Academic publishing is at a critical juncture. The challenges faced by the academics are mired in controversy. Among theseare three hotly debated concerns. First is the issue of whether technological innovations such as artificial intelligence (AI)improves research efficiency or if its use sacrifices research integrity.Another is the controversy between paywall publishingand open access. Lastly, adapting an appropriate business model for sustainability is a contentious issue and the choice betweena commercial or a university-based publishing platform is a difficult one.

Traditional models of scientific investigation relied on tedious intellectual calisthenics in all aspects of research —identifying research gaps, reviewing of published literature, devising valid methodology, collecting data, analysing results, and,finally, drawing conclusions. With the advent of powerful tools employing artificial intelligence, these heavy tasks are efficientlycarried out. The dilemma lies in determining which parts of the work can be attributed to the authors and which are ascribedto the output of large language models (LLMs) and other automated assistance employed.Despite requiring adequate vettingby experts of these AI-aided output, many in the scientific community still question these methods. Can research employingAI be considered honest work? Will full disclosure answer doubts as to the integrity of the scientific work?

Indeed, LLMs just gather information that is already out there, albeit more efficiently. After all, science progresses bystanding on the shoulder of giants. AI makes such work comprehensive and efficient. Standing on those proverbial shoulders,however, require access to prior work, hence our next challenge in academic publishing--open access versus paid access.Paywalls limit the benefits of valuable research to institutions and universities with the capacity to pay. Excluded from these arethose from low resourced countries, with nations from the global south being affected disproportionately. Additionally, whilenumerous authors appreciate the features of open access as it improves their impact and visibility, many feel unduly burdenedsince the cost of publishing in this format is passed on to them.

This brings us to our third issue: who bears the cost of academic publishing? Indeed, it is a lucrative industry, generatingan annual revenue of US$19 billion and an estimated 40 percent profit margin. Many, however, find fault in this businessmodel as concerns about the profit motives of the commercial publishers far overshadow their sustainability goals.

How do we navigate this landscape of controversies? We, at the ACTA, as part of the community of scholars, would needto clarify our mission. Our goals for this publication should be consistent with our values. These values, such as scientific rigor,integrity, and accountability, should be reflected in our policies. We should be cognizant of the role we play in national scientificdiscourse while we endeavor to make an impact in the global scene. We are accountable to our stakeholders — nurturingearly career scholars, supplying evidence to health policymakers, and being accountable to those who provide resources tosustain us. This stewardship is essential so that ACTA will stand shoulder to shoulder with the giants on which science buildsupon to benefit future generations.

Artificial Intelligence ; Commerce ; Costs And Cost Analysis ; Disclosure ; Drawing ; Efficiency ; Family Characteristics ; Forecasting ; Goals ; Gymnastics ; Health ; Health Resources ; Industry ; Intelligence ; Inventions ; Language ; Literature ; Methods ; Play And Playthings ; Policy ; Publications ; Publishing ; Research ; Residence Characteristics ; Role ; Science ; Shoulder ; Social Responsibility ; Universities ; Ursidae ; Volition ; Work ; World Health Organization

OBJECTIVES

Adiposity rebound (AR), the childhood period at which body mass index (BMI) rises from its lowest point, is linked to increased risk of later obesity. The study aims to determine the average age at AR, describe baseline characteristics and analyze the correlation between these characteristics and timing of AR in a population of Filipino pediatric outpatients.

DESIGN

Seven subjects born between 2016 and 2019 from a University Hospital Outpatient Department participated in this cross-sectional analytic study. Childhood anthropometrics were retrospectively collected to determine the age at AR by plot visual inspection. Sex, birth weight and gestational age were obtained from hospital records; breastfeeding duration, maternal BMI, parental obesity, maternal age, maternal smoking, education, parity and family income were gathered through a questionnaire completed by mothers or guardians. Associations were assessed using bootstrap univariate linear regression.

RESULTS

The mean age at AR was 3.2 years (SD = 1.2). Vaginal delivery was significantly associated with later age at AR compared to cesarean section (p = 0.035). Socioeconomic status at ages 2 to 5 showed positive association with delayed AR. Higher monthly family income (≥₱19,000) at ages 2 to 5 years was significantly associated with delayed age at AR. Other baseline childhood and parental factors showed no significant correlation with age at AR.

CONCLUSION

These results highlight the complex and context-dependent nature of AR, emphasizing the need for further studies to better understand and mitigate early obesity risk in Filipino children.

