1 In Viet Nam, the updated data of WHOreported the prevalence of depressive disorders of 5.73%, and the rate ofsuicide in 2015 was 5.87 per 100,000 population.2 Without proper treated,deDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen provinceDepression-related factors and the effectiveness of community-based intervention with Stepped Care Model in Thai Nguyen province
The overview of depression
Definition of depression 3 1.1.2 Some epidemiological factors of depression 4 1.1.3 Etiology of depression 7 1.1.4 Diagnostic criteria for depression 12 1.1.5 Treatment of depression 13 1.2 Depression-related factors
The concept and classification of depression has evolved and changed significantly from the 18 th century 17 The term depression is extremely broad, variably defining an affect, mood states, disorders, or syndromes.
A depressive affect usually occurs in response to a specific situation and is defined as a transient feeling ‘depressed’, ‘sad’, or ‘blue’.
At a higher level, a depressive mood is more pervasive, more likely to be experienced as negative ideation, and may influence behavior It generally lasts minutes to days in non-clinical situations.
At the highest level, a depressive episode is generally distinguished by a longer duration (usually minimum duration of 2 weeks), more clinical and pathological features, and remarkable social impairment Additional clinical features about severity and sub-typing, especially social impairment criterion, cleaves ‘normal’ mood states from clinical depressive conditions.
In this study, we used the terms “depression” and “depressive disorders” with the same meaning that refers to the individuals with significant depressive symptoms which can range from a large spanning subclinical depression and adjustment disorders, to clinical depression To reach larger populations, the identification and intervention of depression focused on the long-term impact on depressive symptoms, rather than diagnosed depressive disorders This approach is considered as suitable for community intervention with limited resources and less burden for specialist levels in general 7,18
1.1.2 Some epidemiological factors of depression
Firstly, the prevalence of depression varies depending on studies with different classification methods This proportion ranges from 17% for diagnosis interviews to 31% based on screening tools, and 22% for combinations 19 The report from 30 countries found that utilizing self- reporting tools, studies in women, and nations with a medium human development index had considerably higher prevalence 20 Generally, a recent systematic review of depression prevalence represents a predominant upward trend within populations worldwide 21
Secondly, the depression rate depends on the demographic characteristics of the study population The prevalence in women is generally 1.5 to 3 times higher than that of men, and this figure of the 18-29-year-old group three times higher than that of people over 60 22 This figure may be higher in specific occupation with high work pressure such as doctors, nurses and teachers 23–25 Among 55 industries, the prevalence of clinical depression ranged from 6.9 to 16.2%, especially with high levels of stress, low levels of physical exercise, frequent or challenging interactions 26 A review in China observed a higher prevalence of depression in rural areas, 27 while a study in Canada noticed a higher prevalence of 18% in urban areas 28 A review detected that higher prevalence of depression in specific developing regions is affected by age, regional and ecological factors 29 A systematic review of depression in Africa and the Middle East found a predominant prevalence ranging from 4% to 53% with common risk factors including women, old, poverty, and chronic disease 30
Thirdly, a review of epidemiological studies demonstrated that estimates of depression's lifetime prevalence vary by nations 31 In UnitedKingdom (UK), the study indicated the point prevalence rate of 2.3% for depression 32 The prevalence of depression in China was estimated to be 1.6% currently, 2.3% over the course of a year, and 3.3% throughout the course of lifetime 27 The community surveys using the WHO Composite International Diagnostic Interview in 10 countries showed that the prevalence of depression in Japan is 3%, Turkey 6.3%, Czech Republic 7.8%, Mexico 8.1%, Canada 8.3%, Chile 9%, Brazil 12.6%, Netherlands 15.7%, and America 16.9% 33
In Vietnam, the rates of depression in the community differ depending on the time and locality studied Bui The Khanh (2001) investigated clinical epidemiology of some common mental illnesses in a ward in Buon Ma Thuot city and found that the depression rate was 2.1% 34 Tran Viet Nghi (2002) studied the clinical epidemiology of depressive disorders in some community populations in Thai Nguyen, found that the rate of depression in one commune was 8.35% and in one ward was 4.2% 35 Tran Huu Binh (2007) studied depressive disorders in Le Dai Hanh ward of Hanoi found that the rate of depression was 4.18% 36 Nguyen Thanh Cao (2012) found that the rate of depression in a ward in Bac Can town was 4.3% 37 The updated data of WHO reported the prevalence of depressive disorders along with 5.73% in Vietnam, and the rate of suicide in 2015 was 5.87 per 100,000 population 2
Recently, there are many studies in Vietnam about depression and related factors, especially during and after the COVID-19 pandemic A study among Vietnamese youth from 15 to 24 years old revealed the depression rate of 10% 38 A meta-analysis exhibited the pooled prevalence of depression was14.64% during the pandemic, especially in health care workers 39 Using thePatient Health Questionnaire-9 to screen for depressive symptoms among university students in Vietnam, it found that 46% of 302 students had depressive symptoms, particularly in individuals with low physical activity 40 The likelihood of depressive symptoms was proven to be higher in poor people, specifically in men and major ethnic groups 41 A study in 1,085 men in rural areas showed the depressive symptom rate of 6.39%, and related factors included older age, educational level less than high school, and low financial status 42 In general, the burden of depressive disorders is increasing in Vietnam which need more attention and effective management.
According to the WHO, by 2030 depression will become the third leading cause of the global burden of disease 1 The consequences of depression can be long-lasting or recurrent and can dramatically impact at all levels.
