A trajectory-based approach to understand the factors associated with persistent depressive symptoms in primary care

Combining the GP's assessment and the PHQ-9 questionnaire leads to more reliable and clinically relevant diagnoses in primary care

Background

Screening questionnaires are not sufficient to improve diagnostic quality of depression in primary care. The additional consideration of the general practitioner’s (GP’s) assessment could improve the accuracy of depression diagnosis. The aim of this study was to examine whether the GP rating supports a reliable depression diagnosis indicated by the PHQ-9 over a period of three months.

Methods

We performed a secondary data analysis from a previous study. PHQ-9 scores of primary care patients were collected at the time of recruitment (t1) and during a follow-up 3 months later (t2). At t1 GPs independently made a subjective assessment whether they considered the patient depressive (yes/no). Two corresponding groups with concordant and discordant PHQ-9 and GP ratings at t1 were defined. Reliability of the PHQ-9 results at t1 and t2 was assessed within these groups and within the entire sample by Cohen’s Kappa, Pearson’s correlation coefficient and Bland-Altman plots.

Results

364 consecutive patients from 12 practices in the region of Upper Bavaria/Germany participated in this longitudinal study. 279 patients (76.6%) sent back the questionnaire at t2. Concordance of GP rating and PHQ-9 at t1 led to higher replicability of PHQ-9 results between t1 and t2. The reliability of PHQ-9 was higher in the concordant subgroup (κ = 0.507) compared to the discordant subgroup (κ = 0.211) (p = 0.064). The Bland-Altman Plot showed that the deviation of PHQ-9 scores at t1 and t2 decreased by about 15% in the concordant subgroup. Pearson’s correlation coefficient between PHQ-9 scores at t1 and t2 increased significantly if the GP rating was concordant with the PHQ-9 at t1 (r = 0.671) compared to the discordant subgroup (r = 0.462) (p = 0.044).

Conclusions

The combination of PHQ-9 and GP rating might improve diagnostic decision making regarding depression in general practices. PHQ-9 positive results might be more reliable and accurate, when a concordant GP rating is considered.

Determinants of patient-reported outcome trajectories and symptomatic recovery in Improving Access to Psychological Therapies (IAPT) services

BACKGROUND

Despite evidence for the general effectiveness of psychological therapies, there exists substantial heterogeneity in patient outcomes. We aimed to identify factors associated with baseline severity of depression and anxiety symptoms, rate of symptomatic change over the course of therapy, and symptomatic recovery in a primary mental health care setting.

METHODS

Using data from a service evaluation involving 35 527 patients in England's psychological and wellbeing [Improving Access to Psychological Therapies (IAPT)] services, we applied latent growth models to explore which routinely-collected sociodemographic, clinical, and therapeutic variables were associated with baseline symptom severity and rate of symptomatic change. We used a multilevel logit model to determine variables associated with symptomatic recovery.

RESULTS

Being female, younger, more functionally impaired, and more socioeconomically disadvantaged was associated with higher baseline severity of both depression and anxiety symptoms. Being older, less functionally impaired, and having more severe baseline symptomatology was associated with more rapid improvement of both depression and anxiety symptoms (male gender and greater socioeconomic disadvantage were further associated with rate of change for depression only). Therapy intensity and appointment frequency seemed to have no correlation with rate of symptomatic improvement. Patients with lower baseline symptom severity, less functional impairment, and older age had a greater likelihood of achieving symptomatic recovery (as defined by IAPT criteria).

CONCLUSIONS

We must continue to investigate how best to tailor psychotherapeutic interventions to fit patients' needs. Patients who begin therapy with more severe depression and/or anxiety symptoms and poorer functioning merit special attention, as these characteristics may negatively impact recovery.

Use of Artificial Intelligence-Based Strategies for Assessing Suicidal Behavior and Mental Illness: A Literature Review

Mental illness leading to suicide attempts is prevalent in a large portion of the population especially in low and middle-income nations. There remains a significant social stigma associated with mental illness that can lead to stigmatization of patients. Hence, patients are reluctant to communicate their problems to health care providers. Physicians have difficulty in timely identification of patients at risk for suicide. Novel and rigorously designed strategies are needed to determine the population at risk for suicide. This would be the first step in overcoming the multitude of barriers in the management of mental illness. Clinical tools and the use of electronic medical records (EMR) are time intensive. Recently, several artificial intelligence (AI)-based predictive technologies have gained momentum. The aim of this review is to summarize the recent advances in this landscape.

Depressive symptom trajectories and polygenic risk scores in individuals with an immune-mediated inflammatory disease

OBJECTIVE

To develop group-based trajectories of depressive symptoms in immune-mediated inflammatory disease (IMID) to understand their evolution and identify any associated factors, with the overall goal of identifying those at highest risk of higher depressive symptom burden.

METHOD

922 participants had an IMID or anxiety/depression. The PHQ-9 was administered at four visits, and polygenic risk scores (PRS) for major depressive disorder, depressive symptoms, and body mass index (BMI) were generated. Group-based trajectory modelling of PHQ-9 scores estimated distinct trajectories. Regression tested whether specific factors were associated with the trajectories. Mediation analyses assessed whether IMID mediated the association between BMI PRS and trajectories.

RESULTS

Three trajectories were identified. Regression demonstrated those in Group 3 ('high symptoms') had significantly higher PRS for the three traits, compared to Group 1 ('minimal symptoms') (OR: 1.34-1.66, P < 0.01). Stratified analyses in the IMID subgroup revealed an increased effect for BMI PRS in Group 3 (OR: 2.31, P < 0.001), in contrast, BMI PRS was no longer associated in the non-IMID sample. No significant indirect effect of BMI PRS on depressive symptoms trajectories was identified via IMID.

