Public Assessments Research Articles

Escalating threat of human-perceived heatwaves in Brazil

Abstract Heatwaves pose significant threats to socioeconomic and environmental systems, with their intensity and frequency expected to increase due to climate change. Despite their critical impacts, future heatwaves in Brazil remain underexplored, especially from a human-perceived perspective, which is crucial for assessing potential public health impacts. Here, we propose a method to assess heatwaves using the humidex (H) – a climate index that combines temperature and relative humidity to indicate human-perceived heat - alongside traditional temperature-based measures. Using bias-corrected simulations from 10 CMIP6 models under SSP2-4.5 and SSP5-8.5 scenarios, we quantified projected changes in heatwaves across Brazil. The results indicate that heatwaves will become more severe and prolonged, with greater changes under the SSP5-8.5 scenario by the end of the century, particularly in the North, Northeast, and Central regions. The magnitude of human-perceived heatwaves is expected to rise faster than temperature-based ones, underscoring the need for public health-focused assessments. CMIP6 models strongly agree on increased future heatwaves, potentially tripling population exposure in most Brazilian states, with the Southeast experiencing greater changes due to its larger population. These events are expected not only to affect more people but also to be more severe, exceeding over 60 days per year of serious danger (H > 45°C) by the end of the century under SSP5-8.5. Record-shattering events in the historical period are projected to become the norm by mid-century, highlighting the accelerating nature of these extreme events. Our findings emphasize the importance of considering human-perceived heat in climate impact studies and public health planning to mitigate potential impacts.

HiCorr: an influenza surveillance model using over-the-counter sales from community pharmacies

Abstract Background In large-scale community transmission, such as seasonal influenza, monitoring geographic trends and estimating the transmission intensity are critical to support public health decision-making. Previous studies have successfully used sales data from over-the-counter (OTC) products in community pharmacies to detect and monitor different epidemiological outbreaks, developing surveillance systems that are able to anticipate the load on primary care services and hospitals by up to 3 weeks. Methods The subset of OTC products sold in Portuguese community pharmacies was selected by correlating sales data to primary care attendance in previous flu seasons. This data pertained to daily coded episodes of influenza-like-illness (International Classification of Primary Care, 2nd Edition, code R80) in the Portuguese health cluster Oeste Sul. By fitting a moving epidemic method to historical sales data and then applying it to daily collected sales data, the developed index was used to anticipate the relative load to the primary care system as well as the start and the peak of epidemic activity for the current flu season. Results were compared to the public health data available on respiratory infections in Portugal. Results The model pinpointed the onset of the 2023-2024 flu epidemic in week 47 and its peak in week 52. The index curve showed a high correlation with the data published by the Portuguese national health service, with no time lag. However, the availability of consolidated public data was delayed, on average, by approximately two weeks. Discussion and conclusions Data from community pharmacies significantly enhance the early detection of seasonal flu trends, while reflecting population distribution. This underscores their invaluable contribution to public health assessments and the potential for improving the timeliness and accuracy of seasonal flu surveillance. Key messages • Community pharmacy data significantly enhance the early detection of seasonal flu trends. • Real world sales data maybe useful to support epidemic surveillance in public health.

Integrating health in urban planning curriculum across Indian planning institutes

Urban planning significantly influences the physical and health profile of urban environments. This paper explores the critical nexus between urban planning and public health, emphasizing the urgent need to integrate health considerations into the urban planning curriculum in India. Current urban planning courses often overlook public health aspects, resulting in a disconnect that could hinder the ability of urban environments to meet the health and well-being needs of their populations. Through a comprehensive review and analysis of curriculum data from selected Indian institutions of national importance—including the School of Planning and Architecture, Indian Institute of Technology Kharagpur, and National Institute of Technology, Bhopal—this study identifies significant gaps in the inclusion of health-related content in urban planning education. The analysis reveals a low occurrence of health-related themes within the planning curriculum, with essential topics like public health history, environmental health, and health impact assessments seldom addressed. To bridge these gaps, the paper suggests incorporating mandatory health-focused courses, such as Health Impact Assessments and public health fundamentals, into the curriculum. It also recommends interdisciplinary collaboration with public health professionals to enrich planning education. By restructuring the curriculum to include more comprehensive health-related education, future urban planners can be better equipped to create healthier and more sustainable urban environments, ultimately enhancing public health outcomes in rapidly urbanizing spaces. This research not only sheds light on current educational inadequacies but also proposes actionable steps towards a more holistic integration of health and urban planning disciplines.

