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Development and Validation of Prediction Models for Perceived and Unmet Mental Health Needs in the Canadian General Population: Model-Based Synthetic Estimation Study
Abstract
Background
Research has shown that perceptions of a mental health need are closely associated with service demands and are an important dimension in needs assessment. Perceived and unmet mental health needs are important factors in the decision-making process regarding mental health services planning and resources allocation. However, few prediction tools are available to be used by policy and decision makers to forecast perceived and unmet mental health needs at the population level.
Objective
We aim to develop prediction models to forecast perceived and unmet mental health needs at the provincial and health regional levels in Canada.
Methods
Data from 2018, 2019, and 2020 Canadian Community Health Survey and Canadian Urban Environment were used (n=65,000 each year). Perceived and unmet mental health needs were measured by the Perceived Needs for Care Questionnaire. Using the 2018 dataset, we developed the prediction models through the application of regression synthetic estimation for the Atlantic, Central, and Western regions. The models were validated in the 2019 and 2020 datasets at the provincial level and in 10 randomly selected health regions by comparing the observed and predicted proportions of the outcomes.
Results
In 2018, a total of 17.82% of the participants reported perceived mental health need and 3.81% reported unmet mental health need. The proportions were similar in 2019 (18.04% and 3.91%) and in 2020 (18.1% and 3.92%). Sex, age, self-reported mental health, physician diagnosed mood and anxiety disorders, self-reported life stress and life satisfaction were the predictors in the 3 regional models. The individual based models had good discriminative power with C statistics over 0.83 and good calibration. Applying the synthetic models in 2019 and 2020 data, the models had the best performance in Ontario, Quebec, and British Columbia; the absolute differences between observed and predicted proportions were less than 1%. The absolute differences between the predicted and observed proportion of perceived mental health needs in Newfoundland and Labrador (−4.16% in 2020) and Prince Edward Island (4.58% in 2019) were larger than those in other provinces. When applying the models in the 10 selected health regions, the models calibrated well in the health regions in Ontario and in Quebec; the absolute differences in perceived mental health needs ranged from 0.23% to 2.34%.
Conclusions
Predicting perceived and unmet mental health at the population level is feasible. There are common factors that contribute to perceived and unmet mental health needs across regions, at different magnitudes, due to different population characteristics. Therefore, predicting perceived and unmet mental health needs should be region specific. The performance of the models at the provincial and health regional levels may be affected by population size.
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Background:
Suicide is one of the leading causes of death in the USA and population risk prediction models can inform decisions on the type, location, and timing of public health interventions. We aimed to develop a prediction model to estimate county-level suicide risk in the USA using population characteristics.
Methods:
We obtained data on all deaths by suicide reported to the National Vital Statistics System between Jan 1, 2005, and Dec 31, 2019, and age, sex, race, and county of residence of the decedents were extracted to calculate baseline risk. We also obtained county-level annual measures of socioeconomic predictors of suicide risk (unemployment, weekly wage, poverty prevalence, median household income, and population density) and state-level prevalence of major depressive disorder and firearm ownership from US public sources. We applied conditional autoregressive models, which account for spatiotemporal autocorrelation in response and predictors, to estimate county-level suicide risk.
Findings:
Estimates derived from conditional autoregressive models were more accurate than from models not adjusted for spatiotemporal autocorrelation. Inclusion of suicide risk and protective covariates further reduced errors. Suicide risk was estimated to increase with each SD increase in firearm ownership (2·8% [95% credible interval (CrI) 1·8 to 3·9]), prevalence of major depressive episode (1·0% [0·4 to 1·5]), and unemployment rate (2·8% [1·9 to 3·8]). Conversely, risk was estimated to decrease by 4·3% (-5·1 to -3·2) for each SD increase in median household income and by 4·3% (-5·8 to -2·5) for each SD increase in population density. An increase in the heterogeneity in county-specific suicide risk was also observed during the study period.
Interpretation:
Area-level characteristics and the conditional autoregressive models can estimate population-level suicide risk. Availability of near real-time situational data are necessary for the translation of these models into a surveillance setting. Monitoring changes in population-level risk of suicide could help public health agencies select and deploy targeted interventions quickly.