CONCLUSIONS

A significant association between polygenicity and PHQ-9 trajectories supports a role for genetic inheritance in the variability in depressive symptoms in IMID.

Mental health specialist video consultations versus treatment as usual in patients with depression or anxiety disorders in primary care: study protocol for an individually randomised superiority trial (the PROVIDE-C trial)

BACKGROUND

Most people with mental disorders, including those with severe and chronic disorders, are treated solely by their general practitioner (GP). Nevertheless, specialised mental health care may be required for specific patients. Notably, the accessibility of mental health specialist care is mainly complicated by (a) long waiting times for an appointment with specialists, (b) long travel distances to specialists, particularly in rural and remote areas, and (c) patients' reservations about mental health specialist care (including fear of being stigmatised by seeking such care). To mitigate those barriers, technology-based integrated care models have been proposed. The purpose of this study is to examine the effectiveness and cost-effectiveness of a mental health specialist video consultations model versus treatment as usual in patients with depression or anxiety disorders in primary care.

METHODS

In an individually randomised, prospective, two-arm superiority trial with parallel group design, N = 320 patients with anxiety and/or depressive disorder will be recruited in general practices in Germany. The intervention includes a newly developed treatment model based on video consultations with focus on diagnostics, treatment planning, and short-term intervention by mental health specialists. We will systematically compare the effectiveness, cost-effectiveness, and adverse effects of this new model with usual care by the GP: the primary outcome is the absolute change in the mean depressive and anxiety symptom severity measured on the Patient Health Questionnaire Anxiety and Depression Scale (PHQ-ADS) from baseline to 6 months after baseline assessment. Follow-up in both groups will be conducted by blinded outcome assessors at 6 months and 12 months after baseline. The main analysis will be based on the intention-to-treat principle. We will optimise the likelihood of treatment effectiveness by strict inclusion criteria for patients, enhanced intervention integrity, and conducting a process evaluation.

DISCUSSION

To the best of our knowledge, this is the first confirmatory study on a video-based, integrated care model for the treatment of anxiety and depressive disorders in GP patients in Germany.

TRIAL REGISTRATION

ClinicalTrials.gov, United States National Institutes of Health NCT04316572 . Prospectively registered on 20 March 2020.

Clinical efficacy of a Decision Support Tool (Link-me) to guide intensity of mental health care in primary practice: a pragmatic stratified randomised controlled trial

BACKGROUND

The volume and heterogeneity of mental health problems that primary care patients present with is a substantial challenge for health systems, and both undertreatment and overtreatment are common. We developed Link-me, a patient-completed Decision Support Tool, to predict severity of depression or anxiety, identify priorities, and recommend interventions. In this study, we aimed to examine if Link-me reduces psychological distress among individuals predicted to have minimal/mild or severe symptoms of anxiety or depression.

METHODS

In this pragmatic stratified randomised controlled trial, adults aged 18-75 years reporting depressive or anxiety symptoms or use of mental health medication were recruited from 23 general practices in Australia. Participants completed the Decision Support Tool and were classified into three prognostic groups (minimal/mild, moderate, severe), and those in the minimal/mild and severe groups were eligible for inclusion. Participants were individually and randomly assigned (1:1) by a computer-generated allocation sequence to receive either prognosis-matched care (intervention group) or usual care plus attention control (control group). Participants were not blinded but intervention providers were only notified of those allocated to the intervention group. Outcome assessment was blinded. The primary outcome was the difference in the change in scores between the intervention and control group, and within prognostic groups, on the 10-item Kessler Psychological Distress Scale at 6 months post randomisation. The trial was registered on the Australian and New Zealand Clinical Trials Registry, ACTRN12617001333303.

OUTCOMES

Between Nov 21, 2017, and Oct 31, 2018, 24 616 patients were invited to complete the eligibility screening survey. 1671 of these patients were included and randomly assigned to either the intervention group (n=834) or the control group (n=837). Prognosis-matched care was associated with greater reductions in psychological distress than usual care plus attention control at 6 months (p=0·03), with a standardised mean difference (SMD) of -0·09 (95% CI -0·17 to -0·01). This reduction was also seen in the severe prognostic group (p=0·003), with a SMD of -0·26 (-0·43 to -0·09), but not in the minimal/mild group (p=0·73), with a SMD of 0·04 (-0·17 to 0·24). In the complier average causal effect analysis in the severe prognostic group, differences were larger among those who received some or all aspects of the intervention (SMD range -0·58 to -1·15). No serious adverse effects were recorded.

INTERPRETATION

Prognosis-based matching of interventions reduces psychological distress in patients with anxiety or depressive symptoms, particularly in those with severe symptoms, and is associated with better outcomes when patients access the recommended treatment. Optimisation of the Link-me approach and implementation into routine practice could help reduce the burden of disease associated with common mental health conditions such as anxiety and depression.

FUNDING

Australian Government Department of Health.

Association between trauma exposure and mood trajectories in patients with mood disorders

BACKGROUND

Trauma exposure is associated with the development of mood disorders and their phenotypic presentation. Cross-sectional associations between trauma exposure and mood disorders are well documented. Data on the association of trauma with longitudinal mood trajectories are lacking. We investigated the association between trauma exposure and weekly mood trajectories.