Human ; Young Adult: 19-24 Yrs Old ; Universities ; Regression (psychology) ; Hospital Records ; Gestational Age ; Body Mass Index ; Obesity, Maternal

OBJECTIVES

Clinical pathways (CPs) ensure adherence to heart failure (HF) management guidelines. To optimize quality care in a low resource setting, an evidence-based care pathway for the management of acute HF was implemented at the emergency department (ED) of the Philippine General Hospital (PGH), the designated national tertiary hospital and referral center. This study aimed to describe the characteristics of adults with acute HF admitted at the ED and evaluate the quality of care they received, measured using physician adherence to the hospital’s acute heart failure CP.

METHODS

This was a retrospective, descriptive cohort study. We reviewed the inpatient charts of all adult patients with acute HF admitted to the ED of the PGH and referred to the Division of Cardiovascular Medicine between December 1, 2022 and May 31, 2023. Quality of care was assessed based on adherence to quality indicators adapted from routine and conditional order sets detailed in the pathway. Descriptive statistics was utilized to describe patient characteristics, quality of care, and outcomes.

RESULTS

Two hundred thirty-six (236) patients were included, with a mean age of 51.8 years. Majority were male (53.4%); hypertension (61.4%) and ischemic heart disease (53.8%) were the most common comorbidities, and infection the most common precipitant of decompensation (60.6%). There were optimal adherence rates to routine orders, which included referrals to Internal Medicine and Cardiology, baseline vital signs monitoring, fluid intake and output monitoring, chest radiograph, complete blood count, blood urea nitrogen, sodium, potassium, prothrombin time, partial thromboplastin time, arterial blood gas, urinalysis, and N-terminal pro b-type natriuretic peptide. Conditional orders, such as oxygen support, focused echocardiography, thyroid - stimulating hormone, and the use of vasopressors, diuretics, and venous thromboembolism prophylactic agents, were optimally performed when warranted. However, we noted suboptimal adherence to certain resource-intensive conditional orders, such as hourly monitoring of urine output (61.4%), hooking to cardiac monitor (53.8%), and performance of 12-lead ECG within 10 minutes (56.8%). Further, only 43.9% of patients were referred to the intensive care unit. Troponin I, calcium, magnesium, and albumin were ordered in excess.

CONCLUSION

Overall adherence rate of physicians to the hospital’s Acute Heart Failure Pathway was satisfactory. Work is needed to improve adherence to hourly urine output monitoring, consistent hooking to cardiac monitor, and timely performance of 12-lead ECG – an effort that begins with expanding in-hospital diagnostic equipment and human resource supply. We recommend continuous pathway implementation with periodic evaluation and stakeholder feedback to further improve quality of care.

Human ; Male ; Female ; Middle Aged: 45-64 Yrs Old ; Adult ; Albumins ; Blood ; Blood Urea Nitrogen ; Calcium ; Cardiology ; Chart ; Charts ; Cohort Studies ; Critical Care ; Critical Pathways ; Diagnostic Equipment ; Disease ; Diuretics ; Echocardiography ; Electrocardiography ; Emergencies ; Emergency Service, Hospital ; Equipment And Supplies ; Evaluation Studies As Topic ; Feedback ; Heart ; Heart Diseases ; Heart Failure ; Hormones ; Hospitals ; Hospitals, General ; Humans ; Hypertension ; Indicators And Reagents ; Infection ; Infections ; Inpatients ; Intensive Care Units ; Internal Medicine ; Lead ; Magnesium ; Male ; Medicine ; Myocardial Ischemia ; Natriuretic Peptide, Brain ; Natriuretic Peptides ; Nitrogen ; Overall ; Oxygen ; Partial Thromboplastin Time ; Patients ; Peptides ; Philippines ; Physicians ; Potassium ; Prothrombin ; Prothrombin Time ; Quality Of Health Care ; Referral And Consultation ; Sodium ; Statistics ; Tertiary Care Centers ; Thorax ; Thromboembolism ; Thromboplastin ; Thyroid Gland ; Time ; Troponin ; Troponin I ; Universities ; Urea ; Urinalysis ; Urine ; Venous Thromboembolism ; Vital Signs ; Work ; Workforce

OBJECTIVES

This study aims to create a study protocol that will explore UST administrators’ perceptions of the benefits and risks of AI use in higher education learning environments.

METHODS

A qualitative descriptive design will be employed, using semi-structured interviews with at least fifteen administrators selected through purposive sampling. Audio-recorded interviews will be transcribed verbatim and subjected to thematic analysis using NVivo software

RESULTS

Administrators from different college-level fields perceive and engage with AI across various academic contexts. Exploring these perceptions will allow guidance in the development of coherent, contextually grounded institutional policies that promote responsible GenAI use and support digital leadership in Philippine higher education.

