RESUMO
BACKGROUND: Identifying individuals with depressive symptomatology (DS) promptly and effectively is of paramount importance for providing timely treatment. Machine learning models have shown promise in this area; however, studies often fall short in demonstrating the practical benefits of using these models and fail to provide tangible real-world applications. OBJECTIVE: This study aims to establish a novel methodology for identifying individuals likely to exhibit DS, identify the most influential features in a more explainable way via probabilistic measures, and propose tools that can be used in real-world applications. METHODS: The study used 3 data sets: PROACTIVE, the Brazilian National Health Survey (Pesquisa Nacional de Saúde [PNS]) 2013, and PNS 2019, comprising sociodemographic and health-related features. A Bayesian network was used for feature selection. Selected features were then used to train machine learning models to predict DS, operationalized as a score of ≥10 on the 9-item Patient Health Questionnaire. The study also analyzed the impact of varying sensitivity rates on the reduction of screening interviews compared to a random approach. RESULTS: The methodology allows the users to make an informed trade-off among sensitivity, specificity, and a reduction in the number of interviews. At the thresholds of 0.444, 0.412, and 0.472, determined by maximizing the Youden index, the models achieved sensitivities of 0.717, 0.741, and 0.718, and specificities of 0.644, 0.737, and 0.766 for PROACTIVE, PNS 2013, and PNS 2019, respectively. The area under the receiver operating characteristic curve was 0.736, 0.801, and 0.809 for these 3 data sets, respectively. For the PROACTIVE data set, the most influential features identified were postural balance, shortness of breath, and how old people feel they are. In the PNS 2013 data set, the features were the ability to do usual activities, chest pain, sleep problems, and chronic back problems. The PNS 2019 data set shared 3 of the most influential features with the PNS 2013 data set. However, the difference was the replacement of chronic back problems with verbal abuse. It is important to note that the features contained in the PNS data sets differ from those found in the PROACTIVE data set. An empirical analysis demonstrated that using the proposed model led to a potential reduction in screening interviews of up to 52% while maintaining a sensitivity of 0.80. CONCLUSIONS: This study developed a novel methodology for identifying individuals with DS, demonstrating the utility of using Bayesian networks to identify the most significant features. Moreover, this approach has the potential to substantially reduce the number of screening interviews while maintaining high sensitivity, thereby facilitating improved early identification and intervention strategies for individuals experiencing DS.
Assuntos
Algoritmos , Teorema de Bayes , Depressão , Humanos , Depressão/diagnóstico , Adulto , Feminino , Masculino , Brasil/epidemiologia , Pessoa de Meia-Idade , Aprendizado de Máquina , Programas de Rastreamento/métodos , Sensibilidade e Especificidade , Inquéritos EpidemiológicosRESUMO
OBJECTIVES: Depression is a prevalent mental health condition that also often affects older adults. The PROACTIVE psychosocial intervention was developed to reduce depressive symptomatology among older adults within primary care settings in Brazil. An important psychological marker that affects individuals' aging experience relates to how old people feel. Known as subjective age, this marker has been shown to be a risk factor for experiencing greater depressive symptoms if individuals report feeling older than their (chronological) age. In this study, we perform secondary analyses of the PROACTIVE cluster-randomized controlled trial to examine the role of subjective age. METHOD: The sample included 715 Brazilian older adults (74% female, Mage 68.6, SD = 6.9, age range: 60-94 years) randomized to intervention (n = 360, 74% female, Mage 68.4, SD = 6.6, age range: 60-89 years) or control (n = 355, 74% female, Mage 68.9, SD = 7.2, age range: 60-94 years) arms. Here our primary outcome was depressive symptoms at the 8-month follow-up assessed with the 9-item Patient Health Questionnaire (PHQ-9) as a continuous variable. Our previous analyses demonstrated improved recovery from depression at follow-up in the intervention compared with the control arm. RESULTS: Relevant main effects and interactions in regression models for PHQ-9 presented here found that those reporting older subjective age had worse depressive symptoms at follow-up but that they benefitted more from the intervention when initial levels of depression were high. For participants who reported younger subjective ages the intervention showed positive effects that were independent of initial levels of depression. CONCLUSION: Our findings emphasize the importance of investigating possible underlying mechanisms that can help clarify the impact of mental health interventions.
