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Record W3217037750 · doi:10.21203/rs.3.rs-957500/v1

Happiness and Hope for Success in T1DM Patients

2021· preprint· en· W3217037750 on OpenAlexaff
Katarzyna Cyranka, Domnika Dudek, Bartłomiej Matejko, Piotr P. Małecki, Maciej T. Małecki, Maciej Pilecki, Tomasz Klupa

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsAbbott (Canada)
FundersAbbott Diabetes CareUniwersytet Jagielloński Collegium Medicum
KeywordsHappinessPolitical sciencePsychologyAestheticsSocial psychologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract Happiness and hope are essential parts of human health. One of the main purposes of health care, including diabetes care, are to achieve happiness and a sense of purpose in life. Material and methodDuring educational workshops a short survey concerning the level of happiness and hope for success in the group of Type 1 Diabetes Mellitus (T1DM) patients was carried out. 120 patients anonymously filled in Subjective Happiness Scale (SHS) and a Hope for Success Questionnaire (KNS).Results and conclusionsThe level of subjective happiness in T1DM patients was lower than in general population for both sexes, for all age categories apart from people older than 50, who seem to be happy and satisfied with their life with no differences compared to the general population. In terms of hope for success, T1DM teenagers and adults aged 27-50 did not differ from the general population. T1DM patients older than 50 turned out to have higher hope for success in life that other T1DM patients. Special attention should be paid to patients in young adulthood (18-26), who seem to be the most pessimistic group of T1DM patients, with low self-esteem and low believe in their possibilities.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.064
GPT teacher head0.439
Teacher spread0.375 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2021
Admission routes1
Has abstractyes

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