Funding:
US National Institute of Mental Health.
Decades of research have revealed numerous risk factors for mental disorders beyond genetics, but their consistency and magnitude remain uncertain. We conducted a “meta-umbrella” systematic synthesis of umbrella reviews, which are systematic reviews of meta-analyses of individual studies, by searching international databases from inception to January 1, 2021. We included umbrella reviews on non-purely genetic risk or protective factors for any ICD/DSM mental disorders, applying an established classification of the credibility of the evidence: class I (convincing), class II (highly suggestive), class III (suggestive), class IV (weak). Sensitivity analyses were conducted on prospective studies to test for temporality (reverse causation), TRANSD criteria were applied to test transdiagnosticity of factors, and A Measurement Tool to Assess Systematic Reviews (AMSTAR) was employed to address the quality of meta-analyses. Fourteen eligible umbrella reviews were retrieved, summarizing 390 meta-analyses and 1,180 associations between putative risk or protective factors and mental disorders. We included 176 class I to III evidence associations, relating to 142 risk/protective factors. The most robust risk factors (class I or II, from prospective designs) were 21. For dementia, they included type 2 diabetes mellitus (risk ratio, RR from 1.54 to 2.28), depression (RR from 1.65 to 1.99) and low frequency of social contacts (RR=1.57). For opioid use disorders, the most robust risk factor was tobacco smoking (odds ratio, OR=3.07). For non-organic psychotic disorders, the most robust risk factors were clinical high risk state for psychosis (OR=9.32), cannabis use (OR=3.90), and childhood adversities (OR=2.80). For depressive disorders, they were widowhood (RR=5.59), sexual dysfunction (OR=2.71), three (OR=1.99) or four-five (OR=2.06) metabolic factors, childhood physical (OR=1.98) and sexual (OR=2.42) abuse, job strain (OR=1.77), obesity (OR=1.35), and sleep disturbances (RR=1.92). For autism spectrum disorder, the most robust risk factor was maternal overweight pre/during pregnancy (RR=1.28). For attention-deficit/hyperactivity disorder (ADHD), they were maternal pre-pregnancy obesity (OR=1.63), maternal smoking during pregnancy (OR=1.60), and maternal overweight pre/during pregnancy (OR=1.28). Only one robust protective factor was detected: high physical activity (hazard ratio, HR=0.62) for Alzheimer’s disease. In all, 32.9% of the associations were of high quality, 48.9% of medium quality, and 18.2% of low quality. Transdiagnostic class I-III risk/protective factors were mostly involved in the early neurodevelopmental period. The evidence-based atlas of key risk and protective factors identified in this study represents a benchmark for advancing clinical characterization and research, and for expanding early intervention and preventive strategies for mental disorders.
Background.
Many studies report a positive association between smoking and mental illness. However, the literature remains mixed regarding the direction of this association. We therefore conducted a systematic review evaluating the association of smoking and depression and/or anxiety in longitudinal studies.
Methods.
Studies were identified by searching PubMed, Scopus, and Web of Science and were included if they: 1) used human participants, 2) were longitudinal, 3) reported primary data, 4) had smoking as an exposure and depression and/or anxiety as an outcome, or 5) had depression and/or anxiety as the exposure and smoking as an outcome.
Results.
Outcomes from 148 studies were categorised into: smoking onset, smoking status, smoking heaviness, tobacco dependence and smoking trajectory. The results for each category varied substantially, with evidence for positive associations in both directions (smoking to later mental health and mental health to later smoking) as well as null findings. Overall, nearly half the studies reported that baseline depression/anxiety was associated with some type of later smoking behaviour, while over a third found evidence that a smoking exposure was associated with later depression/anxiety. However, there were few studies directly supporting a bidirectional model of smoking and anxiety, and very few studies reporting null results.
Conclusions.
The literature on the prospective association between smoking and depression and anxiety is inconsistent in terms of the direction of association most strongly supported. This suggests the need for future studies that employ different methodologies, such as Mendelian randomisation, that will allow us to draw stronger causal inferences.
