scholarly journals Case definitions for common mental health disorders among adolescents using electronic primary care data: a comparison with self-reported data from ALSPAC

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Rosie Cornish ◽  
Ann John ◽  
Andy Boyd ◽  
Kate Tilling ◽  
John Macleod
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Help Seeking ◽  
Common Mental Disorders ◽  
Case Definitions ◽  
Clinical Databases ◽  
Primary Care Data ◽  
Parents And Children ◽  
Reported Data ◽  
Clinical Records

ABSTRACT ObjectivesRates of common mental disorders may be increasing among children and adolescents, though evidence of this is mixed. Symptom questionnaires in population surveys may overestimate clinical disease. Conversely, lower participation of individuals with mental disorders may lead to underestimates in surveys. Clinical databases may have greater population coverage and contain information of more obvious clinical validity; however, several factors, including the help-seeking behaviour of individuals and the recording practices of clinicians, may influence burden-of-disease estimates based on these databases. The aim of the current investigation was to compare case definitions of common mental disorders (CMD) using linked electronic primary care data to definitions derived from self-reported data obtained in an observational study. ApproachWe studied 1,562 adolescents who had completed the Revised Clinical Interview Schedule (CIS-R) in the Avon Longitudinal Study of Parents and Children (ALSPAC) at age 17-18 years and had linkage established to their electronic primary care records for at least 6 months after the time they completed the CIS-R. We used lists of Read codes corresponding to diagnoses, symptoms and treatment to create twelve definitions of CMD and also of depression alone. We calculated sensitivities and specificities of these, using CIS-R case definitions as the reference standard. All analyses were carried in Stata 13.0. ResultsSensitivities ranged from 5.2% to 24.3% for depression and from 3.8% to 19.2% for CMD. The specificities of all definitions were above 98% for depression and above 96% for CMD. For both depression and CMD, the definition that included current diagnosis, treatment or symptoms identified the highest proportion of cases. ConclusionsMost individuals meeting case definitions for CMD based on information in clinical records also met CMD case definitions based on symptoms reported in a contemporaneous survey. Conversely, many individuals identified as CMD cases based on reported symptoms had no evidence of CMD in their clinical records. A small number of individuals with CMD recorded in their clinical records had not reported symptoms of this in the survey. Overall, these data suggest that clinical databases are likely to yield underestimates of the burden of CMD in the population. Clinical records appear to yield highly valid diagnoses of common mental disorders which may be useful for studying risk factors and outcomes of these conditions. The greatest epidemiological value is likely to be obtained when the combination of information from both survey and clinical records is possible.

scholarly journals Assessing and predicting adolescent and early adulthood common mental disorders using electronic primary care data: analysis of a prospective cohort study (ALSPAC) in Southwest England

BMJ Open ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. e053624
Author(s):  
Daniel Smith ◽  
Kathryn Willan ◽  
Stephanie L Prady ◽  
Josie Dickerson ◽  
Gillian Santorelli ◽  
...  
Keyword(s):  
Primary Care ◽  
Cohort Study ◽  
Mental Disorders ◽  
Outcome Measures ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Common Mental Disorders ◽  
Free Text ◽  
Primary Care Data ◽  
Time Point