At an individual level, depression is related to various negative consequences in both physical and mental health Depression can lead to higher risk of various physical diseases, leading excess mortality with the overall relative risk of 1.52 43,44 Moreover, the comorbid physical conditions have poorer prognosis 45 According to the Global Burden of Disease Study, depression were the leading causes of disability-adjusted life years, with significantly increasing number of all-age years of healthy life lost due to disability during 2007-2017 46 Severe depression can lead to 20-fold higher risk of suicide, and the mortality was 1.8 times higher 47 The population attributable risk of depression was 12.7% and 4.8% for all-cause deaths and suicides respectively 48 It also account for 10% of all-cause death 49
At socio-economical level, depressive people are demonstrated to be less often married, more often unemployed and incapable in daily functioning.
Depression without proper treatment results in reduced productivity, and is estimated to lost 50 million years of life expectancy each year, causing a loss of about $925 billion 50 In UK, the cost is significant at £17 billion in lost output and direct health care costs to the economy annually, and a £9 billion impact on benefit payments and lost tax receipts 51
Recently, the burden of depression is exacerbated by the Corona Virus Disease of 2019 (COVID-19) pandemic, with the average proportion up to more than 34-36% in China and nearly 30% in other countries 52 A recent large- scale study notified a significant increase in depression prevalence globally, especially in women, healthcare workers, and COVID-19-infected patients 53 Basically, the depressive symptoms can be identified until more than 12 weeks following this infection with the frequency of about 28% 54 In sum, this increasing prevalence is attributed to the enhanced awareness of population, more access to mental health care, and more common diagnostic criteria and tools, not merely increase in incidence 55
In Vietnam, a study reviewed the burden of depression from 1990 to 2019 demonstrated that depressive disorders comprised 2,629,000 estimated cases and 380,000 estimated DALYs, in particular among women 56 Although notable change in mental health services in recent years, the disease burden has been high and lack of integrating and promoting equity 57 Along with other common mental illness, depression risk was associated with social factors such as disadvantaged familial characteristics, low socio-economic status 58 These evidence suggest that a community-based strategy aimed at lowering home risk factors and offering helpful assistance could be a useful tactic to reduce the depression burden in Vietnam.
Depression is considered as multifactorial disorders with multiple etiological pathways 59,60 Therefore, it is of necessity to explore the depressive disorders with a biopsychosocial model instead of the biomedical model 3
● Biogenic amine hypothesis (monoamine theory)
The biogenic amine dysfunctions are traditional, evidence-based hypotheses with 3 major monoamine systems including serotonin, dopamine, norepinephrine It is the basis of using medication in depression treatment with different mechanisms 3,61 Firstly, serotonin controlling the affects, aggression, sleep, and appetite, is proved to contribute to the pathogenesis of depression 22 The serotonergic dysfunction range from reduced concentration in central nervous system (CNS) to decreased specific receptors, as well as lower number of transporter binding sites in the midbrain and amygdala 59,62 Secondly, dopamine is known as a important catecholamine for drive, pleasure, sex, and psychomotor activity 17 The dopaminergic alterations are supported by the high comorbidity of depression with Parkinson’s disease, and the dopaminergic properties of some antidepressants 3,17,59 Thirdly, the noradrenergic dysregulation is one of the main mechanisms of depression combining with anxiety, including low concentration of norepinephrine metabolites, increased β-adrenergic receptors in the CNS, and the stress response 59 Moreover, some research proposed the role of glutamate γ- aminobutyric acid, brain-derived neurotrophic factors, thyrotropin-releasing hormone, corticotropin - releasing factor, acetylcholinergic neurons in the etiology of depression 17,62–64 In general, it involves more complicated dysregulation than the single neurotransmitter hypothesis predicts.
● Neuroendocrine causes and stress responses
Biological factors 21 1.2.2 Psychological factors 25 1.2.3 Socio-environmental factors 26 1.3 The community-based intervention with Stepped Care Model for
There is a lot of literature that emphasizes the higher prevalence of depression in women compared to men, the ratio of women to men is approximately 2:1 3,17,22 According to DSM-V, prevalence of this disease in women is 1.5 to 3 times higher than that of men in early adulthood 22 The study suggested gender as a related factors for depressive disorder 62,134 Although there have been many changes in women’s social positions over time, a recent systematic review revealed that the gender gap in depression has not significantly decreased among adults 135
To be specific, the higher risk of depression in women is influenced by a myriad of factors Women usually have more hazardous thyroid activities,unstable sexual hormones levels, which contributes to depression, especially in postpartum, premenstrual and menopause periods 17,65 Furthermore, women may have higher psychological susceptibility for depression including neuroticism, rumination, body shame and dissatisfaction 136 Also, the researchers found that big rapid social life transitions like childbirth, menopause, retirement, empty-nest transition, and midlife crises might trigger depression in women more severely 137 The meta-analyses demonstrated that there is a considerable negative correlation between depression and femininity, whereas masculinity acts as a protective factor for depression 138 The prevalence of depression was noticed to be higher in lesbian, gay and bisexual population compared to the heterosexual population 139–141
Although depressive disorders can appear at any age, the likelihood of the onset rises significantly during puberty In US, the peak incidence of depression is studied to be in the 20s 22 According to the APA, the 12-month prevalence of depressive disorders of age group from 18 to 29 is 3 times higher than that of the group aged 60 and over 142 Moreover, the literature indicating that the depression rate reaches a climax around age 13-15, and the distribution of onset age of major depression is bimodal with two points of thirties and fifties 3 Sadock suggested that the average age of onset of depression is about 40 years, with 50% of patients having an onset of between 20 and 50 years old 143 In the community, Williams found that typical depression is less common in older people than in young people 144
