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Next Generation NCLEX Case Study Sample Questions

One of the big changes on the Next Generation NCLEX exam is a shift toward case studies. Case studies often require a deeper level of critical thinking, and understanding diseases on a more in-depth level (especially the pathophysiology) will make these types of questions easier to answer.

In this article, you’ll be able to watch a free video to help you prepare for the new Next Generation NCLEX case study format. Nurse Sarah will walk you step-by-step through each scenario and help you understand how to use critical thinking and nursing knowledge to answer these types of questions.

Next Generation NCLEX Case Study Review Questions Video

NGN Case Study Sample Questions and Answers

First, let’s take a look at our case study summary below:

Case Study Summary:

A 68-year-old male is admitted with shortness of breath. He reports difficulty breathing with activity, lying down, or while sleeping. He states that in order to “breathe easier,” he has had to sleep in a recliner for the past week. The patient has a history of hypertension, myocardial infarction (2 years ago), and cholecystectomy (10 years ago). The patient is being transferred to a cardiac progressive care unit for further evaluation and treatment.

Question 1 of 6: The nurse receives the patient admitted with shortness of breath. What findings are significant and require follow-up? The options are listed below. Select all that apply.

To answer this first question in the NGN case study, let’s look at the information provided in the nursing notes and vital signs tabs provided:

This question is asking us to identify findings that are significant and require the nurse to follow-up. In other words, what is presenting that we can’t ignore but need to investigate further.

Therefore, let’s comb through the nursing notes and vital signs to see what is abnormal and requires follow-up.

First, the patient arrived to the room via stretcher. That’s fine and doesn’t necessarily require follow-up.

Next, the patient is alert and oriented x 4 (person, place, time, event). This tells us that the patient’s neuro status is intact so far. Therefore, the shortness of breath isn’t affecting the patient’s mental function yet (we have enough oxygen on board right now for brain activity).

However, the nurse has noticed the shortness of breath with activity and talking, which should not normally happen. This tells us something is wrong and is significant enough to require follow-up. We want to know why is this happening, is it going to get worse, etc.

The patient’s weight and vital signs were collected (this is good). Weight is 155 lbs. and BMI is within a healthy range (doesn’t tell us too much but may be useful later). The patient is also connected to a bedside monitor, so they need to be monitored constantly like on a progressive care unit.

The monitor shows sinus tachycardia . This is significant because it seems the patient’s shortness of breath is causing the heart to compensate by increasing the heart rate to provide more oxygen (hence the lungs may be compromised).

Then we find out that the lungs are indeed compromised because crackles are heard in both lungs , and this may be why our patient is short of breath. This is significant (could the patient have pulmonary edema?)

Then we find out the nurse has noted an S3. This is an extra heart sound noted after S2. And what jumps out to me about this is that it is usually associated with volume overload in the heart like in cases of heart failure . However, S3 may be normal in some people under 40 or during pregnancy, but that’s not the case with our patient based on what we read in the case summary.

Therefore, based on everything I’m reading in this case study, I’m thinking this patient may have heart failure, but we need those test results back (especially the echo and chest x-ray, and hopefully a BNP will be in there too).

We are also told that the patient has an 18 gauge IV inserted (which is good thing to have so we can give medications if required), orders have been received, labs drawn, and testing results are pending.

Now let’s look at the “Vital Signs” tab above, and ask yourself what is normal vs. abnormal for this patient (adult male).

• The heart rate is high at 112 (tachycardia), and should normally be 60-100 bpm (see heart rhythms ).
• Blood pressure is higher than normal (normal is 120/80), which indicates hypertension.
• Oxygen saturation is 94% (this is on the low side as we’d normally want around 95% or higher, and the patient is on 4 L nasal cannula, which tells us the lungs are not okay).
• Respiratory rate is increased (26 breaths per minute)…normal is 12-20 breaths per minute.

Based on the information we were provided, I’ve selected the answers below. These findings are significant and definitely require follow-up by the nurse.

When answering these NGN case study questions, it’s helpful to think of the ABCDE (airway, breathing, circulation, etc.) as all of these fall into that category. If we don’t follow-up on the shortness of breath, crackles, respiratory rate, o2 saturation (94% on 4 L nasal cannula), the respiratory system can further decline.

In addition, the sinus tachycardia, S3 gallop, and hypertension could indicate fluid overload in the heart. This may cause the heart to tire out and lead the lethal rhythm. On the other hand, temperature, pain, weight, and BMI are not abnormal and do not require follow-up.

See the Complete Next Generation NCLEX Case Study Review

Each question in the case study builds on the previous question. To see how these questions evolve based on the patient’s condition and labs, watch the entire Next Generation NCLEX Case Study Review video on our YouTube Channel (RegisteredNurseRN).

NCLEX Practice Quizzes

We’ve developed many free NCLEX review quizzes to test your knowledge on nursing topics and to help you prepare for the Next Generation NCLEX exam.

