A Cross-Sectional Study of the Psychological Needs of Adults Living with Cystic Fibrosis
Bibliographic record
Abstract
BACKGROUND: Depression and anxiety are prevalent in people with cystic fibrosis (CF), yet psychological services are rarely accessible in CF clinics. This cross-sectional single center study reports on a psychological needs assessment of people with CF. METHODS: We asked adults attending a CF clinic, without integrated psychological services, to complete a psychological needs assessment survey that included items on: a) past access to psychological services (via a CF referral service), b) concerns relevant to discuss with a psychologist, and c) their likelihood of accessing psychological services if available at the CF clinic, and standardized measures of depression (CES-D) and anxiety (GAD-7). RESULTS: We enrolled 49 participants and 45 (91.8%) completed the survey. Forty percent reported elevated symptoms of depression and 13% had elevated anxiety. A majority of individuals (72.2% and 83.3%, respectively) indicated they would be likely to use psychological services, if available at the clinic. Concerns considered most relevant to discuss with a psychologist were: 1) worries (51.1%), 2) mood (44.4%), 3) life stress (46.6%), 4) adjustment to CF (42.2%), 5) life transitions (42.2%) and 6) quality of life (42.2%). CONCLUSIONS: This study highlights the rationale for screening adults with CF for depression and anxiety, and to facilitate provision of psychological services and preventative mental health interventions as an integral component of multi-disciplinary CF care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".