Protecting whose welfare? A document analysis of competition regulatory decisions in four jurisdictions across three harmful consumer product industries

Background and methodsCompetition regulation has a strong influence on the relative market power of firms. As such, competition regulation can complement industry-specific measures designed to address harms associated with excessive market power in harmful consumer product industries. This study aimed to examine, through a public health lens, assessments and decisions made by competition authorities in four jurisdictions (Australia, South Africa, the United States (US), and the European Union (EU)) involving three harmful consumer product industries (alcoholic beverages, soft drinks, tobacco). We analysed legal case documents, sourced from online public registers and dating back as far as the online records extended, using a narrative approach. Regulatory decisions and harms described by the authorities were inductively coded, focusing on the affected group(s) (e.g., consumers) and the nature of the harms (e.g., price increases) identified.ResultsWe identified 359 cases published by competition authorities in Australia (n = 202), South Africa (n = 44), the US (n = 27), and the EU (n = 86). Most cases (n = 239) related to mergers and acquisitions (M&As). Competition authorities in Australia, the US, and the EU were found to make many decisions oriented towards increasing the affordability and accessibility of alcohol beverages, soft drinks, and tobacco products. Such decisions were very often made despite the presence of consumption-reduction public health policies. In comparison, South Africa’s competition authorities routinely considered broader issues, including ‘Black Economic Empowerment’ and potential harms to workers.ConclusionMany of the competition regulatory decisions assessed likely facilitated the concentration of market power in the industries we explored. Nevertheless, there appears to be potential for competition regulatory frameworks to play a more prominent role in promoting and protecting the public’s health through tighter regulation of excessive market power in harmful consumer product industries.

Коммуникативные приемы управления цифровой репутацией органов исполнительной власти

The article considers the concept of digital reputation in relation to the executive authorities of the Russian Federation, as well as identifies the technological and communicative methods of its formation and maintenance. The digital reputation of a public administration body is a multicriterial assessment of its activities. It appears in media space and reflects the opinions of socially active population. Digital reputation is not identical to digital image. The authors revealed the following discursive factors that shape stereotypes about public administration. For instance, an indefinitely wide range of addressees lack basic knowledge in public administration; public assessments are flexible and unpredictable; some Internet users practice provocative speech behavior, etc. The research featured internet posts made by the Ministry of Science and Higher Education of the Russian Federation in the social network VKontakte. The service Popsters.ru made it possible to rate them by user involvement. A discursive and stylistic analysis of the posts with a high engagement coefficient revealed the following effective tools for managing the digital reputation of the authorities: hashtags as means of data distribution and systematization, dialogical and personalized presentation, interactive forms of communication (voting, polls, etc.), timely reaction to user comments, etc.

Diverging perceptions of artificial intelligence in higher education: A comparison of student and public assessments on risks and damages of academic performance prediction in Germany

The integration of Artificial Intelligence (AI) into higher education, particularly through Academic Performance Prediction (APP), promises enhanced educational outcomes. However, it simultaneously raises concerns regarding data privacy, potential biases, and broader socio-technical implications. Our study, focusing on Germany–a pivotal player in shaping the European Union's AI policies–seeks to understand prevailing perceptions of APP among students and the general public. Initial findings of a large standardized online survey suggest a divergence in perceptions: While students, in comparison to the general population, do not attribute a higher risk to APP in a general risk assessment, they do perceive higher societal and, in particular, individual damages from APP. Factors influencing these damage perceptions include trust in AI and personal experiences with discrimination. Students further emphasize the importance of preserving their autonomy by placing high value on self-determined data sharing and explaining their individual APP. Recognizing these varied perceptions is crucial for educators, policy-makers, and higher education institutions as they navigate the intricate ethical landscape of AI in education. This understanding can inform strategies that accommodate both the potential benefits and concerns associated with AI-driven educational tools.