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Chapter 11 Case Research

Case research, also called case study, is a method of intensively studying a phenomenon over time within its natural setting in one or a few sites. Multiple methods of data collection, such as interviews, observations, prerecorded documents, and secondary data, may be employed and inferences about the phenomenon of interest tend to be rich, detailed, and contextualized. Case research can be employed in a positivist manner for the purpose of theory testing or in an interpretive manner for theory building. This method is more popular in business research than in other social science disciplines.

Case research has several unique strengths over competing research methods such as experiments and survey research. First, case research can be used for either theory building or theory testing, while positivist methods can be used for theory testing only. In interpretive case research, the constructs of interest need not be known in advance, but may emerge from the data as the research progresses. Second, the research questions can be modified during the research process if the original questions are found to be less relevant or salient. This is not possible in any positivist method after the data is collected. Third, case research can help derive richer, more contextualized, and more authentic interpretation of the phenomenon of interest than most other research methods by virtue of its ability to capture a rich array of contextual data. Fourth, the phenomenon of interest can be studied from the perspectives of multiple participants and using multiple levels of analysis (e.g., individual and organizational).

At the same time, case research also has some inherent weaknesses. Because it involves no experimental control, internal validity of inferences remain weak. Of course, this is a common problem for all research methods except experiments. However, as described later, the problem of controls may be addressed in case research using “natural controls”. Second, the quality of inferences derived from case research depends heavily on the integrative powers of the researcher. An experienced researcher may see concepts and patterns in case data that a novice researcher may miss. Hence, the findings are sometimes criticized as being subjective. Finally, because the inferences are heavily contextualized, it may be difficult to generalize inferences from case research to other contexts or other organizations.

It is important to recognize that case research is different from case descriptions such as Harvard case studies discussed in business classes. While case descriptions typically describe an organizational problem in rich detail with the goal of stimulating classroom discussion and critical thinking among students, or analyzing how well an organization handled a specific problem, case research is a formal research technique that involves a scientific method to derive explanations of organizational phenomena.

Case research is a difficult research method that requires advanced research skills on the part of the researcher, and is therefore, often prone to error. Benbasat et al. (1987) [8] describe five problems frequently encountered in case research studies. First, many case research studies start without specific research questions, and therefore end up without having any specific answers or insightful inferences. Second, case sites are often chosen based on access and convenience, rather than based on the fit with the research questions, and are therefore cannot adequately address the research questions of interest. Third, researchers often do not validate or triangulate data collected using multiple means, which may lead to biased interpretation based on responses from biased interviewees. Fourth, many studies provide very little details on how data was collected (e.g., what interview questions were used, which documents were examined, what are the organizational positions of each interviewee, etc.) or analyzed, which may raise doubts about the reliability of the inferences. Finally, despite its strength as a longitudinal research method, many case research studies do not follow through a phenomenon in a longitudinal manner, and hence present only a cross-sectional and limited view of organizational processes and phenomena that are temporal in nature.

Key Decisions in Case Research

Several key decisions must be made by a researcher when considering a case research method. First, is this the right method for the research questions being studied? The case research method is particularly appropriate for exploratory studies for discovering relevant constructs in areas where theory building at the formative stages, for studies where the experiences of participants and context of actions are critical, and for studies aimed at understanding complex, temporal processes (why and how of a phenomenon) rather than factors or causes (what). This method is well-suited for studying complex organizational processes that involve multiple participants and interacting sequences of events, such as organizational change and large-scale technology implementation projects.

Second, what is the appropriate unit of analysis for a case research study? Since case research can simultaneously examine multiple units of analyses, the researcher must decide whether she wishes to study a phenomenon at the individual, group, and organizational level or at multiple levels. For instance, a study of group decision making or group work may combine individual-level constructs such as individual participation in group activities with group-level constructs, such as group cohesion and group leadership, to derive richer understanding than that can be achieved from a single level of analysis.

Third, should the researcher employ a single-case or multiple-case design? The single case design is more appropriate at the outset of theory generation, if the situation is unique or extreme, if it is revelatory (i.e., the situation was previously inaccessible for scientific investigation), or if it represents a critical or contrary case for testing a well-formulated theory. The multiple case design is more appropriate for theory testing, for establishing generalizability of inferences, and for developing richer and more nuanced interpretations of a phenomenon. Yin (1984) [9] recommends the use of multiple case sites with replication logic, viewing each case site as similar to one experimental study, and following rules of scientific rigor similar to that used in positivist research.

Fourth, what sites should be chosen for case research? Given the contextualized nature of inferences derived from case research, site selection is a particularly critical issue because selecting the wrong site may lead to the wrong inferences. If the goal of the research is to test theories or examine generalizability of inferences, then dissimilar case sites should be selected to increase variance in observations. For instance, if the goal of the research is to understand the process of technology implementation in firms, a mix of large, mid-sized, and small firms should be selected to examine whether the technology implementation process differs with firm size. Site selection should not be opportunistic or based on convenience, but rather based on the fit with research questions through a process called “theoretical sampling.”

