Clinical Validation of Nursing Diagnoses

We are reprinting selected papers occasionally to share withreaders the history of the research work and the methodologiesinvolved. This article is reprinted from Monographs of theInvitational Conference on Research Methods for Vali-dating Nursing Diagnoses.

The purpose of this presentation is to address the areaof clinical validation of nursing diagnoses.

In the dictionary the word valid is given severalmeanings, all suggesting soundness or correctness. Tovalidate is to declare something valid, to officially sanc-tion, substantiate, or verify. In research we conceive ofvalidity as actually measuring what we say we are mea-suring. Campbell and Stanley (1963) suggested twotypes of validity, internal and external. Internal validityis the capacity to infer that the independent variable isrelated to the dependent variable. As one moves fromvery controlled studies with randomization and compa-rable groups to quasi-experimental and ex post factostudies, the control of extraneous variables becomesmore difficult, thus creating threats to internal validity.The second type, external validity, has to do with thegeneralizability of the research findings. Sample sizeand selection and environment affect the generalizabil-ity of research findings.

When we ask if a nursing diagnosis is clinically validwe want to know if the diagnosis was appropriatelymade to the exclusion of other diagnoses that may sharesome of the same characteristics. We want to know if,given certain patient phenomena, the diagnosis willhold from patient to patient. Finally, we want to know ifwe have accurately represented the observable data.That is, we want to know if the diagnosis truly repre-sents the behaviors and characteristics of the patient. Inthe process of making a nursing diagnosis, internal va-lidity is threatened because the data may or may notrepresent the actual patient circumstance. External va-lidity is affected if we cannot feel secure that the samediagnosis will be made given the same observationsacross patient populations.

International Journal of Nursing Terminologies and Classifications Volume 15, No. 4, October-December, 2004 123

Models of Clinical Validation

Clinical validation models have been developed andused. Gordon and Sweeney (1979) addressed metho-dologic aspects of identifying and standardizing nursingdiagnoses. They identified two relevant conceptual is-sues. One is the need to operationally define nursing di-agnostic terms when there is a lack of agreement abouthow nursing is conceptualized. The second conceptualconcern is in the choice between inductive and deductivemethods. Gordon and Sweeney stated that whichevermethod is used, a diagnostic label should be concise,clear, and clinically useful.

Gordon and Sweeney (1979) identified three modelsfor identifying and validating nursing diagnoses.

■ The retrospective identification model uses the accu-mulated experiences of nurses and includes the earlynational conference work. Variables that need to beconsidered with this method include nurses� educa-tional and experience level with patients who displayparticular nursing diagnosis behaviors as well as withthe concept of nursing diagnosis. The type of clinicalsetting and geographic location will also affect out-comes of the use of this model.

■ The nurse validation model focuses on determining ifdefining characteristics occur across cases and ifnurses agree on the appropriateness of labels. The di-agnostic abilities of the nurse continue as importantfor the success in the use of this model.

■ The clinical model focuses on data collected directlyfrom the patient. Again, the knowledge and expertiseof the nurse collecting the data for use in diagnosis isimportant in this validating effort. The nurse�s abilityto communicate clearly in writing or verbally be-comes important. An assessment protocol, as well asguidelines for diagnoses and data management, be-come important in achieving a successful end result.

Tanner and Hughes (1984) also addressed the prob-lem of clinical validation. They contended that �the pat-tern of cues that occur concurrently and the strength of

A Second Look

Clinical Validation of Nursing Diagnoses

Nancy S. Creason, PhD, RN

the relationship between cues and diagnoses are vali-dated through repeated, systematic observations of alarge sample of patients �(p. 32). They labeled the ap-proach of the National Conference Group in develo-pingfactual diagnosis as �group empiricism.� This approachmaximized the contribution of expert clinicians whilepotentially limiting the development of a comprehensivetaxonomy because it depended on the expertise of thenurses in attendance. There was also the possibility of in-troducing individual bias because of dependency on thememory of nurses. They suggested that systematic in-vestigations are needed to reduce bias in validating cuepatterns and to identify high frequency cues and etiolo-gies. They offered some helpful advice in approachingthe problem of validating nursing diagnoses by obtaining empirical evidence. This can be done by in-cluding the clinician in the design and conduct of nurs-ing diagnosis research. Clinicians can help focus studiesby identifying common cue patterns and by helping todevelop standardized observational methods. The focusof inquiry must be carefully identified. Finally, assess-ment measures that will yield quality data must be con-structed or adapted. They suggested that tools must beuseful to the practitioner as well as the researcher and at-tention to this will strengthen research as well as patientcare.

