Sample Size Selection Research Articles

Evaluation of the Effect of 2022 Flooding on Business Activities in Lokoja Metropolis

Flooding has become a global issue and its effect varies with the level of flooding at a given period. In the wake of urban floods, public and commercial institutions are currently finding it difficult to develop and assess risk management and adjustment methods that include land use planning and urbanization patterns in addition to systems for flood prevention and early notifications. Flooding is one of the negative effects of global warming and most countries in the world are making effort to reduce its associated effects. This study examined the effect of 2022 flooding on business activities in Lokoja Metropolis. The study used a survey research design and a Taro Yamani sample size selection method to select 400 respondents. Questionnaire was administered to the respondents based on simple random selection and the data was analysed using Analysis of Variance (ANOVA) regression. The findings show that 2022 flooding exerts negative and statistically significant effect on business activities. there was low business patronage and high cost of goods during the flood period. Also, the findings show that small businesses were mostly affected during the flood period than large businesses. The study therefore recommends dredging of the River Niger and River Benue to increase water holding capacity. Also, there should be enactment of laws against building or citing of businesses along flood route to reduce the level of damages during flooding

Medial quadriceps tendon femoral ligament reconstruction and medial patellofemoral ligament reconstruction have no significant differences in clinical outcomes for treatment of lateral patellar instability: a matched-cohort study

ObjectivesThe purpose of this study was to compare clinical outcomes of medial quadriceps tendon-femoral ligament reconstruction (MQTFLR) and medial patellofemoral ligament reconstruction (MPFLR) among patients with recurrent lateral patellar instability. MethodsA retrospective matched-cohort study was conducted involving patients who underwent MQTFLR or MPFLR with or without tibial tubercle osteotomy (TTO) from 2019 to 2021. Subjects were matched 1:1 on age, concomitant osteochondral allograft (OCA), concomitant TTO, and follow-up time. Measured outcomes included 90-day complications, Visual Analog Scale (VAS) knee pain, return to sport/work, Kujala score, Tegner score, and MPFL-Return to Sport after Injury (MPFL-RSI) score. Outcomes were compared between groups using Mann–Whitney U-test for continuous variables and Fisher's exact test for categorical variables. P-values <0.05 were considered significant. ResultsTen MQTFLR patients (mean age 28.7 years, 80% female, mean follow-up 19.7 months) and ten MPFLR patients (mean age 29.1 years, 90% female, mean follow-up 28.3 months) were included in the study. One MQTFLR patient (10%) and three MPFLR patients (30%) underwent reoperation for postoperative arthrofibrosis. Postoperative VAS resting pain was not significantly different between the groups (MQTFLR mean 1.1, MPFLR mean 0.6, p ​= ​0.31). There were no significant differences in rates of recurrent subluxations (MQTFLR 20%, MPFLR 0%, p ​= ​0.47), return to sport (MQTFLR 50%, MPFLR 75%, p ​= ​0.61), return to work (MQTFLR 100%, MPFLR 88%, p ​= ​1.00), or MPFL-RSI pass rate (MQTFLR 75% vs. MPFLR 38%, p ​= ​0.31). ConclusionThere were no significant differences in knee pain and function, return to work, and rates of recurrent patellar instability between patients who underwent MQTFLR versus MPFLR, though these results should be interpreted with caution given the small sample size and potential selection bias. Level of EvidenceIII.

The strategic vision of the Directorate of Sports and Scout Activity in Education of Salah al-Din from the viewpoint of teachers and teachers of physical education

It will look for the strategic theory of the Directorate of Sports Activity and Kafawi in the Directorate of Education Salahuddin, in light of the variables of character (teachers, teachers) and geographical location, years of service.Seeking a range of philosophies (school, district, and district) and between (age groups).The researcher used the descriptive method - the survey method - in search of your school teachers and the school of physical education in the Directorate of Education Salah al-Din, the number (30) were selected sample size (10) sample sample exploratory experiment, and then another sample of (20) The main research, number (30).The researcher used the strategic viewfinder as a key tool for data collection. . . And after ascertaining that the property characteristics are met (honesty, consistency). . . The researchers applied the scale to the main sample. Using statistical pouch (spss), the data was processed and the results were presented.In the light of the results of the research, the researcher reached some conclusions that the Directorate of Sports Activity and Scouts in the Directorate General of Education Salahuddin, does not have a strategic vision from the point of view of teachers and teachers of physical education. The results did not indicate a difference in the opinion of the research sample in the strategic vision.