These high-risk age groups may be due to multiple mechanisms The dysregulated growth hormone and early puberty are demonstrated to be risk factors of depression, particularly in the childhood and adolescence 3 The puberty period marks lots of neurobiological and social changes in adolescents, from sex characteristics and body changes to interpersonal conflicts among peers In addition, the up-to-date contemporary life may cause various negative social interactions such as virtual harassment, bullying or isolation, leading to the development of depression in the youngster 135
1.2.1.3 Cortisol (HPA axis function) and neuroendocrine factors
There is evidence showing that HPA axis disorders are present in 50% to 75% of depressed cases, both anatomically and functionally 67 According to the modern stress diathesis hypothesis, the excessive secretion of cortisol and associated hormones are critical factors In particular, research showed the hyperactivity and impaired feedback regulation of the HPA axis; decreased corticotropin-releasing factor’s receptors in the frontal cortex 3,59 Moreover, the systematic review and meta-analysis of 75 prospective articles identified cortisol as the only biomarker that can be a potential predictor of depressive disorders’ onset, relapse or recurrence 84
1.2.1.4 CNS condition, the neuroamine and neurophysiological factors
The relationship between CNS condition and depression is proven in cases of Parkinson’s disease, post-stroke depression with higher rate of depression 3 Furthermore, the frontal lobe hypoactivation is proved to be a risk factor of depression in the period of infancy 3,145 Moreover, the biogenic amine dysfunctions which are consequences of CNS conditions may contribute to depression pathophysiology 146 The reduced serotonin availability is related to the rapid relapse of depressive symptoms 59 The monoamine transmitter is considered as an attribute to the higher risk of depression among females It can be explained that women have a greater level of monoamine oxidase enzyme compared to men 17
1.2.1.5 Physical condition (non-CNS condition) and the inflammatory factors
The depression-related physical factors are explained by the inflammatory theory The meta-analysis of 99 studies showed that elevated interleukin-6 was significantly related to the depression 147 A systematic review and meta-analysis of 73 studies noticed the relating abnormal blood chemokines, suggesting the potential implication of identifying depression based on inflammatory biomarker profile 148 An updated review highlighted the association between depressive symptoms and different immunological alterations, suggesting that inflammation is an important disease modifier 149 The inflammation was considered as a precipitating element that leads to depression, as well as a perpetuating factor that makes recovery difficult 66 Moreover, the influence of physical condition towards depression can be clearly seen in people with chronic diseases with biological and financial impairments The metabolically health status, and having at least 4 metabolic risk factors are proved to be risk factors for depression 4 In particular, unhealthy obesity was linked to a 30–83% higher risk of depression, while metabolically unhealthy non-obesity was linked to a 19-60% higher risk 150
1.2.1.6 Family history and the genetic factors
The genetic studies showed that depression risk is two to four times higher in first-degree relatives of those with the condition than in the general population Early onset and recurrent depression seems to have greater relative hazards, and neuroticism is a personality attribute that contributes significantly to this heritability 22 The latest genome-wide association meta- analysis also pointed out many promising genetic risk factors and architecture of depressive disorders in different populations 151,152
1.2.1.7 Gut microbiome and other biomarkers
The gut brain axis dysfunction is proved to relate to the metabolic and appetite disturbances, and functional gastrointestinal symptoms 72 The gut microbiota may regulate brain activities such as the HPA axis, immune system, and neurogenesis 71 Additionally, the evidence of mitochondrial dysregulation, nutritional factors, gut permeability and neuroprogression in the depression’s chronicity and treatment resistance suggest promising dietary modifications and microbiome for depressed people 55
Depression is attribute to various psychological factors such as personality, emotional resilience, early trauma, and cognitive styles.
The different personality traits can differentially relate to depressive mood 153 The low self-esteem is more likely to cause an individual to sink into depression in a difficult environment 17 On the contrary, people with high self- esteem have been shown to have a lower possibility for developing depression, regardless of whether or not having narcissistic self- enhancement 154 Other common traits relating to depression are neuroticism, anxious, impulsive and obsessional, especially low extraversion and conscientiousness, and high neuroticism 3,155 A systematic review found that the temperament characteristics of high harm avoidance (anticipated fear of challenging events) and low self-directedness (the adaptive capacity to achieve personal goals) seem to be reliable indicators of an individual's susceptibility to depression, even predicting response to treatment 153
1.2.2.2 The early trauma and adverse childhood experiences
The literature showed that early adversity and childhood maltreatment are of paramount importance in depression, especially in vulnerable people 3,17 Childhood maltreatment includes separation, physical neglect or abuse,emotional or sexual abuse, and witnessing domestic violence, all occur before the age of 11 and lasting for a minimum 6 months 85 A meta-analysis about the role of childhood trauma towards adult depression emphasized that the neglect and emotional abuse are the strongest childhood risk factors 156 Moreover, these early maltreatments can be risk factors for depression with more severe, early- onset and treatment-resistant characteristics 157 The premature life adversities are considered to relate to low response of depression treatment, higher risk of relapse and more prolonged course 59
1.2.2.3 The emotional resilience and cognitive styles
The temperamental instability is proved to be a risk factor for depressive disorders 17 The unstable emotion which typically precedes clinical depressive episodes, appears to be a trigger for stressful events The thinking of self as helpless, interpreting life events negatively, and believing the future to be hopeless are common characteristics of depressive people, which can lead to misinterpretations of daily circumstances 88,143 The past experience of social powerlessness contributes to depressive symptoms through low capacity and inadequate good reinforcement 158 It is known that the positive affectivity and cognitive flexibility are protective factors towards depression.
