Polygraph-based deception detection and Machine Learning. Combining the Worst of Both Worlds?

At a time when developments in computational approaches, often associated with the now much-vaunted terms Machine Learning (ML) and Artificial Intelligence (AI), face increasing challenges in terms of fairness, transparency and accountability, the temptation for researchers to apply mainstream ML methods to virtually any type of data seems to remain irresistible. In this paper we critically examine a recent proposal to apply ML to polygraph screening results (where human interviewers have made a conclusion about deception), which raises several questions about the purpose and the design of the research, particularly given the vacuous scientific status of polygraph-based procedures themselves. We argue that in high-stake environments such as criminal justice and employment practice, where fundamental rights and principles of justice are at stake, the legal and ethical considerations for scientific research are heightened. Specifically, we argue that the combination of ambiguously labelled data and ad hoc ML models does not meet this requirement. Worse, such research can inappropriately legitimise otherwise scientifically invalid, indeed pseudo-scientific methods such as polygraph-based deception detection, especially when presented in a reputable scientific journal. We conclude that methodological concerns, such as those highlighted in this paper, should be addressed before research can be said to contribute to resolving any of the fundamental validity issues that underlie methods and techniques used in legal proceedings.

Determining an Appropriate Sample Size for Qualitative Interviews to Achieve True and Near Code Saturation: Secondary Analysis of Data.

BACKGROUND: In-depth interviews are a common method of qualitative data collection, providing rich data on individuals' perceptions and behaviors that would be challenging to collect with quantitative methods. Researchers typically need to decide on sample size a priori. Although studies have assessed when saturation has been achieved, there is no agreement on the minimum number of interviews needed to achieve saturation. To date, most research on saturation has been based on in-person data collection. During the COVID-19 pandemic, web-based data collection became increasingly common, as traditional in-person data collection was possible. Researchers continue to use web-based data collection methods post the COVID-19 emergency, making it important to assess whether findings around saturation differ for in-person versus web-based interviews. OBJECTIVE: We aimed to identify the number of web-based interviews needed to achieve true code saturation or near code saturation. METHODS: The analyses for this study were based on data from 5 Food and Drug Administration-funded studies conducted through web-based platforms with patients with underlying medical conditions or with health care providers who provide primary or specialty care to patients. We extracted code- and interview-specific data and examined the data summaries to determine when true saturation or near saturation was reached. RESULTS: The sample size used in the 5 studies ranged from 30 to 70 interviews. True saturation was reached after 91% to 100% (n=30-67) of planned interviews, whereas near saturation was reached after 33% to 60% (n=15-23) of planned interviews. Studies that relied heavily on deductive coding and studies that had a more structured interview guide reached both true saturation and near saturation sooner. We also examined the types of codes applied after near saturation had been reached. In 4 of the 5 studies, most of these codes represented previously established core concepts or themes. Codes representing newly identified concepts, other or miscellaneous responses (eg, "in general"), uncertainty or confusion (eg, "don't know"), or categorization for analysis (eg, correct as compared with incorrect) were less commonly applied after near saturation had been reached. CONCLUSIONS: This study provides support that near saturation may be a sufficient measure to target and that conducting additional interviews after that point may result in diminishing returns. Factors to consider in determining how many interviews to conduct include the structure and type of questions included in the interview guide, the coding structure, and the population under study. Studies with less structured interview guides, studies that rely heavily on inductive coding and analytic techniques, and studies that include populations that may be less knowledgeable about the topics discussed may require a larger sample size to reach an acceptable level of saturation. Our findings also build on previous studies looking at saturation for in-person data collection conducted at a small number of sites.

Beyond human-likeness: Socialness is more influential when attributing mental states to robots.

We sought to replicate and expand previous work showing that the more human-like a robot appears, the more willing people are to attribute mind-like capabilities and socially engage with it. Forty-two participants played games against a human, a humanoid robot, a mechanoid robot, and a computer algorithm while undergoing functional neuroimaging. We confirmed that the more human-like the agent, the more participants attributed a mind to them. However, exploratory analyses revealed that the perceived socialness of an agent appeared to be as, if not more, important for mind attribution. Our findings suggest top-down knowledge cues may be equally or possibly more influential than bottom-up stimulus cues when exploring mind attribution in non-human agents. While further work is now required to test this hypothesis directly, these preliminary findings hold important implications for robotic design and to understand and test the flexibility of human social cognition when people engage with artificial agents.

