Skip to main content
Download PDF

Interventions to improve the detection of depression in primary healthcare: systematic review

Systematic Reviews volume 12, Article number: 25 (2023) Cite this article

Abstract

Background

Several studies have been conducted on the effect of interventions on the detection of depression in primary healthcare (PHC). Systematic reviews have also been done on the effectiveness of separate interventions. However, systematic reviews are not done on the comparative effectiveness of several interventions. This study, therefore, aimed at synthesizing the global evidence on the effectiveness of interventions to improve the detection of depression in PHC.

Methods

We searched PubMed, Embase, PsycINFO, Web of Science, Cochrane Database of Systematic Reviews, Global Index Medicus, African Index Medicus, and African Journals Online, from the inception of the databases to until the 4th week of April 2020. We also searched references of the included articles. We included randomized trials, cluster randomized trials, or quasi-experimental studies, which evaluated the effectiveness of an intervention to improve detection of depression in the PHC setting. Two of the review authors independently extracted data from the included studies. The methodological quality of the included studies was assessed using the Assessment Tool for Quantitative Studies developed by the Effective Public Health Practice Project. The protocol for the review was registered on PROSPERO (CRD42020166291).

Results

Of 23,305 records identified, we included 58 articles in the review. Diverse types of interventions were evaluated to improve clinician diagnosis of depression in the PHC setting. Interventions related to implementation of guidelines, screening with feedback, educational interventions which incorporated active learning and clinical practice, and disclosure of screening results were found to be mostly effective. Interventions which combined education, screening, and feedback were particularly more effective. Most of the included studies were weak or moderate in their methodological quality.

Conclusions

Our review indicates that implementation of a single type of intervention does not improve the detection of depression in PHC. Combining aspects of each type of intervention which are more effective may be useful. Education and training interventions which include more simulation and role playing are found to be effective over time. Most of the studies conducted in the area are from high-income countries and are weak in their methodological quality. There is need to conduct more number of studies in low-income settings.

Peer Review reports

Background

Depression is projected to be the second leading contributor to the global burden of diseases worldwide by 2030 [1]. This is due to the high prevalence of depression, ranging from 10 to 25% in women and 5 to 12% in men and its impact on daily functioning and mortality [2, 3]. There is also a predominant increasing trend in depression prevalence overtime [4]. Depression is a leading cause of disability, workplace absenteeism, diminished or lost productivity, and increased use of healthcare resource [5]. In addition, depression is associated with increased mortality across all age groups, decreased quality of life, and increased healthcare cost [3]. Depressive disorders accounted for 40.5% of disability-adjusted life years (DALYs) caused by mental and substance use disorders [6]. It is often co-morbid with other several physical as well as mental health conditions with worse outcomes [7].

The prevalence of depression is particularly high in the primary healthcare setting [8, 9]. In a large international study of participants from 14 countries, 24% of attendees of primary care were found to have depression [10]. Studies from Africa also reported almost similar figures [11]. Depression is one of the most common conditions treated in primary care, and nearly 10% of all primary care visits are depression related [12]. Most patients suffering from depression are treated by their primary care physician [13]. Nevertheless, several studies both from high-income and low- and middle-income countries (LMICs) showed recognition of depression in primary care to be suboptimal [14, 15]. In high-income countries, more than 50% of cases with depression may be unrecognized [16]. The detection rate of depression in LMICs by primary care clinicians is extremely low [11]. A study in rural Ethiopia found that over 95% of patients presenting to primary care with potential depression do not receive a clinical diagnosis of depression [17].

Although detection is not a guarantee for treatment, it is a precondition for a patient with depression to be in the path towards appropriate care [18]. Lower level of detection has also a serious impact on the recent efforts to scale up the integration of mental healthcare in the primary care setting [17]. Hence, understanding the factors that impede detection of depression by primary care staff and addressing these factors are of crucial importance. Despite the challenges with recognition of depression in primary care, there is strong evidence that treating depression improves outcomes and is cost-effective [19]. Thus, there is a need to focus more effort and resources on coordinated, multilevel interventions that would improve the recognition of depression in primary care [20].

Several interventions that address the system level needs and the needs of the clinician as well as addressing patient and family/community level barriers to improving the detection of depression in primary care have been evaluated [16, 19, 21, 22]. These include screening [21], clinician education (educational interventions directed at primary care physicians) [23, 24], guidelines [25], case management [15], collaborative care [26], and stepped care [25]. Previous individual original studies, mostly conducted in high-income countries, found that coordinated interventions, such as screening and the chronic care model, are likely to be most effective to detect depression in the PHC setting [27]. Systematic reviews of effectiveness of different interventions to improve the detection of depression in primary care found that the best strategies are those with complex interventions that incorporated clinician education, case management by nurses, and greater collaboration between primary care providers and mental health specialists [25].

Considerable research has focused on the effect of these methods to improve the detection of depression in primary care [27]. Systematic reviews and meta-analysis have also been done to synthesize the evidence on the effectiveness of separate interventions (e.g., screening) to improve the detection of depression [19, 21]. Nevertheless, to the best of our knowledge, there are no reviews which examined the effectiveness of several interventions together. A systematic review focusing on the types and effectiveness of interventions to improve the detection of depression in primary healthcare would allow to identify which interventions have been evaluated and how effective these interventions are. The review would also highlight gaps in the evidence base.

This systematic review, therefore, aimed to address the following questions:

  • 1) What interventions have been tested to improve the detection of depression in primary healthcare?

  • 2) How effective are these interventions to improve the detection of depression in primary healthcare?

Methods

We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines throughout our review [28]. The protocol for the review was registered on PROSPERO (CRD42020166291).

Population and scope of review

Studies with adult or adolescent participants (age 15 or over) attending primary care facilities with depression, including major depressive disorder, bipolar depression, masked depression, secondary depression, minor depression, and subthreshold depression, were considered for inclusion in the review. We included all the different types of depression diagnoses, ranging from major depressive disorder to subthreshold depression; however, this has to be ascertained either through clinician diagnosis or using a structured symptom scale with a validated cut of point. A study was included if it examined the effectiveness of an intervention with the aim to improve detection of depression in the primary care setting. The inclusion criteria can be presented with the PICOS (population, intervention, comparator, outcome, and setting) framework as follows:

  • • P = Adults or adolescents (age 15 or over) attending primary care facilities and have depression

  • • I = Any intervention with the aim to improve detection of depression in the primary care setting

  • • C = Any comparator, a study was included if there was no comparator at all.

  • • O = Change in rate of detection of depression by PHC workers

  • • S = Study conducted anywhere in the world but in PHC setting

We excluded a study if it has reported only the prevalence of depression or detection rate of depression. We also excluded a study if it was not conducted in a primary care setting (e.g., conducted in a specialist hospital or community setting) even if it has evaluated the effectiveness of an intervention to improve the detection rate of depression. We also excluded a study if it is a review of any kind.

Outcome of interest

The outcome of interest in this systematic review was improvement of detection of depression in the primary care setting. In this review, detection is understood as the proportion of the number of patients correctly diagnosed as having depression by primary care clinicians compared to a diagnosis using a locally validated screening tool or a confirmatory clinical diagnosis by a mental health expert. Improvement in detection of depression is understood as change in the number of patients diagnosed as having depression by primary care clinicians following the intervention. This can be compared to diagnosis using screening tools, case vignettes, review of medical records, and clinical diagnosis by a mental health expert.