The better coping skills and high ability to find meaning in difficulties helps individuals to overcome and prevent the relapse of depressive symptoms 59 These theories are the foundation for the new psychotherapeutic approaches such as CBT in depression treatment 3,17
Research shows that various socio-cultural and environmental factors related to depression from family to socio-environmental conditions 59,63,98
Firstly, the impact of family factors towards depressive disorders can be observed from childhood Sexual, emotional, or physical abuse, a dysfunctional upbringing, parental separation or mental illness are the most frequent childhood challenges 55 Not only does it have a negative impact on the psychological development of children, these early exposure to stress relates to cortical circuits and the HPA axis Maternal illness, family conflict or parental stress are common risk factors of depression, respectively 3
Secondly, the role of family is seen as the vulnerable adults with negative familial characteristics Marital status is considered to be an important factor relating to the development of depression in adults Being single, divorced, separated or widowed are common risk factors 4,17 Moreover, the systematic review and meta-analysis emphasized the moderate to strong relationship between intimate partner violence and depression in women, including physical and psychological threats in both short term and long term 159
RESEARCH SUBJECTS AND METHODS 46 2.1 Study subjects
Study time and sites
The study was conducted in 10 selected communes of Thai Nguyen city in Thai Nguyen province including Quyet Thang, Tan Thinh, Thinh Dan, TanLap, Trung Thanh, Gia Sang, Huong Son, Cam Gia, Tich Luong, Phu Xa.
- Time of research: From August 2020 to December 2022.
- Time of intervention: From September 2020 to February 2021.
- Time of follow-up: From March 2021 to March 2022.
- Objective (2): An intervention study, quasi-experimental design (pre- test and post-test studies) with quantitative data.
- Objective (3): A qualitative study including in-depth interviews and group discussions.
Sample size and sampling method
The sample size was calculated using the formula for estimating the sample size in the before-after study: 230
2𝐶 (1 − 𝑟) 𝑛 = (𝐸𝑆)2 In which, n = minimum sample size of the intervention group.
C = 13 is a constant related to type I and type II error with α = 0.05, β 0.05. r = 0.6: the correlation coefficient.
ES = d / s: the effect size with d = 2 (desired mean effect of the intervention) and s = 6.12 (the standard deviation of the PHQ-9 score in the depressed patient group in Vietnam) 123
Thus, the minimum sample size of the intervention group is n = 97.
With the estimated rate of ineligibility and refusal to participate in the intervention group of 40%, our study is expected to recruit at least 162 people(97/0,6 = 161.67) with scores of PHQ-9 ≥ 10 in 10 communes of ThaiNguyen city According to Tran Viet Nghi (2002), the rate of depression in one commune of Thai Nguyen province was 8.35%, so that the minimum pre- screening PHQ-2 population in our study is: N = 162 x 8.35 = 1352.7.
Therefore, the study was expected to screen for depression in at least 1,353 people by using the PHQ-2 In fact, this study approached 1,689 people to screen for depression with the PHQ-2 in the community.
The research team contacted localities and Provincial Psychiatric Hospitals to select 10 communes in Thai Nguyen city that had appropriate and convenient CHSs to organize intervention and monitoring.
The trained collaborators (5 people/commune) randomly came to households and interviewed the eligible people who were present at home.
The selection interviews were conducted with structured paper forms until the sample size reached at least 140-150 subjects/commune.
Randomly selecting 20 subjects who participated in the group intervention (2 people/commune) and contacted in-person (at 3 months) or via mobile-phone (at 12 months follow-up) The researcher eliminated overlapping cases between two interview times.
During the study process, there were 20 CHS staff/10 communes and 6 provincial psychiatrists participating in the screening and group intervention at the CHS In total, 26 medical staff were recruited in the study at baseline.
In the follow-up period, one representative CHS staff/commune and all 6 psychiatrists were invited to join qualitative study However, there was one CHS staff member who was absent because of a personal problem at the specific time of interview Therefore, 15 medical staff (including 9 CHS staff and 6 psychiatrists) participated in group discussions after the intervention.
The detailed description of variables was put on the Appendix 2.
- The outcome or dependent variable was the prevalence of depressive symptoms as measured by the PHQ-2 scale, which was categorized into a binary variable: 'No depression' for scores below 3, and 'Depression' for scores equal or greater than 3.
+ Age: This variable captures the chronological age of the subjects.
+ Sex: This categorical variable is coded as 1 for male and 2 for female subjects.
+ Educational level: This ordinal variable represents the highest level of education attained by the subjects, with categories coded as follows: 1 for Primary School, 2 for Secondary School, 3 for High School, and 4 for College/University.
+ Marital status: The current marital status was classified as 1 for being single/divorced/widowed, and as 2 for being married.
+ Medical insurance: This variable indicates the level of health insurance coverage, with 0 denoting no coverage, 1 for 80% coverage, 2 for 95% coverage, and 3 for 100% coverage.
+ Household income (Viet Nam Dong): This ordinal variable reflects the average monthly income of the entire family over the past 12 months, with categories as follows: 1 for less than 500,000 VND, 2 for 500,000 to less than 2,000,000 VND, 3 for 2,000,000 to less than 5,000,000 VND, 4 for 5,000,000 to less than 10,000,000 VND, and 5 for more than 10,000,000 VND.
The qualitative data included in-depth questions about the personal reasons of participation among group subjects This result explored clearer for quantitative data in objective 1.
- The primary outcomes or dependent variables include:
+ Depression score: Assessed with the Patient Health Questionnaire (PHQ-9), which consists of 9 questions The total score can range from 0 to 36 In the range from 5 and above, higher scores indicated more severe depressive symptoms.