The art and science of research methodology, biostatistics, manuscript writing, and publication ethics: An invigorating training for improving research aptitudes in southern Indian biomedical institutions.

The basic concepts of research are learned through systematic literature searches which form the basis of a research statement and research topic. Then the research question, hypothesis, aim, and objectives, as well as the experimental design, are developed. Given the context provided, the primary focus is on the importance of adequately training postgraduates and young research investigators in research methodology and project development. It is evident that there is a lack of proper training in these areas, and the rapid expansion of colleges in India exacerbates this issue. To address this, research students must receive comprehensive instruction in scientific research methodology, experimental design, statistics, scientific writing, publishing, and research ethics. Our team has been conducting workshops and symposia for more than two decades to improve the current teaching methods in these areas. Most recently, we organized a series of national and international workshops and seminars in multiple states across India to fortify the core concepts of scientific research for students and faculty members. This report highlights the key aspects of these workshops and the positive outcomes experienced by participants.

Prioritized neural processing of social threats during perceptual decision-making.

Emotional signals, notably those signaling threat, benefit from prioritized processing in the human brain. Yet, it remains unclear whether perceptual decisions about the emotional, threat-related aspects of stimuli involve specific or similar neural computations compared to decisions about their non-threatening/non-emotional components. We developed a novel behavioral paradigm in which participants performed two different detection tasks (emotion vs. color) on the same, two-dimensional visual stimuli. First, electroencephalographic (EEG) activity in a cluster of central electrodes reflected the amount of perceptual evidence around 100 ms following stimulus onset, when the decision concerned emotion, not color. Second, participants' choice could be predicted earlier for emotion (240 ms) than for color (380 ms) by the mu (10 Hz) rhythm, which reflects motor preparation. Taken together, these findings indicate that perceptual decisions about threat-signaling dimensions of facial displays are associated with prioritized neural coding in action-related brain regions, supporting the motivational value of socially relevant signals.

[How to: correctly read scientific articles : Research design and methodology]. / How to: einen wissenschaftlichen Artikel richtig lesen : Forschungsdesign und Methodik.

Criteria for assessment of the significance of scientific articles are presented. The focus is on research design and methodology, illustrated by the classical study on prehospital volume treatment of severely injured individuals with penetrating torso injuries by Bickell et al. (1994). A well-thought out research design is crucial for the success of a scientific study and is documented in a study protocol beforehand. A hypothesis is a provisional explanation or prediction and must be testable, falsifiable, precise, and relevant. There are various types of randomization methods, with the randomized controlled trial being the gold standard for clinical interventional studies. When reading a scientific article it is important to verify whether the research design and setting align with the research question and whether potential sources of error have been considered and controlled. Critical scrutiny should also be applied to references, the funding and expertise of the researchers.

A scoping review shows that no single existing risk of bias assessment tool considers all sources of bias for cross-sectional studies.

OBJECTIVES: Different tools to assess the potential risk of bias (RoB) for cross-sectional studies have been developed, but it is unclear whether all pertinent bias concepts are addressed. We aimed to identify RoB concepts applicable to cross-sectional research validity and to explore coverage for each in existing appraisal tools. STUDY DESIGN AND SETTING: This scoping review followed the Joanna Briggs Institute methodology. We included records of any study design describing or reporting methods, concepts or tools used to consider RoB in health research reported to be descriptive/prevalence survey or analytic/association (cross-sectional) study designs. Synthesis included quantitative and qualitative analysis. RESULTS: Of the 4556 records screened, 90 were selected for inclusion; 67 (74%) described the development of, or validation process for, appraisal tools, 15 (17%) described methodological content or theory relevant to RoB for cross-sectional studies and 8 (9%) records of methodological systematic reviews. Review of methodological reports identified important RoB concepts for both descriptive/prevalence and analytic/association studies. Tools identified (n = 64 unique tools) were either intended to appraise quality or assess RoB in multiple study designs including cross-sectional studies (n = 21; 33%) or cross-sectional designs alone (n = 43; 67%). Several existing tools were modified (n = 17; 27%) for application to cross-sectional studies. The RoB items most frequently addressed in the RoB tools were validity and reliability of the exposure (53%) or outcome (65%) measurement and representativeness of the study population (59%). Most tools did not consider nonresponse or missingness appropriately or at all. CONCLUSION: Assessing cross-sectional studies involve unique RoB considerations. We identified RoB tools designed for broad applicability across various study designs as well as those specifically tailored for cross-sectional studies. However, none of the identified tools comprehensively address all potential biases pertinent to cross-sectional studies. Our findings indicate a need for continued improvement of RoB tools and suggest that the development of context-specific or more precise tools for this study design may be necessary.