Human ; Artificial Intelligence ; Universities ; Software ; Administrative Personnel ; Intelligence ; Risk ; Policy

BACKGROUND

Generative artificial intelligence (GenAI) is increasingly integrated into healthcare, including occupational therapy (OT), with potential applications in its service delivery and clinical decision-making. While GenAI offers promising educational and clinical support, its generative nature introduces risks related to contextual accuracy, transparency, and ethical use, particularly within supervised clinical training settings where professional judgment is still developing. Empirical research examining GenAI integration in OT clinical training remains limited, especially within the Philippine context.

OBJECTIVE

This is a protocol for a study which aims to explore the perceptions of OT interns in Manila, Philippines, regarding GenAI integration in clinical training, including perceived benefits, challenges, and ethical considerations, guided by Rogers’ Diffusion of Innovations Theory

METHODS

This qualitative study protocol describes an exploratory design that will be used to gather rich and contextualized insights from 24 to 32 OT interns enrolled in universities in Manila with established institutional AI-use policies. Data will be collected through semi-structured online focus group discussions (FGD). Thematic analysis will be used with assistance from atlas.ti. 

EXPECTED RESULTS

The study is expected to generate meaningful themes that describe the perceptions of OT interns regarding the integration of GenAI within supervised clinical training contexts. Results are expected to reflect how interns perceive the role of GenAI in supporting clinical decision-making, as well as its perceived challenges and ethical concerns related to institutional policies, data privacy, reliability, and variability in AI-generated outputs.

Human ; Therapeutics ; Universities ; Volition ; Philippines ; Clinical Decision-making ; Artificial Intelligence

BACKGROUND

Due to the COVID-19 outbreak, schools had to switch online. The sudden transition to blended teaching and learning (BTL) poses challenges for students and teachers, especially for health science programs that require hands-on practical experience. The validity, reliability, and responsiveness of these self-report questionnaires (SRQs) should be established to ensure the accuracy of the results as intended by the SRQ.

OBJECTIVES

This study critically appraised, compared, and summarized the psychometric properties of SRQ evaluating BTL among health science university students. This review determined the SRQ’s reliability, internal consistency, various forms of validity (content, criterion, construct), and responsiveness.

METHODS

Following a 10-step procedure based on COSMIN guidelines, we conducted a systematic review of SRQs used by health science university students to evaluate blended teaching and learning. Studies were eligible if they reported psychometric properties of SRQs related to blended learning among university health science students; exclusions included studies focusing on perceptions, attitudes, self-efficacy, and satisfaction, as well as articles such as biographies, editorials, and conference materials. Searches covered multiple electronic databases until April 26, 2023, including PubMed, EMBASE, Web of Science, MEDLINE (OVID), PsycInfo, CINAHL, EBSCOHOST, ERIC, Scopus, Science Direct, Google Scholar, JSTOR, Acta Medica Philippina, Philippine Journal of Health Research and Development, and HERDIN, managed through Zotero. Two independent reviewers performed database searches, title and abstract screening, and full-text evaluations, with a third reviewer resolving any disputes. The COSMIN Risk of Bias Checklist was employed to evaluate included studies on the development and various measurement properties of SRQs. The reviewers assessed SRQ standards, including validity, reliability, internal consistency, measurement error, responsiveness, interpretability, and feasibility. Data extraction and result tabulation were independently completed, with content comparison by two health education experts. This evaluation categorized the SRQs into three quality and validity levels.

RESULTS

The study examined five articles; four were rated as 'doubtful' and one as 'inadequate' in the overall development of SRQ. All four 'doubtful' studies demonstrated questionable content validity when university students were asked about the questionnaire's relevance, comprehensiveness, and comprehensibility. Only half of these studies achieved an 'adequate' rating for content validity based on expert opinions on relevance and comprehensiveness. All but one study scored from 'very good' to 'adequate' in structural validity. Three out of the four studies scored a very good rating for internal consistency, while one was deemed 'inadequate' in internal consistency, cross-cultural validity, and reliability. Three out of four studies scored 'very good' on construct validity, but all overlooked criterion validity and responsiveness. Conducted in various locations, including Australia, Romania, Turkey, and Taiwan, these studies highlighted both common characteristics and limitations in questionnaire development according to the COSMIN guidelines. Four studies were deemed reliable and valid for BTL constructs (Category A); Wu et al. requires further validation (Category B). Study limitations included heterogeneity in populations, settings, and questionnaire versions, potential subjective bias in SRQ content comparison, and the evolving nature of SRQs in blended learning contexts.