Fifth, what techniques of data collection should be used in case research? Although interview (either open-ended/unstructured or focused/structured) is by far the most popular data collection technique for case research, interview data can be supplemented or corroborated with other techniques such as direct observation (e.g., attending executive meetings, briefings, and planning sessions), documentation (e.g., internal reports, presentations, and memoranda, as well as external accounts such as newspaper reports), archival records (e.g., organization charts, financial records, etc.), and physical artifacts (e.g., devices, outputs, tools). Furthermore, the researcher should triangulate or validate observed data by comparing responses between interviewees.

Conducting Case Research

Most case research studies tend to be interpretive in nature. Interpretive case research is an inductive technique where evidence collected from one or more case sites is systematically analyzed and synthesized to allow concepts and patterns to emerge for the purpose of building new theories or expanding existing ones. Eisenhardt (1989) [10] propose a “roadmap” for building theories from case research, a slightly modified version of which is described below. For positivist case research, some of the following stages may need to be rearranged or modified; however sampling, data collection, and data analytic techniques should generally remain the same.

Define research questions. Like any other scientific research, case research must also start with defining research questions that are theoretically and practically interesting, and identifying some intuitive expectations about possible answers to those research questions or preliminary constructs to guide initial case design. In positivist case research, the preliminary constructs are based on theory, while no such theory or hypotheses should be considered ex ante in interpretive research. These research questions and constructs may be changed in interpretive case research later on, if needed, but not in positivist case research.

Select case sites. The researcher should use a process of “theoretical sampling” (not random sampling) to identify case sites. In this approach, case sites are chosen based on theoretical, rather than statistical, considerations, for instance, to replicate previous cases, to extend preliminary theories, or to fill theoretical categories or polar types. Care should be taken to ensure that the selected sites fit the nature of research questions, minimize extraneous variance or noise due to firm size, industry effects, and so forth, and maximize variance in the dependent variables of interest. For instance, if the goal of the research is to examine how some firms innovate better than others, the researcher should select firms of similar size within the same industry to reduce industry or size effects, and select some more innovative and some less innovative firms to increase variation in firm innovation. Instead of cold-calling or writing to a potential site, it is better to contact someone at executive level inside each firm who has the authority to approve the project or someone who can identify a person of authority. During initial conversations, the researcher should describe the nature and purpose of the project, any potential benefits to the case site, how the collected data will be used, the people involved in data collection (other researchers, research assistants, etc.), desired interviewees, and the amount of time, effort, and expense required of the sponsoring organization. The researcher must also assure confidentiality, privacy, and anonymity of both the firm and the individual respondents.

Create instruments and protocols. Since the primary mode of data collection in case research is interviews, an interview protocol should be designed to guide the interview process. This is essentially a list of questions to be asked. Questions may be open-ended (unstructured) or closed-ended (structured) or a combination of both. The interview protocol must be strictly followed, and the interviewer must not change the order of questions or skip any question during the interview process, although some deviations are allowed to probe further into respondent’s comments that are ambiguous or interesting. The interviewer must maintain a neutral tone, not lead respondents in any specific direction, say by agreeing or disagreeing with any response. More detailed interviewing techniques are discussed in the chapter on surveys. In addition, additional sources of data, such as internal documents and memorandums, annual reports, financial statements, newspaper articles, and direct observations should be sought to supplement and validate interview data.

Select respondents. Select interview respondents at different organizational levels, departments, and positions to obtain divergent perspectives on the phenomenon of interest. A random sampling of interviewees is most preferable; however a snowball sample is acceptable, as long as a diversity of perspectives is represented in the sample. Interviewees must be selected based on their personal involvement with the phenomenon under investigation and their ability and willingness to answer the researcher’s questions accurately and adequately, and not based on convenience or access.

Start data collection . It is usually a good idea to electronically record interviews for future reference. However, such recording must only be done with the interviewee’s consent. Even when interviews are being recorded, the interviewer should take notes to capture important comments or critical observations, behavioral responses (e.g., respondent’s body language), and the researcher’s personal impressions about the respondent and his/her comments. After each interview is completed, the entire interview should be transcribed verbatim into a text document for analysis.

Conduct within-case data analysis. Data analysis may follow or overlap with data collection. Overlapping data collection and analysis has the advantage of adjusting the data collection process based on themes emerging from data analysis, or to further probe into these themes. Data analysis is done in two stages. In the first stage (within-case analysis), the researcher should examine emergent concepts separately at each case site and patterns between these concepts to generate an initial theory of the problem of interest. The researcher can interview data subjectively to “make sense” of the research problem in conjunction with using her personal observations or experience at the case site. Alternatively, a coding strategy such as Glasser and Strauss’ (1967) grounded theory approach, using techniques such as open coding, axial coding, and selective coding, may be used to derive a chain of evidence and inferences. These techniques are discussed in detail in a later chapter. Homegrown techniques, such as graphical representation of data (e.g., network diagram) or sequence analysis (for longitudinal data) may also be used. Note that there is no predefined way of analyzing the various types of case data, and the data analytic techniques can be modified to fit the nature of the research project.