Evaluating a research methodology workshop among postgraduate students using Kirkpatrick's model.

BACKGROUND: In this era of evidence-based medicine, only systematic research can help in providing judicious and precise healthcare to individual patients based on updated knowledge and skills. However, many medical professionals do not feel competent and confident enough to conduct research. One of the reasons could be the lack of a research-based curriculum in undergraduate courses. The National Medical Council has also stressed the need for formal training in research methodology for healthcare professionals. The research methodology workshops help to familiarize the participants with basic, clinical, and translational research required to impart optimum patient care. The objective of our study was to evaluate a research methodology workshop conducted for postgraduate students by assessing the participant's knowledge, feedback, and expected impact using Kirkpatrick's evaluation model. MATERIALS AND METHODS: A quasi-experimental, single-group study was conducted among 132 first-year postgraduate students. The four levels of Kirkpatrick's model were applied for evaluation. Feedback forms, scores of the pretest and posttest, quality of the research proposal drafted by the postgraduates for their thesis, and finally successful submission of the research proposal were the components used to evaluate the four levels of outcome of Kirkpatrick's model. STATISTICAL ANALYSIS: Data collected were compiled and tabulated into MS Excel. Proportions were calculated for categorical variables and mean and standard deviation (SD) for scores. A comparison of means between pre- and postworkshop scores was made with paired t-test. A value of P < 0.05 was considered statistically significant. Statistical analysis was done using IBM SPSS Statistics version 20.0 software. RESULTS: Out of 132 participants, 29% (38) were males and 71% (94) were females. The mean ± SD pretest and posttest scores at a 95% confidence interval were 10.55 ± 2.537 and 12.43 ± 2.484, respectively. The difference was found to be statistically significant by paired sample t-test (P < 0.001). CONCLUSION: Participant feedback is vital for improving research methodology workshops. The workshop met the overall requirements of the participants. There was a significant improvement in the knowledge of participants after the workshop completion.

Assessment of knowledge and self-efficacy among health professionals and clinical scientists following the Cameroon HIV/AIDS Research Forum (CAM-HERO 2022) research methodology and bioethics training.

To inform public health policymakers that the generation of local evidence-based knowledge is key. Research capacity in low- and middle-income countries (LMIC) to generate medical knowledge is often weak and insufficiently resourced and efforts to tackle these challenges are not standardized. Continuous research training can equip researchers with the required knowledge and research skills, but its effectiveness largely depends on the quality and pertinence of the training methods used. We aim to assess the effectiveness of the Cameroon HIV/AIDS Research Forum (CAM-HERO) 2022 Research Methodology and Bioethics Training with the objective to describe the knowledge gained and the self-efficacy of health professionals and clinical scientists. A survey was conducted during the one-day training among health professionals and clinical scientists. Participants took an online self-administered questionnaire before and after the training related to the topics taught. The questionnaire consisted of two parts: 1) 18 Multiple Choice Questions (MCQs) to assess knowledge and 2) Nine items to evaluate self-efficacy using a five-point Likert scale. Mean scores were calculated, analysed, and compared using paired t-test for the pre- and post-test results. A total of 30 participants (57% women) completed the socio-demographic form. The median age (IQR) of participants was 33.5 (13.3) years. We registered 38 respondents for the pre-test and 33 respondents for the post-test. There was a rise in knowledge mean score from 13.0 to 14.8 (p=0.001) and an improvement in the perception of self-efficacy with a mean score increase from 2.9 to 3.7 (p < 0.001). Knowledge and perception of self-efficacy on research methodology improved among participants after the training. These results suggest that the CAM-HERO 2022 training had an immediate positive impact on skills and self-efficacy. Hence, we recommend the implementation of this training on a larger scale, periodically, and with long-term follow-up to evaluate its impact.

Opportunities to improve feedback to reduce blood component wastage: Results of a national scheme evaluation.

