Joumal of Advanced Nursing, 1992,17,1171-1181
Diagnostic reasoning among second-year nursing students Krystyna M Cholowski RN MEd Stud Assisiani Leciurer, Deparimeni of Commumiy and Menial Healih Nursmg, Umverstiy of Newcasile
and Loma K S Chan BEd(Hons) PhD Associate Professor, Deparimeni of Educahon, University of Newcastle, Callaghan, New Souih Wales, Auskalia
Accepted for pubhcahon 17 February 1992
CHOLOWSKI K M & CHAN L K S (1992) journal of Advanced Nursmg 17,
1I71-II81 Diagnostic reasoning among second-year nursing students This paper reports on a study mvestigatmg the relationship of nursing students' approaches to leammg and processing of information, science content knowledge, ability in interpreting and organizing clmical data (nursmg assessment), and logical reasomng ability with the accuracy and quabty of the nursing diagnosis made in a simulated diagnostic reasonmg task One hundred and sixty-mne second-year pre-service nursing students participated in the study Results of path analyses mdicated a set of pathways from surface approach to low-quality nursing diagnosis that reflected less competent diagnostic reasonmg, and a second set from deep/achievmg approach through content knowledge and logical reasonmg to higher-quality nursing diagnosis that reflected more competent diagnostic reasonmg The implications of these findings for nurse education are discussed
DIAGNOSING NURSING PROBLEMS
and nurses' approaches to information proeessmg (see Table 1)
Reeent researeh in nursing has suggested that an important dimension of professional nursing rests on the eompetenee of nurses to diagnose nursmg problems aeeurately Diagnosing elient problems is required daily and has been ldenhfied by nursing bodies as a enhcal eomponent of nursing praetiee (Gordon 1980, Jones 1988) In this study, a model of diagnostie reasomng in nursmg IS explored The model incorporates ftve interrelated elements The five elements are presumed to measure vanous behaviours and aehvities earned out by nurses m diagnoshc reasonmg These melude nursmg diagnosis, logical reasoning, eontent knowledge, nursing assessment
Nursing diagnosis Nursing diagnosis as used m this paper refers to the label given to the patient's health problem In nursing, the tenn 'diagnosis' is used m broad eontext rather than m the narrow sense of ldenhfying disease Nursing diagnoses do not label medieal entities sueh as disease processes that require surgery or presenphve drugs Nursing diagnoses refer to eonditions or behaviours that are relevant to health management and ean be helped or dianged by nursing aetion A nursing helps g diagnosis g p nurses to communicate
Correspondetxe Krystyna M Cholowski Assistant lecturer Deparhnent of ^lgar and COnase information about t h e pahent's Current Commumty and Mental Health Nursmg University of Newcastle Callaghan New , ,,, ^ ^ , , , , . . -ri.
L
health state and provides a basis tor pahent care The 1171
KM CholowsktandLKS Chan Table 1 3P Model of diagnosic reasoning m nursmg
knowledge a nurse brmgs to the diagnoshc task plays a cntical role m determining how the problem will be mterpreted and which items of dimcal information will be Process Process attended to Thus, reference to pnor content knowledge is Presage Product level one level two a prelude to decision makmg and may have an important influence on the proficiency of the diagnostic reasomng Approaches to Content Nursing Nursing processes that take place (Balla et al 1990, Benner 1984, assessment mformation knowledge diagnosis Bordage & Zacks 1984, Corcoran 1986, Holden & Klmgner processmg 1988) Logical Much of the research mveshgatmg the role of content reasorung knowledge m diagnostic reasomng has comefi'omexpertnovice compansons (Benner 1985, Corcoran 1986, Itano 1989, Pardue 1987, Rohwer & Thomas 1989) Thompson NANDA (North Amencan Nurses' Association) dassifi- and associates (1990) condude that experts are seledive m cation of nursmg diagnoses provides nurses with a hst of the content knowledge used, utilizing only that knowledge 76 nursing diagnoses (Kim & Montz 1984) du-ectlyrelevantto a solution, thus yielding simpler assoaAs a number of NANDA nursing diagnoses may be ahons between new chmcal data and known informahon used to descnbe a vanety of health problems for any one This suggests that the development of expertise results patient, the nursmg diagnoses for any one patient may fi-om a content knowledge that is effiaently stored in need to be orgamzed accordmg to some cntena Often, memory and structured mto networks of informahon for example, nursmg diagnoses are orgamzed accordmg to mtercormected by rational links their pnonty m nursmg action In this study, the orgamzAccordmg to Putnam (1987), it is this nchly lnterconahon of nursing diagnoses was based on the potential neded structure of knowledge that constitutes understandsystemic