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Record W2022963715 · doi:10.1037/0278-6133.26.6.753

Health incongruence in later life: Implications for subsequent well-being and health care.

2007· article· en· W2022963715 on OpenAlexfundno aff
Joelle C. Ruthig, Judith G. Chipperfield

Bibliographic record

VenueHealth Psychology · 2007
Typearticle
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchManitoba Health Research Council
KeywordsPessimismOptimismPsychologyLife satisfactionCompromiseHealth careGerontologyDevelopmental psychologyClinical psychologyMedicineSocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: The premise that pessimistic health appraisals compromise well-being whereas optimistic appraisals are compensatory was examined in a longitudinal study of 232 community-dwelling older adults (ages 79-98 years). DESIGN: Subjective health (SH) appraisals were contrasted with objective health (OH) to identify realists, whose ratings were congruent (SH = OH), distinguishing them from health pessimists (SH < OH) and health optimists (SH > OH), whose ratings were incongruent. Analyses of covariance were used to examine group differences 2 years later on well-being and health care. MAIN OUTCOME MEASURES: Outcome measures were psychological well-being (life satisfaction, positive and negative emotions), functional well-being (objective and perceived physical activity, activity restriction), and health care (health care management, hospital admissions, length of hospital stays). RESULTS: Compared with realists, pessimists had significantly poorer outcomes and optimists had better outcomes. Because perceived control (PC) was weaker among pessimists and stronger among optimists, supplemental analysis determined whether PC differences explained these findings. When accounting for PC, many pessimism and optimism effects became nonsignificant, yet effects on functional well-being remained unchanged. CONCLUSION: Findings have implications for older adults at risk of functional decline.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.572
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.047
GPT teacher head0.445
Teacher spread0.398 · 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

Citations54
Published2007
Admission routes1
Has abstractyes

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