METHOD

Mood disorder patients (N = 107; female = 81; mean age = 37.04 years), assessed for trauma exposure at baseline using the Childhood Trauma Questionnaire (CTQ) and Life Events Checklist (LEC), completed weekly telephonic mood assessments using the Quick Inventory of Depressive Symptomatology (QIDS) and Altman Self-Rating Mania scale (ASRM) over a 16 week period commencing at one week post-discharge from hospital. Associations between trauma exposure, severity of mood symptoms and mood trajectories were analysed using Pearson's correlations, LS Mean scores, F-statistics, and RMANOVA.

RESULTS

Trauma exposure was persistently associated, albeit with some fluctuation in the strength of the association, with depressive symptomatology. Emotional abuse showed the most persistent association over time. Sexual abuse was minimally associated with depressive symptomatology. The severity of childhood trauma exposure was positively correlated with the severity of depressive symptoms. Lifetime traumatic events were significantly associated with mania scores, however there was no association between childhood trauma exposure and mania symptoms.

CONCLUSION

Identification of both a history of childhood abuse and neglect and lifetime traumatic event exposure is important in the assessment and management of patients with mood disorders, as trauma can exert a persistent impact on depression trajectories and on symptom severity.

Machine learning discovery of longitudinal patterns of depression and suicidal ideation

Background and aim

Depression is often accompanied by thoughts of self-harm, which are a strong predictor of subsequent suicide attempt and suicide death. Few empirical data are available regarding the temporal correlation between depression symptoms and suicidal ideation. We investigated the anecdotal concern that suicidal ideation may increase during a period of depression improvement.

Data

Longitudinal Patient Health Questionnaire (PHQ)-9 is a questionnaire of 9 multiple-choice questions to assess the frequency of depressive symptoms within the previous two weeks. We analyzed a chronic depression treatment population’s electronic health record (EHR) data, containing 610 patients’ longitudinal PHQ-9 scores (62% age 45 and older; 68% female) within 40 weeks.

Methods

The irregular and sparse EHR data were transformed into continuous trajectories using Gaussian process regression. We first estimated the correlations between the symptoms (total score of the first 8 questions; PHQ-8) and suicide ideation (9th question score; Item 9) using the cross-correlation function. We then used an artificial neural network (ANN) to discover subtypes of depression patterns from the fitted depression trajectories. In addition, we conducted a separate analysis using the unfitted raw PHQ scores to examine PHQ-8’s and Item 9’s pattern changes.

Results

Results showed that the majority of patients’ PHQ-8 and Item 9 scores displayed strong temporal correlations. We found five patterns in the PHQ-8 and the Item 9 trajectories. We also found 8% - 13% of the patients have experienced an increase in suicidal ideation during the improvement of their PHQ-8. Using a trajectory-based method for subtype pattern detection in depression progression, we provided a better understanding of temporal correlations between depression symptoms over time.

Assessing decision regret in caregivers of deceased German people with cancer-A psychometric validation of the Decision Regret Scale for Caregivers

Background

Decisional regret during or after medical treatments is linked to significant distress. Regret affects not only patients but also caregivers having an active or passive role during decision making. The Decision Regret Scale (DRS) is a self‐report measure for regret in patients after treatment decisions. However, practical and psychometrically robust instruments assessing regret in caregivers are lacking.

Objective

To develop and validate a caregiver version of the DRS (Decision Regret Scale for Caregivers [DRS‐C]).

Design

Psychometric validation based on a web survey.

Setting and participants

361 caregivers of deceased German people/patients with cancer.

Main variables studied

Besides structural validity and test‐retest reliability, we evaluated measurement invariance accounting for gender, age and closeness of relationship, and tested hypotheses on convergent/discriminant validity.

Results

Forty‐five per cent of all caregivers demonstrated decision regret. Confirmatory factor analyses strongly supported the unidimensional structure of the DRS‐C and pointed to strict invariance. The DRS‐C demonstrated very good internal consistency (α = 0.83, 95% CI [0.81, 0.86]) and test‐retest reliability (ICC [A,1] = 0.73, 95% CI [0.59, 0.83]) along with sound convergent/discriminant validity. Concerning responsiveness, DRS‐C scores remained stable over a 12‐week period in 83.3% of all caregivers. Receiver operating characteristic analysis yielded a cut point of 43 for the identification of significant decision regret (AUC = 0.62, 95% CI [0.56, 0.68]).

Discussion and conclusions

The lack of a gold standard instrument prevented us from examining the criterion validity and determining a minimally important difference. Nevertheless, the DRS‐C provides valid and reliable information regarding caregiver regret following medical decisions. Above all, it captures a crucial aspect of the treatment experience in caregivers.

Exploring comorbid depression and physical health trajectories: A case-based computational modelling approach

While comorbid depression/physical health is a major clinical concern, the conventional methods of medicine make it difficult to model the complexities of this relationship. Such challenges include cataloguing multiple trends, developing multiple complex aetiological explanations, and modelling the collective large-scale dynamics of these trends. Using a case-based complexity approach, this study engaged in a richly described case study to demonstrate the utility of computational modelling for primary care research. N = 259 people were subsampled from the Diamond database, one of the largest primary care depression cohort studies worldwide. A global measure of depressive symptoms (PHQ-9) and physical health (PCS-12) were assessed at 3, 6, 9, and 12 months and then annually for a total of 7 years. Eleven trajectories and 2 large-scale collective dynamics were identified, revealing that while depression is comorbid with poor physical health, chronic illness is often low dynamic and not always linked to depression. Also, some of the cases in the unhealthy and oscillator trends remain ill without much chance of improvement. Finally, childhood abuse, partner violence, and negative life events are greater amongst unhealthy trends. Computational modelling offers a major advance for health researchers to account for the diversity of primary care patients and for developing better prognostic models for team-based interdisciplinary care.