+ Depression reliable improvement/deterioration: An decrease/increase in the PHQ-9 score of at least 6 points from the initial assessment was considered a reliable improvement/deterioration, respectively.
+ Depression recovery: was determined by a reduction of PHQ-9 score at least 50% compared to baseline PHQ-9 scores to be less than the cut-off score of 10.
+ Quality of Life Score: represented by the Quality of Life Enjoyment and Satisfaction Questionnaire Short Form (Q-LES-Q-SF) with 14 questions.
The total score ranges from 0 to 70, with higher scores reflecting better quality of life.
+ Anxiety Score: measured by the Generalized Anxiety Disorder-7 items scale (GAD-7) Scores range from 0 to 21, with higher scores from 5 and above suggesting greater anxiety levels Note: this is not a diagnostic anxiety assessment.
+ Brief Resilient Coping Score: assessed by the Brief Resilient Coping Scale (BRCS) with 4 questions, total score ranges from 4 to 20 Higher scores indicated a more resilient coping capacity.
+ Employment rate: the percentage of the group subjects who had a job at baseline and after 3-, 6-, 12 months of follow-ups.
The qualitative data included in-depth questions about the perceived effectiveness of group intervention in group subjects after 3 months and 12 months This result explained more clearly for quantitative data in objective 2.
Based on previous theoretical frameworks about the acceptability and feasibility of healthcare interventions in public health, this study assessed the following qualitative themes via in-depth interviews and group discussions: 231,232
● The acceptability of community-based group psychological intervention at CHS including:
+ Participatory and Burden: personal motivation and effort to participate, participatory rate of group intervention.
+ Affective attitude, Ethicality, and Intervention Coherence: personal feeling and impression about the intervention, research subjects’ understanding and application of learned skills; required costs and resources to participate in the intervention.
+ Perceived effectiveness and Self-efficacy: intervened subjects’ perceived changed emotion and skills, social network and quality of life; the change of personal awareness about mental health and depression after the intervention.
● The feasibility of community-based group psychological intervention at CHS including:
+ For group subjects: Perceived advantages and benefits of group psychotherapy at CHS (content of intervention, group organization, socio- cultural factors); Barriers and disadvantages of intervention (space, time,group activity, socio-cultural factors); the maintained activities and the need of continuous group intervention in the long term.
+ For primary health care staff: the change of capacity in depression identification and intervention, personal skills; the coordination with provincial specialists.
+ For provincial specialists: the change of personal capacity in community intervention and communication skills, the coordination with primary health care settings in depression intervention.
2.6 Some research assessment criteria in the study
2.6.1 Research measurements for quantitative data:
Statistical analysis
● Quantitative data was collected via paper questionnaires by the program coordinator at baseline and at 3-month, 6-month, and 12-month follow-ups Data was entered using Epi Data v3.1 software and analyzed by SPSS 20.0 software.
- Quantitative variables are tested for standard distribution The normal distribution variable was expressed as mean ± SD.
-Compare between two quantitative variables by Student T test (if normal distribution variable) or Mann-Whitney-U test (if distribution variable is not standard).
-Comparing more than two quantitative variables: if the normal distribution variables and the variances between groups were similar, we used ANOVA to compare the differences of all groups If the variables did not meet the assumptions of the ANOVA variance analysis, the Kruskal-Wallis test was used instead.
-Logistic regression was performed to explore risk factors with subjects screened for depression using that PHQ-2 score.
-Cohen's d was determined by calculating the mean difference between two groups, and then dividing the result by the pooled standard deviation We used the following rule of thumb when interpreting Cohen's d:
+ A value of 0.2 represents a small effect size.
+ A value of 0.5 represents a medium effect size.
+ A value of 0.8 represents a large effect size.
-This study was not suitable for time series analysis for the following reasons Firstly, the most appropriate approach for a quasi-experimental public health intervention study without randomization and no control group was interrupted time series analysis 242 In this analysis, an important assumption was that the pre-intervention trend was linear However, this study had only one pre-intervention assessment that could not replicate the pre-intervention trend, thus violating that assumption 243 Studies also showed that fewer pre- intervention assessments reduced the strength of the model to perform time series models 244 Secondly, the time series analysis estimates have not been controlled for covariates, and there is no comparator against which to adjust the results for changes that should not be attributed to the intervention itself 242 Therefore, we use the generalized estimating equation (GEE) model to evaluate confounding factors that affect intervention effectiveness.
-GEE was used to estimate the parameters of a generalized linear model with a possible unmeasured correlation between observations from different time points The GEE model is well-suited for analyzing outcomes in intervention studies without a control group and involves more than two measurement points A main advantage of employing GEE lies in its robustness in yielding unbiased estimates of population-averaged effects, maintaining accuracy despite potential inaccuracies in the assumed correlation structure among repeated measurements.
-The level of significance was set at p value less than 0.05.
● The qualitative data was recorded and taped during the in-depth interviews and group discussion Thematic analysis was used to identify topics that highlight group subjects and health-care workers' responses to acceptability and feasibility of community intervention, the study subjects' benefit and experience Microsoft Word and Excel software were used to assist with data processing and analysis Qualitative variables were expressed in percentages and compared by the 2 test or Fisher Exact test.
STUDY RESULT 66 3.1 The depression situation and depression-related factors among study subjects
The depressive symptoms among 1,689 people screened in the community67 3.1.2 Several depression-related factors in screening population 71 3.2 The initial effectiveness of the community-based intervention with
Figure 3.2 Distribution of sample based on gender (n=1,689)
Figure 3.2 shows that 86.9% of screened citizens were female (1,468 people) and 13.1% were male (221 people) The ratio of female/male was about 6.6.