Assuntos
Depressão , Intervenção Psicossocial , Humanos , Idoso , Feminino , Masculino , Brasil , Idoso de 80 Anos ou mais , Pessoa de Meia-Idade , Depressão/terapia , Depressão/psicologia , Intervenção Psicossocial/métodos , Envelhecimento/psicologiaRESUMO
Scalable solutions to treat depression in older adults in low-resourced settings are urgently needed. The PRODIGITAL-D pragmatic, single-blind, two-arm, individually randomized controlled trial assessed the effectiveness of a mobile messaging psychosocial intervention in improving depressive symptomatology among older adults in socioeconomically deprived areas of Guarulhos, Brazil. Older adults (aged 60+ years) registered with 24 primary care clinics and identified with depressive symptomatology (9-item Patient Health Questionnaire (PHQ-9) scores ≥ 10) received the 6-week Viva Vida intervention based on psychoeducation and behavioral activation (n = 298) or a single message (n = 305). No health professional support was offered. The primary outcome was improvement from depressive symptomatology (PHQ-9 < 10) at 3 months. Of the 603 participants enrolled (mean age = 65.1 years; 451 (74.8%) women), 527 (87.4%) completed the follow-up assessment. In the intervention arm, 109 of 257 (42.4%) participants had an improved depressive symptomatology, compared with 87 of 270 (32.2%) participants in the control arm (adjusted odds ratio = 1.57; 95% confidence interval = 1.07-2.29; P = 0.019). No severe adverse events related to trial participation were observed. These results demonstrate the usefulness of a digital messaging psychosocial intervention in the short-term improvement from depressive symptomatology that can potentially be integrated into primary care programs for treating older adults with depression. Brazilian Registry of Clinical Trials registration: ReBEC ( RBR-4c94dtn ).
Assuntos
Depressão , Humanos , Feminino , Idoso , Masculino , Depressão/terapia , Método Simples-Cego , BrasilRESUMO
BACKGROUND: There is an urgent need to reduce the burden of depression among older adults in low-income and middle-income countries (LMICs). We aimed to evaluate the efficacy of a task-shared, collaborative care psychosocial intervention for improving recovery from depression in older adults in Brazil. METHODS: PROACTIVE was a pragmatic, two-arm, parallel-group, cluster-randomised controlled trial conducted in Guarulhos, Brazil. Primary care clinics (clusters) were stratified by educational level and randomly allocated (1:1) to either enhanced usual care alone (control group) or to enhanced usual care plus the psychosocial intervention (intervention group), which involved a 17-week psychosocial programme based on psychoeducation and behavioural activation approaches. Individuals approached for the initial screening assessment were selected randomly from a list of individuals provided by the Health Secretariat of Guarulhos. Face-to-face baseline assessments were conducted among adults aged 60 years or older registered with one of the primary care clinics and identified with clinically significant depressive symptomatology (9-item Patient Health Questionnaire [PHQ-9] score ≥10). Community health workers delivered the programme through home sessions, supported by a dedicated tablet application. Masking of clinic staff and community health workers who delivered the intervention was not feasible; however, research assistants conducting recruitment and follow-up assessments were masked to trial allocation. The primary outcome was recovery from depression (PHQ-9 score <10) at 8-month follow-up. All primary analyses were performed by intention to treat with imputed data. Adaptations to the protocol were made due to the COVID-19 pandemic; recruitment and intervention home sessions were stopped, and follow-up assessments were conducted by telephone. This trial is registered with the ISRCTN registry, ISRCTN57805470. FINDINGS: We identified 24 primary care clinics in Guarulhos that were willing to participate, of which 20 were randomly allocated to either the control group (ten [50%] clusters) or to the intervention group (ten [50%] clusters). The four remaining eligible clusters were kept as reserves. Between May 23, 2019, and Feb 21, 2020, 8146 individuals were assessed for eligibility, of whom 715 (8·8%) participants were recruited: 355 (49·7%) in the control group and 360 (50·3%) in the intervention group. 284 (80·0%) participants in the control group and 253 (70·3%) in the intervention group completed follow-up at 8 months. At 8-month follow-up, 158 (62·5%) participants in the intervention group showed recovery from depression (PHQ-9 score <10) compared with 125 (44·0%) in the control group (adjusted odds ratio 2·16 [95% CI 1·47-3·18]; p<0·0001). These findings were maintained in the complete case analysis. No adverse events related to the intervention were observed. INTERPRETATION: Although the COVID-19 pandemic altered delivery of the intervention, the low-intensity psychosocial intervention delivered mainly by non-mental health professionals was highly efficacious in improving recovery from depression in older adults in Brazil. Our results support a low-resource intervention that could be useful to reduce the treatment gap for depression among older people in other LMICs. FUNDING: São Paulo Research Foundation and Joint Global Health Trials (UK Department for International Development, Medical Research Council, and the Wellcome Trust).