Persistent Depressive Symptoms in a Population With High Levels of Occupational Stress: Trajectories Offer Insights Into Both Chronicity and Resilience

Religious participation and spirituality are linked to good mental health. However, clergy may experience more depression than is observed in the general population, which may be due in part to high job strain. The objectives of this study were to identify distinct longitudinal trajectories of depressive symptoms in clergy and to identify variables associated with each course. The sample was 1172 clergy who were followed for up to 66 months. Depressive symptoms were measured using the Patient Health Questionnaire (PHQ-8), which was administered approximately every 6 months. Latent class trajectory analysis was conducted for group identification, and a 3-class trajectory model fit the data best. Class 1 (38% of the sample) had minimal or no depressive symptoms over time, class 2 (47%) had chronic mild symptoms, and class 3 (15%) had persistent moderate/severe symptoms. Occupational distress was significantly associated with trajectory class. The odds of being in either the chronic mild or the persistent moderate/severe depressive symptom class were significantly higher for those who were female, for those with fair/poor self-rated health, for those with more perceived financial or occupational stress, for those with lower levels of perceived emotional support, and/or for those with lower levels of spiritual well-being. The class exhibiting resilience to depressive symptoms had higher levels of perceived support and spiritual well-being as well as lower levels of perceived financial and occupational stress. A substantial percentage of clergy, and possibly people in similar helping occupations, may experience significant levels of depressive symptoms that do not remit over time. These individuals may benefit from treatments that address work-related coping.

Classes of depression symptom trajectories in patients with major depression receiving a collaborative care intervention

PURPOSE

Collaborative care is effective in improving symptoms of patients with depression. The aims of this study were to characterize symptom trajectories in patients with major depression during one year of collaborative care and to explore associations between baseline characteristics and symptom trajectories.

METHODS

We conducted a cluster-randomized controlled trial in primary care. The collaborative care intervention comprised case management and behavioral activation. We used the Patient Health Questionnaire-9 (PHQ-9) to assess symptom severity as the primary outcome. Statistical analyses comprised latent growth mixture modeling and a hierarchical binary logistic regression model.

RESULTS

We included 74 practices and 626 patients (310 intervention and 316 control recipients) at baseline. Based on a minimum of 12 measurement points for each intervention recipient, we identified two latent trajectories, which we labeled 'fast improvers' (60.5%) and 'slow improvers' (39.5%). At all measurements after baseline, 'fast improvers' presented higher PHQ mean values than 'slow improvers'. At baseline, 'fast improvers' presented fewer physical conditions, higher health-related quality of life, and had made fewer suicide attempts in their history.

CONCLUSIONS

A notable proportion of 39.5% of patients improved only 'slowly' and probably needed more intense treatment. The third follow-up in month two could well be a sensible time to adjust treatment to support 'slow improvers'.

Measurement of Symptom Change Following Web-Based Psychotherapy: Statistical Characteristics and Analytical Methods for Measuring and Interpreting Change

BACKGROUND

Accurate measurement of treatment-related change is a key part of psychotherapy research and the investigation of treatment efficacy. For this reason, the ability to measure change with accurate and valid methods is critical for psychotherapy.

OBJECTIVE

The aims of this study were to (1) explore the underlying characteristics of depressive symptom change, measured with the nine-item Patient Health Questionnaire (PHQ-9), following psychotherapy, and (2) compare the suitability of different ways to measure and interpret symptom change. A treatment sample of Web-based psychotherapy participants (n=1098) and a waitlist sample (n=96) were used to (1) explore the statistical characteristics of depressive symptom change, and (2) compare the suitability of two common types of change functions: linear and proportional change.

METHODS

These objectives were explored using hypotheses that tested (1) the relationship between baseline symptoms and the rate of change, (2) the shape of symptom score distribution following treatment, and (3) measurement error associated with linear and proportional measurement models.

RESULTS

Findings demonstrated that (1) individuals with severe depressive baseline symptoms had greater reductions in symptom scores than individuals with mild baseline symptoms (11.4 vs 3.7); however, as a percentage measurement, change remained similar across individuals with mild, moderate, or severe baseline symptoms (50%-55%); (2) positive skewness was observed in PHQ-9 score distributions following treatment; and (3) models that measured symptom change as a proportional function resulted in greater model fit and reduced measurement error (<30%).

CONCLUSIONS

This study suggests that symptom scales, sharing an implicit feature of score bounding, are associated with a proportional function of change. Selecting statistics that overlook this proportional change (eg, Cohen d) is problematic and leads to (1) artificially increased estimates of change with higher baseline symptoms, (2) increased measurement error, and (3) confounded estimates of treatment efficacy and clinical change. Implications, limitations, and idiosyncrasies from these results are discussed.

Treatment course and its predictors in patients with somatoform disorders: A routine outcome monitoring study in secondary psychiatric care

AIM

Somatoform disorders are common and often chronic. It would be helpful to distinguish those patients who are likely to have a positive treatment course from those who are likely to follow a negative course. Such studies of different somatoform disorders are scarce, especially in secondary psychiatric care. This study examined the 6-month treatment course of psychological, physical symptoms, and functioning, and its predictors in a naturalistic sample of secondary psychiatric care outpatients with somatoform disorders.