Reward exploitation or exploration? The effects of local government sustainability strategies and performance information on citizen evaluation

ABSTRACT Given the growing attention on citizen involvement in local sustainability, this study explores how citizens evaluate government sustainability performance stemming from exploitation (established policies) and exploration strategies (pioneering initiatives). Our survey experiment finds that positive sustainability performance resulting from exploitation achieves more favourable citizen evaluations compared to exploration. Negative sustainability performance does not moderate the associations between sustainability strategies and public assessments. Furthermore, Republicans, individuals with low climate beliefs, Hispanics, and low-income citizens prefer exploitation over exploration. As an early attempt to examine citizen preferences for organizational strategies, this study extends performance management research by linking organizational strategies with performance.

Implications of public acceptance assessments for site selections in the small modular reactors using system dynamics

This study investigates the feasibility of siting a nuclear power plant (NPP) within a densely populated university campus. Site selection for NPPs is a complex process involving numerous interconnected factors. To address this complexity, we employ system dynamics (SD) modeling, a methodology renowned for its ability to quantify both technological and social aspects. Our simulation results indicate that public acceptance (PA) is a critical determinant in site selection. In the fourth month of the simulation, the model's values were identical in both PA and non-PA scenarios. However, subsequent simulations revealed a significant divergence, with PA-implicated values reaching 85.398 compared to 24.240 in the non-PA scenario. This disparity underscores the primacy of PA in the decision-making process. Given the extended timeline of NPP construction, the gap between PA and non-PA outcomes is likely to widen further, particularly in the context of positive public sentiment toward the NPP. The insights gleaned from this research can be applied to other industries, such as oil refineries, where the potential for atmospheric pollution due to toxic gas leaks necessitates careful site selection.

Invasive Pneumococcal Infections Among Moroccan Children: Pneumococcal Vaccination Challenges in the Mature Vaccine Era.

Streptococcus pneumoniae, a major contributor to global morbidity and mortality, disproportionately affects children, the elderly, and immunocompromised individuals. Despite vaccination efforts, the challenge of serotype replacement highlights the ongoing struggle against invasive pneumococcal diseases (IPD) in Morocco, emphasizing the need for updated public health strategies and vaccine efficacy assessments. This study was conducted at the Ibn Rochd University Hospital Center and the Mohammed VI University Hospital Center from 2019 to 2022, focusing on hospitalized children. It involved the analysis of 74 strains of IPD, assessing the distribution of pneumococcal serotypes and their antibiotic sensitivity in the post-vaccination era. The prevalence of meningitis or meningo-encephalitis was found to be 66% among the study subjects, with the most frequent serotypes being 3, 19A, 6B, 14, and 11. These serotypes varied significantly by age and location. Coverage rates for the pneumococcal conjugate vaccines, PCV-10 and PCV-13, were 20.27% and 56.75%, respectively. Notably, 43% of the strains were non-vaccine serotypes, with serotypes 3 and 19 accounting for 36% of the infections in children, indicating a lack of vaccine efficacy against these types. Additionally, 31.3% of the strains were Penicillin non-susceptible Streptococcus pneumoniae (PNSP), with 81.25% associated with non-vaccine serotypes. This study highlights the persistence of IPD in Moroccan children, revealing significant challenges despite vaccination efforts. With the reintroduction of PCV-13, concerns about the efficacy against non-vaccine serotypes, particularly 3 and 19A, remain. Continuous surveillance and adaptable vaccination strategies are essential to combat these serotype replacements and ensure the effectiveness of future preventive measures.