Types of study to be included

We included randomized controlled trials (RCT), cluster randomized trials, or quasi-experimental studies that involved the following:

  • • Development of an intervention which aimed to improve the detection of depression at a primary care setting

  • • Sociocultural adaptation of an intervention that would help to improve the detection of depression in primary healthcare

  • • Test the efficacy of an intervention to improve detection of depression in primary care

  • • Evaluate the effectiveness of an intervention to improve detection of depression in primary care

Search strategies

We searched major databases (PubMed, Embase, PsycINFO, Web of Science, and Cochrane Database of Systematic Reviews) from the inception of the databases to until the 4th week of April 2020. We also searched other databases, such as the Global Index Medicus which include Latin American and Caribbean Health Sciences Literature (LILACS), African Index Medicus (AIM), and African Journals Online (AJOL). References of included studies and authors who have conducted studies on detection and management of depression in primary care were also consulted.

We identified a number of terms to represent the four big terms. To identify the big term depression, we used such terms as depression, depressive disorder, major depressive disorder, minor depression, and bipolar depression. The search terms that were used for detection include detection, detection rate, prevalence, screening, case finding, and diagnosis. For primary health care, we used such terms as primary health care, primary care, health center, and primary hospital. To represent the term intervention, we used the terms intervention, strategies, methods, mechanisms, etc.

Depending on the database, we tried to find standardized terms representing each of our big terms and include them in our search. Then, the terms for depression, detection, intervention, and primary healthcare were combined with the Boolean term “AND.” On the basis of these search terms, detailed search strategy was developed before searching from each database. We reported the complete search strategy for the PubMed database (see Additional file 3).

Screening and data extraction

Three of the authors of this review (KH, RB, and MD) independently screened the titles and abstracts of 10% of the studies identified from the databases searched and those identified from additional sources. Additional sources were references of included studies identified from the databases and from consultation with authors who conducted research on detection and management of depression in primary care. Then, the rate of agreement to include or exclude these articles among the three screeners based on title and abstract screening was computed. Equal proportion of the rest of the titles and abstracts of the identified studies was screened only by one of the three authors stated above. As the rate of agreement was quite high (more than 90%), we decided the rest of the titles/abstracts to be screened by just one person. When a screener was not sure to include/exclude, they consulted the other two screeners and decided based on consensus. This was done to identify studies that potentially meet the inclusion criteria stated above. Then, the full text of the eligible studies were retrieved and assessed independently for eligibility by two members of the review team. Any disagreement between the two independent screeners over the eligibility of full-text studies was resolved through discussion with and by the recommendation of another member of the review team, who is more senior and experienced. We documented excluded articles and reasons for exclusion.

We developed and used a data extraction form for study characteristics and outcome data. This data extraction form was pilot tested before actual implementation. Two of the review authors independently extract the following data from included studies:

  • • Author/s

  • • Study country

  • • Study design

  • • Study setting

  • • Population

  • • Sample size

  • • Sample characteristics (gender and age)

  • • Intervention/s

  • • Control condition/s

  • • Length of follow-up

  • • Outcome/s measured (detection or prevalence)

  • • Outcome measures

  • • Summary of results

Quality assessment

All included studies were assessed for risk of bias independently by 2 researchers. We assessed the methodological quality of the included studies with reference to several criteria, including the methods of selection, allocation, blinding of outcome assessors, dropout, and intervention integrity. Differences of opinion were resolved by a third senior reviewer. The “Quality Assessment Tool for Quantitative Studies” developed by the Effective Public Health Practice Project (EPHPP) [29] was used to assess specific dimensions of the quality of the studies. The tool has eight items which assess selection bias, allocation bias, control of confounders, blinding of outcome assessors, data collection methods, withdrawals and dropouts, intervention integrity, and analysis. The tool allows global rating of “weak,” “moderate,” or “strong” for each included article. An article can be rated as “strong” if poor rating was not made in any of the eight items, “moderate” if poor rating was made in just one of the items, and “weak” if poor rating was made in two or more of the items. For each item, there are specific criteria to rate “good,” “fair,” or “poor.”

We reported the data for six of the eight items. We did not report the data for two of the items (intervention integrity and data analysis). This is because overall rating can be made with the first six items, and we found no difference in the rating of the included articles in terms of these last two items as almost all papers reported good intervention integrity and used the right data analysis. We used the Quality Assessment Tool for Quantitative Studies because it is designed to assess the methodological quality of studies with different quantitative designs: RCT, cluster RCT, and different types of quasi-experimental designs (such as before-after with control group and before-after with no control group).

Strategy for data synthesis

Narrative synthesis of the findings from the included studies was provided. The synthesis was structured in line with the review questions into the following: interventions developed, adapted, or tested to improve detection of depression, effectiveness of interventions to improve detection of depression, and quality of the studies included in the review.

We summarized key findings in the form of figures, tables, and text. Our original plan was to conduct meta-analysis and network meta-analysis, generate summary effect sizes of interventions, and determine direct as well as indirect effects and rank order interventions in terms of their effect to improve the detection of depression. However, we were not able to do all these because of the heterogeneity of the included studies in terms of several factors, including type of intervention, study design, content and duration of interventions, duration of follow-up, format of intervention delivery, outcome measures, and methods of statistical analysis used to determine effect size.

Results

We identified a total of 23,304 records from our search of databases. Of these, 5107 were excluded as they were duplicates. Of 18,197 articles, 17,891 were excluded after title/abstract screen as they were not related to depression or detection of depression or they do not involve any kind of intervention, or the studies were not conducted in PHC setting. Of the 306 studies included in full-text screen, 249 were excluded because of several reasons: duplicates, outcome not depression detection, the study does not involve any intervention, not original study, protocol paper, not published article, published not in English language, and full-text article not found. We included one more full-text article from screening 21 articles obtained from the references of the included studies. Hence, 58 articles were included in the final analysis. The PRISMA flow chart which describes the identification, screening, and inclusion process is presented in Fig. 1.

Fig. 1
figure 1

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) flow diagram

Full size image

Characteristics of the included studies

Most of the studies were from high-income countries (n = 47/58), particularly from the UK and USA. Only six studies were from low-income countries. In terms of study design, nearly half of the studies (n = 28) were before-after with no control group. Twenty-five studies were randomized (18 RCT and 7 cluster RCT). Many of the studies had small sample size; around half of the studies had sample size less than 150. Most of the studies (n = 34) used either purposive sampling or convenience sampling to select participants. Five of the studies did not describe the sampling technique they used to select participants.

The included studies in the review were diverse in terms of measuring depression detection (Table 1). While most of the studies used screening tool (n = 36), the other studies used case vignettes (n = 5), psychiatric interview (n = 6), and record review or chart audit (n = 11). Most of the studies were weak (n = 14) or moderate (n = 30) in their methodological quality. Only 14 out of 58 studies were assessed as strong in their methodological quality. For details of characteristics of the included studies, see Additional file 1.