ObjectivesWe aimed to examine agreement between common mental disorders (CMDs) from primary care records and repeated CMD questionnaire data from ALSPAC (the Avon Longitudinal Study of Parents and Children) over adolescence and young adulthood, explore factors affecting CMD identification in primary care records, and construct models predicting ALSPAC-derived CMDs using only primary care data.Design and settingProspective cohort study (ALSPAC) in Southwest England with linkage to electronic primary care records.ParticipantsPrimary care records were extracted for 11 807 participants (80% of 14 731 eligible). Between 31% (3633; age 15/16) and 11% (1298; age 21/22) of participants had both primary care and ALSPAC CMD data.Outcome measuresALSPAC outcome measures were diagnoses of suspected depression and/or CMDs. Primary care outcome measure were Read codes for diagnosis, symptoms and treatment of depression/CMDs. For each time point, sensitivities and specificities for primary care CMD diagnoses were calculated for predicting ALSPAC-derived measures of CMDs, and the factors associated with identification of primary care-based CMDs in those with suspected ALSPAC-derived CMDs explored. Lasso (least absolute selection and shrinkage operator) models were used at each time point to predict ALSPAC-derived CMDs using only primary care data, with internal validation by randomly splitting data into 60% training and 40% validation samples.ResultsSensitivities for primary care diagnoses were low for CMDs (range: 3.5%–19.1%) and depression (range: 1.6%–34.0%), while specificities were high (nearly all >95%). The strongest predictors of identification in the primary care data for those with ALSPAC-derived CMDs were symptom severity indices. The lasso models had relatively low prediction rates, especially in the validation sample (deviance ratio range: −1.3 to 12.6%), but improved with age.ConclusionsPrimary care data underestimate CMDs compared to population-based studies. Improving general practitioner identification, and using free-text or secondary care data, is needed to improve the accuracy of models using clinical data.

scholarly journals Help-seeking and receipt of treatment among UK service personnel

2010 ◽  
Vol 197 (2) ◽  
pp. 149-155 ◽  
Author(s):  
Amy C. Iversen ◽  
Lauren van Staden ◽  
Jamie Hacker Hughes ◽  
Tess Browne ◽  
Neil Greenberg ◽  
...  
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Help Seeking ◽  
Service Use ◽  
Common Mental Disorders ◽  
Armed Forces ◽  
Service Utilisation ◽  
Professional Help ◽  
Military Health ◽  
The Uk

BackgroundFor armed forces personnel, data on help-seeking behaviour and receipt of treatment for mental disorders are important for both research and policy.AimsTo examine mental healthcare service use and receipt of treatment in a sample of the UK military.MethodParticipants were drawn from an existing UK military health cohort. The sample was stratified by reserve status and by participation in the main war-fighting period of the Iraq War. Participants completed a telephone-based structured diagnostic interview comprising the Patient Health Questionnaire and Primary Care Post-Traumatic Stress Disorder Screen (PC–PTSD), and a series of questions about service utilisation and treatment receipt.ResultsOnly 23% of those with common mental disorders and still serving in the military were receiving any form of medical professional help. Non-medical sources of help such as chaplains were more widely used. Among regular personnel in receipt of professional help, most were seen in primary care (79%) and the most common treatment was medication or counselling/psychotherapy. Few regular personnel were receiving cognitive–behavioural therapy (CBT). These findings are comparable with those reported for the general population.ConclusionsIn the UK armed forces, the majority of those with mental disorders are not currently seeking medical help for their symptoms. Further work to understand barriers to care is important and timely given that this is a group at risk of occupational psychiatric injury.

scholarly journals Defining adolescent common mental disorders using electronic primary care data: a comparison with outcomes measured using the CIS-R

BMJ Open ◽  
2016 ◽  
Vol 6 (12) ◽  
pp. e013167 ◽  
Author(s):  
Rosie P Cornish ◽  
Ann John ◽  
Andy Boyd ◽  
Kate Tilling ◽  
John Macleod
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Common Mental Disorders ◽  
Primary Care Data

scholarly journals Assessing and predicting adolescent and early adulthood common mental disorders in the ALSPAC cohort using electronic primary care data

2021 ◽  
Author(s):  
Daniel Smith ◽  
Kathryn Willan ◽  
Stephanie L Prady ◽  
Josie Dickerson ◽  
Gillian Santorelli ◽  
...  
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Outcome Measures ◽  
Predictive Accuracy ◽  
Common Mental Disorders ◽  
Early Adulthood ◽  
Predictive Modelling ◽  
Free Text ◽  
Reference Standard ◽  
Primary Care Data

