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Depression questionnaire cutoffs are calibrated for screening accuracy and not to assess prevalence, but the Geriatric Depression Scale (GDS-15) is often used to estimate diagnostic prevalence among older adults, most commonly with scores of ≥ 5. We conducted an individual participant data meta-analysis to compare depression prevalence based on GDS-15 ≥ 5 to Structured Clinical Interview for Diagnostic and Statistical Manual (SCID) diagnoses and assessed whether an alternative cutoff could be more accurate. We used generalized linear mixed models to estimate prevalence. Data from 14 studies (3602 participants, 434 SCID major depression) were included. Pooled GDS-15 ≥ 5 prevalence was 34.2% (95% confidence interval [CI] 27.5–41.6%), and pooled SCID prevalence was 14.8% (95% CI 10.0–21.5%; difference of 17.6%, 95% CI 11.6–23.6%). GDS-15 ≥ 8 provided the closest estimate to SCID with mean difference of − 0.3% (95% prediction interval − 17.0–16.5%). Prevalence estimate differences were not associated with study or participant characteristics. In sum, GDS-15 ≥ 5 substantially overestimated depression prevalence. A cutoff of ≥ 8 was accurate overall, but heterogeneity was too high for implementation in practice. Validated diagnostic interviews should be used to estimate major depression prevalence among older adults. [ABSTRACT FROM AUTHOR]

Objectives: Optimal cutoff thresholds are selected to separate 'positive' from 'negative' screening results. We evaluated how depression screening tool studies select optimal cutoffs. Methods: We included studies from previously conducted meta‐analyses of Patient Health Questionnaire‐9, Edinburgh Postnatal Depression Scale, or Hospital Anxiety and Depression Scale—Depression accuracy. Outcomes included whether an optimal cutoff was selected, method used, recommendations made, and reporting guideline and protocol citation. Results: Of 212 included studies, 172 (81%) attempted to identify an optimal cutoff, and 147 of these 172 (85%) reported one or more methods. Methods were heterogeneous with Youden's J (N = 35, 23%) most common. Only 23 of 147 (16%) studies described a rationale for their method. Rationales focused on balancing sensitivity and specificity without describing why desirable. 131 of 172 studies (76%) identified an optimal cutoff other than the standard; most did not make use recommendations (N = 56; 43%) or recommended using a non‐standard cutoff (N = 53; 40%). Only 4 studies cited a reporting guideline, and 4 described a protocol with optimal cutoff selection methods, but none used the protocol method in the published study. Conclusions: Research is needed to guide how selection of cutoffs for depression screening tools can be standardized and reflect clinical considerations. [ABSTRACT FROM AUTHOR]

The diagnostic accuracy of a screening tool is often characterized by its sensitivity and specificity. An analysis of these measures must consider their intrinsic correlation. In the context of an individual participant data meta-analysis, heterogeneity is one of the main components of the analysis. When using a random-effects meta-analytic model, prediction regions provide deeper insight into the effect of heterogeneity on the variability of estimated accuracy measures across the entire studied population, not just the average. This study aimed to investigate heterogeneity via prediction regions in an individual participant data meta-analysis of the sensitivity and specificity of the Patient Health Questionnaire-9 for screening to detect major depression. From the total number of studies in the pool, four dates were selected containing roughly 25%, 50%, 75% and 100% of the total number of participants. A bivariate random-effects model was fitted to studies up to and including each of these dates to jointly estimate sensitivity and specificity. Two-dimensional prediction regions were plotted in ROC-space. Subgroup analyses were carried out on sex and age, regardless of the date of the study. The dataset comprised 17,436 participants from 58 primary studies of which 2322 (13.3%) presented cases of major depression. Point estimates of sensitivity and specificity did not differ importantly as more studies were added to the model. However, correlation of the measures increased. As expected, standard errors of the logit pooled TPR and FPR consistently decreased as more studies were used, while standard deviations of the random-effects did not decrease monotonically. Subgroup analysis by sex did not reveal important contributions for observed heterogeneity; however, the shape of the prediction regions differed. Subgroup analysis by age did not reveal meaningful contributions to the heterogeneity and the prediction regions were similar in shape. Prediction intervals and regions reveal previously unseen trends in a dataset. In the context of a meta-analysis of diagnostic test accuracy, prediction regions can display the range of accuracy measures in different populations and settings. [ABSTRACT FROM AUTHOR]