Table 1 Summary of the data extracted from the included studies (n = 58)
Full size table

Interventions to improve detection of depression in primary healthcare

Diverse types of interventions were tested to improve the detection rate of depression in the primary healthcare setting. We grouped these interventions into six types. They included the following: (i) clinician training (education), (ii) screening alone, (iii) screening with feedback (disclosure of screening results to clinicians), (iv) combination of education, screening, and feedback interventions, (v) implementation of guidelines/collaborative care packages or quality improvement programs, and (vi) request for antidepressants. A relatively larger number of the studies tested clinician training (education) intervention (n = 22/58), followed by implementation of guidelines, collaborative care packages, or quality improvement programs (n = 10/58). Nine studies tested the effectiveness of screening intervention. Seven studies evaluated the effectiveness of screening with feedback, whereas another nine studies tried to check for the effectiveness of combining training, screening, and feedback interventions. Only one study evaluated the effectiveness of patient request for antidepressants to improve the ability of primary care clinicians to detect depression. Although different studies evaluated the same type of intervention (e.g., training or screening or feedback), the duration, intensity, content, and format of the intervention differed. The interventions tested in each of the included studies are summarized in Tables 2, 3, 4, and 5.

Table 2 Description of interventions and results of studies with clinician training (education) intervention
Full size table
Table 3 Description of interventions and results of studies with screening and feedback intervention
Full size table
Table 4 Description of interventions and results of studies with combination of interventions (education, screening, and feedback)
Full size table
Table 5 Description of interventions and results of studies with development and dissemination of guidelines/collaborative care package/quality improvement interventions
Full size table

Most of the clinician training interventions involved didactic sessions on the diagnosis, treatment, and referral of PHC depression [31, 32, 34, 37, 47]. The use of active learning methods (discussion, role play, and presentation) was particularly useful [35, 42, 45]. Training interventions included a theoretical part and a practical part, focusing on case discussion, role-playing games, and use of vignettes for clinical cases [30, 36]. Many of the educational interventions also involved clinical practice in assessment and treatment of depression using real or standardized patients or visit to outpatient departments [35,36,37, 40, 42]. A few educational interventions involved providing educational packet which included a copy of screening tool, treatment algorithm, and medication dosing guidelines [24, 41]. Training on the use (administration, scoring, and interpretation) of a depression screening scale was also an important aspect of educational interventions [49, 50]. One study tested a tailored and activating educational intervention (tailored according to the participants’ readiness to change) [48]. The duration of the training was diverse, ranging from 1 h to 2 weeks [31, 36, 45], and trainers were mostly psychiatrists or clinical psychologists. See Table 2.

Regarding studies which evaluated screening/feedback interventions, several types of screening tools were used, including different versions of the Patient Health Questionnaire (PHQ) [52,53,54,55,56], Zung Self-Rating Depression Scale (SDS) [53, 64], Quick Inventory for Depression Symptomatology Self-report (QIDS-SR) [58], General Health Questionnaire (GHQ) [60, 61, 63, 65], Edinburgh Postnatal Depression Scale (EPDS) [51], and Primary Care Evaluation of Mental Disorders (PRIME-MD) [66] (Table 3). Nevertheless, PHQ and GHQ were the most commonly used screening tools. The screening tools were mostly administered by nurses, general practitioners, and research assistants. In some studies, screening tools were self-administered [53, 58], and scoring was done by either nurse assistants or healthcare providers. While some of the studies used screening only as intervention [51, 52, 55,56,57,58,59], other studies used screening with feedback [53, 54, 60,61,62,63,64,65,66]. In most cases, results were given to the clinicians before or at the same time they saw the patient. The feedback gave the total score, the subscale scores, and the individual items the patient had answered positively.

Taking into account the limitations and strengths of each of the three types of interventions (clinician training, screening, and communicating the results of screening to clinicians), some studies combined two or all the three types of these interventions (Table 4). While some of the studies combined providing brief training to clinicians and screening of depression [68, 70, 74, 75], others combined all the three types of interventions: providing training to healthcare providers, depression screening with brief structured tools, and then providing feedback to the providers about the results of the screening [67, 71,72,73]. One study combined screening and then communicating screening results to clinicians [69].

The last type of intervention was related to development or adaptation and implementation of evidence-based guidelines, collaborative care packages, and quality improvement programs. This type of intervention was diverse in terms of who developed the intervention, its content, and duration of implementation (Table 5). Some examples of this type of intervention included implementation of evidence-based guideline on the identification of depressive symptoms [76], the World Health Organization’s International Classification of Diseases 10th version (WHO ICD-10) PHC guideline [77, 84], Behavioral health Screening, Brief Intervention, and Referral to Treatment (SBIRT) program [78], Mental Healthcare Plan (MHCP) [79]; adaptation and implementation of the WHO mhGAP [80]; implementation of a chronic diseases management approach [83], and organized, multi-faced collaborative approach to quality improvement [82, 85]. The guidelines/care packages/quality improvement programs were either locally developed by the research team or adapted from international guidelines/care packages/quality improvement programs. The duration of implementation varied from as short as 3 months [84] to as long as 12 months [77, 80, 81].

Effectiveness of interventions to improve detection of depression in primary healthcare

Of the 58 studies included in the review, 42 found positive results (i.e., significant improvement in the detection of depression in the PHC setting). Interventions that were found to be usually effective included implementation of comprehensive evidence-based guidelines/collaborative care packages/quality improvement programs [78, 79, 81, 83, 85]; screening with feedback supported by basic training and supervision [67, 74, 75]; multifaceted educational interventions which incorporated active learning, discussion, role play and clinical practice [33, 35, 36, 40, 48];and feedback or disclosure of screening results, particularly, of high screening scores [60, 61, 64, 65]. Interventions which combined education, screening, and feedback were particularly more effective in increasing recognition of depression [67, 74, 75]. Training interventions usually had short-term effects. Improvements in detection of depression after training of healthcare staff were observed; however, this improvement was not sustained.

Effectiveness of clinician training/education interventions

A study which evaluated a single evening 3 and half hour long seminar, which focused on the diagnosis, treatment, and referral of depression brought about significant improvement in accuracy of depression diagnosis (mean depression diagnosis accuracy in the intervention group 1.35 and in the control group 0.97) [32]. Another study, which used a 2–3 training sessions together with regular consultations between GPs and psychiatrists increased cases with clinically diagnosed depression from 4.0 to 7.9% (P < 0.05) [33]. Agreement between HAD diagnosis and clinical evaluation of depressive disorders improved from 20% (k = 0.18) to 45% (k = 0.54). After 1 year, GPs identified twice as many of the patients that suffered from anxiety or depression in comparison to before the intervention. A training intervention which involved a 60-min seminar plus a 60 min practical clinical skill improved diagnosis of depression among adolescents (from 0.89 to 2.22%) [35]. The odds of receiving a new diagnosis of depression were almost three times higher after training (OR = 2.7; P < .0001)

Two weeks onsite training which consisted of 2 h of didactic session on a topic, followed by a 2 hour visit to the outpatient department significantly improved mean scores on case vignettes (from 42.4 at baseline to 83.4 post-training) [36]. Eight hours training on depression to PHC providers, which consisted of a theoretical part and a practical part focusing on case discussion, role play, and use of case vignettes increased the rate of identification of depression from 5.9% (n = 97/1647) before training to 10.64% (n = 196/1832) after training [37]. Five-day training on mental health using a toolkit originally designed for Kenya improved detection of depression from 0 to 9% [40]. A 1-h minimal education intervention consisting of information, skill training, and discussion in small groups significantly improved recognition of depression among the elderly 3 months following the intervention (25% in the intervention group vs. 7% in the control group) [45]. One study tailored the intervention according to readiness to change and used interactive and multi-faceted learning activities, including case illustrations, standardized patients, role play, buzz group and programmed lecture [48]. The intervention was 2-day interactive training workshop. Printed materials were also given to the training participants. At post-intervention, mean of performance regarding depression diagnosis at the intervention group A vs. control group was 63 and 49, respectively (P = 0.007), whereas intervention group B vs. control group was 49 and 22, respectively (P < 0.001).

