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Record W2150923287 · doi:10.1177/1084713811425751

The Need for Evidence in an Anecdotal World

2011· editorial· en· W2150923287 on OpenAlexaboutno aff
Charles J. Limb

Bibliographic record

VenueTrends in Amplification · 2011
Typeeditorial
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialScientific evidenceOutcome (game theory)Health carePsychologyProcess (computing)Patient satisfactionMEDLINEEvidence-based medicineMedicineAlternative medicineNursingComputer scienceSurgeryPolitical science

Abstract

fetched live from OpenAlex

One of the most difficult aspects of providing health care is the tension that exists between objective evidence, collectively accumulated over generations, and the fact that subjective practitioners deliver care one patient at a time. Although we may strive to understand the continuously developing scientific literature that is the foundation of our understanding of disease, it still remains far from obvious how exactly that literature should be applied to a patient who needs help. In science, the ostensible goal is the generation of data and knowledge that can then be applied as necessary. However, the delivery of health care is not a pure scientific process. There are many cases in which a patient’s satisfaction with his or her treatment will take precedence over the provider’s view of how well the treatment adhered to the best available evidence. And in the end, all of the evidence in the world may provide little comfort to a patient who has a poor outcome. There is a wide range of variables beyond a provider’s control that ultimately may have as huge an impact on a patient’s outcome as any randomized controlled trial. Rational decision making is easily disturbed when it comes to factors such as money, time, and emotion. Even when randomized controlled trials exist, it is often unclear how the results should be applied to patients whose profiles do not quite match those of the patients who were enrolled in the trials. As a result of these difficulties, there has been an ever-increasing emphasis on applicability—hence, the trend toward more translational research and the rise of clinician-scientists who naturally approach basic science from a clinical perspective. Meta-analysis has evolved as a useful approach to gather, evaluate, and consolidate the broad range of data available on just about any topic. The proper design and execution of randomized controlled clinical trials are widely accepted as the gold standards to be used when evaluating the quality of scientific data. These important developments, however, also shed an uncomfortable light on just how poor most of the clinical data have been to date (and continues to be today). This is not simply attributable to ignorance or lack of effort but instead to the realities of patient care where most questions to be answered just do not have randomized controlled trial data on which to base the answer. In the treatment of carcinomas of the ear, for example, this type of rigorous evidence is hard to come by. When a patient presents with this disease, surgeons do the best they can to interpret the available literature. However, the stakes are too high to proceed slowly, waiting for better data to become available as a tumor grows. As a result, we proceed swiftly, aware that our decisions are not based on the best possible evidence but rather that there are few alternatives—a decision must be made. Although not every patient has a life-threatening condition, this situation has obvious parallels to more routine situations—which hearing aid is really the best for a patient? What is the quality of the evidence to support one’s decision? It is almost impossible to ignore one’s own experience. In other words, the personal experiences we have as providers—anecdotal evidence if it were to be evaluated—typically do affect how we make decisions. Some of the wisest, most experienced practitioners in the world today are valued precisely because of the wealth of anecdotal evidence that they possess, and for a patient, it is more comforting to have an experienced, confident health care provider who has “seen it all,” than to have a naive student who may know the scientific literature extremely well yet has little personal experience. Most of the details that separate an experienced clinician from an inexperienced clinician will never be substantiated by high-level evidence and will instead remain anecdotal. Thus, it is important to acknowledge that we live anecdotal lives, personally, professionally, and even scientifically. The mistake, however, is to overestimate the significance of one’s own anecdotal evidence. What if two experienced practitioners have had completely valid yet exactly opposite experiences? It would be difficult to know how to decide the best course of action if we only had the benefit of these two opinions, as valuable as they may be. Instead, we would want to look beyond the experience of these two individuals. We would want to benefit from the accumulated wisdom and experiences of all of the practitioners that have encountered similar situations. We would want an unbiased, objective understanding of what the outcomes were. We would want to have all of the best available evidence, and we would want to differentiate this type of evidence from anecdotes that may be fascinating but perhaps irrelevant. We would also want to recognize that this evidence, however high in quality, is intrinsically limited and will itself become supplanted by newer, better evidence in the future. With this background in mind, I applaud the authors of the series of four articles presented here in this double issue. This series of articles begins with the idea that although evidence-based practice can be fraught with difficulties, it remains important to integrate high-quality research evidence and clinical experience to improve the quality and effectiveness of treatment for the patients in our care. The second article uses a knowledge-to-action framework to complete a synthesis of current audiological outcome measures for infants and children to be considered for inclusion in a guideline for clinical practice. The third article uses a pediatric audiologist community of practice to evaluate the individual components of the guideline called The University of Western Ontario Pediatric Audiological Monitoring Protocol (UWO PedAMP). The fourth article presents clinical data from infants and children with hearing loss who wear hearing aids to supply further evidence, including case studies, to augment clinical implementation of the UWO PedAMP in practice. It is notable how the articles presented here, though based on research done in Canada, apply equally well to those of us in other parts of the world. To me, these articles are a clear reminder that the hearing health sciences have often lagged behind in this effort to employ evidence-based practice. Articles like the ones presented here will hopefully contribute in a significant way toward the cultural shift—yes, our own lives are anecdotal and this is often how we learn. When it comes to proper treatment decisions for the delivery of health care, however, we should find something better than that.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.247
metaresearch head score (Gemma)0.636
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.753
Threshold uncertainty score0.929

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2470.636
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0120.007
Science and technology studies0.0060.038
Scholarly communication0.0280.074
Open science0.0070.019
Research integrity0.0240.054
Insufficient payload (model declined to judge)0.0090.004

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 head0.846
GPT teacher head0.588
Teacher spread0.258 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainMethods
GenreEditorial

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

Citations5
Published2011
Admission routes1
Has abstractyes

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