The diagnostic accuracy of a screening tool is often characterized by its sensitivity and specificity. An analysis of these measures must consider their intrinsic correlation. In the context of an individual participant data meta-analysis, heterogeneity is one of the main components of the analysis. When using a random-effects meta-analytic model, prediction regions provide deeper insight into the effect of heterogeneity on the variability of estimated accuracy measures across the entire studied population, not just the average. This study aimed to investigate heterogeneity via prediction regions in an individual participant data meta-analysis of the sensitivity and specificity of the Patient Health Questionnaire-9 for screening to detect major depression. From the total number of studies in the pool, four dates were selected containing roughly 25%, 50%, 75% and 100% of the total number of participants. A bivariate random-effects model was fitted to studies up to and including each of these dates to jointly estimate sensitivity and specificity. Two-dimensional prediction regions were plotted in ROC-space. Subgroup analyses were carried out on sex and age, regardless of the date of the study. The dataset comprised 17,436 participants from 58 primary studies of which 2322 (13.3%) presented cases of major depression. Point estimates of sensitivity and specificity did not differ importantly as more studies were added to the model. However, correlation of the measures increased. As expected, standard errors of the logit pooled TPR and FPR consistently decreased as more studies were used, while standard deviations of the random-effects did not decrease monotonically. Subgroup analysis by sex did not reveal important contributions for observed heterogeneity; however, the shape of the prediction regions differed. Subgroup analysis by age did not reveal meaningful contributions to the heterogeneity and the prediction regions were similar in shape. Prediction intervals and regions reveal previously unseen trends in a dataset. In the context of a meta-analysis of diagnostic test accuracy, prediction regions can display the range of accuracy measures in different populations and settings. [ABSTRACT FROM AUTHOR]

Item 10 of the Edinburgh Postnatal Depression Scale (EPDS) is intended to assess thoughts of intentional self-harm but may also elicit concerns about accidental self-harm. It does not specifically address suicide ideation but, nonetheless, is sometimes used as an indicator of suicidality. The 9-item version of the EPDS (EPDS-9), which omits item 10, is sometimes used in research due to concern about positive endorsements of item 10 and necessary follow-up. We assessed the equivalence of total score correlations and screening accuracy to detect major depression using the EPDS-9 versus full EPDS among pregnant and postpartum women. We searched Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science from database inception to October 3, 2018 for studies that administered the EPDS and conducted diagnostic classification for major depression based on a validated semi-structured or fully structured interview among women aged 18 or older during pregnancy or within 12 months of giving birth. We conducted an individual participant data meta-analysis. We calculated Pearson correlations with 95% prediction interval (PI) between EPDS-9 and full EPDS total scores using a random effects model. Bivariate random-effects models were fitted to assess screening accuracy. Equivalence tests were done by comparing the confidence intervals (CIs) around the pooled sensitivity and specificity differences to the equivalence margin of δ = 0.05. Individual participant data were obtained from 41 eligible studies (10,906 participants, 1407 major depression cases). The correlation between EPDS-9 and full EPDS scores was 0.998 (95% PI 0.991, 0.999). For sensitivity, the EPDS-9 and full EPDS were equivalent for cut-offs 7–12 (difference range − 0.02, 0.01) and the equivalence was indeterminate for cut-offs 13–15 (all differences − 0.04). For specificity, the EPDS-9 and full EPDS were equivalent for all cut-offs (difference range 0.00, 0.01). The EPDS-9 performs similarly to the full EPDS and can be used when there are concerns about the implications of administering EPDS item 10. Trial registration: The original IPDMA was registered in PROSPERO (CRD42015024785). [ABSTRACT FROM AUTHOR]

Objectives: Accurate and complete study reporting allows evidence users to critically appraise studies, evaluate possible bias, and assess generalizability and applicability. We evaluated the extent to which recent studies on depression screening accuracy were reported consistent with Standards for Reporting of Diagnostic Accuracy Studies (STARD) statement requirements. Methods: MEDLINE was searched from January 1, 2018 through May 21, 2021 for depression screening accuracy studies. Results: 106 studies were included. Of 34 STARD items or sub‐items, the number of adequately reported items per study ranged from 7 to 18 (mean = 11.5, standard deviation [SD] = 2.5; median = 11.5), and the number inadequately reported ranged from 3 to 17 (mean = 10.1, SD = 2.5; median = 10.0). There were eight items adequately reported, seven partially reported, 11 inadequately reported, and four not applicable in ≥50% of studies; the remaining four items had mixed reporting. Items inadequately reported in ≥70% of studies related to the rationale for index test cut‐offs examined, missing data management, analyses of variability in accuracy results, sample size determination, participant flow, study registration, and study protocol. Conclusion: Recently published depression screening accuracy studies are not optimally reported. Journals should endorse and implement STARD adherence. [ABSTRACT FROM AUTHOR]

