MétaCan
Menu
← Back to cohort

549 Preventing work disability in workers with depression; a systematic review

2018· review· en· W2800843993 on OpenAlexaff
Kimberley Cullen, Emma Irvin, Dwayne Van Eerd, Rob Saunders

Bibliographic record

Venuenot available
Typereview
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsInstitute for Work & Health
Fundersnot available
KeywordsPsychological interventionSick leaveRehabilitationDepression (economics)Intervention (counseling)MedicineWork (physics)Occupational therapyEvidence-based practicePsychologyPsychiatryPhysical therapyAlternative medicine

Abstract

fetched live from OpenAlex

Introduction By the year 2020, depression will be the second most burdensome illness in developed economies. In addition to its adverse individual effects, the associated workplace effects of depression are extensive. This review is provides a synthesis of the evidence to determine effective intervention approaches for managing depression in the workplace: both to help workers stay-at-work while experiencing symptoms and to return-to-work after an episode of time away from work. Methods We followed a systematic review process developed by the Institute for Work and Health and an adapted best evidence synthesis. Articles that met the following criteria were considered: working age individuals with depression; workplace-based interventions; including a comparison group; outcomes of work functioning, work disability, or recurrences of work disability. Result Seven electronic databases were searched from inception up to June 2015. The review examined 8123 titles and abstracts for relevance and found 20 RCTs and seven nRCTs from various jurisdictions. These studies evaluated a range of interventions, including; cognitive-behavioural therapy (CBT), work-focused CBT, problem solving therapy (PST), work-focused PST, enhanced care delivery, coordination of services, short- and long-term psychodynamic therapy, stress reduction programs, exercise training, part-time sick leave and nature-based rehabilitation. Our findings indicate that CBT and PST interventions can help workers with depression stay-at-work while managing their symptoms; however, only work-focused CBT is sufficient to help workers return-to-work after an absence. There is currently not enough evidence from the scientific literature to guide practice for the remaining interventions identified in this review. Discussion We synthesised the current best evidence on workplace interventions to help employees manage symptoms of depression. The interventions identified in this review focused on strategies targeting personal resilience and coping skills of individuals with depression. More work is needed to evaluate interventions aimed at mitigating workplace factors such as psychosocial working conditions.

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)0.007
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.030
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.068
GPT teacher head0.467
Teacher spread0.399 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same topicResilience and Mental Health→French-language works237,207→