BACKGROUND: Blood components are costly and scarce. The Blood Stocks Management Scheme (BSMS) was established in the United Kingdom (UK) to support hospital transfusion services and national blood services through collection, analysis, and monthly feedback of data on blood component inventory and wastage management. There is a growing evidence base on how best to deliver feedback for quality improvement. We assessed the quality and utility of the monthly BSMS component reports. METHODS: We assessed the content of BSMS reports issued in March 2023 against established criteria for effective feedback. Two researchers independently rated whether criteria spanning the five domains of goal setting, data collection, feedback content, feedback display and feedback delivery were fully, partially or not met. Disagreements were resolved through discussion. We conducted an online questionnaire survey of recipients of BSMS reports during March 2023 to assess their use of reports and seek suggestions for improvement. RESULTS: Five out of 20 criteria for effective feedback were fully met. Areas for improvement included placing more emphasis in the feedback on positive change, linking data and summary messages, and including specific suggestions for action. Respondents highlighted the value of benchmarked comparisons with other hospital transfusion services. CONCLUSION: There is scope for enhancing the effectiveness and utility of BSMS feedback reports and hence reducing wastage of blood components. This methodology for evaluation of feedback could be utilized to improve other areas of transfusion practice.

Particularity, Engagement, Actionable Inferences, Reflexivity, and Legitimation tool for rigor in mixed methods implementation research.

BACKGROUND: Implementation science helps generate approaches to expedite the uptake of evidence in practice. Mixed methods are commonly used in implementation research because they allow researchers to integrate distinct qualitative and quantitative methods and data sets to unravel the implementation process and context and design contextual tools for optimizing the implementation. To date, there has been limited discussion on how to ensure rigor in mixed methods implementation research. PURPOSE: To present Particularity, Engagement, Actionable Inferences, Reflexivity, and Legitimation (PEARL) as a practical tool for understanding various components of rigor in mixed methods implementation research. DATA SOURCES: This methodological discussion is based on a nurse-led mixed methods implementation study. The PEARL tool was developed based on an interpretive, critical reflection, and purposive reading of selected literature sources drawn from the researchers' knowledge, experiences of designing and conducting mixed methods implementation research, and published methodological papers about mixed methods, implementation science, and research rigor. CONCLUSION: An exemplar exploratory sequential mixed methods study in nursing is provided to illustrate the application of the PEARL tool. The proposed tool can be a useful and innovative tool for researchers and students intending to use mixed methods in implementation research. The tool offers a straightforward approach to learning the key rigor components of mixed methods implementation research for application in designing and conducting implementation research using mixed methods. CLINICAL RELEVANCE: Rigorous implementation research is critical for effective uptake of innovations and evidence-based knowledge into practice and policymaking. The proposed tool can be used as the means to establish rigor in mixed methods implementation research in nursing and health sciences.

Using a Semiautomated Procedure (CleanADHdata.R Script) to Clean Electronic Adherence Monitoring Data: Tutorial.

BACKGROUND: Patient adherence to medications can be assessed using interactive digital health technologies such as electronic monitors (EMs). Changes in treatment regimens and deviations from EM use over time must be characterized to establish the actual level of medication adherence. OBJECTIVE: We developed the computer script CleanADHdata.R to clean raw EM adherence data, and this tutorial is a guide for users. METHODS: In addition to raw EM data, we collected adherence start and stop monitoring dates and identified the prescribed regimens, the expected number of EM openings per day based on the prescribed regimen, EM use deviations, and patients' demographic data. The script formats the data longitudinally and calculates each day's medication implementation. RESULTS: We provided a simulated data set for 10 patients, for which 15 EMs were used over a median period of 187 (IQR 135-342) days. The median patient implementation before and after EM raw data cleaning was 83.3% (IQR 71.5%-93.9%) and 97.3% (IQR 95.8%-97.6%), respectively (Δ+14%). This difference is substantial enough to consider EM data cleaning to be capable of avoiding data misinterpretation and providing a cleaned data set for the adherence analysis in terms of implementation and persistence. CONCLUSIONS: The CleanADHdata.R script is a semiautomated procedure that increases standardization and reproducibility. This script has broader applicability within the realm of digital health, as it can be used to clean adherence data collected with diverse digital technologies.

Investigating SARS-CoV-2 Incidence and Morbidity in Ponce, Puerto Rico: Protocol and Baseline Results From a Community Cohort Study.