Conduct cross-case analysis. Multi-site case research requires cross-case analysis as the second stage of data analysis. In such analysis, the researcher should look for similar concepts and patterns between different case sites, ignoring contextual differences that may lead to idiosyncratic conclusions. Such patterns may be used for validating the initial theory, or for refining it (by adding or dropping concepts and relationships) to develop a more inclusive and generalizable theory. This analysis may take several forms. For instance, the researcher may select categories (e.g., firm size, industry, etc.) and look for within-group similarities and between-group differences (e.g., high versus low performers, innovators versus laggards). Alternatively, she can compare firms in a pair-wise manner listing similarities and differences across pairs of firms.

Build and test hypotheses. Based on emergent concepts and themes that are generalizable across case sites, tentative hypotheses are constructed. These hypotheses should be compared iteratively with observed evidence to see if they fit the observed data, and if not, the constructs or relationships should be refined. Also the researcher should compare the emergent constructs and hypotheses with those reported in the prior literature to make a case for their internal validity and generalizability. Conflicting findings must not be rejected, but rather reconciled using creative thinking to generate greater insight into the emergent theory. When further iterations between theory and data yield no new insights or changes in the existing theory, “theoretical saturation” is reached and the theory building process is complete.

Write case research report. In writing the report, the researcher should describe very clearly the detailed process used for sampling, data collection, data analysis, and hypotheses development, so that readers can independently assess the reasonableness, strength, and consistency of the reported inferences. A high level of clarity in research methods is needed to ensure that the findings are not biased by the researcher’s preconceptions.

Interpretive Case Research Exemplar

Perhaps the best way to learn about interpretive case research is to examine an illustrative example. One such example is Eisenhardt’s (1989) [11] study of how executives make decisions in high-velocity environments (HVE). Readers are advised to read the original paper published in Academy of Management Journal before reading the synopsis in this chapter. In this study, Eisenhardt examined how executive teams in some HVE firms make fast decisions, while those in other firms cannot, and whether faster decisions improve or worsen firm performance in such environments. HVE was defined as one where demand, competition, and technology changes so rapidly and discontinuously that the information available is often inaccurate, unavailable or obsolete. The implicit assumptions were that (1) it is hard to make fast decisions with inadequate information in HVE, and (2) fast decisions may not be efficient and may result in poor firm performance.

Reviewing the prior literature on executive decision -making, Eisenhardt found several patterns, although none of these patterns were specific to high-velocity environments. The literature suggested that in the interest of expediency, firms that make faster decisions obtain input from fewer sources, consider fewer alternatives, make limited analysis, restrict user participation in decision-making, centralize decision-making authority, and has limited internal conflicts. However, Eisenhardt contended that these views may not necessarily explain how decision makers make decisions in high-velocity environments, where decisions must be made quickly and with incomplete information, while maintaining high decision quality.

To examine this phenomenon, Eisenhardt conducted an inductive study of eight firms in the personal computing industry. The personal computing industry was undergoing dramatic changes in technology with the introduction of the UNIX operating system, RISC architecture, and 64KB random access memory in the 1980’s, increased competition with the entry of IBM into the personal computing business, and growing customer demand with double-digit demand growth, and therefore fit the profile of the high-velocity environment. This was a multiple case design with replication logic, where each case was expected to confirm or disconfirm inferences from other cases. Case sites were selected based on their access and proximity to the researcher; however, all of these firms operated in the high-velocity personal computing industry in California’s Silicon Valley area. The collocation of firms in the same industry and the same area ruled out any “noise” or variance in dependent variables (decision speed or performance) attributable to industry or geographic differences.

The study employed an embedded design with multiple levels of analysis: decision (comparing multiple strategic decisions within each firm), executive teams (comparing different teams responsible for strategic decisions), and the firm (overall firm performance). Data was collected from five sources:

• Initial interviews with Chief Executive Officers: CEOs were asked questions about their firm’s competitive strategy, distinctive competencies, major competitors, performance, and recent/ongoing major strategic decisions. Based on these interviews, several strategic decisions were selected in each firm for further investigation. Four criteria were used to select decisions: (1) the decisions involved the firm’s strategic positioning,

(2) the decisions had high stakes, (3) the decisions involved multiple functions, and (4) the decisions were representative of strategic decision-making process in that firm.

• Interviews with divisional heads: Each divisional head was asked sixteen open-ended questions, ranging from their firm’s competitive strategy, functional strategy, top management team members, frequency and nature of interaction with team, typical decision making processes, how each of the previously identified decision was made, and how long it took them to make those decisions. Interviews lasted between 1.5 and 2 hours, and sometimes extended to 4 hours. To focus on facts and actual events rather than respondents’ perceptions or interpretations, a “courtroom” style questioning was employed, such as when did this happen, what did you do, etc. Interviews were conducted by two people, and the data was validated by cross-checking facts and impressions made by the interviewer and note-taker. All interview data was recorded, however notes were also taken during each interview, which ended with the interviewer’s overall impressions. Using a “24-hour rule”, detailed field notes were completed within 24 hours of the interview, so that some data or impressions were not lost to recall.
• Questionnaires: Executive team members at each firm were completed a survey questionnaire that captured quantitative data on the extent of conflict and power distribution in their firm.
• Secondary data: Industry reports and internal documents such as demographics of the executive teams (responsible for strategic decisions), financial performance of firms, and so forth, were examined.
• Personal observation: Lastly, the researcher attended a 1-day strategy session and a weekly executive meeting at two firms in her sample.