Given its high prevalence and impact on quality of life, more research is needed in identifying factors that may prevent depression. This review examined whether physical activity (PA) is protective against the onset of depression.
A comprehensive search was conducted up until December 2012 in the following databases: MEDLINE, Embase, PubMed, PsycINFO, SPORTDiscus, and Cochrane Database of Systematic Reviews. Data were analyzed between July 2012 and February 2013. Articles were chosen for the review if the study used a prospective-based, longitudinal design and examined relationships between PA and depression over at least two time intervals. A formal quality assessment for each study also was conducted independently by the two reviewers.
The initial search yielded a total of 6363 citations. After a thorough selection process, 30 studies were included for analyses. Among these, 25 studies demonstrated that baseline PA was negatively associated with a risk of subsequent depression. The majority of these studies were of high methodologic quality, providing consistent evidence that PA may prevent future depression. There is promising evidence that any level of PA, including low levels (e.g., walking <150 minutes/weeks), can prevent future depression.
From a population health perspective, promoting PA may serve as a valuable mental health promotion strategy in reducing the risk of developing depression.
This article reviews the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) in model selection and the appraisal of psychological theory. The focus is on latent variable models, given their growing use in theory testing and construction. Theoretical statistical results in regression are discussed, and more important issues are illustrated with novel simulations involving latent variable models including factor analysis, latent profile analysis, and factor mixture models. Asymptotically, the BIC is consistent, in that it will select the true model if, among other assumptions, the true model is among the candidate models considered. The AIC is not consistent under these circumstances. When the true model is not in the candidate model set the AIC is efficient, in that it will asymptotically choose whichever model minimizes the mean squared error of prediction/estimation. The BIC is not efficient under these circumstances. Unlike the BIC, the AIC also has a minimax property, in that it can minimize the maximum possible risk in finite sample sizes. In sum, the AIC and BIC have quite different properties that require different assumptions, and applied researchers and methodologists alike will benefit from improved understanding of the asymptotic and finite-sample behavior of these criteria. The ultimate decision to use the AIC or BIC depends on many factors, including the loss function employed, the study's methodological design, the substantive research question, and the notion of a true model and its applicability to the study at hand.
This study of Australian and Dutch people with anxiety or depressive disorder aims to examine people's perceived needs and barriers to care, and to identify possible similarities and differences.
Data from the Australian National Survey of Mental Health and Well-Being and the Netherlands Study of Depression and Anxiety were combined into one data set. The Perceived Need for Care Questionnaire was taken in both studies. Logistic regression analyses were performed to check if similarities or differences between Australia and the Netherlands could be observed.
In both countries, a large proportion had unfulfilled needs and self-reliance was the most frequently named barrier to receive care. People from the Australian sample (N = 372) were more likely to perceive a need for medication (OR 1.8; 95% CI 1.3-2.5), counselling (OR 1.4; 95% CI 1.0-2.0) and practical support (OR 1.8; 95% CI 1.2-2.7), and people's overall needs in Australia were more often fully met compared with those of the Dutch sample (N = 610). Australians were more often pessimistic about the helpfulness of medication (OR 3.8; 95% CI 1.4-10.7) and skills training (OR 3.0; 95% CI 1.1-8.2) and reported more often financial barriers for not having received (enough) information (OR 2.4; 95% CI 1.1-5.5) or counselling (OR 5.9; 95% CI 2.9-11.9).
In both countries, the vast majority of mental health care needs are not fulfilled. Solutions could be found in improving professionals' skills or better collaboration. Possible explanations for the found differences in perceived need and barriers to care are discussed; these illustrate the value of examining perceived need across nations and suggest substantial commonalities of experience across the two countries.
Administrative databases in the Canadian health sector do not contain socio-economic information. To facilitate the monitoring of social inequalities for health planning, this study proposes a material and social deprivation index for Canada. After explaining the concept of deprivation, we describe the methodological aspects of the index and apply it to the example of premature mortality (i.e. death before the age of 75). We illustrate variations in deprivation and the links between deprivation and mortality nationwide and in different geographic areas including the census metropolitan areas (CMAs) of Toronto, Montréal and Vancouver; other CMAs; average-size cities, referred to as census agglomerations (CAs); small towns and rural communities; and five regions of Canada, namely Atlantic, Quebec, Ontario, the Prairies and British Columbia. Material and social deprivation and their links to mortality vary considerably by geographic area. We comment on the results as well as the limitations of the index and its advantages for health planning.