A study which evaluated a 3-day training course locally developed from the WHO mhGAP intervention guide in Nigeria on ability of PHC workers to make accurate diagnosis of depression found no improvement (92.5% pre-training and 93.8% post-training, P = 0.200) [30]. One hour training which provided basic information about depression and demonstration of a depression screening strategy did not improve accuracy of identification of cases of depression (22.2% in the intervention group and 16.7% in the control group, P > 0.05) [31]. Participants who were given a standard 2 h training which had role play did not bring improvement in their ability to recognize depression (1.91 per 100 visits in the intervention and 1.68 in the control were identified) [42]. A study tested the effectiveness of a brief 2-day training program for depression designed by the World Psychiatric Association (WPA) using a training module in the form of a seminar [49]. Case histories were used to make the seminar interactive. The attendees also received a printed copy of the materials. The participating physicians diagnosed depression in 14.2% (n = 176) of the patients before the training and 15.2% (n = 204) after the training (change = 1%, P = 0.474). Agreement between the physician and patient self-reported diagnosis remained poor and showed no improvement following the educational program.

A study tested the effect of a training which consisted of eight sessions of 2.5 h each [46]. Each session followed a similar structure: discussion of the normal practices and difficulties of the trainees; a short lecture by the psychiatrist trainer; illustration with video-taped consultations; introduction of guidelines and protocols for screening, diagnosis, or interventions; practice using various forms of hands-on learning (e.g., role playing); and evaluation. The study found no overall significant pre-post differences (OR = 1.39, P = 0.15) in diagnosis of depression. Rate of depression diagnosis was pre-training 40% and post-training 48%, P = 0.12).

Effectiveness of screening interventions with or without feedback

Overall, implementing routine screening of depression in the PHC setting improved detection of depression [51, 52, 54, 56]. These improvements did not mostly have statistical and practical significance. Almost all of the studies which tested screening intervention, however, had before-after quasi-experimental design. Implementation of routine screening of depression in the PHC setting was found to be more effective in terms of increasing recognition of depression when it was accompanied by feedback (disclosure of screening results to clinicians). Almost all of the studies, with screening intervention accompanied by feedback, brought about significant improvement in detection of depression [60, 61, 64, 65]. Nevertheless, many of the studies were non-randomized trials.

Effectiveness of combined education, screening, and feedback interventions

Improvement in PHC diagnosis of depression was found to be much higher when the three types of interventions were combined (clinician training, screening, and feedback). Almost all of the studies which evaluated a combination of these interventions (e.g., raising clinicians’ awareness and skills of managing depression, mass depression screening, and communicating the results to the clinician) found significant increase in recognition of depression [67, 69,70,71, 73,74,75]. A study which evaluated combining screening, feedback, and sensitization (by asking the clinician to rate the patient’s level of depression) improved detection of depression (32% in the intervention group compared to 8% in the control group) [69]. A few studies also evaluated interventions which combined clinician training and screening [68, 70, 71, 74]. Although these studies found improvement in PHC diagnosis of depression, effects were not as much as those interventions which combined education, screening, and feedback. Two out of the four studies (which tested interventions combining education and screening) did not find statistically significant improvement in detection of depression [68, 70].

Effectiveness of implementation of guidelines/collaborative care packages/quality improvement programs

Six of the ten studies [78,79,80,81, 83, 85], which evaluated effectiveness of implementation of guidelines/collaborative care packages/quality improvement programs found significant improvement in detection of depression at the PHC setting. For instance, implementation of a behavioral health Screening, Brief Intervention, and Referral to Treatment (SBIRT) program [78] found that 25.3% of the SBIRT intervention site patients had positive findings for depression compared with 11.4% of the control site patients (P < .001). A Mental Health Care Plan (MHCP) developed and implemented in Nepal, with training packages and supervision for health workers to detect, diagnose, and initiate treatment for depression increased the recognition of depression 15 to 24.6% [79]. Four of the ten studies, on the other hand, did not find statistically significant improvement [76, 77, 82, 84]. For instance, local development and dissemination of the WHO ICD-10 PHC guidelines [84] found no significant difference between guideline practices and usual-care practices. These interventions were diverse and multi-faceted, which involved development or adaptation and implementation of guidelines/care packages/quality improvement programs, supervision, collaboration and training.

Quality of included studies

Assessment of the quality of the included articles using the Quality Assessment Tool for Quantitative Studies showed weak quality in 14 studies out of 58. More than half of the studies (30 out of 58 articles) were rated as moderate quality, and the remaining 14 were rated as strong. In terms of selection bias, 31 studies were rated as moderate, 14 as weak, and 13 as strong. Most of the studies were rated as moderate (20 out of 58 studies) or strong (21 out of 58 studies) in their study design; 17 studies were rated as weak. Most of the studies were rated as weak (17 out of 58 studies) or moderate (30 out of 58 studies) in terms of blinding. Only 11 studies were rated as strong quality in taking care of blinding. More than half of the studies were rated as strong (35 out of 58 studies) in adjusting for confounding factors, whereas 18 studies were rated as weak and five studies as moderate. With regard to withdrawal and dropout, 24 out of 58 studies were rated as weak, 13 studies as moderate and 21 studies as strong. For details of the results of the quality assessment, see Additional file 2.

Discussion

To our knowledge, this is the first systematic review study which synthesized the global evidence on the effectiveness of diverse types of interventions to improve the detection of depression in the primary healthcare setting. Previous systematic reviews focused on effectiveness of single interventions, such as clinician education [22] and routine screening [16]. The current review, on the other hand, included studies which tested the effect of diverse interventions to improve primary care clinicians’ diagnosis of depression. Most of the studies are conducted in high-income countries; only six of the 58 studies were from low-income countries. Most of the studies (44 out of 58 studies) are weak or moderate in their global rating of quality assessment; only 14 studies are found to have strong methodological quality. This is on the basis of the results of the assessment of the quality of the included studies using the “Quality Assessment Tool for Quantitative Studies.”

Six groups of interventions were identified: clinician education, screening, screening with feedback, combination of interventions, and implementation of guidelines/collaborative care packages/quality improvement programs with one study testing the effect of patient request for antidepressants. Different studies evaluated the effectiveness of the same intervention (e.g., clinician education, screening or feedback); however, the duration, intensity, content, and format of the interventions in each study are quite different.