Figure 3.3 The distribution of age groups in study subjects (n=1,689)
The average age of the screened population was 50.54 ± 10.75 (Mean ± SD) Figure 3.3 represents that age group of from-50-to-59-year-old accounted for the majority with 37.7%, followed by the age group of 60-69 (accounting for 25%), then the age group of 40-49 (accounting for 19.2%).
There were only 8 subjects under 20 years old, accounting for 0.5%.
Table 3.1 Demographic characteristics of the study population (n = 1,689)
Table 3.1 describes that most subjects were married, had medical insurance, and had the educational level of secondary school and high school.
The study subjects had about 3 family members and monthly household income less than 10,000,000 VND on average.
(a) Using the PHQ-2 cutoff of 2 (b) Using the PHQ-2 cutoff of 3
Figure 3.4 The prevalence of depression according to the PHQ-2.
Screening 1,689 people in the community for depressive symptoms with the PHQ-2 scale, it found that 720 people were at risk of depression, which accounted for 43% with a cutoff of 3 (Figure 3.2b); and this figure was 92% with the cutoff of 2 (n = 1,552/1,689) (Figure 3.2a) In general, the cutoff score of 2 in the PHQ-2 with higher sensitivity was suitable for public screening in the community However, to assess the depression rate with related factors, we used a cutoff score of 3 in the PHQ-2 with higher specificity.
3.1.2 Several depression-related factors in screening population (n=1,689)
Table 3.2 The demographic characteristics of screening population according to the PHQ-2 scale with the cutoff score of 3
High school or less 808 (58.0%) 586 (42.0%) 1394 (100.0%) College/University 161 (54.6%) 134 (45.4%) 295 (100.0%)
The prevalence of depression in people over 50 years old was higher when compared to people under 50 years old (36.3% and 46.4% respectively).
This difference was statistically significant with p-values less than 0.05.
Table 3.3 The association between demographic characteristics and depression in study subjects (n=1,689)
Primary school Secondary school High school College/University
Table 3.3 shows the result of logistic regression models exploring the association between depression and risk factors Individuals aged over 50 were
1.75 times as likely to exhibit symptoms of depression compared to those under50 Besides, the study subjects having 100% coverage of medical insurance were more than two times more likely to suffer from depression than those having no medical insurance In addition, people having average household income more than 10 million VND were at a 50% reduced likelihood of experiencing depressive symptoms compared to those earning less than 500,000 VND.
3.2 The initial effectiveness of the community-based intervention with Stepped Care Model for depression in Thai Nguyen (n56)
Among 427 people having a PHQ-9 score of 10 or higher, 382 eligible people were invited to the group intervention at the CHS In which, 359 individuals agreed to join the group intervention at CHS and were interviewed for data collection at the baseline At 3 months, 6 months, and 12 months after the intervention, researchers and local collaborators contacted to invite research subjects to go to the CHS for re-evaluating and data gathering If the research subjects refused to participate, their information was stored for further contact by health workers in the locality As a result, 3 subjects did not participate in data collection after the intervention for personal reasons.
(Figure 3.5) No adverse events were recorded during the intervention and follow-ups.
Table 3.4 Demographic characteristics of the intervention group (n = 356)
Most intervention subjects were female (93.54%), and the average age was 55.1 years old Most of them completed secondary school or higher (92.98%) The number of married individuals accounted for more than 70% of the intervention population.
The effectiveness of the group intervention in terms of depressive
Figure 3.5 Distribution of depression severity over follow-up time.
At baseline, most subjects predominantly exhibited moderate to severe depressive symptoms, with moderate levels of approximately 75% After 3 months, a significant shift was observed with the vast majority of study subjects showing either an absence of symptoms or only mild symptoms remained Notably, moderate-to-moderately-severe-symptom group persisted in nearly 10% of subjects After 12 months, over 80% of study subjects were seen without depressive symptoms It is noteworthy that moderate-to-severe- symptom groups were confined to a mere 4 individuals, constituting 1.2% of the intervention population.
Figure 3.6 The change of average PHQ-9 scores at baseline and 3 months, 6 months, and 12 months after intervention (n56)
Overall, the mean score of PHQ-9 decreased significantly between the time before and after the intervention, and there was a gradual decline of this figure over 12 months of follow-up after the intervention In particular, after three months of follow-up, PHQ-9 scores reduced dramatically from an average of 13.29 points before the intervention to an average of 4.96 points.
At the 12- month follow-up, the mean PHQ-9 score dramatically decreased to2.83, equivalent to a nearly five times reduction.
Table 3.5 The change of PHQ-9 scores at baseline compared to the time at 3 months, 6 months, 12 months after the intervention (n56)
PHQ-9 scores Baseline After intervention
Pre-post effect size (Cohen's d) p- value
After three months, the average PHQ-9 score of the study subjects decreased significantly from 13.29 to 4.96, then continued to decline to 3.55 points at the six-month follow-up with an effect size of 3.09 After 12 months, the intervention helped the mean depressive score reduce by 10.45 points.
Table 3.6 The change of depression severity based on the PHQ-9 score at baseline compared to the time of 3-, 6-, 12-months follow-up (n56)
Depression severity based on PHQ-9 score
Before the intervention, all subjects had moderate-to-severe depression, this rate decreased to less than 10% at the point of 3 months after the end of the intervention, and decreased to less than 4% after 12 months At 12 months post- intervention, the majority of patients had returned to the depression-free level In the cases which remained depressive symptoms, most were mild The differences in depression levels at 3-, 6-, and 12 months after the intervention compared to the baseline were statistically significant (p < 0.001).