Unraveling the Influence of Satellite-Observed Land Surface Temperature on High-Resolution Mapping of Ground-Level Ozone Using Interpretable Machine Learning.

Accurately mapping ground-level ozone concentrations at high spatiotemporal resolution (daily, 1 km) is essential for evaluating human exposure and conducting public health assessments. This requires identifying and understanding a proxy that is well-correlated with ground-level ozone variation and available with spatiotemporal high-resolution data. This study introduces a high-resolution ozone modeling method utilizing the XGBoost algorithm with satellite-derived land surface temperature (LST) as the primary predictor. Focusing on China in 2019, our model achieved a cross-validation R2 of 0.91 and a root-mean-square error (RMSE) of 13.51 μg/m3. We provide detailed maps highlighting ground-level ozone concentrations in urban areas, uncovering spatial variations previously unresolved, along with time series aligning with established understandings of ozone dynamics. Our local interpretation of the machine learning model underscores the significant contribution of LST to spatiotemporal ozone variations, surpassing other meteorological, pollutant, and geographical predictors in its influence. Validation results indicate that model performance decreases as spatial resolution becomes coarser, with R2 decreasing from 0.91 for the 1 km model to 0.85 for the 25 km model. The methodology and data sets generated by this study offer new insights into ground-level ozone variability and mapping and can significantly aid in exposure assessment and epidemiological research related to this critical environmental challenge.

Challenging unverified assumptions in causal claims: Do gas stoves increase risk of pediatric asthma?

The use of unverified models for risk estimates and policy recommendations can be highly misleading, as their predictions may not reflect real-world health impacts. For example, a recent article states that NO2 from gas stoves “likely causes ∼50,000 cases of current pediatric asthma from long-term NO2 exposure alone” annually in the United States. This explicitly causal claim, which is contrary to several methodology and review articles published in this journal, among others, reflects both (a) An unverified modeling assumption that pediatric asthma burden is approximately proportional to NO2; and (b) An unverified causal assumption that the assumed proportionality between exposure and response is causal. The article is devoid of any causal analysis showing that these assumptions are likely to be true. It does not show that reducing NO2 exposure from gas stoves would reduce pediatric asthma risk. Its key references report no significant associations – let alone causation – between NO2 and pediatric asthma. Thus, the underlying data suggests that the number of pediatric asthma cases caused by gas stoves in the United States is indistinguishable from zero. This highlights the need to rigorously validate modeling assumptions and causal claims in public health risk assessments to ensure scientifically sound foundations for policy decisions.

Effectiveness of Updated 2023-2024 (Monovalent XBB.1.5) COVID-19 Vaccination Against SARS-CoV-2 Omicron XBB and BA.2.86/JN.1 Lineage Hospitalization and a Comparison of Clinical Severity-IVY Network, 26 Hospitals, October 18, 2023-March 9, 2024.

Assessing variant-specific COVID-19 vaccine effectiveness (VE) and severity can inform public health risk assessments and decisions about vaccine composition. BA.2.86 and its descendants, including JN.1 (referred to collectively as "JN lineages"), emerged in late 2023 and exhibited substantial divergence from co-circulating XBB lineages. We analyzed patients hospitalized with COVID-19-like illness at 26 hospitals in 20 U.S. states admitted October 18, 2023-March 9, 2024. Using a test-negative, case-control design, we estimated effectiveness of an updated 2023-2024 (Monovalent XBB.1.5) COVID-19 vaccine dose against sequence-confirmed XBB and JN lineage hospitalization using logistic regression. Odds of severe outcomes, including intensive care unit (ICU) admission and invasive mechanical ventilation (IMV) or death, were compared for JN versus XBB lineage hospitalizations using logistic regression. 585 case-patients with XBB lineages, 397 case-patients with JN lineages, and 4,580 control-patients were included. VE in the first 7-89 days after receipt of an updated dose was 54.2% (95% CI = 36.1%-67.1%) against XBB lineage hospitalization and 32.7% (95% CI = 1.9%-53.8%) against JN lineage hospitalization. Odds of ICU admission (adjusted odds ratio [aOR] 0.80; 95% CI = 0.46-1.38) and IMV or death (aOR 0.69; 95% CI = 0.34-1.40) were not significantly different among JN compared to XBB lineage hospitalizations. Updated 2023-2024 COVID-19 vaccination provided protection against both XBB and JN lineage hospitalization, but protection against the latter may be attenuated by immune escape. Clinical severity of JN lineage hospitalizations was not higher relative to XBB.