METHOD

The present study used routine outcome monitoring data of patients with somatoform disorders regarding their 6-month treatment course of psychological and physical symptoms as well as functioning. The following patient groups were included: total group of somatoform disorders (N = 435), and undifferentiated somatoform disorder (N = 242), pain disorder (N = 102), body dysmorphic disorder (N = 51), and hypochondriasis (N = 40). Measures were Mini-International Neuropsychiatric Interview plus, Brief Symptom Inventory, Montgomery-Ǻsberg Depression Rating Scale, Brief Anxiety Scale, Short Form Health Survey 36, and Physical Symptom Checklist (PSC).

RESULTS

The study population generally showed high co-morbidity, especially with anxiety and mood disorders. The PSC total score, body dysmorphic disorder, and hypochondriasis were significant predictors for the treatment course of symptoms (Brief Symptom Inventory), whereas the PSC total score was the only significant predictor for the course of functioning (Short Form Health Survey 36).

CONCLUSION

Secondary psychiatric care outpatients with somatoform disorders showed high co-morbidity with anxiety and mood disorders, and an unfavourable 6-month course of both symptoms and functioning. Clinical implications are discussed, such as additional treatment of co-morbidity in somatoform disorders.

Development of a prognostic model for predicting depression severity in adult primary patients with depressive symptoms using the diamond longitudinal study

BACKGROUND

Depression trajectories among primary care patients are highly variable, making it difficult to identify patients that require intensive treatments or those that are likely to spontaneously remit. Currently, there are no easily implementable tools clinicians can use to stratify patients with depressive symptoms into different treatments according to their likely depression trajectory. We aimed to develop a prognostic tool to predict future depression severity among primary care patients with current depressive symptoms at three months.

METHODS

Patient-reported data from the diamond study, a prospective cohort of 593 primary care patients with depressive symptoms attending 30 Australian general practices. Participants responded affirmatively to at least one of the first two PHQ-9 items. Twenty predictors were pre-selected by expert consensus based on reliability, ease of administration, likely patient acceptability, and international applicability. Multivariable mixed effects linear regression was used to build the model.

RESULTS

The prognostic model included eight baseline predictors: sex, depressive symptoms, anxiety, history of depression, self-rated health, chronic physical illness, living alone, and perceived ability to manage on available income. Discrimination (c-statistic =0.74; 95% CI: 0.70-0.78) and calibration (agreement between predicted and observed symptom scores) were acceptable and comparable to other prognostic models in primary care.

LIMITATIONS

More complex model was not feasible because of modest sample size. Validation studies needed to confirm model performance in new primary care attendees.

CONCLUSION

A brief, easily administered algorithm predicting the severity of depressive symptoms has potential to assist clinicians to tailor treatment for adult primary care patients with current depressive symptoms.

Target-D: a stratified individually randomized controlled trial of the diamond clinical prediction tool to triage and target treatment for depressive symptoms in general practice: study protocol for a randomized controlled trial

BACKGROUND

Depression is a highly prevalent and costly disorder. Effective treatments are available but are not always delivered to the right person at the right time, with both under- and over-treatment a problem. Up to half the patients presenting to general practice report symptoms of depression, but general practitioners have no systematic way of efficiently identifying level of need and allocating treatment accordingly. Therefore, our team developed a new clinical prediction tool (CPT) to assist with this task. The CPT predicts depressive symptom severity in three months' time and based on these scores classifies individuals into three groups (minimal/mild, moderate, severe), then provides a matched treatment recommendation. This study aims to test whether using the CPT reduces depressive symptoms at three months compared with usual care.

METHODS

The Target-D study is an individually randomized controlled trial. Participants will be 1320 general practice patients with depressive symptoms who will be approached in the practice waiting room by a research assistant and invited to complete eligibility screening on an iPad. Eligible patients will provide informed consent and complete the CPT on a purpose-built website. A computer-generated allocation sequence stratified by practice and depressive symptom severity group, will randomly assign participants to intervention (treatment recommendation matched to predicted depressive symptom severity group) or comparison (usual care plus Target-D attention control) arms. Follow-up assessments will be completed online at three and 12 months. The primary outcome is depressive symptom severity at three months. Secondary outcomes include anxiety, mental health self-efficacy, quality of life, and cost-effectiveness. Intention-to-treat analyses will test for differences in outcome means between study arms overall and by depressive symptom severity group.

DISCUSSION

To our knowledge, this is the first depressive symptom stratification tool designed for primary care which takes a prognosis-based approach to provide a tailored treatment recommendation. If shown to be effective, this tool could be used to assist general practitioners to implement stepped mental-healthcare models and contribute to a more efficient and effective mental health system.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ANZCTR 12616000537459 ). Retrospectively registered on 27 April 2016. See Additional file 1 for trial registration data.

A retrospective cohort study of high-impact users among patients with cerebrovascular conditions

OBJECTIVE

To apply group-based trajectory modelling (GBTM) to the hospital administrative data to evaluate, model and visualise trends and changes in the frequency of long-term hospital care use of the subgroups of patients with cerebrovascular conditions.

DESIGN

A retrospective cohort study of patients with cerebrovascular conditions.

SETTINGS

Secondary care of all patients with cerebrovascular conditions admitted to English National Hospital Service hospitals.

PARTICIPANTS

All patients with cerebrovascular conditions identified through national administrative data (Hospital Episode Statistics) and subsequent emergency hospital admissions followed up for 4 years.

MAIN OUTCOME MEASURE

Annual number of emergency hospital readmissions.

