Self-Administered Interventions Based on Natural Language Processing Models for Reducing Depressive and Anxiety Symptoms: Systematic Review and Meta-Analysis.

BACKGROUND: The introduction of natural language processing (NLP) technologies has significantly enhanced the potential of self-administered interventions for treating anxiety and depression by improving human-computer interactions. Although these advances, particularly in complex models such as generative artificial intelligence (AI), are highly promising, robust evidence validating the effectiveness of the interventions remains sparse. OBJECTIVE: The aim of this study was to determine whether self-administered interventions based on NLP models can reduce depressive and anxiety symptoms. METHODS: We conducted a systematic review and meta-analysis. We searched Web of Science, Scopus, MEDLINE, PsycINFO, IEEE Xplore, Embase, and Cochrane Library from inception to November 3, 2023. We included studies with participants of any age diagnosed with depression or anxiety through professional consultation or validated psychometric instruments. Interventions had to be self-administered and based on NLP models, with passive or active comparators. Outcomes measured included depressive and anxiety symptom scores. We included randomized controlled trials and quasi-experimental studies but excluded narrative, systematic, and scoping reviews. Data extraction was performed independently by pairs of authors using a predefined form. Meta-analysis was conducted using standardized mean differences (SMDs) and random effects models to account for heterogeneity. RESULTS: In all, 21 articles were selected for review, of which 76% (16/21) were included in the meta-analysis for each outcome. Most of the studies (16/21, 76%) were recent (2020-2023), with interventions being mostly AI-based NLP models (11/21, 52%); most (19/21, 90%) delivered some form of therapy (primarily cognitive behavioral therapy: 16/19, 84%). The overall meta-analysis showed that self-administered interventions based on NLP models were significantly more effective in reducing both depressive (SMD 0.819, 95% CI 0.389-1.250; P<.001) and anxiety (SMD 0.272, 95% CI 0.116-0.428; P=.001) symptoms compared to various control conditions. Subgroup analysis indicated that AI-based NLP models were effective in reducing depressive symptoms (SMD 0.821, 95% CI 0.207-1.436; P<.001) compared to pooled control conditions. Rule-based NLP models showed effectiveness in reducing both depressive (SMD 0.854, 95% CI 0.172-1.537; P=.01) and anxiety (SMD 0.347, 95% CI 0.116-0.578; P=.003) symptoms. The meta-regression showed no significant association between participants' mean age and treatment outcomes (all P>.05). Although the findings were positive, the overall certainty of evidence was very low, mainly due to a high risk of bias, heterogeneity, and potential publication bias. CONCLUSIONS: Our findings support the effectiveness of self-administered NLP-based interventions in alleviating depressive and anxiety symptoms, highlighting their potential to increase accessibility to, and reduce costs in, mental health care. Although the results were encouraging, the certainty of evidence was low, underscoring the need for further high-quality randomized controlled trials and studies examining implementation and usability. These interventions could become valuable components of public health strategies to address mental health issues. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42023472120; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023472120.

In-Person and Teleconsultation Services at a National Hospital in Peru: Time Series Analysis of General and Psychiatric Care Amid the COVID-19 Pandemic.

BACKGROUND: The COVID-19 pandemic led to a global reduction in health care accessibility for both infected and noninfected patients, posing a particular burden on those with chronic conditions, including mental health issues. Peru experienced significant devastation from the pandemic, resulting in a collapsed health care system and leading to the world's highest per capita mortality rate as a result of COVID-19. Understanding the trends in health care utilization, particularly in mental health care, is crucial for informing pandemic response efforts and guiding future recovery strategies. OBJECTIVE: This study aims to analyze the trends of outpatient medical and psychiatric consultations during the COVID-19 pandemic in a national hospital in Peru. METHODS: This observational study was conducted at a national hospital in Lima, Peru. We analyzed data on user care across all services, including psychiatric services, from May 2019 to December 2022. The data were calculated for users served per month, including the number of users seen monthly in mental health services. Sociodemographic variables such as sex (female or male), age (≥0 years), type of medical appointment (regular or additional), and modality of care (in-person or teleconsultations) were taken into account. An interrupted time series regression model was conducted to assess the number of outpatient medical and psychiatric consultations. Subgroup analyses were performed based on service modality, including overall consultations, telemonitoring/teleconsultations only, or face-to-face only, for all service users and for mental health service users. RESULTS: A total of 1,515,439 participants were included, with females comprising 275,444/484,994 (56.80%) of the samples. Only 345,605/1,515,439 (22.81%) visits involved telemedicine. The total monthly outpatient visits were significantly reduced compared with the expected projection (P<.001) at the beginning of the pandemic, followed by a later monthly increment of 298.7 users. Face-to-face interventions experienced a significant reduction at the beginning of the pandemic (P<.001), gradually recovering in the following months. By contrast, telemedicine use initially increased but subsequently declined toward the end of the pandemic. A similar trend was observed in mental health units. CONCLUSIONS: During the pandemic years, health care utilization in both general and psychiatric services experienced a significant decrease, particularly at the beginning of the pandemic (March 2020). However, no significant trends were observed in either case throughout the pandemic period. Telemedicine consultations witnessed a significant increase overall during this period, particularly among mental health users.