Public attitudes to xenotransplantation: A national survey in the United States

Xenotransplantation (XTx) presents a potential clinical alternative to the shortage of human organs for transplantation. Before clinical trials occur in the United States, public assessments are crucial to understand potential barriers to acceptance. The purpose of this study was to explore barriers and identify characteristics associated with attitudes toward XTx. A survey assessing demographic characteristics and attitudes toward XTx was distributed to a nationally representative sample of adults aged ≥18 years in the United States. Regression analysis was employed to identify characteristics associated with attitudes toward XTx. Between May 25 and June 14, 2023, 5008 respondents completed the survey. Importantly, half of the respondents expressed low or no knowledge of either transplantation or XTx. Approximately 40% expressed discomfort with receiving a pig organ for themselves or a loved one. Despite a lack of xenotransplant outcome data, 36% were open to experimental XTx if they needed a transplant. However, 57% rated lack of current evidence of success or fear of complications as top concerns. Regression models consistently associated being younger, female, not needing an organ, or being a member of a racial minority group with lower acceptance. This survey is the largest to date exploring public attitudes toward XTx. Despite overall acceptance, concerns persist. Increasing public acceptance is key as the field advances.

The Ojai California Earthquake of 20 August 2023: Earthquake Early Warning Performance and Alert Recipient Response in the Mw 5.1 Event

Abstract A magnitude 5.1 earthquake in California rarely generates more than momentary notice—a headline in local newspapers and a mention with footage on the evening news—then fades into obscurity for most people. But this earthquake, which occurred near the city of Ojai, is important for seismologists, social scientists, emergency managers, policymakers, and others who are engaged in implementing and improving earthquake early warning (EEW) technology and in assessing its value in public warnings. In this earthquake, ShakeAlert, the EEW system for the West Coast of the United States operated by the U.S. Geological Survey (USGS), was publicly activated and, for the first time, a substantial number of those who received alerts provided feedback on various aspects of the alerts they received. To capture data related to public attitudes and assessments regarding this and future alerts, a supplemental questionnaire was developed and associated with the “Did You Feel It?” (DYFI) earthquake reporting system, also operated by the USGS. The DYFI system received over 14,000 felt reports; 2490 of these were by people who received or expected to receive an alert before the onset of earthquake motion at their locations. This article analyzes the aggregate results of these EEW user reports, touching on the respondent’s situation upon receiving the alert, characteristics of the alert received, and, perhaps, most importantly, how the alert recipient responded if received before feeling earthquake motion. The new DYFI EEW supplemental questionnaire also inquired about respondent views of alert usefulness and preferences in future alerts. Our report provides a first glimpse of a range of behaviors, attitudes, and assessments by users of the recently implemented EEW system for the U.S. West Coast.

On alert for Ebola: public health risk assessment of travellers from Uganda to the USA during the 2022 outbreak.