BACKGROUND: A better understanding of SARS-CoV-2 infection risk among Hispanic and Latino populations and in low-resource settings in the United States is needed to inform control efforts and strategies to improve health equity. Puerto Rico has a high poverty rate and other population characteristics associated with increased vulnerability to COVID-19, and there are limited data to date to determine community incidence. OBJECTIVE: This study describes the protocol and baseline seroprevalence of SARS-CoV-2 in a prospective community-based cohort study (COPA COVID-19 [COCOVID] study) to investigate SARS-CoV-2 infection incidence and morbidity in Ponce, Puerto Rico. METHODS: In June 2020, we implemented the COCOVID study within the Communities Organized to Prevent Arboviruses project platform among residents of 15 communities in Ponce, Puerto Rico, aged 1 year or older. Weekly, participants answered questionnaires on acute symptoms and preventive behaviors and provided anterior nasal swab samples for SARS-CoV-2 polymerase chain reaction testing; additional anterior nasal swabs were collected for expedited polymerase chain reaction testing from participants that reported 1 or more COVID-19-like symptoms. At enrollment and every 6 months during follow-up, participants answered more comprehensive questionnaires and provided venous blood samples for multiantigen SARS-CoV-2 immunoglobulin G antibody testing (an indicator of seroprevalence). Weekly follow-up activities concluded in April 2022 and 6-month follow-up visits concluded in August 2022. Primary study outcome measures include SARS-CoV-2 infection incidence and seroprevalence, relative risk of SARS-CoV-2 infection by participant characteristics, SARS-CoV-2 household attack rate, and COVID-19 illness characteristics and outcomes. In this study, we describe the characteristics of COCOVID participants overall and by SARS-CoV-2 seroprevalence status at baseline. RESULTS: We enrolled a total of 1030 participants from 388 households. Relative to the general populations of Ponce and Puerto Rico, our cohort overrepresented middle-income households, employed and middle-aged adults, and older children (P<.001). Almost all participants (1021/1025, 99.61%) identified as Latino/a, 17.07% (175/1025) had annual household incomes less than US $10,000, and 45.66% (463/1014) reported 1 or more chronic medical conditions. Baseline SARS-CoV-2 seroprevalence was low (16/1030, 1.55%) overall and increased significantly with later study enrollment time (P=.003). CONCLUSIONS: The COCOVID study will provide a valuable opportunity to better estimate the burden of SARS-CoV-2 and associated risk factors in a primarily Hispanic or Latino population, assess the limitations of surveillance, and inform mitigation measures in Puerto Rico and other similar populations. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/53837.

Neighborhood ethnic density and disparities in proximal blood donation opportunities.

BACKGROUND: Despite being the largest racial/ethnic minority group in the United States, Hispanic/Latinos (H/L) are significantly underrepresented among blood donors. A lack of proximal blood donation opportunities may be one factor contributing to these disparities. However, few studies have investigated this possibility. STUDY DESIGN AND METHODS: Proprietary data on mobile blood collections in Maricopa County, Arizona, were gathered for the period of January 01, 2022 to April 30, 2022 and paired with census tract information using ArcGIS. Maricopa County encompasses the city of Phoenix with a total population of approximately 4.5 million people, including 1.5 million H/L residents. Blood drive count was regressed on H/L ethnic density and total population, and model estimates were exponentiated to obtain odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: During the specified period, approximately 27,000 red blood cell units were collected through mobile drives. Consistent with expectations, when controlling for total neighborhood population, each 10% increase in H/L ethnic density lowered the odds of having a blood drive in the corresponding neighborhood by 12% (OR = 0.88, 95% CI (0.83, 0.92), p < .001). DISCUSSION: These findings provide initial evidence of fewer proximal donation opportunities in areas with greater H/L population density which may contribute to H/L underrepresentation in blood donation and the need for more inclusive collection efforts. Improved access to blood collection is modifiable and could help to increase the overall blood supply, enhance the ability to successfully match specific blood antigen needs of an increasingly diverse population, and bring about a more resilient blood system.

Evolution of public funding since primary care research was considered as a priority research domain in france.