Data analysis involved a combination of quantitative and qualitative techniques. Quantitative data on conflict and power were analyzed for patterns across firms/decisions. Qualitative interview data was combined into decision climate profiles, using profile traits (e.g., impatience) mentioned by more than one executive. For within-case analysis, decision stories were created for each strategic decision by combining executive accounts of the key decision events into a timeline. For cross-case analysis, pairs of firms were compared for similarities and differences, categorized along variables of interest such as decision speed and firm performance. Based on these analyses, tentative constructs and propositions were derived inductively from each decision story within firm categories. Each decision case was revisited to confirm the proposed relationships. The inferred propositions were compared with findings from the existing literature to reconcile examine differences with the extant literature and to generate new insights from the case findings. Finally, the validated propositions were synthesized into an inductive theory of strategic decision-making by firms in high-velocity environments.

Inferences derived from this multiple case research contradicted several decision-making patterns expected from the existing literature. First, fast decision makers in high-velocity environments used more information, and not less information as suggested by the previous literature. However, these decision makers used more real-time information (an insight not available from prior research), which helped them identify and respond to problems, opportunities, and changing circumstances faster. Second, fast decision makers examined more (not fewer) alternatives. However, they considered these multiple alternatives in a simultaneous manner, while slower decision makers examined fewer alternatives in a sequential manner. Third, fast decision makers did not centralize decision making or restrict inputs from others, as the literature suggested. Rather, these firms used a two-tiered decision process in which experienced counselors were asked for inputs in the first stage, following by a rapid comparison and decision selection in the second stage. Fourth, fast decision makers did not have less conflict, as expected from the literature, but employed better conflict resolution techniques to reduce conflict and improve decision-making speed. Finally, fast decision makers exhibited superior firm performance by virtue of their built-in cognitive, emotional, and political processes that led to rapid closure of major decisions.

Positivist Case Research Exemplar

Case research can also be used in a positivist manner to test theories or hypotheses. Such studies are rare, but Markus (1983) [12] provides an exemplary illustration in her study of technology implementation at the Golden Triangle Company (a pseudonym). The goal of this study was to understand why a newly implemented financial information system (FIS), intended to improve the productivity and performance of accountants at GTC was supported by accountants at GTC’s corporate headquarters but resisted by divisional accountants at GTC branches. Given the uniqueness of the phenomenon of interest, this was a single-case research study.

To explore the reasons behind user resistance of FIS, Markus posited three alternative explanations: (1) system-determined theory: resistance was caused by factors related to an inadequate system, such as its technical deficiencies, poor ergonomic design, or lack of user friendliness, (2) people-determined theory: resistance was caused by factors internal to users, such as the accountants’ cognitive styles or personality traits that were incompatible with using the system, and (3) interaction theory: resistance was not caused not by factors intrinsic to the system or the people, but by the interaction between the two set of factors. Specifically, interaction theory suggested that the FIS engendered a redistribution of intra-organizational power, and accountants who lost organizational status, relevance, or power as a result of FIS implementation resisted the system while those gaining power favored it.

In order to test the three theories, Markus predicted alternative outcomes expected from each theoretical explanation and analyzed the extent to which those predictions matched with her observations at GTC. For instance, the system-determined theory suggested that since user resistance was caused by an inadequate system, fixing the technical problems of the system would eliminate resistance. The computer running the FIS system was subsequently upgraded with a more powerful operating system, online processing (from initial batch processing, which delayed immediate processing of accounting information), and a simplified software for new account creation by managers. One year after these changes were made, the resistant users were still resisting the system and felt that it should be replaced. Hence, the system-determined theory was rejected.

The people-determined theory predicted that replacing individual resistors or co-opting them with less resistant users would reduce their resistance toward the FIS. Subsequently, GTC started a job rotation and mobility policy, moving accountants in and out of the resistant divisions, but resistance not only persisted, but in some cases increased! In one specific instance, one accountant, who was one of the system’s designers and advocates when he worked for corporate accounting, started resisting the system after he was moved to the divisional controller’s office. Failure to realize the predictions of the people-determined theory led to the rejection of this theory.