The studies included in the review are heterogeneous in terms of the type of intervention and how they delivered the same type of intervention making it difficult to assess the comparative effectiveness of the different interventions. The studies were also heterogeneous in their design, follow-up period, outcome measure, and the method of data analysis they used. The heterogeneity of the included studies in the review, particularly in terms of study design, is partly due to the broader nature of our inclusion criteria. Nevertheless, there were aspects of the different types of interventions that seemed particularly effective. These included screening with feedback and combining training, screening, and feedback interventions. Training interventions showed some improvement in the detection of depression in PHC. However, effects are short term and do not sustain after 6 months. A previous systematic review on the effectiveness of capacity building or training of primary healthcare professionals in the detection of depression in PHC found consistent results with our review [22]. Training interventions which used active learning methods, including role play, discussion, and clinical practice, are particularly more effective than those which used didactic sessions. There seems consensus that education and training will be more effective when it is participatory and active. The knowledge gained and the skills developed will also be long lasting when a training program uses active learning methods such as role play, presentation, and discussion. When didactic sessions dominate a training/education program, then skills will not be developed, and the knowledge obtained will be short lived. Local adaptation and implementation of guidelines, collaborative care packages, and quality improvement programs are also mostly effective. These interventions seem resource intensive; however, they are cost-effective in the long term [86].

Most of the included studies were conducted in high-income countries, with just six of the 58 studies carried out in low-income country settings. There is a large difference, both in the rate of detection and treatment coverage of depression, between high-income countries and LMICs [87]. Thus, findings from high-income countries cannot be generalized into LMICs. The methodological quality of most studies was also rated as weak or moderate necessitating new high-quality studies with randomized-controlled trial designs, particularly in LMIC settings.

Our review indicates that combination of interventions is likely to be required to improve the detection of depression in a PHC setting. There is need to focus on combining interventions and implement them in the form of guideline, collaborative care package, or quality improvement program. Implementation of routine screening alone does not seem to be effective; it has to be accompanied by disclosure of screening results to the clinician, training of the clinical and other relevant staff, and supportive supervision. A previous systematic review that was done to determine the effect of screening on improving recognition of depression [16] in the PHC setting found that if used alone, it appears to have little or no impact. This finding is on both the detection and the management of depression by PHC clinicians.

Our review also indicates that the implementation of guidelines, collaborative care, and quality improvement programs are more effective than usual care both for increasing the detection rate of depression in PHC and improving outcomes of depression treatment. A previous systematic review and meta-analysis of effectiveness of collaborative care for depression [86] found that collaborative care packages significantly improve recognition of depression by PHC workers. This intervention also improved outcomes of depression treatment in the PHC setting.

Little research has been done in LMICs, despite the rate of detection and treatment coverage of depression in PHC being extremely low [87]. Hence, more number of randomized-controlled trials, which addressed the limitations of previous studies and focused on more effective interventions, need to be conducted. There is also uncertainty about the sustainability of the effect of the interventions, which should be addressed in future studies.

Our systematic review is comprehensive in that we searched more than five databases with detailed search strategy and no geographical restriction. In addition, we consulted the references of the included articles. Our review covered studies which tested all types of interventions to improve the detection of depression in PHC. However, the findings of this review should be interpreted taking the following limitations into account. Our systematic review included studies which are published only in English language. Our review also did not search the gray literature. The studies included in the review were heterogeneous in terms of design, type, and content of the intervention, outcome measure, and measure of effect. Even when different studies evaluated the same intervention, they used different designs, different methods of analysis, and also operationalized detection of depression quite differently. Hence, it was not possible to conduct meta-analysis and network meta-analysis. Most of the included studies were from high-income countries which make it difficult to generalize the findings into low-income country settings. Most of the studies were weak or moderate in their methodological quality; about one in every four studies was rated as weak.

Conclusions

Our systematic review shows that several types of interventions were tested to improve the rate of detection of depression in PHC. Nevertheless, findings are inconsistent, and implementation of a single type of intervention does not seem to work. Implementation of a combination of interventions, focusing on aspects of each type of intervention which are more effective, seems promising. Combining healthcare staff training, screening, and feedback interventions is likely to increase recognition of depression in LMICs. Clinician education and training interventions, which incorporated simulation and role play, are found to be more effective. There is need to evaluate effectiveness of implementation of collaborative care packages and quality improvement programs to improve detection of depression in PHC in low-income country settings. Most of the studies conducted in the area are from high-income countries; studies are also weak in terms of their methodological quality. Hence, conducting high-quality RCT studies particularly from LMICs is warranted.

Availability of data and materials

All of the data used for the study are made available within the manuscript and supplementary materials.

Abbreviations

AIM:

African Index Medicus

AJOL:

African Journals OnLine

DALYs:

Disability-adjusted life years

EPDS:

Edinburgh Postnatal Depression Scale

EPHPP:

The Effective Public Health Practice Project

GHQ:

General Health Questionnaire

ICD-10:

International Classification of Diseases 10th version

LILACS:

Latin American & Caribbean Health Sciences Literature

LMICs:

Low- and middle-income countries

MHCP:

Mental Healthcare Plan

mhGAP:

Mental Health Gap Action Programme

OR:

Odds ratio

PHC:

Primary healthcare

PHQ:

Patient Health Questionnaire

PRIME-MD:

Primary Care Evaluation of Mental Disorders

PRISMA:

The Preferred Reporting Items for Systematic Reviews and Meta-Analysis

RCT:

Randomized controlled trials

QIDS-SR:

Quick Inventory for Depression Symptomatology Self-report

SBIRT:

Behavioral health Screening, Brief Intervention, and Referral to Treatment

SDS:

Zung Self-Rating Depression Scale

WHO:

World Health Organization

WPA:

World Psychiatric Association

References

  1. Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS medicine. 2006;3(11): e442.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Bromet E, Andrade LH, Hwang I, Sampson NA, Alonso J, de Girolamo G, de Graaf R, Demyttenaere K, Hu C, Iwata N, et al. Cross-national epidemiology of DSM-IV major depressive episode. BMC medicine. 2011;9:90.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Lépine J-P, Briley M. The increasing burden of depression. Neuropsychiatr Dis Treat. 2011;7(Suppl 1):3.

    PubMed  PubMed Central  Google Scholar 

  4. Moreno-Agostino D, Wu Y-T, Daskalopoulou C, Hasan MT, Huisman M, Prina M. Global trends in the prevalence and incidence of depression: a systematic review and meta-analysis. J Affect Disord. 2021;281:235–43.

    PubMed  Google Scholar 

  5. Vos T, Lim SS, Abbafati C, Abbas KM, Abbasi M, Abbasifard M, Abbasi-Kangevari M, Abbastabar H, Abd-Allah F, Abdelalim A. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet. 2020;396(10258):1204–22.

    Article  Google Scholar 

  6. Ferrari AJ, Charlson FJ, Norman RE, Patten SB, Freedman G, Murray CJ, Vos T, Whiteford HA. Burden of depressive disorders by country, sex, age, and year: findings from the global burden of disease study 2010. PLoS medicine. 2013;10(11): e1001547.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Kang H-J, Kim S-Y, Bae K-Y, Kim S-W, Shin I-S, Yoon J-S, Kim J-M. Comorbidity of depression with physical disorders: research and clinical implications. Chonnam Med J. 2015;51(1):8–18.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Tylee A, Gandhi P. The importance of somatic symptoms in depression in primary care. Prim Care Companion J Clin Psychiatry. 2005;7(4):167–76.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Katon W, Schulberg H. Epidemiology of depression in primary care. Gen Hosp Psychiatry. 1992;14(4):237–47.

    Article  CAS  PubMed  Google Scholar 

  10. Üstün TB, Sartorius N: Mental illness in general health care: an international study: John Wiley & Sons; 1995.