Background: Previous research on the depression scale of the Patient Health Questionnaire (PHQ-9) has found that different latent factor models have maximized empirical measures of goodness-of-fit. The clinical relevance of these differences is unclear. We aimed to investigate whether depression screening accuracy may be improved by employing latent factor model-based scoring rather than sum scores. Methods: We used an individual participant data meta-analysis (IPDMA) database compiled to assess the screening accuracy of the PHQ-9. We included studies that used the Structured Clinical Interview for DSM (SCID) as a reference standard and split those into calibration and validation datasets. In the calibration dataset, we estimated unidimensional, two-dimensional (separating cognitive/affective and somatic symptoms of depression), and bi-factor models, and the respective cut-offs to maximize combined sensitivity and specificity. In the validation dataset, we assessed the differences in (combined) sensitivity and specificity between the latent variable approaches and the optimal sum score (⩾10), using bootstrapping to estimate 95% confidence intervals for the differences. Results: The calibration dataset included 24 studies (4378 participants, 652 major depression cases); the validation dataset 17 studies (4252 participants, 568 cases). In the validation dataset, optimal cut-offs of the unidimensional, two-dimensional, and bi-factor models had higher sensitivity (by 0.036, 0.050, 0.049 points, respectively) but lower specificity (0.017, 0.026, 0.019, respectively) compared to the sum score cut-off of ⩾10. Conclusions: In a comprehensive dataset of diagnostic studies, scoring using complex latent variable models do not improve screening accuracy of the PHQ-9 meaningfully as compared to the simple sum score approach. [ABSTRACT FROM AUTHOR]

Objectives: Depression screening tool accuracy studies should be conducted with large enough sample sizes to generate precise accuracy estimates. We assessed the proportion of recently published depression screening tool diagnostic accuracy studies that reported sample size calculations; the proportion that provided confidence intervals (CIs); and precision, based on the width and lower bounds of 95% CIs for sensitivity and specificity. In addition, we assessed whether these results have improved since a previous review of studies published in 2013–2015. Methods: MEDLINE was searched from January 1, 2018, through May 21, 2021. Results: Twelve of 106 primary studies (11%) described a viable sample size calculation, which represented an improvement of 8% since the last review. Thirty‐six studies (34%) provided reasonably accurate CIs. Of 103 studies where 95% CIs were provided or could be calculated, seven (7%) had sensitivity CI widths of ≤10%, whereas 58 (56%) had widths of ≥21%. Eighty‐four studies (82%) had lower bounds of CIs <80% for sensitivity and 77 studies (75%) for specificity. These results were similar to those reported previously. Conclusion: Few studies reported sample size calculations, and the number of included individuals in most studies was too small to generate reasonably precise accuracy estimates. [ABSTRACT FROM AUTHOR]

Screening is done to improve health outcomes by identifying and effectively treating individuals with unrecognized conditions. Depression screening has been proposed to identify previously unrecognized depression cases. Including individuals already diagnosed or treated for depression in screening test accuracy studies could exaggerate accuracy and the yield of new cases from screening. The present study investigated (1) the proportion of depression screening tool accuracy primary studies published in 2018–2021 that excluded individuals with a confirmed depression diagnosis or who were already undergoing treatment; and (2) whether this has improved since the last review of studies published in 2013–2015, which found that five of 89 (5.6%) primary studies appropriately excluded such individuals. MEDLINE was searched from January 1, 2018 through May 21, 2021 for primary studies on depression screening tool accuracy. Eighteen of 106 (17.0%; 95% Confidence Interval [CI], 11.0% to 25.3%) primary studies excluded currently diagnosed or treated individuals. This was 11.4% (95% CI, 2.8% to 20.0%) greater than in similar studies published in 2013–2015. There has been an improvement since 2015, but the proportion of studies that exclude individuals already known to have depression remains low. This may bias research findings intended to inform clinical practice. [ABSTRACT FROM AUTHOR]