This analysis examines the prevalence of self-reported unmet needs for health care and the extent to which they were attributable to perceived problems with service availability or accessibility or acceptability.
Most data are from the 1998/99 cross-sectional household component of Statistics Canada's National Population Health Survey; 1994/95 and 1996/97 cross-sectional data are used to present trends from 1994/95 to 1998/99. The primary analysis is based on 14, 143 respondents aged 18 or older.
Multivariate logistic regression was used to estimate the association of risk factors with the three types of unmet health care need.
In 1998/99, about 7% of Canadian adults, an estimated 1.5 million, reported having had unmet health care needs in the previous year. Around half of these episodes were attributable to acceptability problems such as being too busy. In 39% of cases, service availability problems, such as long waiting times, were mentioned. Just under 13% of episodes were related to accessibility problems (cost or transportation). Unmet needs attributable to service availability problems were not significantly associated with socio-economic status. By contrast, unmet needs due to accessibility problems were inversely associated with household income.
We compared health status, access to care, and utilization of medical services in the United States and Canada and compared disparities according to race, income, and immigrant status.
We analyzed population-based data on 3505 Canadian and 5183 US adults from the Joint Canada/US Survey of Health. Controlling for gender, age, income, race, and immigrant status, we used logistic regression to analyze country as a predictor of access to care, quality of care, and satisfaction with care and as a predictor of disparities in these measures.
In multivariate analyses, US respondents (compared with Canadians) were less likely to have a regular doctor, more likely to have unmet health needs, and more likely to forgo needed medicines. Disparities on the basis of race, income, and immigrant status were present in both countries but were more extreme in the United States.
United States residents are less able to access care than are Canadians. Universal coverage appears to reduce most disparities in access to care.
Background
The increasing availability of high-potency cannabis-derived compounds and the use of synthetic cannabinoids may be responsible for severe side effects like cognitive impairment, psychosis or self-injurious behaviours (SIB). In particular, SIB like non-suicidal self-injury (NSSI) and deliberate self-harm (DSH) raise growing concern as a possible consequence of cannabis use. However, the research to date has not addressed the relationship between cannabinoid use and SIB systematically.
Methods
We conducted a systematic review on PubMed up to March 2020, using search terms related to cannabinoids and SIB.
Results
The search yielded a total of 440 abstracts. Of those, 37 studies published between 1995 and 2020 were eligible for inclusion. Cannabinoid use was significantly associated with SIB at the cross-sectional (OR=1.569, 95%CI [1.167-2.108]) and longitudinal (OR=2.569, 95%CI [2.207-3.256]) level. Chronic use, presence of mental disorders, depressive symptoms, emotional dysregulation and impulsive traits might further increase the likelihood of self-harm in cannabis users. Synthetic cannabinoids may trigger highly destructive SIB mainly through the psychotomimetic properties of these compounds.
Conclusion
Cannabinoid use was associated with an increased prevalence of self-injury and may act as a causative factor with a duration-dependent manner. Emotional regulation and behavioural impulsivity functions might crucially moderate this association. Future studies should further investigate the mechanisms underlying this association, while exploring potential therapeutic applications of substances modulating the endocannabinoid system.
Objective:
This study aimed to identify correlates of service utilization and perceived need for care among college students with suicidal ideation.
Participants:
Respondents were recruited from introductory psychology courses at an undergraduate college during the Fall 2014 semester.
Methods:
Independent correlates of (1) mental health service utilization, (2) self-perceived need, and (3) other-perceived need for mental health services among college students (N = 190) with suicidal ideation were identified.
Results:
Service utilization was associated with need for care as perceived by others. Perceived need for care by others was associated with suicidal ideation intensity and suicide attempt history. Perceived need by the respondents themselves was correlated with depression severity, sex, and race but was not independently associated with actual service utilization.