  11. Udedi M. The prevalence of depression among patients and its detection by primary health care workers at Matawale Health Centre (Zomba). Malawi Med J. 2014;26(2):34–7.

    PubMed  PubMed Central  Google Scholar 

  12. Zung WW. The role of rating scales in the identification and management of the depressed patient in the primary care setting. J Clin Psychiatry. 1990;51(Suppl):72–6.

    PubMed  Google Scholar 

  13. Coyne JC, Fechner-Bates S, Schwenk TL. Prevalence, nature, and comorbidity of depressive disorders in primary care. Gen Hosp Psychiatry. 1994;16(4):267–76.

    Article  CAS  PubMed  Google Scholar 

  14. Egede LE. Failure to recognize depression in primary care: issues and challenges. J Gen Intern Med. 2007;22(5):701–3.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Craven MA, Bland R. Depression in primary care: current and future challenges. Can J Psychiatry. 2013;58(8):442–8.

    Article  PubMed  Google Scholar 

  16. Gilbody S, Sheldon T, House A. Screening and case-finding instruments for depression: a meta-analysis. Cmaj. 2008;178(8):997–1003.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Fekadu A, Medhin G, Selamu M, Giorgis TW, Lund C, Alem A, Prince M, Hanlon C. Recognition of depression by primary care clinicians in rural Ethiopia. BMC Fam Pract. 2017;18(1):56.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Haavet OR, Sirpal MK, Haugen W, Christensen KS. Diagnosis of depressed young people in primary health care–a validation of HSCL-10. Fam Pract. 2011;28(2):233–7.

    Article  PubMed  Google Scholar 

  19. Gilbody SM, Whitty PM, Grimshaw JM, Thomas RE. Improving the detection and management of depression in primary care. Qual Saf Health Care. 2003;12(2):149–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Ng CW, How CH, Ng YP. Major depression in primary care: making the diagnosis. Singapore Med J. 2016;57(11):591–7.

    Article  PubMed  PubMed Central  Google Scholar 

  21. O’Connor EA, Whitlock EP, Beil TL, Gaynes BN. Screening for depression in adult patients in primary care settings: a systematic evidence review. Ann Intern Med. 2009;151(11):793–803.

    Article  PubMed  Google Scholar 

  22. Gilbody S. What is the evidence on effectiveness of capacity building of primary health care professionals in the detection, management and outcome of depression. Copenhagen: World Health Organization; 2004.

    Google Scholar 

  23. Zuckerbrot RA, Jensen PS. Improving recognition of adolescent depression in primary care. Arch Pediatr Adolesc Med. 2006;160(7):694–704.

    Article  PubMed  Google Scholar 

  24. Thompson C, Kinmonth AL, Stevens L, Peveler RC, Stevens A, Ostler KJ, Pickering RM, Baker NG, Henson A, Preece J, et al. Effects of a clinical-practice guideline and practice-based education on detection and outcome of depression in primary care: hampshire depression project randomised controlled trial. Lancet (London, England). 2000;355(9199):185–91.

    Article  CAS  PubMed  Google Scholar 

  25. Unutzer J, Park M. Strategies to improve the management of depression in primary care. Prim Care. 2012;39(2):415–31.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Nease DE Jr, Nutting PA, Graham DG, Dickinson WP, Gallagher KM, Jeffcott-Pera M. Sustainability of depression care improvements: success of a practice change improvement collaborative. J Am Board Fam Med. 2010;23(5):598–605.

    Article  PubMed  Google Scholar 

  27. Asarnow JR, Jaycox LH, Duan N, LaBorde AP, Rea MM, Murray P, Anderson M, Landon C, Tang L, Wells KB. Effectiveness of a quality improvement intervention for adolescent depression in primary care clinics: a randomized controlled trial. Jama. 2005;293(3):311–9.

    Article  CAS  PubMed  Google Scholar 

  28. Page MJ, Moher D, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. Bmj. 2021;372: n160.

    Article  PubMed  PubMed Central  Google Scholar 

  29. National Collaborating Centre for Methods and Tools. Quality assessment tool for quantitative studies In. Hamilton, ON: McMaster University; 2008.

    Google Scholar 

  30. Adebowale T, Umukoro OL, Gater R, Akinhanmi A, Ogunlesi A, Helme C, Wood G, Ibikunle I: Evaluation of a mental health training course for primary health care workers in Ogun State, South West, Nigeria. African Journal of Psychiatry (South Africa) 2014, 17 (5) (no pagination)(1000141).

  31. Alexander CL, Arnkoff DB, Glass CR, Kaburu AW. Detecting depression in rural primary care clinics in central Kenya: impact of a brief training intervention. Int Perspect Psychol Res Pract Consult. 2013;2(1):14–28.

    Google Scholar 

  32. Andersen SM, Harthorn BH. Changing the psychiatric knowledge of primary care physicians. the effects of a brief intervention on clinical diagnosis and treatment. Gen Hosp Psychiatry. 1990;12(3):177–90.

    CAS  PubMed  Google Scholar 

  33. Bodlund O, Andersson S-O, Mallon L. Effects of consulting psychiatrist in primary care: 1-year follow-up of diagnosing and treating anxiety and depression. Scand J Prim Health Care. 1999;17(3):153–7.

    Article  CAS  PubMed  Google Scholar 

  34. Davidson S, Koritsas S, O’Connnor DW, Clarke D. The feasibility of a GP led screening intervention for depression among nursing home residents. Int J Geriatr Psychiatry. 2006;21(11):1026–30.

    Article  PubMed  Google Scholar 

  35. Fallucco EM, James L, Smotherman C, Greco P. Impact of experiential training with standardized patients on screening and diagnosis of adolescent depression in primary care. J Adolesc Health. 2019;65(1):57–62.

    Article  PubMed  Google Scholar 

  36. Garg K, Manjunatha N, Kumar C, Chand P, Math S. Case vignette-based evaluation of psychiatric blended training program of primary care doctors. Indian J Psychiatry. 2019;61(2):204–7.

    PubMed  PubMed Central  Google Scholar 

  37. Gomez-Restrepo C, Penaranda AB, Benavides MO, Laverde JFG, Tamayo N, Sanchez DR. Health professional’s accuracy in depression diagnosis after an educational intervention in primary level: Colombian results of the international depression project. Revista Colombiana de Psiquiatria. 2007;36(3):439–50.

    Google Scholar 

  38. Hannaford PC, Thompson C, Simpson M. Evaluation of an educational programme to improve the recognition of psychological illness by general practitioners. Br J Gen Pract. 1996;46(407):333–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Haddad M, Pinfold V, Ford T, Walsh B, Tylee A. The effect of a training programme on school nurses’ knowledge, attitudes, and depression recognition skills: The QUEST cluster randomised controlled trial. Int J Nurs Stud. 2018;83:1.

    Article  PubMed  Google Scholar 

  40. Kauye F, Jenkins R, Rahman A. Training primary health care workers in mental health and its impact on diagnoses of common mental disorders in primary care of a developing country, Malawi: a cluster-randomized control trial. Psychol Med. 2014;44(3):657–66.

    Article  CAS  PubMed  Google Scholar 

  41. Kick SD. An educational intervention using the agency for health care policy and research depression guidelines among internal medicine residents. Int J Psychiatry Med. 1999;29(1):47–61.