Nonparametric Bayesian functional clustering with applications to racial disparities in breast cancer

AbstractAs we have easier access to massive data sets, functional analyses have gained more interest. However, such data sets often contain large heterogeneities, noises, and dimensionalities. When generalizing the analyses from vectors to functions, classical methods might not work directly. This paper considers noisy information reduction in functional analyses from two perspectives: functional clustering to group similar observations and thus reduce the sample size and functional variable selection to reduce the dimensionality. The complicated data structures and relations can be easily modeled by a Bayesian hierarchical model due to its flexibility. Hence, this paper proposes a nonparametric Bayesian functional clustering and peak point selection method via weighted Dirichlet process mixture (WDPM) modeling that automatically clusters and provides accurate estimations, together with conditional Laplace prior, which is a conjugate variable selection prior. The proposed method is named WDPM‐VS for short, and is able to simultaneously perform the following tasks: (1) Automatic cluster without specifying the number of clusters or cluster centers beforehand; (2) Cluster for heterogeneously behaved functions; (3) Select vibrational peak points; and (4) Reduce noisy information from the two perspectives: sample size and dimensionality. The method will greatly outperform its comparison methods in root mean squared errors. Based on this proposed method, we are able to identify biological factors that can explain the breast cancer racial disparities.

Conflict in Healthcare: Examining the Role of Social Media and Smartwatches on Healthcare Delivery in Among Students of Afe Babalola University, Ado-Ekiti

Social media can be an instrument that fosters peace and wellbeing. It can also be used to incubate hatred and fan violence. A man’s health can affect his peace and how he relates and function in the world. Social media ensures the swift flow of information between people irrespective of geographical borders. It is therefore pertinent that accurate information and data be corroborated swiftly so as to prevent misleading information dangerous to the health, peace and wellbeing from spreading to the general public. The research looked into how the social media and smartwatches impact on healthcare management and personal wellbeing. The study was conducted among the postgraduate students of Afe Babalola university Ado Ekiti, Nigeria. The selected sample size for the study comprised of 60 participants who were purposively selected and issued survey questionnaires. The study found out that the social media has led to the rise of false information about health practices among graduate students. The study also found that smartwatches has a positive significant effect on health management among graduate students in ABUAD.

A variable metric proximal stochastic gradient method: An application to classification problems

Due to the continued success of machine learning and deep learning in particular, supervised classification problems are ubiquitous in numerous scientific fields. Training these models typically involves the minimization of the empirical risk over large data sets along with a possibly non-differentiable regularization. In this paper, we introduce a stochastic gradient method for the considered classification problem. To control the variance of the objective's gradients, we use an automatic sample size selection along with a variable metric to precondition the stochastic gradient directions. Further, we utilize a non-monotone line search to automatize step size selection. Convergence results are provided for both convex and non-convex objective functions. Extensive numerical experiments verify that the suggested approach performs on par with state-of-the-art methods for training both statistical models for binary classification and artificial neural networks for multi-class image classification. The code is publicly available at https://github.com/koblererich/lisavm.

Principals’ Use of School Curriculum and Promotion of Social Cohesion in Public Secondary Schools in Machakos County, Kenya.

This study sought to investigate how principals’ use curriculum in promoting social cohesion in public secondary schools in Machakos County. The study was guided by the ecological systems theory of human development and socialization. The study adopted the descriptive survey research design wherein a target population of 375 principals’ and 9 Sub County Directors of Education were respondents. Further, the study used stratified proportionate sampling in selecting sample sizes for the study in which case a sample size of 113 principals and 9 Sub County Directors of education totaling to 122 respondents were surveyed. Data was collected using questionnaires, interview schedules and document analysis. Quantitative data was processed and analyzed using SPSS software version 26 and presented in tables. Simple regression analysis was employed in testing hypotheses of the study for inferences. While qualitative data was transcribed into themes and presented in narratives. The findings of the study revealed that principals use of school curriculum t (113) = 10.316; p was statistically significant in contributing to the promotion of social cohesion in public secondary schools in Machakos County. The study recommends among others that MOE makes value creating education mandatory in the school curriculum. Further principals should ensure language policy in schools is enhanced and prohibit the use of vernacular language in schools.