On 20 September 2022, the Ugandan Ministry of Health declared an outbreak of Ebola disease caused by Sudan ebolavirus. From 6 October 2022 to 10 January 2023, Centers for Disease Control and Prevention (CDC) staff conducted public health assessments at five US ports of entry for travellers identified as having been in Uganda in the past 21days. CDC also recommended that state, local and territorial health departments ('health departments') conduct post-arrival monitoring of these travellers. CDC provided traveller contact information, daily to 58 health departments, and collected health department data regarding monitoring outcomes. Among 11 583 travellers screened, 132 (1%) required additional assessment due to potential exposures or symptoms of concern. Fifty-three (91%) health departments reported receiving traveller data from CDC for 10 114 (87%) travellers, of whom 8499 (84%) were contacted for monitoring, 1547 (15%) could not be contacted and 68 (1%) had no reported outcomes. No travellers with high-risk exposures or Ebola disease were identified. Entry risk assessment and post-arrival monitoring of travellers are resource-intensive activities that had low demonstrated yield during this and previous outbreaks. The efficiency of future responses could be improved by incorporating an assessment of risk of importation of disease, accounting for individual travellers' potential for exposure, and expanded use of methods that reduce burden to federal agencies, health departments, and travellers.

Effectiveness of Updated 2023-2024 (Monovalent XBB.1.5) COVID-19 Vaccination Against SARS-CoV-2 Omicron XBB and BA.2.86/JN.1 Lineage Hospitalization and a Comparison of Clinical Severity - IVY Network, 26 Hospitals, October 18, 2023-March 9, 2024.

Assessing COVID-19 vaccine effectiveness (VE) and severity of SARS-CoV-2 variants can inform public health risk assessments and decisions about vaccine composition. BA.2.86 and its descendants, including JN.1 (referred to collectively as "JN lineages"), emerged in late 2023 and exhibited substantial genomic divergence from co-circulating XBB lineages. We analyzed patients hospitalized with COVID-19-like illness at 26 hospitals in 20 U.S. states admitted October 18, 2023-March 9, 2024. Using a test-negative, case-control design, we estimated the effectiveness of an updated 2023-2024 (Monovalent XBB.1.5) COVID-19 vaccine dose against sequence-confirmed XBB and JN lineage hospitalization using logistic regression. Odds of severe outcomes, including intensive care unit (ICU) admission and invasive mechanical ventilation (IMV) or death, were compared for JN versus XBB lineage hospitalizations using logistic regression. 585 case-patients with XBB lineages, 397 case-patients with JN lineages, and 4,580 control-patients were included. VE in the first 7-89 days after receipt of an updated dose was 54.2% (95% CI = 36.1%-67.1%) against XBB lineage hospitalization and 32.7% (95% CI = 1.9%-53.8%) against JN lineage hospitalization. Odds of ICU admission (adjusted odds ratio [aOR] 0.80; 95% CI = 0.46-1.38) and IMV or death (aOR 0.69; 95% CI = 0.34-1.40) were not significantly different among JN compared to XBB lineage hospitalizations. Updated 2023-2024 COVID-19 vaccination provided protection against both XBB and JN lineage hospitalization, but protection against the latter may be attenuated by immune escape. Clinical severity of JN lineage hospitalizations was not higher relative to XBB lineage hospitalizations.

Estimating Disease-Free Life Expectancy Based on Clinical Data from the French Hospital Discharge Database

The development of health indicators to measure healthy life expectancy (HLE) is an active field of research aimed at summarizing the health of a population. Although many health indicators have emerged in the literature as critical metrics in public health assessments, the methods and data to conduct this evaluation vary considerably in nature and quality. Traditionally, health data collection relies on population surveys. However, these studies, typically of limited size, encompass only a small yet representative segment of the population. This limitation can necessitate the separate estimation of incidence and mortality rates, significantly restricting the available analysis methods. In this article, we leverage an extract from the French National Hospital Discharge database to define health indicators. Our analysis focuses on the resulting Disease-Free Life Expectancy (Dis-FLE) indicator, which provides insights based on the hospital trajectory of each patient admitted to hospital in France during 2008–2013. Through this research, we illustrate the advantages and disadvantages of employing large clinical datasets as the foundation for more robust health indicators. We shed light on the opportunities that such data offer for a more comprehensive understanding of the health status of a population. In particular, we estimate age-dependent hazard rates associated with sex, alcohol abuse, tobacco consumption, and obesity, as well as geographic location. Simultaneously, we delve into the challenges and limitations that arise when adopting such a data-driven approach.