Conclusions:
Perceived need by others was the sole significant correlate of service utilization, suggesting it is an important target for public health interventions aimed at facilitating pathways into mental health treatment.
We aimed to establish the treatment effect of physical activity for depression in young people through meta-analysis. Four databases were searched to September 2016 for randomised controlled trials of physical activity interventions for adolescents and young adults, 12–25 years, experiencing a diagnosis or threshold symptoms of depression. Random-effects meta-analysis was used to estimate the standardised mean difference (SMD) between physical activity and control conditions. Subgroup analysis and meta-regression investigated potential treatment effect modifiers. Acceptability was estimated using dropout. Trials were assessed against risk of bias domains and overall quality of evidence was assessed using GRADE criteria. Seventeen trials were eligible and 16 provided data from 771 participants showing a large effect of physical activity on depression symptoms compared to controls (SMD = −0.82, 95% CI = −1.02 to −0.61, p < 0.05, I² = 38%). The effect remained robust in trials with clinical samples ( k = 5, SMD = −0.72, 95% CI = −1.15 to −0.30), and in trials using attention/activity placebo controls ( k = 7, SMD = −0.82, 95% CI = −1.05 to −0.59). Dropout was 11% across physical activity arms and equivalent in controls ( k = 12, RD = −0.01, 95% CI = −0.04 to 0.03, p = 0.70). However, the quality of RCT-level evidence contributing to the primary analysis was downgraded two levels to LOW (trial-level risk of bias, suspected publication bias), suggesting uncertainty in the size of effect and caution in its interpretation. While physical activity appears to be a promising and acceptable intervention for adolescents and young adults experiencing depression, robust clinical effectiveness trials that minimise risk of bias are required to increase confidence in the current finding. The specific intervention characteristics required to improve depression remain unclear, however best candidates given current evidence may include, but are not limited to, supervised, aerobic-based activity of moderate-to-vigorous intensity, engaged in multiple times per week over eight or more weeks. Further research is needed. (Registration: PROSPERO-CRD 42015024388).
Objectives:
Area-based measures of socio-economic status are increasingly used in population health research. Based on previous research and theory, the Canadian Marginalization Index (CAN-Marg) was created to reflect four dimensions of marginalization: residential instability, material deprivation, dependency and ethnic concentration. The objective of this paper was threefold: to describe CAN-Marg; to illustrate its stability across geographic area and time; and to describe its association with health and behavioural problems.
Methods:
CAN-Marg was created at the dissemination area (DA) and census tract level for census years 2001 and 2006, using factor analysis. Descriptions of 18 health and behavioural problems were selected using individual-level data from the Canadian Community Health Survey (CCHS) 3.1 and 2007/08. CAN-Marg quintiles created at the DA level (2006) were assigned to individual CCHS records. Multilevel logistic regression modeling was conducted to examine associations between marginalization and CCHS health and behavioural problems.
Results:
The index demonstrated marked stability across time and geographic area. Each of the four dimensions showed strong and significant associations with the selected health and behavioural problems, and these associations differed depending on which of the dimensions of marginalization was examined.
Conclusion:
CAN-Marg is a census-based, empirically derived and theoretically informed tool designed to reflect a broader conceptualization of Canadian marginalization.
To identify sociodemographic, child, parent, and day care provider factors at age 4 that predict Norwegian children's service use for mental health problems at age 7.
Two birth cohorts of 4-year-old children and their parents living in the city of Trondheim, Norway, were invited (82% consented). We successfully interviewed 995 parents among 1250 drawn to participate using the Preschool Age Psychiatric Assessment to set diagnoses and record parental burden and service use. Information concerning sociodemographics, child impairment, parental social support, and child need for mental health services according to parents, day care teacher, and health nurse were obtained.
Rate of service use among those with a behavioral or emotional disorder was 10.7% at age 4 and 25.2% at age 7. Behavioral disorders (odds ratio [OR] 2.6, confidence interval [CI] 1.3-5.3), but not emotional disorders, predicted service use. When adjusted for incapacity (OR 1.3, CI 1.2-1.6), disorders were no longer predictive. Incapacity, in turn, was not predictive once parental burden (OR 1.1, CI 1.0-1.1) and parents' (OR 2.7, CI 1.0-7.9) and day care teachers' (OR 2.1, CI 1.4-3.2) judgment of child need of help were included. Lower socioeconomic status predicted more service use over and beyond these factors (OR 3.0, CI 1.5-6.1).