lmphcation of the health problem ing and allows the mdividual to recognize a problem state as belonging to a particular category of knowledge The expert nurse is able to access this network readily and Diagnostic reasoning rapidly deade which dimcal information is important, The process by which nurses amve at a diagnosis is which cues are sigmficant, and how to integrate these commonly referred to as diagnoshc reasomng (Camevab et findings to make an appropnate diagnosis (Holden & al 1984, Jones 1988, Thompson ei al 1990) Diagnoshc Khngner 1988, Benner 1984) reasorung is a complex cogmhve activity mvolving both hypothesis generation and a search for information to confirm or rejed the hypothesis A number of researchers have Nursing assessment descnbed the different processmg procedures mvolved It appears, then, that content knowledge is important for when nurses make a diagnosis (Camevah 1984, Gordon proficient diagnoshc reasomng and that such proficiency is 1980, Jones 1988, Tanner et al 1987) Jones (1988) also dependent on the efficient recogmtion of important suggests that httle of the base information needed to make dimcal information The recogmtion and recording of a diagnosis is available when the nurse is mitially faced with dmical information is generally referred to as a nursmg the patient Infonnahon may need to be gathered fi'om assessment and requires the abihty to gather, mterpret and vanous sources such as pahent records, mterviews and the organize dmical mformahon Systemahc dmical data gathnurses' own observahons enng helps nurses to break down the diagnoshc problem According to Tanner (1984), the informahon taken m smaller and more manageable dusters of informahon tends to form dusters of related information In tum, the In dealmg with dusters of information more working dusters of informahon are used to generate diagnostic memory space is released for the cogmhve demands hypotheses (Camevali 1984, Jones 1988) mvolved m accessmg and appl)ang content knowledge, thus ^ahtahng greater understanding of the diagnoshc problem at hand (Kagan 1988) Thus the path towards solvContent knowledge mg the diagnoshc problem becomes a process mvolvmg One important component of diagnoshc reasomng is relahvely simple pieces of informahon combmed and content knowledge (BaUa et al 1990, Bordage & Zacks restructured into large umts of informahon It regularly 1984, Camevali 1983, Patel & Groen 1986) The content mvolves modifymg and strengthening one's knowledge of 1172
Diagnostic reasomng
rtie presentmg situahon by systemahcally mtegratmg new and known information Oones 1988)
Logical reasomng This notion of diagnostic reasoning suggests that the building of connections between new and existing knowledge IS an important fundamental mechanism underlying diagnoshc reasomng processes How efficiently nurses make the connections between new clinical information and the content knowledge they already possess may be related to their logical reasoning abilities Nurses' abihty to reason logically requires the use of content knowledge to explain and elaborate on patients' problems These explanations may include physical, biological or psychological mechanisms underlying a particular diagnoshc problem Logical reasoning serves to develop ideas and suppositions about the structure of a diagnostic problem and yield a growmg line of thought (Schmidt 1983) Finally, logical reasoning helps nurses to provide a clear recapitulation of opinions, actual knowledge and ideas about the problem Balla and associates (1990) have demonstrated a strong relationship between the structural complexity of reasoning among physiaans and the accuracy of a medical diagnosis In other words, their findings suggest that the effiaent use of content knowledge for making a diagnosis is dependent not only on the amount of content knowledge a physician possesses but how coherently that knowledge has been structured in reasonmg and how complex and nch in elaboration the knowledge structures are
Each of the three approaches may be categonzed by ldentifymg the predominant fadors that motivate leamers to engage m a cogmtive task and the strategy that logically flows from that mohve (Newble & Entwistle 1986) Biggs (1987a) proposed that students adopting a deep approach tend to be motivated by an interest in the subject matenal and processmg tends to focus on understanding the matenal and how it related to previous knowledge On the other hand, leamers adopting a surface approach tend to focus on reproducing strategies, and motives are geared at minimally meeting task requirements An achieving approach is based on the motivation to succeed, with strategies auned at optimal management of time and work space Surface, deep and achieving approaches are presumed to have important implications for diagnostic reasoning m nursing The use of a deep approach may be highly consistent with the demands of complex diagnostic reasonmg processes Conversely, the habitual use of a surface approach may well leave the nurse less mdmed to seek relationships between units of climcal mformation juid hence less likely to generate the inferences necessary for higher-quality nursing diagnoses
