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Record W4205629668 · doi:10.1186/s12888-021-03622-3

“You can’t un-ring the bell”: a mixed methods approach to understanding veteran and family perspectives of recovery from military-related posttraumatic stress disorder

2022· article· en· W4205629668 on OpenAlexafffund
Kate St. Cyr, Jenny J. W. Liu, Heidi Cramm, Anthony Nazarov, Renée Hunt, Callista Forchuk, Erisa Deda, J. Don Richardson

Bibliographic record

VenueBMC Psychiatry · 2022
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsQueen's UniversityWestern UniversityLawson Health Research InstitutePublic Health OntarioUniversity of Toronto
FundersMinistère de la Défense Nationale
KeywordsVeterans AffairsPsychologyPosttraumatic stressCoping (psychology)Mental healthClinical psychologyDiscontinuationTraumatic stressPsychiatryPsychotherapistQualitative researchContent analysisNarrativeMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Military-related posttraumatic stress disorder (PTSD) is a complex diagnosis with non-linear trajectories of coping and recovery. Current approaches to the evaluation of PTSD and treatment discontinuation often rely on biomedical models that dichotomize recovery based on symptom thresholds. This approach may not sufficiently capture the complex lived experiences of Veterans and their families. To explore conceptualizations of recovery, we sought perspectives from Veterans and their partners in a pilot study to understand: 1) how Veterans nearing completion of treatment for military-related PTSD and their partners view recovery; and 2) the experience of progressing through treatment towards recovery. METHODS: We employed a concurrent mixed methods design. Nine Veterans nearing the end of their treatment at a specialized outpatient mental health clinic completed quantitative self-report tools assessing PTSD and depressive symptom severity, and an individual, semi-structured interview assessing views on their treatment and recovery processes. Veterans' partners participated in a separate interview to capture views of their partners' treatment and recovery processes. Descriptive analyses of self-report symptom severity data were interpreted alongside emergent themes arising from inductive content analysis of qualitative interviews. RESULTS: While over half of Veterans were considered "recovered" based on quantitative assessments of symptoms, individual reflections of "recovery" were not always aligned with these quantitative assessments. A persistent narrative highlighted by participants was that recovery from military-related PTSD was not viewed as a binary outcome (i.e., recovered vs. not recovered); rather, recovery was seen as a dynamic, non-linear process. Key components of the recovery process identified by participants included a positive therapeutic relationship, social support networks, and a toolkit of adaptive strategies to address PTSD symptoms. CONCLUSIONS: For participants in our study, recovery was seen as the ability to navigate ongoing issues of symptom management, re-engagement with meaningful roles and social networks, and a readiness for discontinuing intensive, specialized mental health treatment. The findings of this study highlight important considerations in balancing the practical utility of symptom severity assessments with a better understanding of the treatment discontinuation-related needs of Veterans with military-related PTSD and their families, which align with a contemporary biopsychosocial approach to recovery.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.078
GPT teacher head0.360
Teacher spread0.282 · 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 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

Citations14
Published2022
Admission routes2
Has abstractyes

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