Behavioral disorders may instigate service use if they result in impairment, and such impairment may operate via increased parental burden and parent and caregiver problem recognition. Service use may be increased through effective screening programs and efforts to increase day care teachers' recognition of emotional problems.
Past research and national survey data on Canadians' perceived need for mental health care (MHC) have focused on unmet needs overall, and have not considered specific types of MHC needs or the extent to which needs are met.
Using data from the 2012 Canadian Community Health Survey-Mental Health, this article describes the prevalence of perceived MHC needs for information, medication, counselling and other services. The degree to which each type of need was met is explored. Associations between risk factors for having MHC needs and the extent to which needs were met are investigated.
In 2012, an estimated 17% of the population aged 15 or older reported having had an MHC need in the past 12 months. Two-thirds (67%) reported that their need was met; for another 21%, the need was partially met; and for 12%, the need was unmet. The most commonly reported need was for counselling, which was also the least likely to be met. Distress was identified as a predictor of perceived MHC need status.
Many Canadians are estimated to have MHC needs, particularly for counselling. People with elevated levels of distress are significantly more likely to have unmet and partially met MHC needs than to have fully met MHC needs, regardless of the presence of mental or substance disorders.
Needs assessment is now a high priority, but it is conceptually muddled and technically difficult. In the past a variety of academic disciplines addressing different aspects of health care have produced a range of definitions on 'need' applicable to their own setting. In the context of the National Health Service Review, 'need' may best be defined as the ability to benefit from 'health care', which depends both on morbidity and on the effectiveness of care. An analysis of its relationship with 'demand', which is the health care that people ask for, and 'supply', which is provided, exposes the limitations of current information sources, and confirms that the formal assessment of needs will inevitably be a lengthy task. Despite these difficulties there is much that can and should be done incrementally to influence contracts between providers and purchasers towards meeting health care needs.
This study addresses an ongoing problem in mental health needs assessment. This involves estimating the prevalence of an identified problem, specifically serious mental illness (SMI), for local areas in a reliable, valid, and cost-effective manner. The aim of the study is the application and testing of a recently introduced methodology from the field of small area estimation to determining SMI rates in the 48 contiguous US states, and in local areas of Massachusetts. It uses 'regression synthetic estimation fitted using area-level covariates', to estimate a model using data from the 2001-2002 replication of the National Comorbidity Study (n = 5593) and apply it, using 2000 STF-3C Census data, to various state and local areas in the United States. The estimates are then compared with independently collected SMI indicators. The estimates show not only face validity and internal consistency, but also predictive validity. The multiple logistic model has a sensitivity of 21.1% and a specificity of 95.1%, based largely on socio-economic disparities. Pearson r validity coefficients for the area estimates range from 0.43 to 0.75. The model generates a national estimate of SMI adults of 5.5%; for the 48 states, rates ranging from 4.7% to 7.0%; and for Massachusetts towns and cities, 1.1% to 7.5%.
A single cycle of the Canadian Community Health Survey (CCHS) may not meet researchers' analytical needs. This article presents methods of combining CCHS cycles and discusses issues to consider if these data are to be combined. An empirical example illustrates the proposed methods.
Two methods can be used to combine CCHS cycles: the separate approach and the pooled approach. With the separate approach, estimates are calculated for each cycle separately and then combined. The pooled approach combines data at the micro-data level, and the resulting dataset is treated as if it is a sample from one population.
For the separate approach, it is recommended that the simple average of the estimates be used. For the pooled approach, it is recommended that weights be scaled by a constant factor where a period estimate covering the time periods of the individual cycles can be created. The choice of method depends on the aim of the analysis and the availability of data.
Combining cycles should be considered only if the most current period estimates do not suffice. Both methods will obscure cycle-to-cycle trends and will not reveal changing behaviours related to public health initiatives.
