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Record W4381887711 · doi:10.1101/2023.06.20.23291667

Determinants of Sense of Coherence among older adults attending a Geriatric Centre in Nigeria A study Protocol

2023· preprint· en· W4381887711 on OpenAlexafffund
Lawrence A. Adebusoye, Oluwagbemiga Oyinlola, Eniola Cadmus

Bibliographic record

VenuemedRxiv · 2023
Typepreprint
Languageen
FieldHealth Professions
TopicHealth, psychology, and well-being
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsRespondentPsychologyQuality of life (healthcare)FeelingGerontologyGeriatric Depression ScaleSpiritualitySalutogenesisInterviewCognitionMedicineClinical psychologySocial psychologyPsychiatryHealth promotionDepressive symptomsNursingAlternative medicinePublic healthSociology

Abstract

fetched live from OpenAlex

Abstract Background Old age is a stage of life in which people face changes in their physical and psycho-emotional aspects. Thus, having an adequate sense of coherence (SOC) is required to face these situations successfully. The SOC (comprehensibility, manageability, and meaningfulness of life) is defined as a global orientation expressing a person’s pervasive and enduring feeling of confidence modified by stimuli derived from one’s internal and external environments while living, the resources available to meet the demands posed by these stimuli, and the fact that these demands are challenges worthy of investment and engagement. Empirical evidence on the SOC available to older persons is lacking in countries like Nigeria. This study aims to investigate the Sense of Coherence (SOC) available to older patients attending the Chief Tony Anenih Geriatric Centre (CTAGC), University College Hospital (UCH), Ibadan, Nigeria and its association with socio-demographic, family relationships, spirituality, cognition, depression, functional disability, quality of life, and level of frailty among them. Methods This will be a cross-sectional descriptive study of 385 older persons (≥60 years) attending the CTAGC, UCH, Ibadan, Nigeria. A semi-structured, interviewer-administered questionnaire will obtain information on the respondents’ demographic, social, economic, family relationships, health profiles, and healthcare utilization patterns. The Sense of Coherence (SOC) status will be measured with Antonovsky’s SOC scale (SOC-13). The information on the respondent’s spirituality, cognition, depression, functional disability, quality of life, family relationship, and level of frailty will be assessed using the spirituality index of well-being, six-item screener, Geriatric depression scale, Barthel’s independence Activities of Daily Living, World Health Organization-Quality of Life brief scale, Sense of Coherence-Family Relations Scale (SCO-FRS), and self-assessment of frailty syndrome, respectively. Data analysis Data will be entered and analyzed using the Statistical Package for Social Sciences (SPSS) Version 27.0. Tables and charts will be summarised using frequency, proportion, and means. Inferential statistics will test for associations between variables using the Student’s t-test and Analysis of Variance (ANOVA) as appropriate. Linear regression analysis will explore the relationship between significant variables in bivariate analysis with SOC. The level of significance will be set at 5%. Implication This investigation holds several promises for enhancing psychological well-being, improving physical health outcomes, informing holistic geriatric care, strengthening social support networks, and guiding policy and program development. By prioritizing research and intervention in these areas, we can foster a society that values and supports the well-being of older adults, ensuring they enjoy a fulfilling and dignified life during their golden years.

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)0.006
metaresearch head score (Gemma)0.004
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.017
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0170.002

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 head0.451
Teacher spread0.388 · 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
GenreProtocol

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

Citations1
Published2023
Admission routes2
Has abstractyes

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