Finally, the interaction theory predicted that neither changing the system or the people (i.e., user education or job rotation policies) will reduce resistance as long as the power imbalance and redistribution from the pre-implementation phase were not addressed. Before FIS implementation, divisional accountants at GTC felt that they owned all accounting data related to their divisional operations. They maintained this data in thick, manual ledger books, controlled others’ access to the data, and could reconcile unusual accounting events before releasing those reports. Corporate accountants relied heavily on divisional accountants for access to the divisional data for corporate reporting and consolidation. Because the FIS system automatically collected all data at source and consolidated them into a single corporate database, it obviated the need for divisional accountants, loosened their control and autonomy over their division’s accounting data, and making their job somewhat irrelevant. Corporate accountants could now query the database and access divisional data directly without going through the divisional accountants, analyze and compare the performance of individual divisions, and report unusual patterns and activities to the executive committee, resulting in further erosion of the divisions’ power. Though Markus did not empirically test this theory, her observations about the redistribution of organizational power, coupled with the rejection of the two alternative theories, led to the justification of interaction theory.

Comparisons with Traditional Research

Positivist case research, aimed at hypotheses testing, is often criticized by natural science researchers as lacking in controlled observations, controlled deductions, replicability, and generalizability of findings – the traditional principles of positivist research. However, these criticisms can be overcome through appropriate case research designs. For instance, the problem of controlled observations refers to the difficulty of obtaining experimental or statistical control in case research. However, case researchers can compensate for such lack of controls by employing “natural controls.” This natural control in Markus’ (1983) study was the corporate accountant who was one of the system advocates initially, but started resisting it once he moved to controlling division. In this instance, the change in his behavior may be attributed to his new divisional position. However, such natural controls cannot be anticipated in advance, and case researchers may overlook then unless they are proactively looking for such controls. Incidentally, natural controls are also used in natural science disciplines such as astronomy, geology, and human biology, such as wait for comets to pass close enough to the earth in order to make inferences about comets and their composition.

The problem of controlled deduction refers to the lack of adequate quantitative evidence to support inferences, given the mostly qualitative nature of case research data. Despite the lack of quantitative data for hypotheses testing (e.g., t-tests), controlled deductions can still be obtained in case research by generating behavioral predictions based on theoretical considerations and testing those predictions over time. Markus employed this strategy in her study by generating three alternative theoretical hypotheses for user resistance, and rejecting two of those predictions when they did not match with actual observed behavior. In this case, the hypotheses were tested using logical propositions rather than using mathematical tests, which are just as valid as statistical inferences since mathematics is a subset of logic.

Third, the problem of replicability refers to the difficulty of observing the same phenomenon given the uniqueness and idiosyncrasy of a given case site. However, using Markus’ three theories as an illustration, a different researcher can test the same theories at a different case site, where three different predictions may emerge based on the idiosyncratic nature of the new case site, and the three resulting predictions may be tested accordingly. In other words, it is possible to replicate the inferences of case research, even if the case research site or context may not be replicable.

Fourth, case research tends to examine unique and non-replicable phenomena that may not be generalized to other settings. Generalizability in natural sciences is established through additional studies. Likewise, additional case studies conducted in different contexts with different predictions can establish generalizability of findings if such findings are observed to be consistent across studies.

Lastly, British philosopher Karl Popper described four requirements of scientific theories: (1) theories should be falsifiable, (2) they should be logically consistent, (3) they should have adequate predictive ability, and (4) they should provide better explanation than rival theories. In case research, the first three requirements can be increased by increasing the degrees of freedom of observed findings, such as by increasing the number of case sites, the number of alternative predictions, and the number of levels of analysis examined. This was accomplished in Markus’ study by examining the behavior of multiple groups (divisional accountants and corporate accountants) and providing multiple (three) rival explanations.

Popper’s fourth condition was accomplished in this study when one hypothesis was found to match observed evidence better than the two rival hypotheses.

[8] Benbasat, I., Goldstein, D. K., and Mead, M. (1987). “The Case Research Strategy in Studies of Information Systems,” MIS Quarterly (11:3), 369-386.

[9] Yin, R. K. (2002), Case Study Research: Design and Methods . Thousand Oaks, CA: Sage Publications.

[10] Eisenhardt, K. M. (1989). “Building Theories from Case Research,” Academy of Management Review

(14:4), 532-550.

[11] Eisenhardt, K. M. (1989). “Making Fast Strategic Decisions in High-Velocity Environments,” Academy of Management Journal (32:3), 543-576.

[12] Markus, M. L. (1983). “Power, Politics, and MIS Implementation,” Communications of the ACM (26:6), 430-444.

• Social Science Research: Principles, Methods, and Practices. Authored by : Anol Bhattacherjee. Provided by : University of South Florida. Located at : http://scholarcommons.usf.edu/oa_textbooks/3/ . License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike

Henry Gustav Molaison: The Curious Case of Patient H.M. 

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Erin Heaning, a holder of a BA (Hons) in Psychology from Princeton University, has experienced as a research assistant at the Princeton Baby Lab.

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Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Henry Gustav Molaison, known as Patient H.M., is a landmark case study in psychology. After a surgery to alleviate severe epilepsy, which removed large portions of his hippocampus , he was left with anterograde amnesia , unable to form new explicit memories , thus offering crucial insights into the role of the hippocampus in memory formation.