A 3P model ofdtagnosttc reasonmg Thus far, five elements of diagnostic reasomng have been descnbed approaches to information processing, content knowledge, nursmg assessment, logical reasonmg and nursing diagnoses The five elements can be placed m the context of a 3P model (Biggs & Telfer 1987) The 3P model refers to presage, process and product factors For the purpose of the current study presage factors refer to the nurse's predisposition towards the task as indicated by Approaches to information processing the nurse's approaches to information processing Process factors include content knowledge, nursing assessment and The different ways nurses go about orgamzing, stmctunng logicail reasonmg Product factors refer to the outcome and dealmg with infonnahon m diagnostic reasomng may of diagnostic reasonmg, that is vanous nursmg diagnoses be related to individual differences in the processing of (see Table 1) mformation The different approaches to informahon According to the 3P model, a relahonship exists among processmg have been studied by a number of researchers presage, process and product factors Presage factors are (Biggs 1987a, Eizenberg 1986, Entwistle & Ramsden 1983, presumed to mfluence both processmg factors and product Moore & Telfer 1990, Watkins 1983) factors Process factors are presumed to influence product Following Speth & Brown (1988), this area of research factors may be categonzed under the common label of approaches to leaming Generally, researchers using the approaches to learmng paradigm agree that there are consistent The study ways leamers approach cogmhve tasks and these may be charactenzed by three general approaches surface, deep The mam purpose of the present study was to exjunme the and achievmg The precise terminology and nahire of viability of the 3P model of diagnostic reasomng as it the approaches, however, will vary accorduig to the apphes to a group of second year nursmg students Specifically the present study aimed to examme the direct and measuronent mstrument used 1173
K.M Choloiosh artd L K.S Chan
mdu-ect influence of the presf^e vanables on nursing diagnosis as well as the mfluence of the process vanables on nursmg diagnosis m the 3P model of diagnoshc reasomng descnbed above METHOD Researdi design The Study Process Queshonnaire (Biggs 1987a) was used to measure subjects' approaches to leammg and information processing A measure of content knowledge was based on a 31-item multiple-choice renal knowledge test To obtam measures of nursmg assessment, logical reasomng and nursmg diagnoses, a diagnoshc reasomng task was developed for the study The task mvolved presenting subjects with a 200-word vignette descnbmg a patient with a dmical renal problem, acute poststreptococcal glomerulonephntis (APSGN) The vignette provided a descnption of a 22-year-old man displajong symptoms such as coffee-coloured unne and a reduced output of unne The pahent was lethargic, with shght oedema aroimd his eyes and his pharyngeal mucosa was shghtly red On exammation it was revealed that his vital signs were raised and his urmalysis revealed haematuna and protemuna Laboratory tests revealed raised electrolyte levels A medical diagnosis of APSGN was provided after all dmical data were presented Subjects were first asked to generate a nursmg assessment for the pahent descnbed Then they were required to list four important nursing diagnoses using the NANDA hst of nursmg diagnoses, and to select one of these as the major diagnosis After that, subjects were asked to explam the reasons for their choice of the major diagnosis Science knowledge
that renal disorder gives nse to alterahcms m the body's homeostasis, subjects should make cc»mechons between the two and deduce that the patient's decreased unnary output and maeased levels of toxms may be related to bdney dysfunction Subsequently, the effiects of bdney dysfunction on other systems of the body should be mferred The level of inference mvolved is hence refleded in the diagnosis nominated as the major diagnosis Thus, the naming of the nursing diagnoses provided an outcome measure and reflected how successfully diagnoshc reasoning was camed out The generation of the nursing assessment provided an mdication of the subjects' abihty to colled, interpret and orgamze chmcal mformahon (provided in the vignette) as a prelude to generatmg a diagnosis The explanation for the choice of the major diagnosis provided an mdicahon of the subject's logical reasomng ability, reflecting how and why information from vanous sources was brought