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Record W2342031308 · doi:10.46743/2160-3715/2016.2269

Walking on Eggshells: The Lived Experience of Partners of Veterans with PTSD

2016· article· en· W2342031308 on OpenAlexaff
Tiffany Beks

Bibliographic record

VenueThe Qualitative Report · 2016
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychologyMental healthPsychological interventionCoping (psychology)ApprehensionGriefInterpretative phenomenological analysisPsychotherapistQualitative researchClinical psychologyPsychiatrySociology

Abstract

fetched live from OpenAlex

This phenomenological study examined the descriptions of lived experience among female partners of veteran men with combat-related posttraumatic stress disorder (PTSD) via internet discussion forums. Personal, self-initiated written accounts of 30 partners were analyzed with respect to meaning, challenges, coping responses, and role in veterans’ healing and rehabilitation. Following data analysis, five descriptive themes emerged: all-consuming effect of the illness, walking on eggshells, ambiguous loss, alone, and facing PTSD as a unit. The central meaning of these themes describes the widespread priority of the veterans’ illness, and the resulting isolation, grief, and apprehension experienced by intimate partners as they assume primary caregiving roles. The findings indicate that the nature of combat-related PTSD places significant burden and responsibility on partners. I argue that mental health supports and services should be implemented in order to meet the needs of partners of veteran with PTSD. Furthermore, the needs and preferences of partners should be considered in the design and delivery of mental health services targeted toward veterans. This study has implications for practitioners and for future planning and implementation of services and interventions for military families affected by combat trauma.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.065
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.386
GPT teacher head0.586
Teacher spread0.200 · 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

Citations23
Published2016
Admission routes1
Has abstractyes

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