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COVID-19 , Intervenção Psicossocial , Idoso , Brasil/epidemiologia , Humanos , Pandemias , Resultado do TratamentoRESUMO
BACKGROUND: Depression in older adults is a challenge for health systems in most low- and middle-income countries (LMICs). Digital strategies for the management of this condition have been emerging worldwide, but the effectiveness of most of them is still unclear, especially among older adults. Thus, we aim to assess the effectiveness and cost-effectiveness of a digital psychosocial intervention to treat depression among older adults living in socioeconomically deprived areas in Guarulhos, Brazil. METHODS: We will conduct a two-arm individually randomised controlled trial with 1:1 allocation ratio. Five hundred older adults aged 60 years or over with depressive symptomatology (9-item Patient Health Questionnaire score, PHQ-9 ≥ 10) and registered with one of the primary care clinics will be recruited to participate in this study. A 6-week digital psychosocial programme, named Viva Vida, will be delivered via WhatsApp to participants allocated to the intervention arm. The Viva Vida will send psychoeducational and behavioural activation audio and visual messages 4 days a week for 6 weeks. The control arm will only receive a single message with general information about depression. The primary outcome will be the proportion of depression recovery (PHQ-9 < 10) assessed at 3 months. The cost-effectiveness of the intervention will be assessed at 5 months. A detailed process evaluation will be used to explore context and important implementation outcomes. DISCUSSION: This programme was based on the PROACTIVE intervention and designed to be delivered without face-to-face contact. If effective, it could be a simple treatment option, appropriate not only when social distancing is required, but it could also be included as a regular public health programme to initiate depression treatment, particularly in LMICs where resources allocated to mental health are scarce. TRIAL REGISTRATION: Registro Brasileiro de Ensaios Clínicos (ReBEC), RBR-4c94dtn. Registered on 22 October 2021 (submitted on 03 August 2021).
Assuntos
Depressão , Intervenção Psicossocial , Idoso , Brasil , Depressão/diagnóstico , Depressão/psicologia , Depressão/terapia , Humanos , Saúde Mental , Ensaios Clínicos Controlados Aleatórios como Assunto , Resultado do TratamentoRESUMO
BACKGROUND: Mental disorders are normally diagnosed exclusively on the basis of symptoms, which are identified from patients' interviews and self-reported experiences. To make mental health diagnoses and monitoring more objective, different solutions have been proposed such as digital phenotyping of mental health (DPMH), which can expand the ability to identify and monitor health conditions based on the interactions of people with digital technologies. OBJECTIVE: This article aims to identify and characterize the sensing applications and public data sets for DPMH from a technical perspective. METHODS: We performed a systematic review of scientific literature and data sets. We searched 8 digital libraries and 20 data set repositories to find results that met the selection criteria. We conducted a data extraction process from the selected articles and data sets. For this purpose, a form was designed to extract relevant information, thus enabling us to answer the research questions and identify open issues and research trends. RESULTS: A total of 31 sensing apps and 8 data sets were identified and reviewed. Sensing apps explore different context data sources (eg, positioning, inertial, ambient) to support DPMH studies. These apps are designed to analyze and process collected data to classify (n=11) and predict (n=6) mental states/disorders, and also to investigate existing correlations between context data and mental states/disorders (n=6). Moreover, general-purpose sensing apps are developed to focus only on contextual data collection (n=9). The reviewed data sets contain context data that model different aspects of human behavior, such as sociability, mood, physical activity, sleep, with some also being multimodal. CONCLUSIONS: This systematic review provides in-depth analysis regarding solutions for DPMH. Results show growth in proposals for DPMH sensing apps in recent years, as opposed to a scarcity of public data sets. The review shows that there are features that can be measured on smart devices that can act as proxies for mental status and well-being; however, it should be noted that the combined evidence for high-quality features for mental states remains limited. DPMH presents a great perspective for future research, mainly to reach the needed maturity for applications in clinical settings.
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Transtornos Mentais , Aplicativos Móveis , Humanos , Transtornos Mentais/diagnóstico , Saúde MentalRESUMO
Depressive and subthreshold depressive symptomatology are common but often neglected in older adults. OBJECTIVE: This study aimed to assess rates of depressive and subthreshold depressive symptomatology, and the characteristics associated, among older adults living in a socioeconomically deprived area of Brazil. METHODS: This study is part of the PROACTIVE cluster randomised controlled trial. 3356 adults aged 60+ years and registered in 20 primary health clinics were screened for depressive symptomatology with the Patient Health Questionnaire-9 (PHQ-9). Depressive status was classified according to the total PHQ-9 score and the presence of core depressive symptoms (depressed mood and anhedonia) as follows: no depressive symptomatology (PHQ-9 score 0-4, or 5-9 but with no core depressive symptom); subthreshold depressive symptomatology (PHQ-9 score 5-9 and at least one core depressive symptom); and depressive symptomatology (PHQ-9 score ≥ 10). Sociodemographic information and self-reported chronic conditions were collected. Relative risk ratios and 95% CIs were obtained using a multinomial regression model. RESULTS: Depressive and subthreshold depressive symptomatology were present in 30% and 14% of the screened sample. Depressive symptomatology was associated with female gender, low socioeconomic conditions and presence of chronic conditions, whereas subthreshold depressive symptomatology was only associated with female gender and having hypertension. CONCLUSIONS: Depressive and subthreshold depressive symptomatology is highly prevalent in this population registered with primary care clinics. Strategies managed by primary care non-mental health specialists can be a first step for improving this alarming and neglected situation among older adults.