    Article  CAS  PubMed  Google Scholar 

  42. Lin EHB, Simon GE, Katzelnick DJ, Pearson SD. Does physician education on depression management improve treatment in primary care? J Gen Intern Med. 2001;16(9):614–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Kutcher S, Udedi M, Gilberds H, Brown A, Chapota R, Perkins K. Clinic outcomes of the pathway to care model: A cross-sectional survey of adolescent depression in Malawi. Malawi Med J. 2017;29(2):97–102.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Pond CD, Mant A, Kehoe L, Hewitt H, Brodaty H. General practitioner diagnosis of depression and dementia in the elderly: can academic detailing make a difference?. Fam Pract. 1994;11(2):141–7.

  45. Van Daele T, Vansteenwegen D, Hermans D, Van den Bergh O, Van Audenhove C. Home nurses and patient depression.  attitudes, competences and the effects of a minimal intervention. J Adv Nurs. 2015;71(1):126–35.

    PubMed  Google Scholar 

  46. Vanos TW, Ormel J, van den Brink RH, Jenner JA, Van der Meer K, Tiemens BG, et al. Training primary care physicians improves the management of depression. Gen Hosp Psychiatry. 1999;21(3):168–76.

    Article  CAS  Google Scholar 

  47. Worrall G, Angel J, Chaulk P, Clarke C, Robbins M. Effectiveness of an educational strategy to improve family physicians’ detection and management of depression: a randomized controlled trial. CMAJ. 1999;161(1):37–40.

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Shirazi M, Lonka K, Parikh SV, Ristner G, Alaeddini F, Sadeghi M, Wahlstrom R. A tailored educational intervention improves doctor’s performance in managing depression: a randomized controlled trial. J Eval Clin Pract. 2013;19(1):16–24.

    Article  PubMed  Google Scholar 

  49. Vicente B, Kohn R, Levav I, Espejo F, Saldivia S, Sartorius N. Training primary care physicians in Chile in the diagnosis and treatment of depression. J Affect Disord. 2007;98(1–2):121–7.

    Article  PubMed  Google Scholar 

  50. Miller ES, Grobman WA, Ciolino J, Zumpf K, Sakowicz A, Gollan J, Jensen R, Wisner KL. 63: is implementation of a perinatal collaborative care program associated with improvements in depression care? Am J Obstet Gynecol. 2020;222(1 Supplement):S53.

    Article  Google Scholar 

  51. Davies BR, Howells S, Jenkins M. Early detection and treatment of postnatal depression in primary care. J Adv Nurs. 2003;44(3):248–55.

    Article  PubMed  Google Scholar 

  52. Kalina EJ: Standardized postpartum depression screening and treatment. Dissertation Abstracts International: Section B: The Sciences and Engineering 2016, 76(9-B(E)):No Pagination Specified.

  53. Kozel D, Zakotnik JM, Grum AT, Kersnik J, Rotar-Pavlic D, Tomori MZ, Ziherl S. Applicability of systematic screening for signs and symptoms of depression in family practice patients in Slovenia. Zdrav Vestn Slov Med J. 2012;81(12):838–46.

    Google Scholar 

  54. Leslie KR, Chike-Harris K. Patient-administered screening tool may improve detection and diagnosis of depression among adolescents. Clin Pediatr. 2018;57(4):457–60.

    Article  Google Scholar 

  55. Lewandowski R, O’Connor B, Bertagnolli A, Beck A, Tinoco A, Gardner WP, Jelinek-Berents CX, Newton DA, Wain KF, Boggs JM, et al. Screening for and diagnosis of depression among adolescents in a large health maintenance organization. Psychiatric Services. 2016;67(6):636–41.

    Article  PubMed  Google Scholar 

  56. Libby JM, Stuart-Shor E, Patankar A. The implementation of a clinical toolkit and adolescent depression screening program in primary care. Clin Pediatr. 2014;53(14):1336–44.

    Article  Google Scholar 

  57. Leng JCF, Changrani J, Tseng C-H, Gany F. Detection of depression with different interpreting methods among Chinese and Latino primary care patients: a randomized controlled trial. J Immigr Minor Health. 2010;12(2):234–41.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Zupancic M, Yu S, Kandukuri R, Singh S, Tumyan A. Practice-based learning and systems-based practice: detection and treatment monitoring of generalized anxiety and depression in primary care. Journal of graduate medical education. 2010;2(3):474–7.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Gledhill J, Kramer T, Iliffe S, Garralda M. Training general practitioners in the identification and management of adolescent depression within the consultation: a feasibility study. J Adolesc. 2003;26(2):245–50.

    PubMed  Google Scholar 

  60. Badger LW, Rand EH. Unlearning psychiatry: a cohort effect in the training environment. Int J Psychiatry Med. 1988;18(2):123–35.

    Article  CAS  PubMed  Google Scholar 

  61. Callahan CM, Dittus RS, Tierney WM. Primary care physicians’ medical decision making for late-life depression. J Gen Intern Med. 1996;11(4):218–25.

    Article  CAS  PubMed  Google Scholar 

  62. Christensen KS, Toft T, Frostholm L, Ørnbol E, Fink P, Olesen F. The FIP study: a randomised, controlled trial of screening and recognition of psychiatric disorders. Br J Gen Pract. 2003;53(495):758–63.

    PubMed  PubMed Central  Google Scholar 

  63. German PS, Shapiro S, Skinner EA, Von Korff M, Klein LE, Turner RW, Teitelbaum ML, Burke J, Burns BJ. Detection and management of mental health problems of older patients by primary care providers. JAMA. 1987;257(4):489–93.

    Article  CAS  PubMed  Google Scholar 

  64. Moore JT, Silimperi DR, Bobula JA. Recognition of depression by family medicine residents: the impact of screening. J Fam Pract. 1978;7(3):509–13.

    CAS  PubMed  Google Scholar 

  65. Rand EH, Badger LW, Coggins DR. Toward a resolution of contradictions. utility of feedback from the GHQ. Gen Hosp Psychiatry. 1988;10(3):189–96.

    CAS  PubMed  Google Scholar 

  66. Schriger DL, Gibbons PS, Langone CA, Lee S, Altshuler LL. Enabling the diagnosis of occult psychiatric illness in the emergency department: a randomized, controlled trial of the computerized, self-administered PRIME-MD diagnostic system. Ann Emerg Med. 2001;37(2):132–40.

    Article  CAS  PubMed  Google Scholar 

  67. Albedaiwi WA, Goldberg BG, Lapidus J, Muench JP. Utility of an intervention to detect depression in primary care. Neurosciences (Riyadh, Saudi Arabia). 2005;10(4):284–90.

    PubMed  Google Scholar 

  68. Diez-Canseco F, Toyama M, Ipince A, Perez-Leon S, Cavero V, Araya R, Miranda J. Integration of a technology-based mental health screening program into routine practices of primary health care services in Peru (the Allillanchu Project): development and implementation. J Med Internet Res. 2018;20(3):e100.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Linn LS, Yager J. The effect of screening, sensitization, and feedback on notation of depression. J Med Educ. 1980;55(11):942–9.