Strategic Integration of Artificial Intelligence in Health-care Systems: Assessing Costs, Technological Upgrades, and Training Timelines

BACKGROUND: In recent years, the evaluation of artificial intelligence (AI) in health-care sector has undergone significant growth and is substantially helpful in supporting clinical decision-making based on evidence. The primary aim of the study is to investigate the strategic integration of AI in health-care systems, specifically focusing on assessing costs, technological upgrades, and training timelines. MATERIALS AND METHODS: This study followed quantitative techniques to explore the AI integration’s importance in the systems of health care highlighting training timelines, upgradation of technology, and associated costs. Using descriptive statistics, data were evaluated and a survey was performed on the professionals of emergency medical care. The study employed a combination of descriptive statistics analysis, such as mean and median calculations, to analyze the data. To select participants, this study applied purposive sampling. The selected sample size of the study was 242 from the Indian health-care context. RESULT: The results of this study indicated that clear training timelines establishment, technological upgradation, and cost assessments are important for successfully integrating AI technologies. In addition, the discussion explored the acceptance of the significance of stakeholders’ collaboration, cost-effective strategies for training, and information technology infrastructure enhancements. The training costs for AI implementation in health care, with 66.12%–69.83% of respondents selecting “strongly agree” and 25.21%–29.75% selecting “agree.” Strong consensus on the necessity of providing specific timelines for AI implementation in emergency departments, with “strongly agree” responses ranging from 66.12% to 68.60%, and “agree” responses from 26.45% to 29.75%. Issues including timeline adherence and funding constraints were discovered, focusing on the necessity for proactive management. CONCLUSION: This research highlighted comprehensive planning’s major role in the integration of AI. Health-care organizations by addressing training timelines, technological upgradation, and cost optimize the incorporation of AI. However, engagement with different financial experts and collaboration with stakeholders are necessary for successfully achieving organizational goals.

The effects of fasting compared to eating a meal or snack during simulated night shift on changes in metabolism associated with circadian misalignment: a protocol and methods paper.

This protocol paper outlines the methods that will be used to examine the impact of altering meal timing on metabolism, cognitive performance, and mood during the simulated night shift. Participants (male and female) will be recruited according to an a priori selected sample size to complete a 7-day within and between participant's laboratory protocol. Participants will be randomly assigned to one of the three conditions: meal at night or snack at night or no meal at night. This protocol includes an 8-hour nighttime baseline sleep, followed by 4 consecutive nights of simulated nightshift (7 hours day sleep; 10:00-17:00 hours), and an 8-hour nighttime sleep (return to dayshift). During the simulated night shift, meals will be provided at ~06:30, 09:30, 14:10, and 19:00 hours (no eating at night); ~06:30, 19:00, and 00:30 hours (meal at night); or ~06:30, 14:10, 19:00, and 00:30 hours (snack at night). Meal composition will be strictly controlled throughout the study (45%-65% carbohydrates, 15%-25% protein, and 20%-35% fat per day) with daily energy provided to meet individual needs using the Harris-Benedict equation (light/sedentary activity). The primary outcome measures are serum concentrations of blood glucose, insulin, and free fatty acids area under the curve in response to the oral glucose tolerance test. Mixed-effect ANOVAs will be conducted. This protocol paper describes a methodology to describe an innovative approach to reduce the metabolic disease impact associated with shift work.

Role of social media in lead generation

The role of social media in lead generation is pivotal for contemporary businesses seeking to expand their customer base. Social media platforms serve as dynamic channels for brand promotion, offering widespread visibility and engagement opportunities. Through targeted advertising, businesses can reach specific demographics, ensuring a higher quality of leads. Content marketing on social media, including informative posts and interactive content, establishes credibility and attracts potential leads. Direct interaction with the audience fosters relationships and builds trust, guiding leads through the sales funnel. Additionally, social media facilitates the promotion of lead magnets, such as eBooks or webinars, incentivizing users to provide contact information. Positive social proof garnered through reviews and testimonials enhances a business’s credibility. The objective of the present study is to study the impact of social media on lead generation. The researchers have used descriptive research design for the present study. The nonprobability convenience sampling method is used for the selection of sample size. The data is collected from 215 respondents, with the help of a well-structured questionnaire using the survey method. The results of this study will be helpful to companies in designing their social media strategies to get more leads for their business.