Objectives: Estimates of depression prevalence in pregnancy and postpartum are based on the Edinburgh Postnatal Depression Scale (EPDS) more than on any other method. We aimed to determine if any EPDS cutoff can accurately and consistently estimate depression prevalence in individual studies. Methods: We analyzed datasets that compared EPDS scores to Structured Clinical Interview for DSM (SCID) major depression status. Random‐effects meta‐analysis was used to compare prevalence with EPDS cutoffs versus the SCID. Results: Seven thousand three hundred and fifteen participants (1017 SCID major depression) from 29 primary studies were included. For EPDS cutoffs used to estimate prevalence in recent studies (≥9 to ≥14), pooled prevalence estimates ranged from 27.8% (95% CI: 22.0%–34.5%) for EPDS ≥ 9 to 9.0% (95% CI: 6.8%–11.9%) for EPDS ≥ 14; pooled SCID major depression prevalence was 9.0% (95% CI: 6.5%–12.3%). EPDS ≥14 provided pooled prevalence closest to SCID‐based prevalence but differed from SCID prevalence in individual studies by a mean absolute difference of 5.1% (95% prediction interval: −13.7%, 12.3%). Conclusion: EPDS ≥14 approximated SCID‐based prevalence overall, but considerable heterogeneity in individual studies is a barrier to using it for prevalence estimation. [ABSTRACT FROM AUTHOR]

Selective cutoff reporting in primary diagnostic accuracy studies with continuous or ordinal data may result in biased estimates when meta‐analyzing studies. Collecting individual participant data (IPD) and estimating accuracy across all relevant cutoffs for all studies can overcome such bias but is labour intensive. We meta‐analyzed the diagnostic accuracy of the Patient Health Questionnaire‐9 (PHQ‐9) depression screening tool. We compared results for two statistical methods proposed by Steinhauser and by Jones to account for missing cutoffs, with results from a series of bivariate random effects models (BRM) estimated separately at each cutoff. We applied the methods to a dataset that contained information only on cutoffs that were reported in the primary publications and to the full IPD dataset that contained information for all cutoffs for every study. For each method, we estimated pooled sensitivity and specificity and associated 95% confidence intervals for each cutoff and area under the curve (AUC). The full IPD dataset comprised data from 45 studies, 15 020 subjects, and 1972 cases of major depression and included information on every possible cutoff. When using data available in publications, using statistical approaches outperformed the BRM applied to the same data. AUC was similar for all approaches when using the full IPD dataset, though pooled estimates were slightly different. Overall, using statistical methods to fill in missing cutoff data recovered the receiver operating characteristic (ROC) curve from the full IPD dataset well when using only the published subset. All methods performed similarly when applied to the full IPD dataset. [ABSTRACT FROM AUTHOR]

Importance: The Patient Health Questionnaire depression module (PHQ-9) is a 9-item self-administered instrument used for detecting depression and assessing severity of depression. The Patient Health Questionnaire-2 (PHQ-2) consists of the first 2 items of the PHQ-9 (which assess the frequency of depressed mood and anhedonia) and can be used as a first step to identify patients for evaluation with the full PHQ-9.Objective: To estimate PHQ-2 accuracy alone and combined with the PHQ-9 for detecting major depression.Data Sources: MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, PsycINFO, and Web of Science (January 2000-May 2018).Study Selection: Eligible data sets compared PHQ-2 scores with major depression diagnoses from a validated diagnostic interview.Data Extraction and Synthesis: Individual participant data were synthesized with bivariate random-effects meta-analysis to estimate pooled sensitivity and specificity of the PHQ-2 alone among studies using semistructured, fully structured, or Mini International Neuropsychiatric Interview (MINI) diagnostic interviews separately and in combination with the PHQ-9 vs the PHQ-9 alone for studies that used semistructured interviews. The PHQ-2 score ranges from 0 to 6, and the PHQ-9 score ranges from 0 to 27.Results: Individual participant data were obtained from 100 of 136 eligible studies (44 318 participants; 4572 with major depression [10%]; mean [SD] age, 49 [17] years; 59% female). Among studies that used semistructured interviews, PHQ-2 sensitivity and specificity (95% CI) were 0.91 (0.88-0.94) and 0.67 (0.64-0.71) for cutoff scores of 2 or greater and 0.72 (0.67-0.77) and 0.85 (0.83-0.87) for cutoff scores of 3 or greater. Sensitivity was significantly greater for semistructured vs fully structured interviews. Specificity was not significantly different across the types of interviews. The area under the receiver operating characteristic curve was 0.88 (0.86-0.89) for semistructured interviews, 0.82 (0.81-0.84) for fully structured interviews, and 0.87 (0.85-0.88) for the MINI. There were no significant subgroup differences. For semistructured interviews, sensitivity for PHQ-2 scores of 2 or greater followed by PHQ-9 scores of 10 or greater (0.82 [0.76-0.86]) was not significantly different than PHQ-9 scores of 10 or greater alone (0.86 [0.80-0.90]); specificity for the combination was significantly but minimally higher (0.87 [0.84-0.89] vs 0.85 [0.82-0.87]). The area under the curve was 0.90 (0.89-0.91). The combination was estimated to reduce the number of participants needing to complete the full PHQ-9 by 57% (56%-58%).Conclusions and Relevance: In an individual participant data meta-analysis of studies that compared PHQ scores with major depression diagnoses, the combination of PHQ-2 (with cutoff ≥2) followed by PHQ-9 (with cutoff ≥10) had similar sensitivity but higher specificity compared with PHQ-9 cutoff scores of 10 or greater alone. Further research is needed to understand the clinical and research value of this combined approach to screening. [ABSTRACT FROM AUTHOR]