CONCLUSION

The systematic review reports the development and evaluation of SRQs for BTL while identifying gaps in their applicability to health science programs. The Blended Learning Scale (BLS) of Lazar et al. and the Blended Learning Questionnaire (BLQ) of Ballouk et al. showed an ‘adequate' rating for content validity. BLS revealed very good structural validity, internal consistency, and adequate content validation. Although the BLQ lacked Confirmatory Factor Analysis, it yielded valuable constructs for evaluating health sciences students' experiences in BTL. Both tools require improvements on recall period, completion time, interpretability, and feasibility. The review underscores the necessity for cont inuous assessment and enhancement of such instruments in BTL, advocating a rigorous scale development process. Furthermore, it encourages the customization of teaching and learning evaluation tools to suit specific institutional contexts while promoting further validation of these questionnaires across different populations in future research.

Human ; Psychometrics ; Checklist ; Self Report ; Universities ; Health Education

BACKGROUND AND OBJECTIVE

The COVID-19 pandemic has disrupted the sports industry, resulting in the postponement of events worldwide. This posed a significant burden in the mental and emotional well-being of athletes due to uncertainties and diminished training levels. As an adaptation, bubble camps emerged as a new approach to resuming training and tournaments under stringent regulations of the COVID-19 protocols. In the national context, the University Athletic Association of the Philippines (UAAP) has adapted the bubble set-up by implementing antigen testing, RTPCR, and other health protocols as a prerequisite to bubble training. However, uncertainties in the future of sports continue to present as a psychological toll to the well-being of student-athletes despite the sense of normalcy instilled by bubble training. Existing literature on bubble training is grounded heavily on the quantitative assessments of an athlete's well-being in a bubble set-up and its effectiveness in mitigating COVID-19 transmission, thereby lacking insights that may be obtained from qualitative data. This study explored the experiences of UAAP Season 84 studentathletes in a bubble set-up by examining personal and contextual factors that impacted their well-being.

METHODS

The study employed a qualitative descriptive phenomenological approach based on Seligman's WellBeing Theory. A purposeful sampling technique was used to recruit UAAP student-athletes through online dissemination of Google Forms for recruitment. Only three student-athletes from UAAP fit the eligibility criteria. Data were collected through on-site and online interviews using a semi-structured interview guide to reveal a narrative of the student-athletes' bubble training experiences, common themes, and patterns. The NVivo software program was used for data analysis, utilizing a deductive thematic approach.

RESULTS

The lived experiences of three UAAP studentathletes were classified into six major themes: (1) Availability and Accessibility of Services; (2) Restrictions; (3) Mental Health; (4) Fostering Relationships; (5) Support Systems; and (6) Individual Growth. Accounts of both positive and negative training perceptions and outcomes regarding the bubble set-up were noted from all student-athletes. The set-up provided studentathletes with easy access to training facilities and services, eventual development of mental fortitude and  perseverance, improved interpersonal relationships, and opportunities for individual growth. However, the restrictions, isolation, internal and external pressures, and routinary nature of the set-up contributed to the elevated levels of stress and anxiety, eventually leading to fatigue and burnout.

CONCLUSION

The study elucidates on the multi-faceted experiences of UAAP student-athletes in bubble training, underpinning the essence of the adequacy of training services and facilities, enhanced support systems, and prompt policy development that caters to improving the holistic well-being of student-athletes amidst adverse changes in the trajectory of sports.

Human ; Qualitative Research ; Universities ; College Athletes ; Athletes

OBJECTIVES: Anxiety is a common negative emotion. Under current social circumstances, university young teachers face multiple stressors and are more prone to anxiety, seriously threatening their physical and mental health. This study aims to investigate the impact of job insecurity on anxiety of university young teachers, while exploring the mediating roles of perceived stress and insomnia on this relationship. METHODS: Using convenience sampling, young teachers from a general university in a Chinese province were surveyed online. Scores of the Job Insecurity Scale, Perceived Stress Scale, Athens Insomnia Scale-Short Form, and Generalized Anxiety Disorder Scale were collected. A chain mediation analysis was conducted using the PROCESS macro. RESULTS: A total of 798 subjects were finally included. The detection rate of anxiety among university young teachers was 36.47%. Mediation analysis showed that job insecurity not only had a direct effect on anxiety, but also indirectly affected anxiety via perceived stress (46.42% of the total effect) and insomnia (7.45%), as well as through the chain-mediating path of perceived stress→ insomnia (13.18%; all P<0.05). CONCLUSIONS Job insecurity is a significant predictor of anxiety in young university faculty. Perceived stress and insomnia serve as sequential mediators in this relationship. Targeted interventions addressing job insecurity, stress perception, and sleep disturbances, alongside efforts to improve mental health literacy and the working environment, may help promote the overall well-being of university young teachers.
Humans ; Sleep Initiation and Maintenance Disorders/epidemiology* ; Universities ; Female ; Anxiety/psychology* ; Male ; Stress, Psychological/psychology* ; Adult ; Faculty/psychology* ; Surveys and Questionnaires ; China/epidemiology* ; Occupational Stress ; Job Security