Objectives: This paper has three objectives: 1) examine agreement between common mental disorders (CMDs) derived from primary health care records and repeated CMD questionnaire data from ALSPAC (the Avon Longitudinal Study of Parents and Children); 2) explore the factors affecting CMD identification in primary care records; and 3) taking ALSPAC as the reference standard, to construct models predicting ALSPAC-derived CMDs using primary care data. Design and Setting: Prospective cohort study (ALSPAC) with linkage to electronic primary care data. Participants: Primary care records were extracted for 11,807 ALSPAC participants (80% of the 14,731 eligible participants). The number of participants with both linked primary care and ALSPAC CMD data varied between 3,633 (age 15/16) to 1,298 (age 21/22). Outcome measures: Outcome measures from ALSPAC data were diagnoses of suspected depression and/or CMDs. For the primary care data, Read codes for diagnosis, symptoms and treatment were used to indicate the presence of depression and CMDs. For each time point, sensitivities and specificities (using ALSPAC-derived CMDs as the reference standard) were calculated and the factors associated with identification of primary care-based CMDs in those with suspected ALSPAC-derived CMDs explored. Lasso models were then performed to predict ALSPAC CMDs from primary care data. Results: Sensitivities were low for CMDs (range: 3.5 to 19.1%) and depression (range: 1.6 to 34.0%), while specificities were high (nearly all >95%). The strongest predictor of identification in the primary care data was symptom severity. The lasso models had relatively low prediction rates, especially for out-of-sample prediction (deviance ratio range: -1.3 to 12.6%), but improved with age. Conclusions: Even with predictive modelling using all available information, primary care data underestimate CMD rates compared to estimates from population-based studies. Research into the use of free-text data or secondary care information is needed to improve the predictive accuracy of models using clinical data.

scholarly journals Detecting common mental disorders in primary care in India: a comparison of five screening questionnaires

2007 ◽  
Vol 38 (2) ◽  
pp. 221-228 ◽  
Author(s):  
V. Patel ◽  
R. Araya ◽  
N. Chowdhary ◽  
M. King ◽  
B. Kirkwood ◽  
...  
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Common Mental Disorders ◽  
General Health Questionnaire ◽  
Diagnostic Interview ◽  
Systematic Sampling ◽  
Health Questionnaire ◽  
Primary Care Settings ◽  
Self Reporting Questionnaire ◽  
Distress Scale

BackgroundScreening of patients for common mental disorders (CMDs) is needed in primary-care management programmes. This study aimed to compare the screening properties of five widely used questionnaires.MethodAdult attenders in five primary-care settings in India were recruited through systematic sampling. Four questionnaires were administered, in pairs, in random order to participants: the General Health Questionnaire (GHQ, 12 items); the Primary Health Questionnaire (PHQ, nine items); the Kessler Psychological Distress Scale (K10, 10 items), and from which we could extract the score of the shorter 6-item K6; and the Self-Reporting Questionnaire (SRQ, 20 items). All participants were interviewed with a structured lay diagnostic interview, the Revised Clinical Interview Schedule (CIS-R).ResultsComplete data were available for 598 participants (participation rate 99.3%). All five questionnaires showed moderate to high discriminating ability; the GHQ and SRQ showed the best results. All five showed moderate to high degrees of correlation with one another, the poorest being between the two shortest questionnaires, K6 and PHQ. All five had relatively good internal consistency. However, the positive predictive value (PPV) of the questionnaires compared with the diagnostic interview ranged from 51% to 77% at the optimal cut-off scores.ConclusionsThere is little difference in the ability of these questionnaires to identify cases accurately, but none showed high PPVs without a considerable compromise on sensitivity. Hence, the choice of an optimum cut-off score that yields the best balance between sensitivity and PPV may need to be tailored to individual settings, with a higher cut-off being recommended in resource-limited primary-care settings.

scholarly journals Latvian Family Physicians’ Experience and Attitude in Diagnosing and Managing Depression