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Depressão , Questionário de Saúde do Paciente , Idoso , Brasil/epidemiologia , Depressão/psicologia , Feminino , Humanos , Razão de Chances , AutorrelatoRESUMO
BACKGROUND: Depression is a common condition in older adults, being often detected and treated initially in primary care. Collaborative care models including, for example, task-shifting and stepped-care approaches have been investigated to overcome the current scarcity of strategies and trained mental health professionals to treat depression. The PROACTIVE study developed a psychosocial intervention, which makes extensive use of technology in an intervention delivered mainly by non-specialists to treat older adults with depression. The aim of this qualitative study is to assess: 1. Health workers' fidelity to the intervention protocol; 2. Acceptability of the psychosocial intervention from the viewpoint of older adult participants; and 3. Perceptions of the psychosocial intervention by the health workers. METHODS: Qualitative methods were used to achieve our aims. The sample included participants (N = 31) receiving the intervention in the pilot trial and health workers (N = 11) working in a Basic Health Unit in the northern area of São Paulo, Brazil. Focus group, non-participant observation and structured interviews were used. Data were analysed using a thematic analysis approach. RESULTS: 1. Health workers' fidelity to the intervention protocol: training, supervision and the structured intervention were crucial and guaranteed health workers' fidelity to the protocol. 2. Acceptability of the psychosocial intervention from the viewpoint of older adult participants: Collaborative care, task-shifting, and stepped-care approaches were well accepted. The structured protocol of the intervention including different activities and videos was important to adherence of older adult participants 3. Perceptions of the psychosocial intervention by the health workers: It was feasible to have the home psychosocial sessions conducted by health workers, who are non-mental health specialists and received 3-day training. Training and supervision were perceived as crucial to support health workers before and during the intervention. Technology served as a tool to structure the sessions, obtain and store patient data, present multi-media content, guarantee fidelity to the protocol and facilitate communication among members of the team. However, extra burden was mentioned by the health workers indicating the need of adjustments in their daily duties. CONCLUSIONS: The PROACTIVE intervention was demonstrated to be feasible and accepted by both health workers and older adult participants. The qualitative assessments suggested improvements in training and supervision to ensure fidelity to protocol. To assess effectiveness a randomised controlled trial of the intervention will be conducted with the addition of improvements suggested by this qualitative study. TRIAL REGISTRATION: The pilot study of which the present study gives support to was registered at the Brazilian Clinical Trials, UTN code: U1111-1218-6717 on 26/09/2018.
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Depressão , Intervenção Psicossocial , Idoso , Brasil , Depressão/psicologia , Depressão/terapia , Humanos , Projetos Piloto , Pesquisa QualitativaRESUMO
BACKGROUND: The elderly population has been growing in most low- and middle-income countries (LMIC), and depression is a common condition among these populations. The lack of integration between mental health and primary healthcare services and the shortage of mental health specialists in the public health system contribute to underdiagnosis and undertreatment of depression. One of the strategies to reduce this gap is task shifting and collaborative care treatments. This study therefore aims to evaluate the effectiveness and cost-effectiveness of a collaborative care psychosocial intervention to improve the clinical management of depression among elderly people in poor neighbourhoods in Guarulhos, Brazil. METHODS: Two-arm, cluster randomised controlled trial with Basic Health Units as the clusters and a 1:1 allocation ratio. Twenty Basic Health Units have been randomly selected and randomised to control or intervention arms. We aim to recruit 1440 adults (72 per cluster) aged 60 years or over identified with depression (9-item Patient Health Questionnaire (PHQ-9) score ≥ 10). The control arm participants will receive an enhanced usual care, while the intervention arm participants will receive an enhanced usual care and a 17-week psychosocial intervention programme delivered at home by community health workers with the help of an application installed on tablet computers. The primary outcome is the proportion with depression recovery (PHQ-9 < 10) at 8 months' follow-up. We will also assess the maintenance of any earlier clinical gains and the cost-effectiveness of the intervention at 12 months. DISCUSSION: This is the first randomised trial to investigate a collaborative care intervention to treat depression among poor elderly in LMIC/Latin America. This is a major public health problem worldwide, but in these countries, there are no locally tested, evidence-based interventions available to date. TRIAL REGISTRATION: International Standard Randomised Controlled Trial Number ISRCTN57805470 . Registered on 25 April 2019.