Table 3.7 Patient's response at 3-, 6-, 12 months after intervention (n56)
After 3 months After 6 months After 12 months n (%) n (%) n (%)
Table 3.7 illustrated the significant response of depressive individuals after the intervention up to one year follow-up At the point of three months after the intervention completion, more than 90% of patients recovered (at least a 50% reduction in baseline PHQ-9 scores), and 75% of study subjects had at least 6 point decline on the PHQ-9 (defined as reliable improvement).
These figures even improved over time of 1-year follow-up with ninety-six percent of study subjects recovered and 90% had reliable amelioration in depressive symptoms.
Table 3.8 Linear regression comparing intervention effect on PHQ-9 score at each time point of follow-up
Pairwise comparison of regression coefficients Coef p-value 95% CI
Table 3.8 demonstrated the results of a univariate linear regression model analyzing the efficacy of each follow-up time point after the intervention The 12-month follow-up period demonstrated the most remarkable intervention efficacy, with an average decrease in PHQ-9 scores of 10.461 points This result is statistically significant with p < 0.001.
Table 3.9 The generalized estimating equation regression model estimating the intervention effectiveness according to the PHQ-9 score
After adjusting for scores of GAD-7, Q-LES-Q-SF, and BRCS, the 12- month follow-up period was associated with the most significant decline inPHQ-9 scores, with an average decrease of 5.87 points.
Table 3.10 The generalized estimating equation regression model estimating the intervention effectiveness according to the PHQ-9 score (Adjusted for demographics)
The generalized estimating equation model, after adjusting for several factors, showed that the mean PHQ-9 score dropped by an average of 4.864,5.313, and 5.811 points at the point of 3-,6-,12-month follow-up, respectively.
3.2.2 The effectiveness of the group intervention in terms of anxiety symptoms, quality of life, and coping skills
Table 3.11 The change of GAD-7 scores at baseline compared to the time at 3-, 6-, 12- months after the intervention (n56)
GAD-7 scores Baseline After intervention
Pre-post effect size (Cohen's d) p- value
Table 3.11 demonstrates the effectiveness of the intervention in reducing GAD-7 scores over a 12-month period At baseline, the mean PHQ-9 score was 9.40, which significantly decreased post-intervention across all time points measured At 3 months, the mean score was reduced by 5.81 points, with a large effect size (Cohen's d = -1.42), indicating a substantial clinical improvement This trend continued at 6 and 12 months, with mean reductions of 7.26 and 8.0 points, respectively, and correspondingly larger effect sizes of -1.90 and -2.21 The p-values for all time points were less than0.001, underscoring the statistical significance of the findings.
Table 3.12 The change of quality of life at baseline compared to the time at at 3-, 6-, 12- months after the intervention (n56)
Q-LES-Q- SF scores Baseline After intervention
Pre-post effect size (Cohen's d) p- value
Table 3.12 provides results of the intervention's effect on Quality of Life Scale (Q-LES-Q-SF) scores at 3, 6, and 12 months post-intervention It is observed that the mean pre-intervention score was static at 31.99 (SD=5.27).
Post-intervention measurements indicate a progressive improvement in quality of life scores, with mean differences of 10.04, 10.38, and 20.97 at 3, 6,and 12 months respectively The effect size, denoted by Cohen's d, suggests a substantial increase from 1.42 at 3 months to 2.10 at 12 months, with all intervals showing statistical significance (p 90% and 96% at 12 months follow-up, respectively These changes were statistically significant after the adjustment for demographic characteristics No adverse effect was observed.
Following 12 months, the anxiety symptoms (GAD-7 score), coping skills (BRCS score), and quality of life (Q-LES-Q-SF score) were noticeably better The employment rate remarkably improved from 50% to 59% even during the pandemic.
3 The acceptability and feasibility of the community-based intervention with Stepped Care Model for adult depression in Thai Nguyen
The qualitative results suggested promising acceptability of group intervention in depressed adults with an agreement rate of nearly 94%.
Research subjects reported various personal benefits such as improved emotions and skills, more positive social network, and better quality of life.
The pleasurable group activities were noted to be most memorable to members up to 12 months after intervention The awareness about mental health and depression also enhanced in general.
The group psychological intervention led by CHS staff was feasible for both health care staff and citizens The in-depth interviews revealed many advantages in facilities and community, content of interventions, convenience and no cost, family support, and legality Some described disadvantages were the lack of space and time, difficulties in group gathering and running, and limited experience of primary staff The group intervention was acknowledged in capacity building for both health care providers at the primary and provincial levels, and strengthening the coordination between central and local systems Most research subjects believed in the possibility of group maintenance and expressed the desire to have more community intervention for mental health problems in the future.
1 All mental health care systems in Vietnam need to have more cost- effective approaches focusing on broader communication and screening activities in depression management, particularly vulnerable populations, such as people with old age, chronic diseases, and low socioeconomic status.
2 The researchers and research organizations in both mental health and public health need to conduct more multi-site evidence-based studies with control groups and long-term follow-up of the Full Stepped Care Model to comprehensively evaluate the effectiveness, cost-effectiveness, and feasibility of this model in depression care in the future.
3 Policy makers and stakeholders involved in implementing community mental health care need collaboration programs and policy changes to implement and scale up this model with practical psychosocial intervention led by trained non-specialists under the specialists’ supervision to more provinces in Vietnam, especially in limited-resource areas.