Differences in family functioning before and during the COVID-19 pandemic: an observational study in Peruvian families.

The COVID-19 pandemic has had a major impact on family relationships, as several families have lost family members due to COVID-19 pandemic and become physically and emotionally estranged due to lockdown measures and critically economic periods. Our study contrasted two hypotheses: (1) family functioning changed notably before and after the COVID-19 pandemic initiation in terms of cohesion, flexibility, communication and satisfaction; (2) balanced families have a greater capacity to strictly comply with quarantine (i.e., social confinement), compared to unbalanced families. We performed an observational study comparing family functioning between two independent groups, evaluated before and during the first wave of the COVID-19 pandemic in Peru. A total of 7,980 participants were included in the study. For the first hypothesis, we found that, during the pandemic, families became more balanced in terms of cohesion (adjusted before-during mean difference or ß1 = 1.4; 95% CI [1.0-1.7]) and flexibility (ß2 = 2.0; 95% CI [1.6-2.4]), and families were less disengaged (ß3 = -1.9; 95% CI [-2.3 to -1.5]) and chaotic (ß4 = -2.9; 95% CI [-3.3 to -2.4]). Regarding the second hypothesis, we confirmed that families with balanced cohesion (adjusted prevalence ratio or aPR = 1.16; 95% CI [1.12-1.19) and flexibility (aPR = 1.23; 95% CI [1.18-1.27]) allowed greater compliance with quarantine restrictions; while disengaged (aPR = 0.91; 95% CI [0.88-0.93]) and chaotic families (aPR = 0.89; 95% CI [0.87-0.92]) were more likely to partially comply or not comply with the quarantine. Finally, family communication (aPR = 1.17; 95% CI [1.11-1.24]) and satisfaction (aPR = 1.18; 95% CI [1.11-1.25]) also played a role in favouring quarantine compliance. This new evidence enlightens the family systems theory while informing future interventions for improving compliance with quarantine measures in the context of social confinement.

Paper promises: Peruvian frontline health workers' perspectives on mental health policies during COVID-19.

Governments globally deployed various non-pharmacological public health measures to respond to the COVID-19 pandemic (i.e. lockdowns and suspension of transportation, amongst others); some of these measures had an influence on society's mental health. Specific mental health policies were therefore implemented to mitigate the potential mental health impact of the pandemic. We aimed to explore the implementation of mental health regulations adopted by the Peruvian health system by focusing on the care services at Community Mental Health Centres (CMHCs), based on the experiences of health workers. We conducted a phenomenological qualitative study to understand the implementation of mental health policies launched in Peru during the COVID-19 pandemic. Data were obtained from a document review of 15 national policy measures implemented during the pandemic (March 2020 to September 2021), and 20 interviews with health workers from CMHCs (September 2021 to February 2022). The analysis was conducted using thematic content analysis. Most implemented policies adapted CMHC care services to a virtual modality during the COVID-19 pandemic; however, various challenges and barriers were evidenced in the process, which prevented effective adaptation of services. Workers perceived that ineffective telemedicine use was attributed to a gap in access to technology at the CMHCs and also by users, ranging from limited access to technological devices to a lack of technological skills. Further, although mental health promotion and prevention policies targeting the community were proposed, CMHC staff reported temporary interruption of these services during the first wave. The disparity between what is stated in the regulations and the experiences of health workers is evident. Policies that focus on mental health need to provide practical and flexible methods taking into consideration both the needs of CMHCs and socio-cultural characteristics that may affect their implementation.

