypothesizes that structural changes in PCRtA could contribute to why it is fairly common for autistic individuals to have gastrointestinal discomfort and struggles eating or swallowing.

“This study was the first to be able to test this 60-year-old hypothesis in living children, and found that specific areas within the brainstem are linked to autism features,” Travers says. “This study directly tests and confirms this prior theory while also extending the literature to show that it is not all of the brainstem but some very specific nuclei that are involved in autonomic processing.”

Even the oldest and most rudimentary part of the brain still presents with great complexity. This work indicates that the brainstem likely plays an important role in the core features of autism but the mechanisms behind it are still a mystery. The study’s results did not reveal to Travers what exact changes to the brainstem are contributing to the core features. “We don’t know from our DTI if it is the myelination or the number of neurons or something else because we’re only looking at how water interacted with the tissues. This study helps us locate differences within the brainstem, but It brings up more questions than it solves,” Travers says. She hopes to answer those questions in future research.

“The brainstem is so important because it is this intersection between the brain and the rest of the body. So much information is transmitted through the brainstem and yet we’ve omitted it from most of our studies,” Travers says. “I’ve learned that the brainstem seems to be important in autism and it’s time that we really dug into this.”

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