1 Mathers C, Fat DM, Boerma JT, eds The Global Burden of Disease:
2 Mental health in Viet Nam Accessed March 22, 2024. https://www.who.int/vietnam/health-topics/mental-health 3 John R.Geddes, Nancy C.Andreasen, Guy M.Goodwin New Oxford
Textbook of Psychiatry 3rd edition Oxford University Press; 2020.
4 Kửhler CA, Evangelou E, Stubbs B, et al Mapping risk factors for depression across the lifespan: An umbrella review of evidence from meta-analyses and Mendelian randomization studies J Psychiatr Res.
2018;103:189-207 doi:10.1016/j.jpsychires.2018.05.020 5 Thornicroft G, Chatterji S, Evans-Lacko S, et al Undertreatment of people with major depressive disorder in 21 countries Br J Psychiatry.
2017;210(2):119-124 doi:10.1192/bjp.bp.116.188078 6 Chris Underhill, Victoria K,Ngo, Tam Nguyen Mental health and economic development in Vietnam In: The Routledge Handbook of
International Development, Mental Health and Wellbeing 1st ed.
7 National Collaborating Centre for Mental Health (UK) Depression: The
Treatment and Management of Depression in Adults (Updated Edition).
British Psychological Society; 2010 Accessed October 23, 2020 http:// www.ncbi.nlm.nih.gov/books/NBK63748/
8 Kohrt BA, Asher L, Bhardwaj A, et al The Role of Communities in Mental Health Care in Low- and Middle-Income Countries: A Meta- Review of Components and Competencies Int J Environ Res Public
9 Singla DR, Kohrt BA, Patel Psychological Treatments for the World:
Lessons from Low- and Middle-Income Countries Annu Rev Clin
Psychol 2017;13(Volume 13, 2017):149-181 doi:10.1146/annurev- clinpsy-032816-045217 10 van Straten A, Hill J, Cuijpers P Stepped care treatment delivery for depression: a systematic review and meta-analysis Psychol Med.
2015;45(2):231-246 doi:10.1017/S0033291714000701 11 World Federation for Mental Health Depression: A Global Crisis World
Mental Health Day, October 10 2012 Published 2012 Accessed September 12, 2021 https://w ww.who.in t/mental_ health/m anagement/ depression/wfmh_paper_depression_wmhd_2012.pdf 12 Ngo VK, Weiss B, Lam T The Vietnam Multicomponent Collaborative
Care for Depression Program: Development of Depression Care for Low- and Middle-Income Nations J Cogn Psychother 2014;28(3):156- 167.
13 Richards DA Stepped Care: A Method to Deliver Increased Access to Psychological Therapies Can J Psychiatry 2012;57(4):210-215. doi:10.1177/070674371205700403 14 Bower P, Gilbody S Stepped care in psychological therapies: access, effectiveness and efficiency: Narrative literature review Br J Psychiatry.
2005;186(1):11-17 doi:10.1192/bjp.186.1.11 15 Andrews G, World Health Organization Collaborating Centre for
Classification in Mental Health Tolkien II: A Needs-Based, Costed,
Stepped-Care Model for Mental Health Services : Recommendations, Executive Summaries, Clinical Pathways, Treatment Flowcharts, Costing Structures World Health Organization Collaborating Centre for
16 Spijker J, Vliet I, Balkom A Update of the multidisciplinary guidelines for anxiety and depression Tijdschr Voor Psychiatr 2010;52:715-718.
17 Benjamin James Sadock, Virginia Alcott Sadock, Pedro Ruiz Mood disorders In: Kaplan and Sadock’s Comprehensive Textbook of
Psychiatry Vol 1 10th edition Wolters Kluwer Health, Lippincott
18 Parikh SV, Quilty LC, Ravitz P, et al Canadian Network for Mood and Anxiety Treatments (CANMAT) 2016 Clinical Guidelines for the Management of Adults with Major Depressive Disorder: Section 2.
Psychological Treatments Can J Psychiatry Rev Can Psychiatr.
2016;61(9):524-539 doi:10.1177/0706743716659418 19 Levis B, Yan XW, Thombs B,D et al Comparison of depression prevalence estimates in meta-analyses based on screening tools and rating scales versus diagnostic interviews: a meta-research review BMC
20 Lim GY, Tam WW, Ho Roger C et al Prevalence of Depression in the Community from 30 Countries between 1994 and 2014 Sci Rep.
2018;8(1):2861 doi:10.1038/s41598-018-21243-x 21 Moreno-Agostino D, Wu YT, Prina Matthew et al Global trends in the prevalence and incidence of depression:a systematic review and meta- analysis J Affect Disord 2021;281:235-243 doi:10.10 16/j.ja 2020.
12.035 22 American Psychiatric Association, ed Depressive Disorders In:
Diagnostic and Statistical Manual of Mental Disorders: DSM-5 5th ed.
23 Wang JN, Sun W, Wang Lie et al Prevalence and associated factors of depressive symptoms among Chinese doctors: a cross-sectional survey.
Int Arch Occup Env Health 2010;83(8):905-911 doi:10.1007/s00420-
24 Kim K, Lee S, Choi YH Relationship between occupational stress and depressive mood among interns and residents in a tertiary hospital, Seoul, Korea Clin Exp Emerg Med 2015;2(2):117-122 doi:10.1 5441/ce em.15.002
25 Desouky D, Allam H Occupational stress, anxiety and depression among Egyptian teachers J Epidemiol Glob Health 2017;7(3):191-198. doi:10.1016/j.jegh.2017.06.002 26 Wulsin L, Alterman T, Shen Rui et al Prevalence rates for depression by industry: a claims database analysis Soc Psychiatry Psychiatr Epidemiol 2014;49(11):1805-1821 doi:10.1007/s00127-014-0891-3