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Record W4382918947 · doi:10.1080/07481187.2023.2230555

Actions taken and barriers encountered by professionals working with adults with intellectual disabilities who experience grief: a qualitative approach

2023· article· en· W4382918947 on OpenAlexaff
María Inmaculada Fernández‐Ávalos, Manuel Fernández‐Alcántara, María Nieves Pérez‐Marfil, Rosario Ferrer‐Cascales, Cyrille Kossigan Kokou‐Kpolou, Francisco Cruz‐Quintana

Bibliographic record

VenueDeath Studies · 2023
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsUniversité Laval
FundersUniversidad de Alicante
KeywordsGriefThematic analysisPsychologyQualitative researchCoping (psychology)Intellectual disabilityPopulationExpectancy theoryDisenfranchised griefLife expectancyClinical psychologyPsychotherapistSocial psychologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

Experience of grief has increased among people with intellectual disability because of their longer life expectancy. Professionals supporting this population are often critical of the lack of adequate tools for dealing with this situation. The objective of this study was to identify the strategies and barriers that these professionals are confronted with when dealing people with intellectual disability who are going through the grieving process. A qualitative study was conducted involving 20 professionals working with people with intellectual disability. Four themes were extracted using thematic analysis: Exclusion of clients from end-of-life and grief processes, Strategies to support the client's grief process, Emotional and personal difficulties faced by the professionals, and Coping and regulation of the professional's grief process. Barriers identified by these professionals include not having the specific skills to support clients in their grief and the emotional impact of the death of a client.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.662

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.161
GPT teacher head0.437
Teacher spread0.276 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations3
Published2023
Admission routes1
Has abstractyes

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