Fehring (1986) suggested one reason for what hecalled a �validity gap� between the NANDA list and ac-tual use in clinical practice was the very nature by whichthe original labels were generated, as well as a paucity ofvalidity studies. He offered what he termed practicalmethodologies based on Gordon and Sweeney�s models.He prepared two models to be used in the validation ofnursing diagnoses.

The first model, the Diagnostic Content ValidityModel, involves three steps. First, 25 to 50 experts rate ona 1�5 Likert scale how well specific characteristics repre-sent a defined diagnosis. Second, a Delphi technique isused to establish consensus among experts. Third,weighed ratios are calculated for each characteristic. Theweights assigned to each response are summed and di-vided by the total number of responses. Those with a

124 International Journal of Nursing Terminologies and Classifications Volume 15, No. 4, October-December, 2004

A Second Look

ratio of .75 or above are labeled �critical� and those witha ratio of less than .50 are discarded. Finally, a total diag-nostic validity score is calculated by summing the indi-vidual characteristic ratings and averaging the results.

Fehring�s second model, the Clinical Diagnostic Valid-ity Model, involves attaching quantifiable labels to Gor-don and Sweeney�s nurse validation model. Two expertclinicians assess patients with a previously identified di-agnosis. Each checks the frequency of the previouslyidentified characteristics with those manifested by thepatient; weighted interrater reliability ratios are calcu-lated and, as with the diagnostic content validity modes,ratios determine which defining characteristics are re-tained. Fehring (1986) also offered a validity modelcalled the etiological correlation ratio arrived at by calcu-lating correlation coefficients to reflect the strength of theetiology�s ability to predict the existence of a diagnosis.This means both the diagnosis and etiology must bemeasured. It is not clear, however, how etiology can pre-dict diagnosis.

At the eighth NANDA Conference, Hoskins (1988)described three phases of validating nursing diagnoses.First, concept analysis is used to clarify the diagnosisthrough the literature and theory. This phase yields a listof defining characteristics. The second phase she calledthe expert validation phase where the lists of characteris-tics are reviewed by experts and agreement is sought.The third phase is clinical validation, which would testwhether or not the findings from the first two phases areactually found in clinical practice. She suggested a modelwhere two expert diagnosticians independently assessand diagnose a known patient population and calculatetheir agreement with the goal of developing a useful listof major and minor defining characteristics.

Validation Research

Of seven validation papers in the Proceedings of theseventh NANDA Conference (McLane, 1987), we find astrong focus on validity studies, three used Fehring�s clin-ical validation model and one used his diagnostic contentvalidity model. One of the remaining three used a Delphi

technique to identify new diagnostic categories (wellness)and two used retrospective data analysis to validatedefining characteristics. Of the 17 poster presentations re-lated to validation, 11 were concerned in some way withclinical validation, 1 used Gordon�s model, 2 used theFehring model, 6 used other or combined methods.

Gordon�s contribution to the 1985 Annual Review ofNursing Research also helps focus some issues related tovalidation. She identified the problem of varied concep-tual definitions of nursing diagnoses and found investi-gators bypassed the conceptual problems and focusedon naming, defining, and testing. She suggested that theidentification and validation of diagnostic concepts re-quires �a large number of studies in which there is ex-plicit definition of the construct (nursing diagnosis)being studied, sampling and description of clients andcontexts, and clear reports of reliability and validity esti-mates� (p. 130). Gordon�s examination of several largestudies revealed some specific areas of agreement andfound areas of disagreement. Frequency of usage wasthe main criterion used in these large studies and theirfindings were all compared with the NANDA listings.

A relatively small number of diagnoses were used atfairly high frequencies across the studies. Some of theseincluded impaired mobility, self-care deficit, pain, anxiety, andimpairment of skin integrity. Few studies were found thatfocused on etiologies. Gordon (1985) concluded that fac-tors affecting her ability to summarize across studies in-cluded a lack of consistency in labels, definitions, and di-agnostic criteria, as well as variations in reliability andvalidity estimates in analyses and reports. She indicatedone research priority should be the refinement of the present concepts. Another priority should be the identifica-tion of what Gordon called �predictor variables� or vari-ables that will affect certain diagnoses (e.g., age, medicaldiagnoses, clinical environment). She also advocated theneed to conduct descriptive studies to identify etiologies.

