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Record W141957184 · doi:10.1177/070674371305800801

Depression in Primary Care: What More Do We Need to Know?

2013· letter· en· W141957184 on OpenAlexvenueaboutno aff
Tony Kendrick

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2013
Typeletter
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsnot available
FundersNational Institutes of HealthNational Institute for Health and Care Research
KeywordsDepression (economics)Primary careMedicineQuality of life (healthcare)Management of depressionCohortPsychiatryPsychologyMEDLINEFamily medicineGerontologyNursingPolitical science

Abstract

fetched live from OpenAlex

AbbreviationsAD antidepressantFP family physicianGP general practitionerIAPT Increasing Access to Psychological TherapiesMDD major depressive disorderQOF Quality and Outcomes FrameworkIn this edition of The Canadian Journal of Psychiatry, Dr Marilyn A Craven and Dr Roger Bland' cite studies suggesting that around 10% of primary care patients are likely to meet diagnostic criteria for MDD, and that numbers will rise as the baby boomer cohort ages and the prevalence of chronic physical disease increases. They suggest that the persistently low rates of detection, treatment, and follow-up found in primary care need addressing to improve treatment adherence and patient outcomes, and that newer evidencebased models of case management and collaborative care need to be adopted, integrating care for depression with that for physical diseases.1Alongside this very useful overview of the issues, Dr Linda Gask2 reviews studies of educating FPs about the identification and treatment of depression, and points out that simple education has largely failed to change practice. She identifies perceived structural obstacles to change, including a relative lack of time and resources in primary care, but highlights a tendency among FPs to conceptualize depression as reactive or endogenous, with subsequent uncertainty about treating it in the face of adverse life events and difficulties.2 This implies that FPs perceive limits to the medical model of depression inherent in the research described by Dr Craven and Dr Bland,1 and the need to take social factors into account, but that they are uncertain about how to do so in practice.We know that the onset of depression is often provoked by adverse social circumstances,3·4 and that the prevalence of depression differs markedly between populations, in accordance with rates of social adversity.5 Cross-sectional surveys using consistent diagnostic criteria suggest that the prevalence of MDD doubled among US adults between 1992 and 2002,6 and all high-income countries saw yearon-year increases in AD prescribing in primary care in the 1990s following the introduction of the selective serotonin reuptake inhibitors,7 prompting talk of a depression epidemic, although we found increased AD prescribing in the United Kingdom to be due to increases in the proportion of sufferers being put on long-term treatment, rather than to a rise in the incidence of depression.7 Rates of consulting for depression actually seemed to be falling during the period of relative affluence in the United Kingdom from 2000 onwards,7-8 at least up until the economic crash in 2008.8 FPs may well question the extent to which they can ameliorate the effects of changes in their patients' financial security, employment, and housing. Anderson et al9 pointed out 20 years ago that the prevalence of case-level psychological distress in a population correlates highly with the mean population level of psychological distress, indicating for them thatThe mental health of society is integral and reflects its social economic and political structure. At this point psychiatric epidemiology and prevention merge into social policy-they cannot exist apart.9·p 484Therefore, interventions are most likely to be effective if they affect the whole of the population rather than the highrisk tail. However, despite this, professionals faced with people in distress must do the best they can for them, even if political solutions may seem to be more likely to make a difference at the population level.The extent to which the recognition of depression by FPs needs to be improved has been questioned, and the old notion that FPs miss 50% or more of cases may be doing them a disservice. Studies have suggested that missed cases tend to be milder,10· and that the recognition of moderateto-severe depression, where the evidence of benefit from treatment is stronger, is actually quite good. In the World Health Organization naturalistic study, in 15 cities around the world, patients whose depression went unrecognized had milder depression at baseline and were not found to have worse outcomes than those recognized. …

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)0.014
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.053
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.058
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0020.003
Science and technology studies0.0040.005
Scholarly communication0.0100.020
Open science0.0030.004
Research integrity0.0140.018
Insufficient payload (model declined to judge)0.0110.002

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 head0.016
GPT teacher head0.300
Teacher spread0.284 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations5
Published2013
Admission routes2
Has abstractyes

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