Purpose: Our study aimed to identify caregiver characteristics (gender, age, occupational status, educational attainment, relation to care recipient), care recipient characteristics (age, disease subtype), and caregiving factors (hours of care, perceived caregiving burden) associated with symptoms of depression among informal caregivers of persons with systemic sclerosis (also known scleroderma). as Materials and methods: A questionnaire was developed and administered online from December 2016 to June 2017 to informal caregivers of people with scleroderma, including the Patient Health Questionnaire-9 to assess depressive symptoms. Multiple linear regression was used to identify factors associated with depressive symptoms. Results: Caregivers (n = 202) were 60.9% male. Average age was 57.2 years (standard deviation = 14.4 years). Most caregivers were partners (72.3%), children (11.9%), or parents (7.4%), of care recipients. Self-reported caregiving burden (standardized regression coefficient β = 0.54, p < 0.001) and hours of care per week ( β = 0.17, p = 0.005) were significantly associated with greater symptoms of depression. Conclusions: Depressive symptoms were primarily associated with caregiving burden among a sample of scleroderma caregivers. There is need to develop interventions targeting caregivers in scleroderma. Rehabilitation professionals should consider the specific needs of scleroderma caregivers and should provide or refer to support services as appropriate. Most people diagnosed with scleroderma are cared for by an informal caregiver and the majority of these caregivers experience mild symptoms of depression. For caregivers that experience moderate to severe symptoms of depression, the ability to provide care to a loved one with scleroderma may be more difficult. Rehabilitation professionals should be aware of the burden faced by caregivers of persons with scleroderma and provide support services or referrals as appropriate. [ABSTRACT FROM AUTHOR]

Background: Screening for major depression with the Patient Health Questionnaire-9 (PHQ-9) can be done using a cutoff or the PHQ-9 diagnostic algorithm. Many primary studies publish results for only one approach, and previous meta-analyses of the algorithm approach included only a subset of primary studies that collected data and could have published results.Objective: To use an individual participant data meta-analysis to evaluate the accuracy of two PHQ-9 diagnostic algorithms for detecting major depression and compare accuracy between the algorithms and the standard PHQ-9 cutoff score of ≥10.Methods: Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, Web of Science (January 1, 2000, to February 7, 2015). Eligible studies that classified current major depression status using a validated diagnostic interview.Results: Data were included for 54 of 72 identified eligible studies (n participants = 16,688, n cases = 2,091). Among studies that used a semi-structured interview, pooled sensitivity and specificity (95% confidence interval) were 0.57 (0.49, 0.64) and 0.95 (0.94, 0.97) for the original algorithm and 0.61 (0.54, 0.68) and 0.95 (0.93, 0.96) for a modified algorithm. Algorithm sensitivity was 0.22-0.24 lower compared to fully structured interviews and 0.06-0.07 lower compared to the Mini International Neuropsychiatric Interview. Specificity was similar across reference standards. For PHQ-9 cutoff of ≥10 compared to semi-structured interviews, sensitivity and specificity (95% confidence interval) were 0.88 (0.82-0.92) and 0.86 (0.82-0.88).Conclusions: The cutoff score approach appears to be a better option than a PHQ-9 algorithm for detecting major depression. [ABSTRACT FROM AUTHOR]

