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Record W3027140680 · doi:10.11575/prism/37683

Understanding the Experiences of Nurses Managing Querulous Complainants: What Does Health Care Know?

2020· dissertation· en· W3027140680 on OpenAlexaboutno aff
Amie Cameal Liddle

Bibliographic record

VenueOpen MIND · 2020
Typedissertation
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsnot available
Fundersnot available
KeywordsNeed to knowHealth careMedicinePsychologyNursingPolitical scienceComputer scienceComputer securityLaw

Abstract

fetched live from OpenAlex

Society demands and rightfully deserves excellence in health care but unfortunately, this expectation is not always met. Having worked in the Department of Patient Relations for 13 years, I am privileged to have conversed with thousands of patients and families to resolve concerns related to unsatisfactory health care experiences. Unfortunately, I have also engaged with countless patients and families who remained unsatisfied with their care and are thus labeled difficult or querulous. I became increasingly perplexed by the presentation of such complainants and recognized that there was more to be understood about the experience of attempting to reach resolution. For this research study, I have utilized a qualitative design of hermeneutic inquiry as guided by the philosophical hermeneutics of Hans-Georg Gadamer (1900-2002) to address my research question: How might we understand experiences of nurses managing querulous complainants? I recruited five Registered Nurses (RN) employed by Alberta Health Services (AHS) as Patient Concerns Consultants (PCC). The data for my research were generated through planned, skilfully conducted, semi-structured interviews with participants. This approach allowed me to listen and be open to the participants’ understandings of their experience with querulous complainants. My research relied on the concepts of the hermeneutic circle and fusion of horizons in order to understand the experiences and bring forth interpretations. Through the research process, new and altered understandings emerged through the interpretations of Apology, War, Monsters, Soldiers, Robots, Gods, and the Black Hole. The research suggests that there is an absence of relationship between querulous complainants and PCCs. Querulous complainants cause distress, suffering, and require a unique concerns management process. The ways in which politics and Groupthink in health care play an integral part in querulous complaint management is also tendered. This study is the first known qualitative research inquiry intended to explore querulous complainants which creates a platform for new research related to managing health care complaints.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.086
GPT teacher head0.397
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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Same venueOpen MINDSame topicWorkplace Violence and BullyingFrench-language works237,207