Hoskins et al. (1986) studied nursing diagnoses inchronic illness and developed a methodology for clinicalvalidation using a human needs conceptual frameworkto develop a needs assessment tool that collected expertinput for content validity. Expert judges examined the


data to determine clusters of signs and symptoms andrelated diagnoses on 60 subjects. Data on a second groupof 108 subjects were then compared to the first findingsusing a computer. Their list of 51 nursing diagnoses waslabeled valid; however, few of the labels correspondedwith the NANDA labels.

More studies have focused on single diagnoses. Somefocused directly on a concept and patient manifestationsof that concept as identified by nurses while others fo-cused on a particular NANDA diagnosis and sought toconfirm it by assessing patients or examining records.

Baer, Delorey, and Fitzmaurice (1984) reported on theapplication of the self-care deficit classification system forpatients with spinal cord injuries. Clinical coordinators onspinal cord injury services assessed 110 patients using Mc-Court�s system for evaluating self-care. They found that asfamiliarity with the tool increased, the ability to identifydeficits improved. They determined the 60% agreementfound per deficit per patient was not satisfactory.

Balistrieri and Jiricka (1984) studied role disturbance.Six clinical specialists identified signs and symptoms ofrole disturbance using the Delphi method. Six other clini-cal specialists identified a problem label based on thesigns and symptoms. Then critical care nurses identified36 patients displaying behaviors suggesting role distur-bance and recorded whether the previously identifiedsigns and symptoms were present. The nurse groupsfound they were unable to establish consensus on criticaldefining chacteristics.

Dalton (1985) examined records of 100 Veterans Ad-ministration patients with decreased cardiac output for sub-jective and objective evidence to support the NANDAdefining characteristics. She found a lack of consistencyand 69 out of the 100 records did not reflect NANDAnomenclature.

Kim et al. (1984) also focused on clinical validation ofcardiovascular nursing diagnoses. Staff nurses used thethird NANDA conference list of 45 nursing diagnosesand others selected as representative of patients with car-diovascular disorders by clinical specialists. Staff nursesassessed a random selection of patients (N = 158) andrecorded data on diagnoses including label, etiologies,

signs and symptoms, and interventions. Clinical special-ists then reassessed 20% of the patients. On average, clin-ical specialists made more diagnoses and identified moredefining characteristics than staff nurses. Researchersconcluded the most frequently identified diagnoses hadface and content validity.

Guzetta and Forsyth (1979) were interested in devel-oping a typology of stress as observed in patients withacute illness. Patients and nurses were interviewed to ob-tain relevant parameters. Guzetta and Forsyth had diffi-culty fitting their data into a predetermined stressor as-sessment sheet. As well, they noted stress would varywith patient variables such as age and clinical diagnoses.

Lo and Kim (1986) worked to establish content valid-ity of sleep pattern disturbance. After a literature reviewdetermined 33 defining characteristics of sleep pattern dis-turbance, baccalaureate-prepared RNs rated each charac-teristic on a 5-point scale as to frequency of occurrence.Finally, 25 hospitalized patients with cardiovascularproblems were assessed by the investigator using an as-sessment guide containing the 33 defining characteristicsfrom phases one and two. Statistical correlations wereused to test homogeneity and quality of items. Fifteenitems were identified as having high internal consistencyand were considered essential defining characteristics.There was fairly high agreement with the NANDAnomenclature.

York and Martin (1986) focused on clinical validationof respiratory nursing diagnoses. First, nurse expertswere asked to rate appropriateness of etiologies anddefining characteristics. Then, researchers identified thepresence or absence of the defining characteristics fromcare plans of patients with respiratory diagnoses. Nurseswho made the diagnoses were interviewed to determinewhich defining characteristics were present when the di-agnoses were made. There were high agreement levelson some characteristics. Use of a care plan audit and thenurse interview helped to provide more complete data.