together The SOLO Taxonomy was used to assess the structural complexity of logical reasonmg as reflected m the wntten explanation Objects Subjeds for the study mcluded 268 second-year Diploma of Health Saence (Nursing) students at a umversity m New South Wales Full data were available on 169 subjects Only subjects with full data were induded m the stahstical analysis Subjects were predommantly female (82%), rangmg from 18 to 49 m age, with a mean age of 21 MATERIALS Study Process Questionnaire The Study Process Queshonnaire (SPQ) (Biggs 1987b) is a 42 item questionnaire designed to ehat preferred approach to the processing of informahon and learmng in tertiary students The SPQ descnbes students m terms of a predisposihon towards surface, deep or aduevmg approaches to learmng It is scored by summing the responses to the fivepoint Likert items through which subjects rate their degree of agreement with each statement A ratmg of 5 mdicates high agreement, I low agreement (Biggs 1987b) Summed deep and achievmg scores may also yield a composite deep/achieving approach
In order to make an accurate nursing diagnosis, subjects had to know the structure of the kidneys and the function they serve m filtenng the blood, excrehng waste products and m reguiatmg the concentrahons of electrolytes mextracellular fluid Without an appropnate saence knowledge base subjects were unlikely to recogmze the importance of symptoms such as reduced output of unne or recognize the potenhal dangers associated with a build up of toxms m the blood This task, therefore, called on subjects to use their saentific knowledge and to attend to important information Renal Knowledge Test providcKJ m the vigi^tte m order to make accurate and higher-quahty nursing diagnoses For example, havmg The Renal Knowledge Test was mduded as a measure of recognized that the patient had a reduced output c^ urme ccmtent knowledge relevant to the diagnoshc reasomng and increased levels of toxms in the blood, and knowmg task. The renal knowledge test mduded 31 multiple-
Diagnostic reasoning among second-year nursing students Krystyna M Cholowski RN MEd Stud Assisiani Leciurer, Deparimeni of Commumiy and Menial Healih Nursmg, Umverstiy of Newcasile
and Loma K S Chan BEd(Hons) PhD Associate Professor, Deparimeni of Educahon, University of Newcastle, Callaghan, New Souih Wales, Auskalia
Accepted for pubhcahon 17 February 1992
CHOLOWSKI K M & CHAN L K S (1992) journal of Advanced Nursmg 17,
1I71-II81 Diagnostic reasoning among second-year nursing students This paper reports on a study mvestigatmg the relationship of nursing students' approaches to leammg and processing of information, science content knowledge, ability in interpreting and organizing clmical data (nursmg assessment), and logical reasomng ability with the accuracy and quabty of the nursing diagnosis made in a simulated diagnostic reasonmg task One hundred and sixty-mne second-year pre-service nursing students participated in the study Results of path analyses mdicated a set of pathways from surface approach to low-quality nursing diagnosis that reflected less competent diagnostic reasonmg, and a second set from deep/achievmg approach through content knowledge and logical reasonmg to higher-quality nursing diagnosis that reflected more competent diagnostic reasonmg The implications of these findings for nurse education are discussed
DIAGNOSING NURSING PROBLEMS
and nurses' approaches to information proeessmg (see Table 1)
Reeent researeh in nursing has suggested that an important dimension of professional nursing rests on the eompetenee of nurses to diagnose nursmg problems aeeurately Diagnosing elient problems is required daily and has been ldenhfied by nursing bodies as a enhcal eomponent of nursing praetiee (Gordon 1980, Jones 1988) In this study, a model of diagnostie reasomng in nursmg IS explored The model incorporates ftve interrelated elements The five elements are presumed to measure vanous behaviours and aehvities earned out by nurses m diagnoshc reasonmg These melude nursmg diagnosis, logical reasoning, eontent knowledge, nursing assessment
Nursing diagnosis Nursing diagnosis as used m this paper refers to the label given to the patient's health problem In nursing, the tenn 'diagnosis' is used m broad eontext rather than m the narrow sense of ldenhfying disease Nursing diagnoses do not label medieal entities sueh as disease processes that require surgery or presenphve drugs Nursing diagnoses refer to eonditions or behaviours that are relevant to health management and ean be helped or dianged by nursing aetion A nursing helps g diagnosis g p nurses to communicate
Correspondetxe Krystyna M Cholowski Assistant lecturer Deparhnent of ^lgar and COnase information about t h e pahent's Current Commumty and Mental Health Nursmg University of Newcastle Callaghan New , ,,, ^ ^ , , , , . . -ri.