Background: Different diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully structured interviews are completely scripted. The Mini International Neuropsychiatric Interview (MINI), a brief fully structured interview, is also sometimes used. It is not known whether interview method is associated with probability of major depression classification.AimsTo evaluate the association between interview method and odds of major depression classification, controlling for depressive symptom scores and participant characteristics.Method: Data collected for an individual participant data meta-analysis of Patient Health Questionnaire-9 (PHQ-9) diagnostic accuracy were analysed and binomial generalised linear mixed models were fit.Results: A total of 17 158 participants (2287 with major depression) from 57 primary studies were analysed. Among fully structured interviews, odds of major depression were higher for the MINI compared with the Composite International Diagnostic Interview (CIDI) (odds ratio (OR) = 2.10; 95% CI = 1.15-3.87). Compared with semi-structured interviews, fully structured interviews (MINI excluded) were non-significantly more likely to classify participants with low-level depressive symptoms (PHQ-9 scores ≤6) as having major depression (OR = 3.13; 95% CI = 0.98-10.00), similarly likely for moderate-level symptoms (PHQ-9 scores 7-15) (OR = 0.96; 95% CI = 0.56-1.66) and significantly less likely for high-level symptoms (PHQ-9 scores ≥16) (OR = 0.50; 95% CI = 0.26-0.97).Conclusions: The MINI may identify more people as depressed than the CIDI, and semi-structured and fully structured interviews may not be interchangeable methods, but these results should be replicated.Declaration of interestDrs Jetté and Patten declare that they received a grant, outside the submitted work, from the Hotchkiss Brain Institute, which was jointly funded by the Institute and Pfizer. Pfizer was the original sponsor of the development of the PHQ-9, which is now in the public domain. Dr Chan is a steering committee member or consultant of Astra Zeneca, Bayer, Lilly, MSD and Pfizer. She has received sponsorships and honorarium for giving lectures and providing consultancy and her affiliated institution has received research grants from these companies. Dr Hegerl declares that within the past 3 years, he was an advisory board member for Lundbeck, Servier and Otsuka Pharma; a consultant for Bayer Pharma; and a speaker for Medice Arzneimittel, Novartis, and Roche Pharma, all outside the submitted work. Dr Inagaki declares that he has received grants from Novartis Pharma, lecture fees from Pfizer, Mochida, Shionogi, Sumitomo Dainippon Pharma, Daiichi-Sankyo, Meiji Seika and Takeda, and royalties from Nippon Hyoron Sha, Nanzando, Seiwa Shoten, Igaku-shoin and Technomics, all outside of the submitted work. Dr Yamada reports personal fees from Meiji Seika Pharma Co., Ltd., MSD K.K., Asahi Kasei Pharma Corporation, Seishin Shobo, Seiwa Shoten Co., Ltd., Igaku-shoin Ltd., Chugai Igakusha and Sentan Igakusha, all outside the submitted work. All other authors declare no competing interests. No funder had any role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review or approval of the manuscript; and decision to submit the manuscript for publication. [ABSTRACT FROM AUTHOR]

Objective: Married persons have, on average, better mental health than nonmarried persons. Among married persons, marital satisfaction is associated with better mental health. Studies on mental health in married and nonmarried persons that consider marital satisfaction have categorized patients as satisfied versus unsatisfied, which reduces statistical power and does not generate clinically useful information on mental health across the satisfaction spectrum. Our objective was to demonstrate a novel regression approach to evaluate mental health in women with systemic sclerosis (SSc), comparing married and unmarried women, accounting for continuously measured marital satisfaction.Methods: Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D) and marital satisfaction with the Dyadic Adjustment Scale-7. A single multiple linear regression model was used to predict CES-D scores from marital status and, among married women, continuously measured marital satisfaction, controlling for demographic and clinical characteristics.Results: Of 725 women, 494 (68%) were married or living as married. On average, married women had mean CES-D scores that were 2.0 points (0.19 SDs) lower than unmarried women (P = 0.013). Among married women, a 1.0 SD increase in marital satisfaction was associated with a 2.2 point (0.21 SDs) decrease in CES-D scores (P < 0.001). Married women whose marital satisfaction scores were below the 19th percentile had greater predicted depressive symptoms than unmarried women. Married women's predicted CES-D scores ranged from 6.7 points lower to 6.9 points higher than those of unmarried women, depending on marital satisfaction.Conclusion: Comparisons of mental health in married and unmarried patients with rheumatic diseases should include continuously measured marital satisfaction. [ABSTRACT FROM AUTHOR]