Fadden, Fehring, and Kenkel-Rossi (1987) focused onclinical validation of anxiety using Gordon and Sweeny�sclinical validation model as modified by Fehring.Ninety-one patients with a diagnosis of anxiety were as-


A Second Look

sessed by clinical nurse specialists using a checklist ofNANDA defining characteristics. As well, the Speil-berger State-Trait Anxiety Inventory was used. None ofthe subjective or objective indicators reached Febring�scritical cut off of 0.50. Depending on the patient, low-to-moderate correlations between the inventory scores andfrequency indicators were found. Since anxiety is arather elusive concept, this use of an established tool hasmerit in clarifying the diagnosis. Gordon�s review andthese studies help us identify procedures as well as prob-lems and issues in clinical validation of nursing diag-noses. We see a majority of researchers going to the liter-ature and nurse experts first to help conceptualize anddefine the diagnosis under study. A few studies used aconceptual framework to guide the study especially iftool development, data collection, and analysis were in-volved. A lack of a common conceptual base as well as alack of taxonomic consistency in the diagnostic cate-gories as we now know them continue as problems weneed to address.

The lack of a standard assessment protocol in nursingis an especially difficult issue when working with largeinpatient and nurse populations. A universally acceptedand used nursing data base, as advocated by Werley andLange (1988), would be most helpful in our clinical vali-dation efforts.

Methodologies that incorporate actual patient data ascollected by staff nurses as well as clinical specialists arebeing used. Variations in studies need to be examined toestablish more standard methods. The knowledge, skill,and ability of nurses who make the assessments and di-agnoses as well as use the research tools all become ex-tremely important. Reliability is an especially importantissue. We see the use of staff nurses, clinical nurse spe-cialists, and �experts� to collect data. Some researchersmade an effort to train data collectors but many did not.There is no mechanism to validate �expert� knowledge.

Patient behaviors are also subject to broad interpreta-tion depending on patient variables. Multiple patientcharacteristics (e.g., age, sex, educational level), as well asthe patients� health state, medical diagnoses, and thehealthcare setting will affect observable behaviors. Some

characteristics can be more or less objectively measuredsuch as height, weight, and range of motion, while oth-ers such as reported cues, change in mental state, crying,and mood changes are quite subjective even to thehighly experienced, knowledgeable nurse. Time of as-sessment is important to consider in some patient popu-lations; even a few minutes or hours may mean a changein cues.

The clinical setting and its geographic location alsoare factors to be reckoned with in clinical validation. Fo-cusing on one diagnosis in one particular type of patientin one locale is useful but not sufficient. We need to espe-cially consider replicating studies with a variety of pa-tient populations in various locales (nationally and inter-nationally). With so many diagnoses this may be difficultto implement. In my review I found efforts to validate la-bels and defining characteristics but little focus on etiolo-gies. If etiologies are the focus of our interventions wemust also focus our research there. The importance ofthis must be stressed.

There is also the potential of congruity or disparity ofthree phenomena that we somehow need to understandand blend. These are the NANDA statements (and po-tential new diagnostic statements); the nursing diagnosesas identified by practicing nurses, the stuff upon whichday-to-day nursing care is based; and the patient charac-teristics and behaviors that serve as the data base formaking diagnoses. Some studies focused specifically onNANDA statements, some used what was found in theclinical setting, and others combined NANDA and non-NANDA statements.

Conceptualization and Definition

A recurring theme in this analysis of studies was thelack of a common theoretical or conceptual base. Giventhe eclectic nature of nursing theoretical and conceptualframeworks, there is no quick and easy solution to thisproblem. Nursing can, however, do a better job of defi-nition. It is imperative that we work toward clearer defi-nitions of all components of nursing diagnoses. I believethis research agenda is central to clinical validation.


However, since we cannot put other clinical validationefforts on hold while we do this for all diagnoses, re-searchers conducting clinical validation research must,at the very least, clearly define the terms used so theyare consistently understood by all those involved indata collection.