RESULTS

GBTM model classified patients with intracranial haemorrhage (n=2605) into five subgroups, whereas ischaemic stroke (n=34 208) and transient ischaemic attack (TIA) (n=20 549) patients were shown to have two conventional groups, low and high impact. The covariates with significant association with high-impact users (17.1%) among ischaemic stroke were epilepsy (OR 2.29), previous stroke (OR 2.18), anxiety/depression (OR 1.63), procedural complication (OR 1.43), admission to intensive therapy unit (ITU) or high dependency unit (HDU) (OR 1.42), comorbidity score (OR 1.36), urinary tract infections (OR 1.32), vision loss (OR 1.32), chest infections (OR 1.25), living alone (OR 1.25), diabetes (OR 1.23), socioeconomic index (OR 1.20), older age (OR 1.03) and prolonged length of stay (OR 1.00). The covariates associated with high-impact users among TIA (20.0%) were thromboembolic event (OR 3.67), previous stroke (OR 2.51), epilepsy (OR 2.25), hypotension (OR 1.86), anxiety/depression (OR 1.63), amnesia (OR 1.62), diabetes (OR 1.58), anaemia (OR 1.55), comorbidity score (OR 1.39), atrial fibrillation (OR 1.27), living alone (OR 1.25), socioeconomic index (OR 1.13), older age (OR 1.04) and prolonged length of stay (OR 1.02). The high-impact users (0.5%) among intracranial haemorrhage were strongly associated with thromboembolic event (OR 20.3) and inversely related to older age (OR 0.58).

CONCLUSION

GBTM effectively assessed trends in the use of hospital care by the subgroups of patients with cerebrovascular conditions. High-impact users persistently had higher annual readmission during the follow-up period.

Polygenic phenotypic plasticity moderates the effects of severe childhood abuse on depressive symptom severity in adulthood: A 5-year prospective cohort study

Objective To test the phenotypic plasticity framework using a polygenic approach in a prospective depression cohort of primary care attendees with and without histories of severe childhood abuse. Methods Depressive symptoms were assessed at baseline and annually for 5 years post-baseline using the Primary Care Evaluation of Mental Disorders Patient Health Questionnaire-9 (PHQ-9) among 288 adult primary care attendees. Twelve polymorphisms in nine genes were genotyped and polygenic phenotypic plasticity allelic load (PAL) calculated. Linear mixed models assessed differences in depressive symptom severity over the 5-year follow-up period by PAL and history of severe childhood abuse. Results A higher PAL conferred greater depressive symptom severity among those with a history of severe childhood abuse but conferred significantly lower symptom severity among those without this history. Importantly, this interaction withstood adjustments for important covariates (e.g., antidepressant use, comorbid anxiety) and was stable over the 5 years of observation. Conclusions Aligned with the phenotypic plasticity framework, depressive symptom severity was dependent on the interaction between PAL and history of severe childhood abuse in a "for better and for worse" manner. Measures of polygenic phenotypic plasticity, such as ours, may serve as a trait marker of sensitivity to negative and potentially positive environmental influences.

Analysis of depression trajectory patterns using collaborative learning

BACKGROUND

Depression is a common, complex, and dynamic mental disorder. Mitigating depression has become a national health priority as it affects 1 out of 10 American adults and is the most common mental illness seen in primary care. The emerging use of electronic health record (EHR) provides an unprecedented information infrastructure to understand depression trajectories.

OBJECTIVE

We aim to effectively analyze patterns in the collected depression trajectories of a treatment population and compare several methods to predict individual trajectories for monitoring treatment outcomes.

METHODS

Our data includes longitudinal Patient Health Questionnaire (PHQ)-9 scores over 4 years for assessing depression severity from the Mental Health Research Network. We analyzed > 3,000 patients with at least six PHQ-9 observations who have ongoing treatment. We used smoothing splines to model individual depression trajectories. We then used K-means clustering and collaborative modeling (CM) to identify subgroup patterns. We further predicted the individuals' PHQ-9 scores based on depression trajectories learnt from individual growth model (IGM), mixed effect model (MEM), CM, and similarity-based CM (SCM), and compared their predictive performances.

RESULTS

We found five broad trajectory patterns in the ongoing treatment population: stable high, stable low, fluctuating moderate, an increasing and a decreasing group. For prediction, the root mean square error (rMSE) in the testing set for IGM, MEM, CM, and SCM are 12.53, 5.91, 5.18, and 3.21.

LIMITATIONS

Our EHR data provide limited information on patients' demographic, socioeconomic, and other clinical factors that may be relevant to improve model performances.

CONCLUSION

We established a trajectory-based framework for depression assessment and prognosis that is adaptable to model population heterogeneity using EHR data. Collaborative modeling outperformed other established methods.

Heterogeneity in the three-year course of major depression among older adults

OBJECTIVE

The objective of this research was to identify distinct trajectories of recovery in older depressed patients in order to identify optimal samples and points for interventions.

METHODS

The sample was 368 patients ages 60 years and older diagnosed with major depression and enrolled in a naturalistic treatment study and followed for up to 3 years.

RESULTS

A model with four trajectory classes fit the data best: a quick recovery class (43%), a persistent moderate symptom class (27%), a persistent high symptom class (15%), and a slow recovery class (15%). Compared with patients in the quick recovery class, patients in the persistent moderate symptom class had more instrumental activities of daily living/mobility limitations and lower levels of subjective social support. Patients in the persistent high symptom class had higher levels of perceived stress and lower levels of social support compared with those with a quick recovery. Patients in the slow recovery class had a younger age of onset compared with those in the quick recovery group. In multinomial logistic regression, levels of perceived stress and social support at baseline significantly differed across classes controlling for demographic and health variables.