    CAS  PubMed  Google Scholar 

  70. Romera I, Montejo AL, Aragones E, Angel Arbesu J, Iglesias-Garcia C, Lopez S, Antonio Lozano J, Pamulapati S, Yruretagoyena B, Gilaberte I: Systematic depression screening in high-risk patients attending primary care: a pragmatic cluster-randomized trial. Bmc Psychiatry 2013, 13.

  71. Sorkin DH, Rizzo S, Biegler K, Sim SE, Nicholas E, Chandler M, Ngo-Metzger Q, Paigne K, Nguyen DV, Mollica R: Novel health information technology to aid provider recognition and treatment of major depressive disorder and posttraumatic stress disorder in primary care. Med Care 2019, 57 Suppl 6 Suppl 2:S190-s196.

  72. Whooley MA, Stone B, Soghikian K. Randomized trial of case-finding for depression in elderly primary care patients. J Gen Intern Med. 2000;15(5):293–300.

    CAS  PubMed  PubMed Central  Google Scholar 

  73. Williams JW Jr, Mulrow CD, Kroenke K, Dhanda R, Badgett RG, Omori D, Lee S. Case-finding for depression in primary care: a randomized trial. Am J Med. 1999;106(1):36–43.

    PubMed  Google Scholar 

  74. Yonkers KA, Smith MV, Lin H, Howell HB, Shao L, Rosenheck RA. Depression screening of perinatal women: an evaluation of the healthy start depression initiative. Psychiatr Serv (Washington, DC). 2009;60(3):322–8.

    Article  Google Scholar 

  75. Yawn BP, Dietrich AJ, Wollan P, Bertram S, Graham D, Huff J, Kurland M, Madison S, Pace WD. TRIPPD: a practice-based network effectiveness study of postpartum depression screening and management. Ann Fam Med. 2012;10(4):320–9.

    PubMed  PubMed Central  Google Scholar 

  76. Bermejo I, Frey C, Kriston L, Schneider F, Gaebel W, Hegerl U, Berger M, Harter M. Stability of the effects of guideline training in primary care on the identification of depressive disorders. Prim Care Community Psychiatry. 2007;12(3–4):99–107.

    Google Scholar 

  77. Croudace T, Evans J, Harrison G, Sharp DJ, Wilkinson E, McCann G, Spence M, Crilly C, Brindle L. Impact of the ICD-10 Primary Health Care (PHC) diagnostic and management guidelines for mental disorders on detection and outcome in primary care. cluster randomised controlled trial. Br J Psychiatry. 2003;182:20–30.

    Article  PubMed  Google Scholar 

  78. Dwinnells R. SBIRT as a vital sign for behavioral health identification, diagnosis, and referral in community health care. Ann Fam Med. 2015;13(3):261–3.

    PubMed  PubMed Central  Google Scholar 

  79. Jordans MJD, Luitel NP, Kohrt BA, Rathod SD, Garman EC, De Silva M, Komproe IH, Patel V, Lund C: Community-, facility-, and individual-level outcomes of a district mental healthcare plan in a low-resource setting in Nepal: a population-based evaluation. PLoS medicine 2019, 16 (2) (no pagination)(e1002748).

  80. Nakku JEM, Rathod SD, Garman EC, Ssebunnya J, Kangere S, De Silva M, Patel V, Lund C, Kigozi FN. Evaluation of the impacts of a district-level mental health care plan on contact coverage, detection and individual outcomes in rural Uganda: a mixed methods approach. Int J Ment Health Syst. 2019;13:63.

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Petersen I, Bhana A, Fairall LR, Selohilwe O, Kathree T, Baron EC, Rathod SD, Lund C: Evaluation of a collaborative care model for integrated primary care of common mental disorders comorbid with chronic conditions in South Africa. BMC Psychiatry 2019, 19 (1) (no pagination)(107).

  82. Sherman SE, Chapman A, Garcia D, Braslow JT. Improving recognition of depression in primary care: a study of evidence-based quality improvement. Jt Comm J Qual. 2004;30(2):80–8.

    Google Scholar 

  83. Scott J, Thorne A, Horn P. Quality improvement report: effect of a multifaceted approach to detecting and managing depression in primary care. BMJ (clinical research ed). 2002;325(7370):951–4.

    Article  PubMed  Google Scholar 

  84. Upton MW, Evans M, Goldberg DP, Sharp DJ. Evaluation of ICD-10 PHC mental health guidelines in detecting and managing depression within primary care. Br J Psychiatry. 1999;175:476–82.

    Article  CAS  PubMed  Google Scholar 

  85. Rinke ML, Bundy DG, Stein REK, O’Donnell HC, Heo M, Sangvai S, Lilienfeld H, Singh H. Increasing recognition and diagnosis of adolescent depression: project RedDE: a cluster randomized trial. Pediatr Qual Saf. 2019;4(5):e217.

    Article  PubMed  PubMed Central  Google Scholar 

  86. Gilbody S, Bower P, Fletcher J, Richards D, Sutton AJ. Collaborative care for depression: a cumulative meta-analysis and review of longer-term outcomes. Arch Intern Med. 2006;166(21):2314–21.

    PubMed  Google Scholar 

  87. Rathod SD, Roberts T, Medhin G, Murhar V, Samudre S, Luitel NP, Selohilwe O, Ssebunnya J, Jordans MJ, Bhana A. Detection and treatment initiation for depression and alcohol use disorders: facility-based cross-sectional studies in five low-income and middle-income country districts. BMJ open. 2018;8(10): e023421.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Not applicable

Funding

This study is jointly funded by the UK Medical Research Council (MRC) and the UK Department for International Development (DFID) under the MRC/DFID concordant agreement through the Africa Research Leader scheme (Grant Ref: MR/M025470/1).

Author information

Authors and Affiliations

  1. School of Psychology, College of Education and Behavioral Studies, Addis Ababa University, Addis Ababa, Ethiopia

    Kassahun Habtamu

  2. Department of Psychiatry, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia

    Rahel Birhane, Mekdes Demissie & Abebaw Fekadu

  3. School of Nursing and Midwifery, College of Health Sciences and Medicine, Haramaya University, Dire Dawa, Haramaya, Ethiopia

    Mekdes Demissie

  4. Centre for Innovative Drug Development and Therapeutic Trials for Africa (CDT-Africa), Addis Ababa University, Addis Ababa, Ethiopia

    Abebaw Fekadu

  5. Global Health & Infection Department, Brighton and Sussex Medical School, Brighton, UK

    Abebaw Fekadu

  6. Department of Psychological Medicine, Center for Affective Disorders, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK

    Abebaw Fekadu

Authors
  1. Kassahun Habtamu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rahel Birhane
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mekdes Demissie
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Abebaw Fekadu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

AF and KH conceived and designed the study. KH, RB, and MD did the database searching, screening, data extraction, and quality assessment. KH did the analysis and drafted the manuscript. AF critically revised and substantially contributed throughout the writing of the manuscript. The authors read and approved the final manuscript.

Corresponding author

Correspondence to Kassahun Habtamu.

Ethics declarations

Ethics approval and consent to participate

N/A

Consent for publication

N/A

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Habtamu, K., Birhane, R., Demissie, M. et al. Interventions to improve the detection of depression in primary healthcare: systematic review. Syst Rev 12, 25 (2023). https://doi.org/10.1186/s13643-023-02177-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13643-023-02177-6

Keywords

Systematic Reviews

ISSN: 2046-4053