The research efforts of others, as well as our initialwork on validation of impaired physical mobility (Creason,Pogue, Nelson, & Hoyt, 1985), made it clear that defini-tion stood in the way of our ability to analyze and reportfindings. As a result, we set about developing a proto-type tool that can be used to develop conceptual and op-erational definitions of nursing diagnoses which thencan be used in clinical validation studies. Conceptualand operational definitions for the etiologies and defin-ing characteristics of impaired physical mobility were de-veloped based on empirical data from experience andthe literature. These were then incorporated into a toolthat asked the respondent to agree or disagree with thedefinition and provide suggestions for change. The toolwas given to 10 nurses with advanced education and ex-pertise in the care of patients with mobility problemsand in the use of nursing diagnosis. This was a multistepprocess focusing first on etiology definitions, then ondefinitions of the defining characteristics. Etiologic state-ments were received, reworked, and resubmitted to theparticipants for a second round. The defining character-istics were responded to, separately, one time. Both setswere finally returned to all participants for a final round.

The next step, as we perceive it, is to take the refineddefinitions to a larger group of nurses across the countrywho work with a variety of patients with mobility prob-lems to further refine them. Then, the refined diagnosis canbe taken to the clinical area for testing by staff nurses andclinical specialists. I perceive using a modification of Gor-don and Sweeney�s clinical and nurse validation modelsand the studies cited above lend support for this approach.

Triangulation

Because of the reality of our research environmentsand the state of our knowledge, we have suggested that

approaches described above all have serious limitations.One way to deal with problems in clinical validationmight be to employ triangulation. Triangulation has re-ceived recent attention in the nursing literature. Mitchell,writing in Advances in Nursing Science in 1986, suggestedthat triangulation is a useful methodological strategy instudying the complex, dynamic phenomena of humanhealth behavior. Duffey, in a 1987 Image article, discussedmethodologic triangulation as a way to merge qualita-tive and quantitative research methods. Sohier (1988), inthe Western Journal of Nursing Research, also advocatedthe use of triangulation as a way of studying the multidi-mensional nature of the phenomenon of nursing.

What is triangulation? According to the dictionary it isa surveying technique in which a region is divided into aseries of triangular elements based on a line of knownlength so accurate measurements of distances and direc-tions may be made by using trigonometry. In navigation,triangulation is the location of an unknown point byforming a triangle, having the unknown point and twoknown points as vertices. One can certainly apply thenavigational metaphor to nursing diagnoses research bythinking through how to effectively use what is known todetermine the unknown (always keeping in mind thereare unexplained phenomena such as the Bermuda trian-gle!). This approach comes from the social science re-search literature. Campbell and Fiske (1959) described thestrategy as convergent methodology or one of multi-method/multitrait. Later, Webb, Campbell, Schwartz,and Sechrist (1966) applied the term triangulation.

Denzin (1978) further advocated triangulation, whichhe defined as �the combination of methodologies in thestudy of the same phenomenon� (p. 291). These view-points focus on the idea that qualitative and quantitativeresearch can compliment rather than oppose. Denzin(1970) identified four types of triangulation:

1. Data triangulation has three types: time, space and per-son. These in turn have three levels: aggregate, inter-active, and collectivity.

2. Investigator triangulation, where there are multiplerather than single observers of the same object.


A Second Look

3. Theory triangulation, in which multiple theoretical per-spectives are used as opposed to a single perspectiveof the same set of objects.

4. Methodologic triangulation, which may be broken downinto within-method and between-method triangula-tion. Data and methodologic triangulation can be es-pecially useful approaches to clinical validation ofnursing diagnoses.

The basic idea of triangulation is that approaching aphenomenon from several viewpoints will yield a betterunderstanding of the phenomenon than if it is ap-proached from only one viewpoint. Jicks (1979) empha-sized a basic underlying assumption regarding triangu-lation: �The effectiveness of triangulation rests on thepremise that the weaknesses in each single method willbe compensated by counter-balancing the strengths inanother triangulation purports to exploit the assets andneutralize, rather than compound the liabilities� (p. 604).Another important point to keep in mind is that triangu-lation may be as useful in uncovering differences orunique variances as it is in identifying similarities.

Data Triangulation

Data triangulation means that multiple sources ofdata are used to focus on the same phenomenon. Time,space, and person data types refer to sources of datasuch as particular subjects from particular populations indifferent places at different times of data collection (day,week, month, year). Levels of person analysis are aggre-gate, in which data are collected on individuals withoutestablished social links; interactive, in which the level ofunit analysis is the interaction of persons (rather thanperson or group); and collectivity, where the observa-tional unit is the organization, group, community, etc.(Denzin, 1970).