Impact of Human Intelligence on Organizational Outcomes: The Moderating Role of Machine Intelligence

This study aims to assess the collective impact of human and machine intelligence on the organizational performance of banking sector employees. A quantitative, deductive research approach is applied to this research. Data is collected through non-probability, and convenience sampling techniques and the selected sample size was 351 for this PLS-SEM (structural equation modeling) was used for data analysis through SMART PLS. The research indicates that EI and CQ influence employee performance. However, the study highlights a minimal moderating effect of employee AI capability in their interactions with customers. In Pakistan, enhancing employee commitment to improving customer experience is essential. This can be achieved by connecting customer feedback to how employees provide services. This connection can substantially improve AI capabilities and overall service quality, particularly in terms of external service performance and organizational outcomes. The definition of emotional and cultural attributes varies from respondent to respondent. Time limitation was also another factor while conducting this research. The data is collected only by Karachi-based banking employees in this way the findings are limited to location. The study emphasizes the paramount of EI on organizational performance internal or external so, to gain competitiveness there is a need to strengthen the EI of employees by involving them in the communication and decision-making process of the organization.

Estimating Mincerian Earning Function for Engineering Trainings in Pakistan

Mincerian Earning Function (MEF), with its standard assumptions, is a dominant model to estimate earning returns to education through its earning-schooling relationship in labor markets. This study explores empirical evidence to estimate the MEF for different years of engineering training in Pakistan. The theoretical model of MEF is used to specify the main determinants of general education, experience, engineering training, and other variables to show a snapshot of technical training and earning relationships in Pakistan. The instrumental variable two stages least square (IV2SLS) technique gives estimates of MEF for the selected sample size of 371 qualified respondents in the fields of engineering education and training in this study. The two-stage random sampling technique is used to collect cross-sectional data, and the results are statistically significant for general education and engineering training in the case of Pakistan. General education, experience, engineering training, and the provinces associations for the respondents likely influence the log earnings of the respondents. The results put forth insightful policy implications for national and provincial public policy processes for human capital formation in the fields of science and technology.

Management education system in the 21st century: Challenges and opportunities

Management education in the 21st century is facing a dynamic and rapidly changing landscape, presenting both challenges and opportunities. It is characterized by its adaptability, technology integration, global orientation, emphasis on soft skills, and a commitment to ethical and sustainable business practices. It aims to produce well-rounded, agile, and socially responsible leaders who can navigate the complexities of the contemporary business landscape. The objective of the present study is to study the present scenario of management education system in India and to identify the challenges and opportunities in front of education sector. The researchers have used descriptive research design for the present study. Non probability convenience sampling method is used for selection of sample size. The data is collected from 285 respondents, with the help of well-structured questionnaire using survey method. The results of this study will be helpful to management education institutes to develop their academic curriculum and future expansion. Keywords: Students, Management Education, Opportunities, Challenges.

Institutional Framework as a Determinant of Variations in Service Quality Between Public and Private Hospitals in Tanzania