L
health state and provides a basis tor pahent care The 1171
KM CholowsktandLKS Chan Table 1 3P Model of diagnosic reasoning m nursmg
knowledge a nurse brmgs to the diagnoshc task plays a cntical role m determining how the problem will be mterpreted and which items of dimcal information will be Process Process attended to Thus, reference to pnor content knowledge is Presage Product level one level two a prelude to decision makmg and may have an important influence on the proficiency of the diagnostic reasomng Approaches to Content Nursing Nursing processes that take place (Balla et al 1990, Benner 1984, assessment mformation knowledge diagnosis Bordage & Zacks 1984, Corcoran 1986, Holden & Klmgner processmg 1988) Logical Much of the research mveshgatmg the role of content reasorung knowledge m diagnostic reasomng has comefi'omexpertnovice compansons (Benner 1985, Corcoran 1986, Itano 1989, Pardue 1987, Rohwer & Thomas 1989) Thompson NANDA (North Amencan Nurses' Association) dassifi- and associates (1990) condude that experts are seledive m cation of nursmg diagnoses provides nurses with a hst of the content knowledge used, utilizing only that knowledge 76 nursing diagnoses (Kim & Montz 1984) du-ectlyrelevantto a solution, thus yielding simpler assoaAs a number of NANDA nursing diagnoses may be ahons between new chmcal data and known informahon used to descnbe a vanety of health problems for any one This suggests that the development of expertise results patient, the nursmg diagnoses for any one patient may fi-om a content knowledge that is effiaently stored in need to be orgamzed accordmg to some cntena Often, memory and structured mto networks of informahon for example, nursmg diagnoses are orgamzed accordmg to mtercormected by rational links their pnonty m nursmg action In this study, the orgamzAccordmg to Putnam (1987), it is this nchly lnterconahon of nursing diagnoses was based on the potential neded structure of knowledge that constitutes understandsystemic lmphcation of the health problem ing and allows the mdividual to recognize a problem state as belonging to a particular category of knowledge The expert nurse is able to access this network readily and Diagnostic reasoning rapidly deade which dimcal information is important, The process by which nurses amve at a diagnosis is which cues are sigmficant, and how to integrate these commonly referred to as diagnoshc reasomng (Camevab et findings to make an appropnate diagnosis (Holden & al 1984, Jones 1988, Thompson ei al 1990) Diagnoshc Khngner 1988, Benner 1984) reasorung is a complex cogmhve activity mvolving both hypothesis generation and a search for information to confirm or rejed the hypothesis A number of researchers have Nursing assessment descnbed the different processmg procedures mvolved It appears, then, that content knowledge is important for when nurses make a diagnosis (Camevah 1984, Gordon proficient diagnoshc reasomng and that such proficiency is 1980, Jones 1988, Tanner et al 1987) Jones (1988) also dependent on the efficient recogmtion of important suggests that httle of the base information needed to make dimcal information The recogmtion and recording of a diagnosis is available when the nurse is mitially faced with dmical information is generally referred to as a nursmg the patient Infonnahon may need to be gathered fi'om assessment and requires the abihty to gather, mterpret and vanous sources such as pahent records, mterviews and the organize dmical mformahon Systemahc dmical data gathnurses' own observahons enng helps nurses to break down the diagnoshc problem According to Tanner (1984), the informahon taken m smaller and more manageable dusters of informahon tends to form dusters of related information In tum, the In dealmg with dusters of information more working dusters of informahon are used to generate diagnostic memory space is released for the cogmhve demands hypotheses (Camevali 1984, Jones 1988) mvolved m accessmg and appl)ang content knowledge, thus ^ahtahng greater understanding of the diagnoshc problem at hand (Kagan 1988) Thus the path towards solvContent knowledge mg the diagnoshc problem becomes a process mvolvmg One important component of diagnoshc reasomng is relahvely simple pieces of informahon combmed and content knowledge (BaUa et al 1990, Bordage & Zacks restructured into large umts of informahon It regularly 1984, Camevali 1983, Patel & Groen 1986) The content mvolves modifymg and strengthening one's knowledge of 1172
Diagnostic reasomng
rtie presentmg situahon by systemahcally mtegratmg new and known information Oones 1988)