Weatherall and Creason�s (1987) study of spiritual dis-tress included literature on the concept of spiritualitywritten by nurses, nursing care plans developed by RNsin a baccalaureate program who had formal class workon the nursing process and nursing diagnosis, and a log

kept by an RN master�s student as she cared for patientswith spiritual distress. The method was content analysisbut these data differed by source and were collected atdifferent locations and times by different data collectors.This process brought to bear three different person per-spectives with time and space variations.

Using the literature to validate diagnoses is com-mon and can be useful providing we keep in mind thatthe written word is not sacred and may not be true.The nurse writer may or may not be an expert and theempirical base of the written word may not be valid.Also, we see how literature relies on other literaturethat may or may not relate to reality. Recognizing theselimitations, one can take the literature perspectives andsee if they relate to the clinical reality as defined bynurses.

It is important to remember that the nurse�s knowl-edge about nursing diagnoses in general, the particularconcept or phenomenon of interest, and assessment abil-ity all affect how data are collected and evaluated priorto making a nursing diagnosis. This problem can be ad-dressed by offering training sessions to nurses who willcollect and record data and by using clinical specialistswho have advanced knowledge in specific areas as wellas in nursing diagnosis.

Using the spirituality study as an example, we wereable to look at the various data sources and the NANDAnursing diagnosis of spiritual distress and identify whichaspects of the phenomenon were similar and which werenot similar. This process then allowed us to raise moredefinitive questions and recommend further research.

Methodologic Triangulation

Methodologic triangulation refers to the use of severaldifferent methods in a single study. In the social scienceliterature on triangulation, we see frequent reference tothe use of field work and survey methodologies. The lit-erature further identifies within and between methods.Within is the use of several examples of the same type ofdata collection methods, such as several scales to mea-sure the same phenomenon. For example, one scale may


measure only certain aspects of a phenomenon so one ormore scales that measure the remaining aspects wouldalso be used. Across or between method is more com-plex in that different but complementary methods areused to measure the same phenomenon with the goal ofachieving convergent validity.

Our work on validating impaired physical mobility hassome characteristics of this method as well as character-istics of data triangulation. Since definition was identi-fied as a problem, that was approached first using the lit-erature and expert knowledge, then the Delphi-likeapproach using nurse experts to establish definitions ofimpaired physical mobility.

Consensus has now been achieved at this level. Next,the definitions will be refined into a simpler tool formatand a larger population of nurses with less well definedexpertise in the area of nursing diagnosis who work withpatients with impaired physical mobility in a variety of set-tings will be asked to agree or disagree with the defini-tions. Finally, data on actual use of the diagnosis in aclinical environment will be collected.

Mitchell (1986) pointed out that when using method-ologic triangulation there needs to be adherence to re-search principles. First, there needs to be a clearly fo-cused research question. Additionally, the strengths andweaknesses of each method should complement eachother, methods should have relevance to the phenomenaunder study, and ongoing evaluation of the methodschosen is needed as the study progresses to see if the firstthree principles hold. Jicks (1979) nicely addressed theissue of convergence and how data can be analyzed todecide if there is convergence, i.e., agreement, or not.This still requires researchers to bring to bear their ownknowledge and expertise.

Jicks also pointed out when there is convergence onecan have more confidence that findings are probably nota result of a method artifact. It can lead to new ways tocapture a problem as well to help identify deviant as-pects of a phenomenon. These positives must be bal-anced with limitations, especially that replication is diffi-cult and that asking the wrong question will still yieldwrong results.

Theoretical Triangulation

Gordon (1985) suggested conceptual bases of nursingdiagnosis are varied and may be viewed in as manyways as we have major theorists. The theorist work as re-ported in Hurley (1986) and McLane (1987) while mov-ing toward consensus does not suggest a unity in per-spective. Recognizing efforts toward a theoretical base,the taxonomic efforts, likewise, continue to suffer fromthis lack of a theoretical/conceptual framework. In theProceedings of the sixth NANDA conference, Kim (1986),Kritek (1986), Gordon (1986), Kirk (1986), and others al-luded to this problem. Given the multitheory conceptualapproach to nursing, theoretical triangulation is an areain need of exploration.