When COVID-19 strikes mental health: a measurement analysis of reassurance seeking behavior scale in Peruvian population.

Background: The long-lasting impact of the COVID-19 pandemic cannot be overstated. To combat its dire consequences, some screening measures have been hastily developed and require robust verification to explore their adequacy across different groups. The present research study aimed to analyze measurement invariance by sociodemographic characteristics of the Coronavirus Reassurance Seeking Behavior Scale (CRSB) in Peruvian adults. Methods: A total of 661 participants completed The Coronavirus Reassurance Seeking Behavior Scale (CRSB), the Coronavirus Anxiety Scale (CAS), and sociodemographic information a subgroup filled in the Patient Health Questionnaire (PHQ-9). Reliability and measurement invariance across sociodemographic characteristics were analyzed. Likewise, associations with depression and dysfunctional coronavirus anxiety were examined. Results: Results showed that the single factor structure of the CRSB with correlated errors fitted the data adequately and the instrument was invariant across gender, age, and loss of a significant relative to COVID-19. In addition, significant associations with depressive symptoms and dysfunctional anxiety were found. Conclusion: The findings of the present study suggest that the Coronavirus Reassurance Seeking Behaviors Scale is invariant across different sociodemographic characteristics.

Profiles of depressive symptoms in Peru: An 8-year analysis in population-based surveys.

Background Profiles of depressive symptoms have been described due to heterogeneity in symptomatology and presentation. In our study, we estimate depressive symptom profiles and relate these symptom profiles to risk factors in the Peruvian population. Methods We carried out an observational study based on the Peruvian Demographic and Health Survey (2014-2022). Men and women aged 15 years and older living in urban and rural areas in all regions of Peru were included. The Patient Health Questionnaire-9 was used to define depressive symptom profiles. We estimated latent class models to define the profiles and performed a Poisson regression analysis to determine the associated factors. Results A total of 259,655 participants were included. The three-class model was found to be the most appropriate, and the classes were defined according to the severity of depressive symptoms (moderate-severe symptoms, mild symptoms, and without depressive symptoms). Also, it was found that the three classes identified have not changed during the years of evaluations, presenting very similar prevalence over the years. In addition, women are more likely than men to belong to a class with more severe depressive symptoms; and the older the age, the higher the probability of belonging to a class with greater severity of depressive symptoms. Conclusions Our study found that at the population level in Peru, depressive symptoms are grouped into three classes according to the intensity of the symptomatology present (no symptoms, mild symptoms and moderate-severe symptoms).

Characteristics of undergraduate and second speciality mental health programmes in Peru: a cross-sectional study.

BACKGROUND: This study aims to describe the training offered and the availability of professionals required by the Ministry of Health for mental health problems management in the community. METHODS: A cross-sectional study was carried out on the training offered in mental health in Peruvian universities. A search for programs was conducted using the University Information System database and universities' websites, as well as using the Ministry of Health's database on health personnel and data on the number of enrolled and current students provided by the University Information System database and the Transparency section of the universities. RESULTS: There were 214 undergraduate, 55 specialty and 7 subspecialty programmes, of which 39%, 47% and 100%, respectively, were offered in the capital city. The duration ranged from 5 to 7 years for undergraduate programs and from 1 to 3 years for subspecialty and second specialty programs. The cost of undergraduate programs ranged from free of charge up to USD 6863.75 for the first semester of study. Second specialty programs ranged from 720 up to 11 986 USD and subspecialty programs ranged from 2267 up to 9138 USD, with medicine being the most expensive. On the other hand, there are a greater number of psychology students (n = 78 781) pursuing undergraduate studies than working professionals (n = 5368), while in the second specialty of psychiatry there are far fewer students pursuing the specialty (n = 67) than working professionals (n = 454). CONCLUSIONS: The problem of professional training in mental health requires that the institutions involved in health and education develop policies to decentralize programs, communicate the demand for professionals in certain areas, make them accessible to the low-income population, respond to mental health problems and guarantee their quality. On the other hand, regarding the low number of mental health personnel working, it is suggested to increase the mental health budget to generate more mental health services and employment.