PURPOSE: Annually, the French Ministry of Health funds clinical research projects based on a national call for projects. Since 2013, the Ministry has prioritized funding of primary care. Projects selected for funding are made public without distinguishing the specific area of research. The objective of this study was to identify and describe the evolution of the primary care research projects funded by the Ministry of Health between 2013 and 2019. METHOD: We reviewed all of the 1796 medical research projects funded between 2013 and 2019 and categorized projects as primary care projects by using a list of specific keywords. This list was established through two approaches: (1) selected by an expert committee, the RECaP primary care working group, and (2) using an automated textual analysis of published articles in the field. The keywords were used to screen the titles of the medical research projects funded. The abstracts (at www. CLINICALTRIALS: gov ) or details (from project leaders) were then analyzed by two independent reviewers to determine true primary care projects. RESULTS: Finally, 49 primary care projects were identified, representing 2.7% of all medical research projects funded, without any significant change over the period. These projects were predominantly interventional (69%), with a median number of patients expected per project of 902. CONCLUSION: Despite the prioritization of primary care research in 2013 by the French ministry of health, the number and proportion of projects funded remains low, with no significant change over the years. TRIAL REGISTRATION: Not applicable.

Building Family Interventions for Scalability and Impact.

Family nursing researchers are charged with addressing the conceptual and methodological underpinnings of family research when developing family-focused interventions. Step-by-step guidance is needed that integrates current science of intervention development with family science and helps researchers progress from foundational work to experimental work with policy integration. The purpose of this manuscript is to provide pragmatic, evidence-based guidance for advancing family intervention research from foundational work through efficacy testing. Guidance regarding the development of family interventions is presented using the first three of Sidani's five-stage method: (a) foundational work to understand the problem targeted for change; (b) intervention development and assessment of acceptability and feasibility; and (c) efficacy testing. Each stage of family intervention development is described in terms of process, design considerations, and policy and practice implications. Examples are included to emphasize the family lens. This manuscript provides guidance to family scientists for intervention development and implementation to advance family nursing science and inform policy.

Chiglitazar and Thiazolidinedione in patients with type 2 diabetes: Which is better?

This published Meta-Analysis by Lin et al is an indirect comparison between two drugs Chiglitazar and Thiazolidinedione which are commonly used for glycemic control in type-II diabetes mellitus. In terms of safety and efficacy, this Meta-Analysis is inconclusive.

Integration of cognitive tasks into artificial general intelligence test for large models.

During the evolution of large models, performance evaluation is necessary for assessing their capabilities. However, current model evaluations mainly rely on specific tasks and datasets, lacking a united framework for assessing the multidimensional intelligence of large models. In this perspective, we advocate for a comprehensive framework of cognitive science-inspired artificial general intelligence (AGI) tests, including crystallized, fluid, social, and embodied intelligence. The AGI tests consist of well-designed cognitive tests adopted from human intelligence tests, and then naturally encapsulates into an immersive virtual community. We propose increasing the complexity of AGI testing tasks commensurate with advancements in large models and emphasizing the necessity for the interpretation of test results to avoid false negatives and false positives. We believe that cognitive science-inspired AGI tests will effectively guide the targeted improvement of large models in specific dimensions of intelligence and accelerate the integration of large models into human society.

Beyond the neoliberal label: A historical perspective on sexual actors and responsibility in HIV prevention in England (1986-2023).

Framed across three distinct periods of the history of neoliberalism and the HIV epidemic in England, this article conducts a detailed examination of the concept of personal responsibility and its contested uses within HIV prevention. The article questions the theoretical potential of neoliberal subjectivities to comprehend behaviours related to the pharmaceuticalised governance (or lack thereof) of gay men's sexual health, exploring the gap between theories emphasising individual responsibility and the practical experiences of gay men. The analysis draws on testimonials from gay men in oral history interviews and archival sources. The article illustrates how the pervasive notion of personal responsibility in England has been co-opted by neoliberal ideologies, leading to the stigmatisation of gay men whose sexual behaviours diverge from public health mandates. The widespread stigmatisation resulting from this ideology underscores a significant limitation in the theoretical framework of neoliberal subjectivities. This constraint extends beyond merely failing to grasp the complexity of sexual behaviours; it also reflects a lack of understanding of any other behaviour related to public health. Therefore, the article concludes by advocating the necessity of employing and constructing alternative theoretical frameworks to comprehend the pharmaceutical governance or lack thereof of gay men's sexual health. Through a concise autoethnography of the authors' pharmaceutical sexual health governance, the article introduces the concept of biocommesuration as an illustrative analysis that transcends the limitations of neoliberal subjectivities.