Objectives: To systematically review evidence on depression screening in coronary heart disease (CHD) by assessing the (1) accuracy of screening tools; (2) effectiveness of treatment; and (3) effect of screening on depression outcomes. Background: A 2008 American Heart Association (AHA) Science Advisory recommended routine depression screening in CHD. Methods: CINAHL, Cochrane, EMBASE, ISI, MEDLINE, PsycINFO and SCOPUS databases searched through December 2, 2011; manual journal searches; reference lists; citation tracking; trial registries. Included articles (1) compared a depression screening instrument to a depression diagnosis; (2) compared depression treatment to placebo or usual care in a randomized controlled trial (RCT); or (3) assessed the effect of screening on depression outcomes in a RCT. Results: There were few examples of screening tools with good sensitivity and specificity using a priori-defined cutoffs in more than one patient sample among 15 screening accuracy studies. Depression treatment with antidepressants or psychotherapy generated modest symptom reductions among post-myocardial infarction (post-MI) and stable CHD patients (N = 6; effect size = 0.20-0.38), but antidepressants did not improve symptoms more than placebo in 2 heart failure (HF) trials. Depression treatment did not improve cardiac outcomes. No RCTs investigated the effects of screening on depression outcomes. Conclusions: There is evidence that treatment of depression results in modest improvement in depressive symptoms in post-MI and stable CHD patients, although not in HF patients. There is still no evidence that routine screening for depression improves depression or cardiac outcomes. The AHA Science Advisory on depression screening should be revised to reflect this lack of evidence. [ABSTRACT FROM AUTHOR]

Objective: Two previous individual participant data meta-analyses (IPDMAs) found that different diagnostic interviews classify different proportions of people as having major depression overall or by symptom levels. We compared the odds of major depression classification across diagnostic interviews among studies that administered the Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D).Methods: Data accrued for an IPDMA on HADS-D diagnostic accuracy were analysed. We fit binomial generalized linear mixed models to compare odds of major depression classification for the Structured Clinical Interview for DSM (SCID), Composite International Diagnostic Interview (CIDI), and Mini International Neuropsychiatric Interview (MINI), controlling for HADS-D scores and participant characteristics with and without an interaction term between interview and HADS-D scores.Results: There were 15,856 participants (1942 [12%] with major depression) from 73 studies, including 15,335 (97%) non-psychiatric medical patients, 164 (1%) partners of medical patients, and 357 (2%) healthy adults. The MINI (27 studies, 7345 participants, 1066 major depression cases) classified participants as having major depression more often than the CIDI (10 studies, 3023 participants, 269 cases) (adjusted odds ratio [aOR] = 1.70 (0.84, 3.43)) and the semi-structured SCID (36 studies, 5488 participants, 607 cases) (aOR = 1.52 (1.01, 2.30)). The odds ratio for major depression classification with the CIDI was less likely to increase as HADS-D scores increased than for the SCID (interaction aOR = 0.92 (0.88, 0.96)).Conclusion: Compared to the SCID, the MINI may diagnose more participants as having major depression, and the CIDI may be less responsive to symptom severity. [ABSTRACT FROM AUTHOR]