CONCLUSIONS

Older patients diagnosed with major depression can have varying patterns of response to treatment. Interventions targeting those patients with higher levels of perceived stress and lower levels of subjective social support at the time of the index episode may lead to more favorable long-term trajectories. Copyright © 2015 John Wiley & Sons, Ltd.

Trajectory Pathways for Depressive Symptoms and Their Associated Factors in a Chinese Primary Care Cohort by Growth Mixture Modelling

Background

The naturalistic course for patients suffering from depressive disorders can be quite varied. Whilst some remit with little or no intervention, others may suffer a more prolonged course of symptoms. The aim of this study was to identify trajectory patterns for depressive symptoms in a Chinese primary care cohort and their associated factors.

Methods and Results

A 12-month cohort study was conducted. Patients recruited from 59 primary care clinics across Hong Kong were screened for depressive symptoms using the Centre for Epidemiologic Studies Depression Scale (CES-D) and monitored over 12 months using the Patient Health Questionnaire-9 items (PHQ-9) administered at 12, 26 and 52 weeks. 721 subjects were included for growth mixture modelling analysis. Using Akaike Information Criterion, Bayesian Information Criterion, Entropy and Lo-Mendell-Rubin adjusted likelihood ratio test, a seven-class trajectory path model was identified. Over 12 months, three trajectory groups showed improvement in depressive symptoms, three remained static, whilst one deteriorated. A mild severity of depressive symptoms with gradual improvement was the most prevalent trajectory identified. Multivariate, multinomial regression analysis was used to identify factors associated with each trajectory. Risk factors associated with chronicity included: female gender; not married; not in active employment; presence of multiple chronic disease co-morbidities; poor self-rated general health; and infrequent health service use.

Conclusions

Whilst many primary care patients may initially present with a similar severity of depressive symptoms, their course over 12 months can be quite heterogeneous. Although most primary care patients improve naturalistically over 12 months, many do not remit and it is important for doctors to be able to identify those who are at risk of chronicity. Regular follow-up and greater treatment attention is recommended for patients at risk of chronicity.

Identifying depressive symptom trajectory groups among Korean adults and psychosocial factors as group determinants

BACKGROUND

Longitudinal research is needed to examine the depressive symptom trajectories of different groups during adulthood and their antecedents and consequences, because depressive symptoms may be changeable and heterogeneous over time.

AIMS

This study examined the number of trajectory groups describing the depressive symptoms of Korean adults, as well as the shape of the trajectories and the association between trajectory group membership and psychosocial factors identified based on the ecosystem model.

METHOD

This study used Nagin's semi-parametric group-based modeling to analyze Year 1 to Year 7 data from Korea Welfare Panel Survey (N = 13,735), a nationally representative sample of community-dwelling adults.

RESULTS

Three distinct trajectory groups were identified: a low stable depressive symptoms group, a moderate depressive symptoms group and a high depressive symptoms group. Result from multinominal logit analysis showed that all psychosocial factors except family relationships affected the likelihood of membership in the three depressive symptoms groups. Especially, self-esteem was the psychosocial factor with the largest impact on depressive symptom trajectory group membership. When screening for depressive symptoms, individuals with a low socioeconomic status should be a primary concern and intervention should be made available to them.

CONCLUSION

Prevention or intervention with members of the identified trajectory groups would likely require integrative approaches targeting psychosocial factors across multiple contexts.

G-protein β3 subunit genetic variation moderates five-year depressive symptom trajectories of primary care attendees

BACKGROUND

Genetic variation in the G-protein β3 subunit (GNB3) has previously been associated with gene splicing that has been further linked to increased signal transduction and major depressive disorder. However, the effect of GNB3 genetic variation on depressive symptom trajectories is currently unknown. The aim of the present study is to examine whether genetic variation in GNB3 moderates depressive symptom trajectories among 301 primary care attendees enrolled in the Diagnosis, Management and Outcomes of Depression in Primary Care (diamond) prospective cohort study.

METHODS

Depressive symptoms were assessed using three measures: (1) DSM-IV criteria, (2) Primary Care Evaluation of Mental Disorders Patient Health Questionnaire-9 (PHQ-9), and (3) Center for Epidemiologic Studies Depression Scale (CESD). DSM-IV criteria were measured at baseline, 24, 36, 48, and 60 months post-baseline, whereas, PHQ-9 and CESD measurements were taken at baseline, 12, 24, 36, 48, and 60 months post-baseline. Two haplotype-tagging single nucleotide polymorphisms [rs5443 (C825T) and rs5440] spanning the GNB3 gene including ~1Kb upstream and downstream of the gene boundaries were genotyped.

RESULTS

Five-year PHQ-9 and CESD depressive symptom trajectories were moderated by rs5440. Carriers of the rs5440 GG genotype had more favourable depressive symptom trajectories compared to AG or AA genotype carriers. The rs5443 polymorphism did not moderate depressive symptom trajectories, regardless of the measure used.

LIMITATIONS

Generalizability to depressed populations outside of the primary care setting may be limited.

CONCLUSIONS

These results provide novel evidence suggesting genetic variation in the 5-prime region of GNB3 moderates depressive symptom trajectories among primary care attendees.

Prevalence and patterns of depression and anxiety in hemodialysis patients: a 12-month prospective study on incident and prevalent populations

OBJECTIVE

Depression is common in dialysis patients and has been shown to be associated with higher morbidity and mortality, but little is known about the course of symptoms over time. The current study set up to explore group and individual patterns of change in symptoms of anxiety and depression within the hemodialysis population and to identify socio-demographic, clinical, and psychological factors that may be associated with different trajectories of emotional distress.