• Henry Gustav Molaison (often referred to as H.M.) is a famous case of anterograde and retrograde amnesia in psychology.
• H. M. underwent brain surgery to remove his hippocampus and amygdala to control his seizures. As a result of his surgery, H.M.’s seizures decreased, but he could no longer form new memories or remember the prior 11 years of his life.
• He lost his ability to form many types of new memories (anterograde amnesia), such as new facts or faces, and the surgery also caused retrograde amnesia as he was able to recall childhood events but lost the ability to recall experiences a few years before his surgery.
• The case of H.M. and his life-long participation in studies gave researchers valuable insight into how memory functions and is organized in the brain. He is considered one of the most studied medical and psychological history cases.

Who is H.M.?

Henry Gustav Molaison, or “H.M” as he is commonly referred to by psychology and neuroscience textbooks, lost his memory on an operating table in 1953.

For years before his neurosurgery, H.M. suffered from epileptic seizures believed to be caused by a bicycle accident that occurred in his childhood. The seizures started out as minor at age ten, but they developed in severity when H.M. was a teenager.

Continuing to worsen in severity throughout his young adulthood, H.M. was eventually too disabled to work. Throughout this period, treatments continued to turn out unsuccessful, and epilepsy proved a major handicap and strain on H.M.’s quality of life.

And so, at age 27, H.M. agreed to undergo a radical surgery that would involve removing a part of his brain called the hippocampus — the region believed to be the source of his epileptic seizures (Squire, 2009).

For epilepsy patients, brain resection surgery refers to removing small portions of brain tissue responsible for causing seizures. Although resection is still a surgical procedure used today to treat epilepsy, the use of lasers and detailed brain scans help ensure valuable brain regions are not impacted.

In 1953, H.M.’s neurosurgeon did not have these tools, nor was he or the rest of the scientific or medical community fully aware of the true function of the hippocampus and its specific role in memory. In one regard, the surgery was successful, as H.M. did, in fact, experience fewer seizures.

However, family and doctors soon noticed he also suffered from severe amnesia, which persisted well past when he should have recovered. In addition to struggling to remember the years leading up to his surgery, H.M. also had gaps in his memory of the 11 years prior.

Furthermore, he lacked the ability to form new memories — causing him to perpetually live an existence of moment-to-moment forgetfulness for decades to come.

In one famous quote, he famously and somberly described his state as “like waking from a dream…. every day is alone in itself” (Squire et al., 2009).

H.M. soon became a major case study of interest for psychologists and neuroscientists who studied his memory deficits and cognitive abilities to better understand the hippocampus and its function.

When H.M. died on December 2, 2008, at the age of 82, he left behind a lifelong legacy of scientific contribution.

Surgical Procedure

Neurosurgeon William Beecher Scoville performed H.M.’s surgery in Hartford, Connecticut, in August 1953 when H.M. was 27 years old.

During the procedure, Scoville removed parts of H.M.’s temporal lobe which refers to the portion of the brain that sits behind both ears and is associated with auditory and memory processing.

More specifically, the surgery involved what was called a “partial medial temporal lobe resection” (Scoville & Milner, 1957). In this resection, Scoville removed 8 cm of brain tissue from the hippocampus — a seahorse-shaped structure located deep in the temporal lobe .

Bilateral resection of the anterior temporal lobe in patient HM.

Further research conducted after this removal showed Scoville also probably destroyed the brain structures known as the “uncus” (theorized to play a role in the sense of smell and forming new memories) and the “amygdala” (theorized to play a crucial role in controlling our emotional responses such as fear and sadness).

As previously mentioned, the removal surgery partially reduced H.M.’s seizures; however, he also lost the ability to form new memories.

At the time, Scoville’s experimental procedure had previously only been performed on patients with psychosis, so H.M. was the first epileptic patient and showed no sign of mental illness. In the original case study of H.M., which is discussed in further detail below, nine of Scoville’s patients from this experimental surgery were described.

However, because these patients had disorders such as schizophrenia, their symptoms were not removed after surgery. In this regard, H.M. was the only patient with “clean” amnesia along with no other apparent mental problems.

H.M’s Amnesia

H.M.’s apparent amnesia after waking from surgery presented in multiple forms. For starters, H.M. suffered from retrograde amnesia for the 11-year period prior to his surgery.

Retrograde describes amnesia, where you can’t recall memories that were formed before the event that caused the amnesia. Important to note, current research theorizes that H.M.’s retrograde amnesia was not actually caused by the loss of his hippocampus, but rather from a combination of antiepileptic drugs and frequent seizures prior to his surgery (Shrader 2012).

In contrast, H.M.’s inability to form new memories after his operation, known as anterograde amnesia, was the result of the loss of the hippocampus.

This meant that H.M. could not learn new words, facts, or faces after his surgery, and he would even forget who he was talking to the moment he walked away.