2019 ◽  
Vol 73 (2) ◽  
pp. 164-170
Author(s):  
Vineta Viktorija Vinogradova ◽  
Jeļena Vrubļevska ◽  
Elmārs Rancāns
Keyword(s):  
Primary Care ◽  
Mental Disorders ◽  
Common Mental Disorders ◽  
Current Knowledge ◽  
Family Physicians ◽  
Research Programme ◽  
Primary Care Settings ◽  
National Research Programme ◽  
Management Approaches ◽  
Training Programmes

Abstract Depression is among the most common mental disorders in primary care. Despite high prevalence rates it remains to be under-diagnosed in primary care settings over the world. This study was aimed to identify Latvian family physicians’ (FPs) experience and attitude in diagnosing and managing depression. It was carried out within the framework of the National Research Programme BIOMEDICINE 2014–2017. After educational seminars on diagnosing and managing depression, FPs were asked to complete a structured questionnaire. In total 216 respondents were recruited. Most of the doctors, or 72.2% (n = 156), agreed with the statement that patients with depression use primary care facilities more often than other patients. More than a half of physicians, or 66.3% (n = 143) quite often asked their patients about their psycho-emotional status and 65.7% (n = 142) of clinicians thought that they can successfully assess a patient’s psychoemotional status and possible mental disorders. The majority, or 91.6 % (n = 198), supposed that routine screening for depression is necessary in Latvia. Despite the fact that a significant number, or 62.6% (n = 135) of FPs thought that their practice was well suitable for the treatment of depressive patients, half of the respondents, or 50.9% (n = 110), assessed their ability to build a trustful contact and to motivate patients for treatment as moderate. Although FPs acknowledged the importance and necessity to treat depression, current knowledge and management approaches were far from optimal. This justifies the need to provide specific training programmes for FPs.

scholarly journals Longitudinal assessment of an anti-stigma campaign related to common mental disorders in rural India

2018 ◽  
Vol 214 (2) ◽  
pp. 90-95 ◽  
Author(s):  
Pallab K. Maulik ◽  
Siddhardha Devarapalli ◽  
Sudha Kallakuri ◽  
Anadya Prakash Tripathi ◽  
Mirja Koschorke ◽  
...  
Keyword(s):  
Mental Health ◽  
Primary Care ◽  
Mental Health Professionals ◽  
Help Seeking ◽  
Common Mental Disorders ◽  
Mental Illnesses ◽  
Rural India ◽  
Time Points ◽  
Positive Effects ◽  
Services Delivery

BackgroundStigma related to mental health and lack of trained mental health professionals is a major cause for an increased treatment gap, particularly in rural India. The Systematic Medical Appraisal, Referral and Treatment (SMART) Mental Health project delivered a complex intervention involving task sharing, an anti-stigma campaign and use of technology-based, decision-support tools to empower primary care workers to identify and manage depression, anxiety, stress and suicide risk.AimsThe aim of this article is to report changes in stigma perceptions over three time points in the rural communities where the anti-stigma campaign was conducted.MethodA multimedia-based anti-stigma campaign was conducted over a 3-month period in the West Godavari district of Andhra Pradesh, India. Following that, the primary care-based mental health service was delivered for 1 year. The anti-stigma campaign was evaluated in two villages and data were captured at three time points over a 24-month period (N = 1417): before and after delivery of the campaign and after completion of the health services delivery intervention. Standardised tools captured data on knowledge, attitude and behaviour towards mental health as well as perceptions related to help seeking for mental illnesses.ResultsMost knowledge, attitude and behaviour scores improved over the three time points. Overall mean scores on stigma perceptions related to help seeking improved by −0.375 (minimum/maximum of −2.7/2.4, s.d. 0.519, P < 0.001) during this time. Loss to follow-up was 10%.ConclusionsThe data highlight the positive effects of an anti-stigma campaign over a 2-year period.Declaration of interestNone.

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