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Record W1579428508 · doi:10.18438/b8gw36

Mental Model Construction in MedlinePlus Information Searching Involves Changes and Developments in Cognition, Emotion, and Behaviour

2013· article· en· W1579428508 on OpenAlexvenueno aff
Antonio P. DeRosa

Bibliographic record

VenueEvidence Based Library and Information Practice · 2013
Typearticle
Languageen
FieldMedicine
TopicTechnology and Human Factors in Education and Health
Canadian institutionsnot available
Fundersnot available
KeywordsSession (web analytics)Task (project management)CognitionComputer sciencePopulationPsychologyMental healthApplied psychologyMultimediaWorld Wide WebMedicinePsychotherapist

Abstract

fetched live from OpenAlex

Objectives – To explore the construction of mental models as a dynamic process and how users understand a consumer health information system, MedlinePlus, during a search session. 
 
 Design – Face-to-face interview. 
 
 Setting – Large university. 
 
 Subjects – A total of 38 undergraduate students participated in the study. All majoring in non-medical fields, such as art history, psychology, business, and communication studies. 
 
 Methods – Participants were randomized into two groups: the simple task group and the complex task group. Simple task group members were asked to perform 12 simple tasks while the complex group members performed three more-involved tasks. Simple tasks were defined as succinct questions with finite answers while complex tasks were open-ended and required more cognitive activity and synthesizing on the part of the individual. Participants in both groups were then given four simple tasks and two complex tasks to perform. Data was derived by video recording search sessions with individuals and interview-like questions for the tasks performed. Participants were given a brief introduction to the search session design and sessions took place in a private lab. Since the aim of the study was to track participants’ mental modeling processes over time, coding of data was caught at three different times throughout the search sessions: T1 (MM1) after five minutes of free exploration, T2 (MM2) after the first search session, and T3 (MM3) after the second search session. 
 
 Main Results – The author discusses the demographic specifics of the population participating in the study. Although participants were split into two groups, the results were combined to be more meaningful. Out of the 38 participants, 20 were female and 18 were male with ages ranging from 18 to 22. They had, on average, 10 years of computer experience and their average spatial ability score was 12.71. Also on average, they spent about 20 minutes completing the first search session and 12 minutes completing the second search session. The results show that participant-developed mental models of the MedlinePlus web space can be clustered into the following five theoretical components (this information is quantified in tables throughout the paper): system, content, information organization, interface, and procedural knowledge. 
 
 Conclusion – The study allowed participants to articulate their mental models and representations while conducting predefined searches during private sessions using MedlinePlus. The study also illustrates how users’ mental models of a system developed during interactions with an online system, on a theoretical level. Little is actually known about how mental models are developed when users interact with an information system. The study serves to explore this arena and reveals that the mental model construction involves changes and developments in three parallel dimensions: cognition, emotion, and behaviour. Also, these dimensions are accompanied by three mental activities: assimilating new concepts, phasing out previously perceived concepts, and modifying existing concepts. The mental model construction process could be a useful tool to build user models and make better design decisions for information systems.

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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.069
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.295
Teacher spread0.273 · 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 designObservational
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

Citations0
Published2013
Admission routes1
Has abstractyes

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