Attention is focused on one important aspect of good performance in probabilistic diagnosis, the 'reliability' (external validity) of probabilistic assertions: a diagnostic alternative claimed to be 90% certain, say, must occur neither more nor less than nine times out of ten on the average. Statistical measures are offered by which departures from such perfect reliability can be estimated, and statistical tests are developed in order to test the hypothesis of perfect reliability. The specific reliability defects looked for include overconfident diagnoses and so-called size bias (common diseases being overdiagnosed). Reliability is contrasted with discriminatory power and other performance aspects. The illustrative data derive from a study of computer-aided diagnosis of the acute abdomen.
This paper discusses the Meharry Medical College Study of Unmet Needs designed to measure the effectiveness of alternative health care delivery systems: (a) comprehensive care with broad outreach, (b) comprehensive care with limited outreach, and (c) traditional care. Unmet needs are defined as the differences between services judged necessary to deal appropriately with health problems and services actually received. The central hypothesis is that comprehensive health programs will be more effective than traditional care in reducing unmet needs. Unmet needs are viewed as measures of program outcome and are one of several types of sociomedical indicators which use factors other than biomedical or biological states as measures of outcome. The distinction is made between unmet needs indicators and health status indicators.
Various approaches to measuring unmet needs are discussed and the relatively limited focus of these is contrasted with the more comprehensive Meharry approach. Household interviews and clinical examinations provide the data base for deriving professional judgments of unmet needs in the medical, dental, nursing, and social services areas. The Meharry work suggests several areas in which further work on unmet needs would be useful.
The Behavioral Model of Health Services Use was initially developed over 25 years ago. In the interim it has been subject to considerable application, reprobation, and alteration. I review its development and assess its continued relevance.
Data from the National Comorbidity Survey are used to study the lifetime prevalences, correlates, course and impairments associated with minor depression (mD), major depression 5-6 symptoms (MD 5-6), and major depression with seven or more symptoms (MD 7-9) in an effort to determine whether mD is on a continuum with MD. There is a monotonic increase in average number of episodes, average length of longest episode, impairment, comorbidity, and parental history of psychiatric disorders as we go from mD to Md 5-6 to MD 7-9. In most of these cases, though, the differences between mD and MD 5-6 are no longer than the differences between MD 5-6 and MD 7-9, arguing for continuity between mD and MD. Coupled with the finding from earlier studies that subclinical depression is a significant risk factor for major depression, these results argue that minor depression is a variant of depressive disorder that should be considered seriously both as a target for preventive intervention and for treatment. The paper closes with suggestions regarding the analysis of mD subtypes in future longitudinal studies.
To illustrate the use of needs-based planning in the identification of physician surpluses and deficits and of resource misallocations within a provincial medical system at a time when provincial governments and medical associations across the country are faced with funding constraints for physician services.
For each of 4 regions in Manitoba, the authors analysed residents' rates of physician visits (whether within the resident's own or another region). Residents' need for physician contact was estimated by means of a statistical analysis of the data on contacts in relation to age, sex and health-related indicators, and the rates of visits needed and actually made were compared.
All Manitoba residents.
Numbers of generalist physicians (general practitioners, family physicians, general internists and general pediatricians) needed to serve each region, and the extent of physician surplus and deficit in each region.
There appeared to be a surplus of physicians in most of urban Manitoba but deficits in northern Manitoba and some parts of the rural south. General internists and general pediatricians in Winnipeg provide a significant part of the ambulatory care that is provided by general practitioners in other parts of the province. The provincial government currently spends more per resident to provide physician services in areas of physician surplus than in areas of physician deficit, although the patterns are inconsistent.
Needs-based planning is possible. If provinces are intent on controlling physician numbers and expenditures, it makes sense to manage the implications of doing so.
The Perceived Need for Care Questionnaire (PNCQ) was designed for the Australian National Survey of Mental Health and Wellbeing. The PNCQ complemented collection of data on diagnosis and disability with the survey participants' perceptions of their needs for mental health care and the meeting of those needs. The four-stage design of the PNCQ mimics a conversational exploration of the topic of perceived needs. Five categories of perceived need are each assigned to one of four levels of perceived need (no need, unmet need, partially met need and met need). For unmet need and partially met need, information on barriers to care is collected.