Purpose of the article: This study was set to determine the influence of institutional framework on service quality in both private and public hospitals. The paper sought to establish the perception of respondents regarding the institutional factors that explain the existence of variations in service quality between public and private hospitals. The institutional framework aspects that were considered in comparing health service quality in public and private hospitals were: institutional culture, control, stability and structure. A descriptive survey design was used because the study sought to know the perception of respondents regarding the factors that influence quality of service in hospitals. Research methods: A multistage sampling method was used to select three public hospitals and three private hospitals from the health service sector. The three public hospitals were Muhimbili referral hospital in Dar es Salaam City, Dodoma regional referral hospital and Geita referral hospital in Geita municipality. Private hospitals included in the study were Bugando referral hospital in Mwanza City, St Francis referral hospital in Ifakara town in Morogoro region and Nkinga referral hospital in Tabora region. Medical doctors, nurses and patients were selected using a systematic random sampling method and patients were selected using a convenience sampling method. The total population for the study comprised 10,650 people (i.e. 2,610 doctors and nurses and 8,040 patients) and the selected sample size, which was determined using McCall’s Table was 400 people. Both primary and secondary data collection sources were used. Analysis of the quantitative data was done using the Statistical Package for Social Sciences (SPSS) and qualitative data were transcribed verbatim, coded and analysed manually. All ethical considerations were observed. Main findings: The findings revealed that private hospitals were better in cleanliness compared to public hospitals and physical arrangement was user friendly in private hospitals compared to public hospitals. There was also more control in private hospitals compared to public hospitals in management of resources and this demonstrates an application of strong institutional framework in private hospitals compared to public hospitals in terms of control, structure and culture. Likewise, there was a more friendly atmosphere in private hospitals compared to public hospitals. However, there was more stability in public hospitals compared to private hospitals in terms of financial stability, affordability of service and medical supplies. It is concluded that quality of service provided in private hospitals is higher compared to quality of service in public hospitals. The possible explanation for the causes for differences in levels of service quality could be the existence of strong institutional framework in private hospitals. It is recommended that for higher service quality, organizations should practice the institutional framework aspects in terms of culture, control, stability and structure.

Spatial predictions of groundwater potential using automated machine learning (AutoML): a comparative study of feature selection and training sample size in Qinghai Province, China.

Predicting groundwater potential is crucial for identifying the spatial distribution of groundwater in a region. It serves as an essential guide for the development, utilization, and protection of groundwater resources. Previous studies have primarily emphasized finding the most accurate prediction model for groundwater potential while giving less attention to the selection of training features and sample sizes. This study aims to predict groundwater potential within Qinghai Province using automated machine learning technology and assess the influence of sample sizes and feature selection on prediction accuracy. Sixteen groundwater conditioning factors were categorized into categorical and numerical variables. Four feature selection modes were utilized as input in training the model. The results indicated that, except for correlations between evaporation and landforms (- 0.8) and precipitation and normalized difference vegetation index (0.8), the Pearson correlation coefficients among the remaining sixteen factors were ≤ 0.5 or ≥ - 0.5. The models XGB-ALL, RF-Entropy, ET-CRITIC, and XGB-PCA yielded accuracy scores of 0.783, 0.685, 0.745, and 0.703, and area under curve (AUC) of 0.819, 0.724, 0.779, and 0.747, respectively. If enough samples are available with the tree model, an increased number of features can improve prediction accuracy. The principal component analysis method showed difficulty in reducing the dimensionality of the input space, while the Entropy method proved efficient. The accuracy and AUC value of the prediction model improved with an increasing number of samples. Training with 8 features and 200 data points achieved an accuracy of 0.745, sufficient to evaluate regional groundwater potential. As for training with 600 samples, the model's performance accuracy rose to 0.9, enabling precise groundwater potential prediction. The outputs of this research can provide decision-makers in groundwater resource management in Qinghai Province with crucial theoretical and practical support. The lessons learned can have future applications in similar situations.

Relationship between Teacher's Interpersonal Supervisory Competencies and Students' Academic Performance in Hoima District Government-Aided Secondary Schools, Uganda

Teachers are the cornerstone of a vibrant and sound education system, and their competencies, work ethic, and motivation are key in guaranteeing quality learner outcomes and the realisation of the national goals of education. Application of teacher interpersonal, supervisory competencies (TISC) during instruction is deemed to significantly impact student's academic performance, but this has not been so in Hoima District Government-aided secondary schools in Uganda. This is despite continued teacher instructional supervision, various legal provisions in place and government financing. The study assessed the relationship between Teachers' interpersonal and supervisory competencies and students' academic performance, to make recommendations to improve the situation. Self-efficacy and Self-determination theories premised the study of 149 respondents using a post-positivism paradigm, mixed-methods approach, where purposive and simple random sampling techniques were used in selecting sample size. Data was collected using a questionnaire, interview schedule and document analysis. Findings indicated a positive significant Pearson correlation coefficient (r (142) = 0.712, P&lt;0.01) and inadequate teacher practising of a number of interpersonal competencies. Recommendations were: District Administration, Head teachers, School Boards, and parents should apply multifaceted approaches towards teachers encompassing professional development workshops and training sessions to develop their interpersonal and supervisory skills, increase their awareness on various social issues, and enhance their creativity and inventiveness in the supervision of student learning. This is in addition to developing supportive policies and practices regarding teaching resources and welfare. Additionally, teachers should maintain a collaborative relationship with parents/guardians and colleagues to develop and practice supportive, integrative, individualised attention to students while promoting collaborative networks with colleagues. The study further proposes that similar studies be carried out in other Government-aided secondary schools and private ones in Uganda