Denzin (1970) suggested a multiple path approach tofundamental theory which he called a �sensitizing-triangu-lated� methodology. Instead of formulating single empiri-cal definitions of key concepts, the investigator works withseveral definitions of central concepts. Doing this shouldlead to adopting different methodologies to capture the rel-evant features of the concepts. Once the distinctive natureof the concepts are found, operationalization can occur.

Application of Triangulation

I thought it might be useful to construct a plan to vali-date a single diagnosis using triangulation (see Table 1).We first examine the literature for conceptual clarifica-tion and then move to expert nurse judgments as to theappropriateness of etiologies and defining characteristicsof the diagnosis as well as obtaining operational defini-tions. The weakness of potential inaccuracies in the liter-ature ran be checked by using input from nurse experts.The weakness of a small number of experts can be over-come by next obtaining a large sample of nurses whocare for patients likely to have the diagnosis from acrossthe country. The focus is, at this point, still on seekingagreement about terminology and definitions. Followingthis clarification, clinical units where patients are ex-pected to have the diagnosis in agencies where nursingdiagnosis is practiced can be identified.


Chart audits can be conducted to determine theuse of the diagnosis as well as to identify assessmentdata to support it. One may want to make an effort tofirst use a unit with a standardized assessment formatand where staff nurses have had nursing diagnosistraining. This draws upon the day-to-day practice ofstaff nurses. To deal with inadequacies of recordeddata, one may also want to consider interviewingeach nurse for her/his definition of a particular diag-nosis and to have her/him identify major and minordefining characteristics. Additionally, master�s-pre-pared nurses who are experts in the concept area andin the use of nursing diagnoses can randomly selectone to two patients per week over a period of severalweeks to independently assess and diagnose. If thepatients are in a rapidly changing acute setting, thisassessment should be done within hours of the staff

A Second Look

Table 1. Model for Application of Triangulation

Clarification of Terminology and Definitions■ Conceptual clarification via literature review■ Expert nurse judgments on appropriateness of etiologies an

defining characteristics and operationalizing definitions(check on strength or weakness of literature)

■ Large sample of nurses caring for patient type from a vari-ety of settings and geographic locations (compensate forsmall number of experts)

Clinical Applications■ Chart audits on units with patients expected to have the di-

agnosis for use and assessment data to support■ Interview nurses for definition of diagnosis and

major/minor defining characteristics (compensates for inad-equacy of recorded data)

■ Master�s-prepared �expert� nurses randomly assess and di-agnoses patients (compensates for potential lace of expertiseof staff nurses)

■ Experts write case studies (provides comprehensive viewand richness)

Data Analysis■ Qualitative■ Quantitative

nurses� assessment. The timing will depend some-what on the patient characteristics. For example,when assessing confusion minutes and hours may beimportant. Clinical specialists can also write a casestudy of a small number of patients over a period ofseveral contacts. The independent assessment and di-agnosis efforts will help eliminate observer bias thatmay occur in a case study, but the latter will provide arich and more comprehensive view of the patientwith a particular diagnosis. In this effort, staff nurses�assessments and diagnoses as recorded in the chartreflect findings from multiple patients over time butthe nurse expertise may not be high in assessment, di-agnosis, or ability to communicate data collected anddiagnoses made. This can be balanced by the expertnurses assessing, diagnosing, and carefully docu-menting data on a smaller number of some of thesame patients. I believe it is critical to examine howdiagnoses are actually being made by staff nurses as apart of our clinical validation effort. Not doing so ig-nores the real world and will serve to keep nursingdiagnosis in isolation and unused. Using data fromstaff nurses will help identify areas of clear agreementand areas in need of careful evaluation. As well, use-ful diagnostic statements and the need for revision ofdiagnostic statements or the development of newones should become evident.

Some of these data are derived from qualitative mea-sures and will require qualitative analysis, others will beavailable for quantification. Overall, by bringing all thesedata sources together, we should obtain a fairly compre-hensive picture of a target diagnosis that will likely in-clude areas of agreement and areas of disagreement butwill, I think, provide clear indications of the direction offuture research.

In summary, issues in clinical validation of nursing di-agnoses that create difficulty for us in making data andmethodologic choices are multiple. Triangulation is oneapproach that may help us deal with these issues andmove forward. By using the concept of triangulation wecan approach the clinical validation of nursing diagnosesin a more comprehensive manner.


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Clinical Validation of Nursing Diagnoses