Inter-rater reliabilities of perceived needs assessed by the PNCQ were examined in a study of 145 anxiety clinic attenders. Construct validity of these items was tested, using a multi-trait multi-method approach and hypotheses regarding extreme groups, in a study with a sample of 51 general practice and community psychiatric service patients.
The instrument is brief to administer and has proved feasible for use in various settings. Inter-rater reliabilities for major categories, measured by the kappa statistic, exceeded 0.60 in most cases; for the summary category of all perceived needs, inter-rater reliability was 0.62. The multi-trait multi-method approach lent support to the construct validity of the instrument, as did findings in extreme groups.
The PNCQ shows acceptable feasibility, reliability and validity, adding to the range of assessment tools available for epidemiological and health services research.
The objective of this study was to investigate the effect of persistent alcohol consumption on the risks of major and minor depression. A retrospective cohort study design was used. The data was derived from a large scale longitudinal national health study (Canadian National Population Health Survey). Depression status was evaluated by using the Composite International Diagnostic Interview-Short Form (CIDI-SF) for major depression. Subjects who did not have major depression at baseline were classified into groups according to the persistence of alcohol consumption during the follow-up period. The incidence of major depression in each group was calculated in men and in women separately and were stratified by age. The same procedures were repeated for minor depression. Women who reported having 5+ drinks on one occasion at least once a month were at an elevated risk of major depression. The same pattern was not observed among men in this analysis. However, no difference was found between the groups in terms of the incidence of minor depression. Frequent heavy alcohol use may be a causal factor for major depression among women. Reducing the frequency and quantities of alcohol consumption may offer an opportunity for prevention of major depression among women.
Few studies have investigated the factors associated with different outcomes in individuals with major depressive episode (MDE) in relation to mental health service utilization.
This study was to, in depressed individuals who used and did not use mental health services, 1) compare the demographic, psychosocial, and clinical characteristics; 2) estimate the risk of MDE in a 6-year follow-up period; and 3) identify the factors associated with the persistence/recurrence of MDE.
This was a population- based longitudinal analysis.
Participants included the longitudinal cohort of the Canadian National Population Health Survey who reported MDE at the baseline survey (n = 609).
MDE was measured by the Composite International Diagnostic Interview-Short Form for Major Depression.
In the 6-year follow-up period, 49.8% of participants with treated depression developed subsequent MDE; 28.7% of those with untreated depression reported MDE. Multivariate analyses showed that, among those who reported the use of mental health services, childhood and adulthood traumatic events and functional impairment were related to the recurrence of MDE. Among those who did not use mental health services, reported negative life events and the severity of depressive symptoms were predictive of recurrent MDE.
The risk of the recurrence of MDE and associated factors differ in mental health service users and nonusers. Future studies need to confirm these results and to identify service barriers for those who do not use the services and who are at a high risk of MDE.
Eliminating barriers to care is important for improving health service use. However, the barriers to mental health care have not been well investigated.
This study was designed to provide information about the barriers to mental health service use and to identify clinical factors associated with perceived barriers among individuals with depressive-, anxiety-, and substance use-related disorders in the communities.
A cross-sectional analysis using data from the Canadian Community Health Survey-Mental Health and Well-being was instituted.
Participants with depressive-, anxiety-, and substance use-related disorders in the past 12 months, assessed by the World Mental Health-Composite International Diagnostic Interview, were included (n = 4094).
In participants with mental disorders, 19.5% reported barriers to mental health service use. The percentage of perceived barriers due to acceptability was higher than those for barriers due to accessibility and availability. Participants with comorbid mental disorders were more likely to have experienced barriers than those with one disorder in both mental health service users and in the nonusers. Role impairment was a significant factor predicting barriers to care, overall and in the service nonusers, in the groups having anxiety disorders only, having any depressive or anxiety disorders, and having any alcohol or drug dependence.
Clinical characteristics play an important role in perceiving barriers to mental health care. Future efforts should pay particular attention to the needs of those with chronic and severe mental health problems and focus on improving the effectiveness of mental health services.
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