METHODS

A total of 159 hemodialysis patients (n = 42 incident and n = 117 prevalent) completed the Hospital Anxiety and Depression Scale and social support and symptoms subscales from the Kidney Disease Quality of Life (Short Form) on two occasions 12 months apart. Clinical cut-offs were used to identify individual patterns of change in anxiety and depression symptoms across time, and analysis of variance (ANOVA) procedures were employed to establish potential correlates of these trajectories.

RESULTS

Mean levels of anxiety and depression symptoms remained unchanged over 1 year with 44.7-54.1% of patients above cut-off at both baseline and follow-up. Individual-level analyses showed that the course of symptoms does not follow a single trajectory. While most patients had either persistent symptoms of distress (39.6% and 31.8% for depression and anxiety, respectively) or no/low symptoms of distress (32.1% and 36.9% for depression and anxiety, respectively), a total of 12.7-18.5% patients either had new-onset symptoms of depression/anxiety or symptoms diminishing over time. Patients with persisting or new-onset symptoms of depression or anxiety reported reduced perceived social support and quality of social interaction compared to the subgroups with low depressive/anxious symptoms.

CONCLUSION

Different patterns of symptoms reflect heterogeneity in patients' emotional reactions and adjustment. More research is needed to identify patients at risk for emotional distress and to explore social support in the context of dialysis. Statement of contribution What is already known on this subject? Depression and poor mental health are common in hemodialysis patients and are associated with higher risk of hospitalization and death. Course of depression in incident hemodialysis patients is variable, but evidence on prevalent patients and course of symptoms of anxiety is largely lacking. What does this study add? Anxiety and depression remain undifferentiated over time with most patients reporting persistently high or no symptoms of anxiety or depression. New-onset symptoms of anxiety or depression or recovery are less frequent. The lack of consistent associations between socio-demographic or clinical parameters with patterns of emotional distress makes early identification difficult. Regular screening as part of clinical care is hence essential. Persistently high or new-onset symptoms of anxiety and/or depression are associated with reduced perceived social support. More research is needed to explore the role of social resources in the context of dialysis.

Effects of neuregulin-1 genetic variation and depression symptom severity on longitudinal patterns of psychotic symptoms in primary care attendees

A better understanding of the factors associated with psychotic symptoms could aid early identification and treatment of psychotic disorders. Previous studies have typically utilized cross-sectional study designs and have focused on individuals with psychotic disorders. Thus, examination of promising correlates of psychotic symptoms using longitudinal designs among more broadly defined populations is warranted. Two such correlates are neuregulin-1 (NRG1) genotypic variation and depression symptom severity. Both NRG1 and depression symptom severity have cross-sectional evidence for an association with psychosis but their affect on longitudinal patterns of psychotic symptoms and their potential interaction effects are less clear. Using repeated measures analysis of variance and covariance we modeled the main and interaction effects of NRG1 genotypic variation and depressive symptom severity on longitudinal psychotic symptom patterns in 301 primary care attendees assessed annually over 4 years. One-fifth (19.9%) of the participants reported one or more psychotic symptoms over the 4-year assessment period. We observed a curvilinear (i.e., cubic) association between depression symptom severity at baseline and longitudinal patterns of psychotic symptoms but did not observe a main effect for NRG1 genotypic variation on psychotic symptom patterns. However, NRG1 rs6994992 genotype moderated the curvilinear association between depression symptom severity and psychotic symptom patterns. Specifically, depression symptom severity had less of an effect on longitudinal psychotic symptoms among carriers of the rs6994992 TT genotype compared to CC and CT carriers. Our findings suggest a curvilinear association between depression symptom severity and longitudinal patterns of psychotic symptoms that is moderated by NRG1 genotype.

Methylenetetrahydrofolate reductase (MTHFR) genetic variation and major depressive disorder prognosis: A five-year prospective cohort study of primary care attendees

Methylenetetrahydrofolate reductase (MTHFR) genetic variation has been associated with the diagnosis of major depressive disorder (MDD) but no study to date has examined the effect MTHFR variation has on MDD prognosis. We sought to examine the prospective effects of two common MTHFR variants (C677T and A1298C) as well as seven haplotype-tagging single nucleotide polymorphisms (htSNPs) on MDD prognosis over a 5-year (60-month) period. Participants were 147 depressed primary care attendees enrolled in the Diagnosis, Management and Outcomes of Depression in Primary Care (diamond) prospective cohort study. Prognosis of MDD was measured using three methods: (1) DSM-IV criteria, (2) Primary Care Evaluation of Mental Disorders Patient Health Questionnaire-9 (PHQ-9), and (3) Center for Epidemiologic Studies Depression Scale (CESD). DSM-IV criteria for MDD was assessed using the Composite International Diagnostic Interview at baseline and 24, 36, 48, and 60 months post-baseline; whereas, PHQ-9 and CESD measures were employed at baseline and 12, 24, 36, 48, and 60 months post-baseline. Repeated measures analysis of variance showed that PHQ-9 symptom severity trajectories differed by C677T genotype (F = 3.34, df = 2,144, P = 0.038), with 677CC genotype showing the most severe symptom severity course over the 60 months of observation. Neither the A1298C polymorphism nor any of the htSNPs were associated with MDD prognosis regardless of measure used. Our results suggest that the MTHFR C677T polymorphism may serve as a marker for MDD prognosis pending independent replication.