The way you assess matters: User interaction design of survey chatbots for mental health

The global pandemic has pushed human society into a mental health crisis, prompting the development of various chatbots to supplement the limited mental health workforce. Several organizations have employed mental health survey chatbots for public mental status assessments. These survey chatbots typically ask closed-ended questions (Closed-EQs) to assess specific psychological issues like anxiety, depression, and loneliness, followed by open-ended questions (Open-EQs) for deeper insights. While Open-EQs are naturally presented conversationally in a survey chatbot, Closed-EQs can be delivered as embedded forms or within conversations, with the length of the questionnaire varying according to the psychological assessment. This study investigates how the interaction style of Closed-EQs and the questionnaire length affect user perceptions regarding survey credibility, enjoyment, and self-awareness, as well as their responses to Open-EQs in terms of quality and self-disclosure in a survey chatbot. We conducted a 2 (interaction style: form-based vs. conversation-based) × 3 (questionnaire length: short vs. middle vs. long) between-subjects study (N=213) with a loneliness survey chatbot. The results indicate that the form-based interaction significantly enhances the perceived credibility of the assessment, thereby improving response quality and self-disclosure in subsequent Open-EQs and fostering self-awareness. We discuss our findings for the interaction design of psychological assessment in a survey chatbot for mental health.

Public Aspirations and Complaints Information System: Improving the Quality of Public Complaints in Sidrap Regency

Public assessments determine the quality of public services, so public complaints are needed to improve service quality. In making the management of public complaints more effective as expected by the government in Presidential Regulation no. 76/2013, the Sidenreng Rappang Regency Government has utilized technology, by creating. public aspirations and complaints information system (SIAPP), but until now, the complaint service is still experiencing problems. The socialization of program innovations and complaint procedures through the SIAPP program is not evenly distributed at every level of society. In addition, the SIAPP admin is less responsive in responding to public complaints. Based on this, this research was carried out to analyze the quality of public complaint services in Sidenreng Rappang Regency through the SIAPP application to support the creation of quality public services. Qualitative research methods, with a descriptive approach, were the researcher's choice. Research data was obtained through interviews, which were also strengthened from observations and literature studies. The data that has been obtained is analyzed by referring to the interactive model. The research results show that the quality of public complaints in Sidenreng Rappang Regency cannot be improved by using the SIAPP application because the standard operational procedures for SIAPP are not yet complete. Regional apparatus organizations are slow in following up on community complaints, and community data security is still weak when using the SIAPP application.

Using Photovoice to Improve Engagement in Community Health Assessments Addressing Behavioral Health.

Behavioral health disorders are well-known to have close links with the social determinants of health, yet little is known about how impacted communities perceive these links. Qualitative participatory methods can not only provide insight into how communities conceptualize these relationships but also empower those with lived experience to contextualize their perspectives and formulate calls to action. This study used Photovoice as a participatory method to supplement the Clark County Health Department Community Health Assessment and determine priority facilitators and barriers contributing to the behavioral health of Clark County, KY, residents. A secondary aim was to gain a greater understanding of how the Photovoice methodology impacts community engagement efforts in Community Health Assessments. Twenty-three Clark County residents participated in four Photovoice groups involving five weekly sessions, which included photograph "show and tell," critical group dialogue, participatory analysis, and planning for dissemination. Secondary analysis of Photovoice focus group discussions revealed behavioral health facilitators and barriers were most influenced by (1) public sector unresponsiveness, (2) strong partnerships formed between community and grassroots organizations, and (3) the siloed division of responsibility between agencies and across sectors. The authors also found the Photovoice method successfully enhanced engagement and empowered those with lived experience to frame their perspectives of the behavioral health landscape. This project has implications for enhancing community engagement and empowerment in behavioral health-focused public health assessments and shaping policy to promote multi-sector collaboration.