Logical reasomng This notion of diagnostic reasoning suggests that the building of connections between new and existing knowledge IS an important fundamental mechanism underlying diagnoshc reasomng processes How efficiently nurses make the connections between new clinical information and the content knowledge they already possess may be related to their logical reasoning abilities Nurses' abihty to reason logically requires the use of content knowledge to explain and elaborate on patients' problems These explanations may include physical, biological or psychological mechanisms underlying a particular diagnoshc problem Logical reasoning serves to develop ideas and suppositions about the structure of a diagnostic problem and yield a growmg line of thought (Schmidt 1983) Finally, logical reasoning helps nurses to provide a clear recapitulation of opinions, actual knowledge and ideas about the problem Balla and associates (1990) have demonstrated a strong relationship between the structural complexity of reasoning among physiaans and the accuracy of a medical diagnosis In other words, their findings suggest that the effiaent use of content knowledge for making a diagnosis is dependent not only on the amount of content knowledge a physician possesses but how coherently that knowledge has been structured in reasonmg and how complex and nch in elaboration the knowledge structures are
Each of the three approaches may be categonzed by ldentifymg the predominant fadors that motivate leamers to engage m a cogmtive task and the strategy that logically flows from that mohve (Newble & Entwistle 1986) Biggs (1987a) proposed that students adopting a deep approach tend to be motivated by an interest in the subject matenal and processmg tends to focus on understanding the matenal and how it related to previous knowledge On the other hand, leamers adopting a surface approach tend to focus on reproducing strategies, and motives are geared at minimally meeting task requirements An achieving approach is based on the motivation to succeed, with strategies auned at optimal management of time and work space Surface, deep and achieving approaches are presumed to have important implications for diagnostic reasoning m nursing The use of a deep approach may be highly consistent with the demands of complex diagnostic reasonmg processes Conversely, the habitual use of a surface approach may well leave the nurse less mdmed to seek relationships between units of climcal mformation juid hence less likely to generate the inferences necessary for higher-quality nursing diagnoses
A 3P model ofdtagnosttc reasonmg Thus far, five elements of diagnostic reasomng have been descnbed approaches to information processing, content knowledge, nursmg assessment, logical reasonmg and nursing diagnoses The five elements can be placed m the context of a 3P model (Biggs & Telfer 1987) The 3P model refers to presage, process and product factors For the purpose of the current study presage factors refer to the nurse's predisposition towards the task as indicated by Approaches to information processing the nurse's approaches to information processing Process factors include content knowledge, nursing assessment and The different ways nurses go about orgamzing, stmctunng logicail reasonmg Product factors refer to the outcome and dealmg with infonnahon m diagnostic reasomng may of diagnostic reasonmg, that is vanous nursmg diagnoses be related to individual differences in the processing of (see Table 1) mformation The different approaches to informahon According to the 3P model, a relahonship exists among processmg have been studied by a number of researchers presage, process and product factors Presage factors are (Biggs 1987a, Eizenberg 1986, Entwistle & Ramsden 1983, presumed to mfluence both processmg factors and product Moore & Telfer 1990, Watkins 1983) factors Process factors are presumed to influence product Following Speth & Brown (1988), this area of research factors may be categonzed under the common label of approaches to leaming Generally, researchers using the approaches to learmng paradigm agree that there are consistent The study ways leamers approach cogmhve tasks and these may be charactenzed by three general approaches surface, deep The mam purpose of the present study was to exjunme the and achievmg The precise terminology and nahire of viability of the 3P model of diagnostic reasomng as it the approaches, however, will vary accorduig to the apphes to a group of second year nursmg students Specifically the present study aimed to examme the direct and measuronent mstrument used 1173