Objectives: A previous individual participant data meta‐analysis (IPDMA) identified differences in major depression classification rates between different diagnostic interviews, controlling for depressive symptoms on the basis of the Patient Health Questionnaire‐9. We aimed to determine whether similar results would be seen in a different population, using studies that administered the Edinburgh Postnatal Depression Scale (EPDS) in pregnancy or postpartum. Methods: Data accrued for an EPDS diagnostic accuracy IPDMA were analysed. Binomial generalised linear mixed models were fit to compare depression classification odds for the Mini International Neuropsychiatric Interview (MINI), Composite International Diagnostic Interview (CIDI), and Structured Clinical Interview for DSM (SCID), controlling for EPDS scores and participant characteristics. Results: Among fully structured interviews, the MINI (15 studies, 2,532 participants, 342 major depression cases) classified depression more often than the CIDI (3 studies, 2,948 participants, 194 major depression cases; adjusted odds ratio [aOR] = 3.72, 95% confidence interval [CI] [1.21, 11.43]). Compared with the semistructured SCID (28 studies, 7,403 participants, 1,027 major depression cases), odds with the CIDI (interaction aOR = 0.88, 95% CI [0.85, 0.92]) and MINI (interaction aOR = 0.95, 95% CI [0.92, 0.99]) increased less as EPDS scores increased. Conclusion: Different interviews may not classify major depression equivalently. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Validation of the Patient Health Questionnaire (PHQ)-9 for prenatal depression screening," by A.C. Sidebottom and colleagues in the October 2012 issue.

A letter to the editor is presented in response to the study "Prevalence of Depression and Depressive Symptoms Among Resident Physicians: A Systematic Review and Meta-Analysis" by D.A. Mata et al in volume 314 issue 22 of the periodical.

A letter to the editor is presented in response to the article "Effects of Befriending on Depressive Symptoms and Distress: Systematic Review and Meta-Analysis."

Objective: Database searches for studies of diagnostic test accuracy are notoriously difficult to filter, highly resource-intensive, and a potential barrier to quality evidence synthesis. We examined published meta-analyses of depression screening tool accuracy to evaluate the (1) proportion of included primary studies found in any online database in the original meta-analyses that were indexed in MEDLINE; (2) the proportion of patients from MEDLINE-indexed studies; and (3) the proportion of depression cases from studies indexed in MEDLINE.Methods: MEDLINE and PsycINFO were searched from January 1, 2005 through October 31, 2014 for meta-analyses in any language on the accuracy of depression screening tools.Results: We identified 16 eligible meta-analyses that included 398 primary study citations, which had been identified via an online database in the original meta-analyses, including 257 unique citations and 234 unique patient samples. The 234 unique patient samples included 69,957 total patients and 11,867 depression cases. Of these, 220 samples (94%) were from studies indexed in MEDLINE, including 97% of all patients and 96% of all depression cases. When applying a peer-reviewed search strategy in MEDLINE, 91% of all samples, 96% of patients and 95% of depression cases were retrieved. Results were similar for total and unique citations.Conclusions: Restricting searches to MEDLINE may capture almost all eligible studies, patients and depression cases. Although not examined in the present study, MEDLINE may not be indexed as quickly as other databases. Thus, MEDLINE searches should be complemented by date-limited searches of other databases for recent citations. [ABSTRACT FROM AUTHOR]

Objectives: Validated diagnostic interviews are required to classify depression status and estimate prevalence of disorder, but screening tools are often used instead. We used individual participant data meta-analysis to compare prevalence based on standard Hospital Anxiety and Depression Scale - depression subscale (HADS-D) cutoffs of ≥8 and ≥11 versus Structured Clinical Interview for DSM (SCID) major depression and determined if an alternative HADS-D cutoff could more accurately estimate prevalence.Methods: We searched Medline, Medline In-Process & Other Non-Indexed Citations via Ovid, PsycINFO, and Web of Science (inception-July 11, 2016) for studies comparing HADS-D scores to SCID major depression status. Pooled prevalence and pooled differences in prevalence for HADS-D cutoffs versus SCID major depression were estimated.Results: 6005 participants (689 SCID major depression cases) from 41 primary studies were included. Pooled prevalence was 24.5% (95% Confidence Interval (CI): 20.5%, 29.0%) for HADS-D ≥8, 10.7% (95% CI: 8.3%, 13.8%) for HADS-D ≥11, and 11.6% (95% CI: 9.2%, 14.6%) for SCID major depression. HADS-D ≥11 was closest to SCID major depression prevalence, but the 95% prediction interval for the difference that could be expected for HADS-D ≥11 versus SCID in a new study was -21.1% to 19.5%.Conclusions: HADS-D ≥8 substantially overestimates depression prevalence. Of all possible cutoff thresholds, HADS-D ≥11 was closest to the SCID, but there was substantial heterogeneity in the difference between HADS-D ≥11 and SCID-based estimates. HADS-D should not be used as a substitute for a validated diagnostic interview. [ABSTRACT FROM AUTHOR]