However, H.M. could perform tasks, and he could even perform those tasks easier after practice. This important finding represented a major scientific discovery when it comes to memory and the hippocampus. The memory that H.M. was missing in his life included the recall of facts, life events, and other experiences.

This type of long-term memory is referred to as “explicit” or “ declarative ” memories and they require conscious thinking.

In contrast, H.M.’s ability to improve in tasks after practice (even if he didn’t recall that practice) showed his “implicit” or “ procedural ” memory remained intact (Scoville & Milner, 1957). This type of long-term memory is unconscious, and examples include riding a bike, brushing your teeth, or typing on a keyboard.

Most importantly, after removing his hippocampus, H.M. lost his explicit memory but not his implicit memory — establishing that implicit memory must be controlled by some other area of the brain and not the hippocampus.

After the severity of the side effects of H.M.’s operation became clear, H.M. was referred to neurosurgeon Dr. Wilder Penfield and neuropsychologist Dr. Brenda Milner of Montreal Neurological Institute (MNI) for further testing.

As discussed, H.M. was not the only patient who underwent this experimental surgery, but he was the only non-psychotic patient with such a degree of memory impairment. As a result, he became a major study and interest for Milner and the rest of the scientific community.

Since Penfield and Milner had already been conducting memory experiments on other patients at the time, they quickly realized H.M.’s “dense amnesia, intact intelligence, and precise neurosurgical lesions made him a perfect experimental subject” (Shrader 2012).

Milner continued to conduct cognitive testing on H.M. for the next fifty years, primarily at the Massachusetts Institute of Technology (MIT). Her longitudinal case study of H.M.’s amnesia quickly became a sensation and is still one of the most widely-cited psychology studies.

In publishing her work, she protected Henry’s identity by first referring to him as the patient H.M. (Shrader 2012).

In the famous “star tracing task,” Milner tested if H.M.’s procedural memory was affected by the removal of the hippocampus during surgery.

In this task, H.M. had to trace an outline of a star, but he could only trace the star based on the mirrored reflection. H.M. then repeated this task once a day over a period of multiple days.

Over the course of these multiple days, Milner observed that H.M. performed the test faster and with fewer errors after continued practice. Although each time he performed the task, he had no memory of having participated in the task before, his performance improved immensely (Shrader 2012).

As this task showed, H.M. had lost his declarative/explicit memory, but his unconscious procedural/implicit memory remained intact. Given the damage to his hippocampus in surgery, researchers concluded from tasks such as these that the hippocampus must play a role in declarative but not procedural memory.

Therefore, procedural memory must be localized somewhere else in the brain and not in the hippocampus.

H.M’s Legacy

Milner’s and hundreds of other researchers’ work with H.M. established fundamental principles about how memory functions and is organized in the brain.

Without the contribution of H.M. in volunteering the study of his mind to science, our knowledge today regarding the separation of memory function in the brain would certainly not be as strong.

Until H.M.’s watershed surgery, it was not known that the hippocampus was essential for making memories and that if we lost this valuable part of our brain, we would be forced to live only in the moment-to-moment constraints of our short-term memory .

Once this was realized, the findings regarding H.M. were widely publicized so that this operation to remove the hippocampus would never be done again (Shrader 2012).

H.M.’s case study represents a historical time period for neuroscience in which most brain research and findings were the result of brain dissections, lesioning certain sections, and seeing how different experimental procedures impacted different patients.

Therefore, it is paramount we recognize the contribution of patients like H.M., who underwent these dangerous operations in the mid-twentieth century and then went on to allow researchers to study them for the rest of their lives.

Even after his death, H.M. donated his brain to science. Researchers then took his unique brain, froze it, and then in a 53-hour procedure, sliced it into 2,401 slices which were then individually photographed and digitized as a three-dimensional map.

Through this map, H.M.’s brain could be preserved for posterity (Wb et al., 2014). As neuroscience researcher Suzanne Corkin once said it best, “H.M. was a pleasant, engaging, docile man with a keen sense of humor, who knew he had a poor memory but accepted his fate.

There was a man behind the data. Henry often told me that he hoped that research into his condition would help others live better lives. He would have been proud to know how much his tragedy has benefitted science and medicine” (Corkin, 2014).

Corkin, S. (2014). Permanent present tense: The man with no memory and what he taught the world. Penguin Books.

Hardt, O., Einarsson, E. Ö., & Nader, K. (2010). A bridge over troubled water: Reconsolidation as a link between cognitive and neuroscientific memory research traditions. Annual Review of Psychology, 61, 141–167.

Scoville, W. B., & Milner, B. (1957). Loss of recent memory after bilateral hippocampal lesions . Journal of neurology, neurosurgery, and psychiatry, 20 (1), 11.

Shrader, J. (2012, January). HM, the man with no memory | Psychology Today. Retrieved from, https://www.psychologytoday.com/us/blog/trouble-in-mind/201201/hm-the-man-no-memory

Squire, L. R. (2009). The legacy of patient H. M. for neuroscience . Neuron, 61 , 6–9.

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