K.M Choloiosh artd L K.S Chan
mdu-ect influence of the presf^e vanables on nursing diagnosis as well as the mfluence of the process vanables on nursmg diagnosis m the 3P model of diagnoshc reasomng descnbed above METHOD Researdi design The Study Process Queshonnaire (Biggs 1987a) was used to measure subjects' approaches to leammg and information processing A measure of content knowledge was based on a 31-item multiple-choice renal knowledge test To obtam measures of nursmg assessment, logical reasomng and nursmg diagnoses, a diagnoshc reasomng task was developed for the study The task mvolved presenting subjects with a 200-word vignette descnbmg a patient with a dmical renal problem, acute poststreptococcal glomerulonephntis (APSGN) The vignette provided a descnption of a 22-year-old man displajong symptoms such as coffee-coloured unne and a reduced output of unne The pahent was lethargic, with shght oedema aroimd his eyes and his pharyngeal mucosa was shghtly red On exammation it was revealed that his vital signs were raised and his urmalysis revealed haematuna and protemuna Laboratory tests revealed raised electrolyte levels A medical diagnosis of APSGN was provided after all dmical data were presented Subjects were first asked to generate a nursmg assessment for the pahent descnbed Then they were required to list four important nursing diagnoses using the NANDA hst of nursmg diagnoses, and to select one of these as the major diagnosis After that, subjects were asked to explam the reasons for their choice of the major diagnosis Science knowledge
that renal disorder gives nse to alterahcms m the body's homeostasis, subjects should make cc»mechons between the two and deduce that the patient's decreased unnary output and maeased levels of toxms may be related to bdney dysfunction Subsequently, the effiects of bdney dysfunction on other systems of the body should be mferred The level of inference mvolved is hence refleded in the diagnosis nominated as the major diagnosis Thus, the naming of the nursing diagnoses provided an outcome measure and reflected how successfully diagnoshc reasoning was camed out The generation of the nursing assessment provided an mdication of the subjects' abihty to colled, interpret and orgamze chmcal mformahon (provided in the vignette) as a prelude to generatmg a diagnosis The explanation for the choice of the major diagnosis provided an mdicahon of the subject's logical reasomng ability, reflecting how and why information from vanous sources was brought together The SOLO Taxonomy was used to assess the structural complexity of logical reasonmg as reflected m the wntten explanation Objects Subjeds for the study mcluded 268 second-year Diploma of Health Saence (Nursing) students at a umversity m New South Wales Full data were available on 169 subjects Only subjects with full data were induded m the stahstical analysis Subjects were predommantly female (82%), rangmg from 18 to 49 m age, with a mean age of 21 MATERIALS Study Process Questionnaire The Study Process Queshonnaire (SPQ) (Biggs 1987b) is a 42 item questionnaire designed to ehat preferred approach to the processing of informahon and learmng in tertiary students The SPQ descnbes students m terms of a predisposihon towards surface, deep or aduevmg approaches to learmng It is scored by summing the responses to the fivepoint Likert items through which subjects rate their degree of agreement with each statement A ratmg of 5 mdicates high agreement, I low agreement (Biggs 1987b) Summed deep and achievmg scores may also yield a composite deep/achieving approach
In order to make an accurate nursing diagnosis, subjects had to know the structure of the kidneys and the function they serve m filtenng the blood, excrehng waste products and m reguiatmg the concentrahons of electrolytes mextracellular fluid Without an appropnate saence knowledge base subjects were unlikely to recogmze the importance of symptoms such as reduced output of unne or recognize the potenhal dangers associated with a build up of toxms m the blood This task, therefore, called on subjects to use their saentific knowledge and to attend to important information Renal Knowledge Test providcKJ m the vigi^tte m order to make accurate and higher-quahty nursing diagnoses For example, havmg The Renal Knowledge Test was mduded as a measure of recognized that the patient had a reduced output c^ urme ccmtent knowledge relevant to the diagnoshc reasomng and increased levels of toxms in the blood, and knowmg task. The renal knowledge test mduded 31 multiple-