OBJECTIVES: Mobile phone dependence has become increasingly prominent among university students, posing significant risks to their social functioning and mental health. Previous studies suggest that perfectionistic personality traits may be key psychological predictors of mobile phone dependence, but the underlying mechanisms remain unclear. This study aims to identify core symptoms of mobile phone dependence among university students and to examine the pattern of associations between different dimensions of perfectionism and mobile phone dependence. METHODS: A cross-sectional questionnaire survey was conducted among 1404 university students nationwide. The Mobile Phone Involvement Questionnaire (MPIQ) and the Forst Multidimensional Perfectionism Scale (FMPS) were used to assess mobile phone use and perfectionism traits. The EBIC-GLASSO network model was constructed to analyze the network structure linking perfectionism and mobile phone dependence. RESULTS: A total of 56.48% of university students in the sample met the criteria for mobile phone dependence. The total FMPS score was positively correlated with the total MPIQ score (r=0.47, P<0.001). Results of multiple linear regression controlling for demographic variables showed that dimensions of FMPS score significantly predicted MPIQ score (all P<0.05). Network analysis revealed that the central dimension in perfectionism is "organization" (expected influence=2.69) and the core symptom of mobile phone dependence was "I lose track of how much I am using my smartphone" (expected influence= 0.78). Bridge centrality analysis identified "organization" as a key bridging factor linking perfectionism and mobile phone dependence (bridge strength=1.96). Among the symptom-to-symptom connections, "parental expectations" showed the strongest positive association with "arguments have arisen with others because of my mobile phone use" (partial correlation coefficient=0.15), serving as a risk factor. In contrast, "organization" was most strongly negatively associated with the same symptom (partial correlation coefficient=-0.13), serving as a protective factor, suggesting a protective effect. CONCLUSIONS Mobile phone dependence is common among college students and is primarily characterized by a lack of self-control in phone use. Although perfectionism is generally positively associated with mobile phone dependence, its internal dimensions appear to exert a dual effect. Specifically, "parental expectations" and "doubt over actions" may increase the risk of mobile phone dependence, whereas "organization" serves as a protective factor, particularly against interpersonal conflicts related to phone dependency.
Humans ; Perfectionism ; Students/psychology* ; Cell Phone ; Universities ; Cross-Sectional Studies ; Male ; Female ; Surveys and Questionnaires ; China ; Young Adult ; Adult ; Adolescent ; Personality

OBJECTIVES: We propose a multimodal model integrating social media text and image data for automated assessment of psychological stress in college students to support the development of intelligent mental health services in higher education institutions. METHODS: Based on deep learning technology, we designed an evaluation framework comprising a text sentiment modeling module, an image sentiment modeling module, and a multimodal fusion prediction module. Text sentiment features were extracted using Bi-LSTM, and image semantic cues were extracted via U-Net. A feature concatenation strategy was used to enable cross-modal semantic collaboration to achieve automatic identification of 3 psychological stress levels: mild, moderate, and severe. We constructed a multimodal annotated dataset using social platform data from 1577 students across multiple universities in Guangdong Province. After data cleaning, 252 samples were randomly selected for model training and testing. RESULTS: In the 3-classification task, the model demonstrated outstanding performance on the test set, and achieved an accuracy of 92.86% and an F1 score of 0.9276, exhibiting excellent stability and consistency. Confusion matrix analysis further revealed the model's ability to effectively distinguish between different pressure levels. CONCLUSIONS The multimodal psychological stress assessment model developed in this study effectively integrates unstructured social behavior data to enhance the scientific rigor and practical applicability of psychological state recognition, and thus provides support for developing intelligent psychological service systems.
Humans ; Stress, Psychological/diagnosis* ; Students/psychology* ; Universities ; Social Media ; Deep Learning