Effect of Adolescents and Sexual Reproductive Health Policy on Girl Child Retention in Public Secondary Schools in Butula Sub-County, Kenya

The challenge of girls' retention in educational institutions has been identified as a significant obstacle. The inability to maintain the enrollment of female students in secondary schools can be regarded as a squandering of valuable human capital and financial investments made in their primary education, as well as a loss of time invested in their initial enrollment. These young females have the potential to develop into a demographic of women lacking in literacy skills, resulting in diminished economic, social, and political contributions. Among the critical contemporary social issues affecting many countries is teenage pregnancies. The matter of ASRH is a global issue affecting both developed and underdeveloped countries. The problem has drawn attention of governments from both developed and underdeveloped nations. Researchers have also given it consideration and studied it to some extent in their efforts to solve the recurring puzzle of solving the sex related matters that affect adolescents. This research was guided by a general objective, the effect of adolescents and sexual reproductive health policy on girl child retention in public secondary schools in Butula sub-county, Kenya. The study also adopted specific objective as; i)To assess the effect of educational opportunities on girl child retention in public secondary schools in Butula Sub-county Kenya.The study was guided by Human Capital theory of adolescence. Research adopted the descriptive survey design. The study also targeted a sample size of 488 respondents, out of the targeted population of 1335 respondents. The criteria for selecting sample size using convenient and purposive sampling techniques was fixed upon Mugenda and Mugenda (2004) formula. Also, the data from both primary and secondary sources was utilized in the study. The instruments for gathering the data comprised questionnaires, interviews, and records from the schools. Before utilizing the instruments in this research, they were tested using test-retest methods to ascertain validity and reliability. To establish links between variables, the study used correlational analysis. Precisely, a SPSS version 25 was used when seeking to establish any link between the Adolescent Sexual Reproductive Health Policy and girl child retention in public secondary schools Butula Sub-County, Busia County. There is an expectation that this study increased towards knowledge or understanding of the effect of teenage pregnancy on class attendance in public secondary schools in Butula Sub-county. Due to the sensitivity of the research all information that was obtained it was regarded as confidential and the participants including the schools kept it anonymous. Also, no one was coerced to become part of the sample space, but consent was the criteria upon selection of respondents in the study. Therefore, this study involved the highest level of confidentiality, acknowledgment and consent when dealing with respondents and sources of data. The finding of the study was that ASRH services were significant to girl retention in schools. Moreover, it was found that information on ASRH on girls’ retention was from media and school. This study recommends that school administrators assume the role of fostering a collaborative relationship between schools and the community. This partnership would facilitate the identification of opportunities for teachers, parents, and community members to collaborate in order to enhance the educational outcomes of students.

The Effect of Computer Self-Efficacy and Utilisation of Electronic Information Resources by Students of a Nigerian University

The study examined the effect of computer selfefficacy, college affiliation, year of study and barriers to utilisation of electronic information resources (EIRs) by students of Samuel Adegboyega University, Ogwa, Edo State, Nigeria. The study undertook quantitative research. Stratified simple random technique was used to select sample size of 200 respondents from 374 undergraduate students of Samuel Adegboyega University, across the three Colleges in the University. Structured questionnaire was used for data collection. Data were analysed using inferential statistics. The study indicated students had high-level of computer self-efficacy in relation to the utilisation of EIRs and high level of utilisation of EIR. The study showed computer self-efficacy, College and Year of study positively influenced students’ utilisation of EIRs. Erratic power supply and poor internet connectivity were the barriers to effective utilisation of EIR by students.

Assessment of Maize Storage Techniques Utilized by Small- Scale Farmers in Anambra State, Nigeria

The study accessed maize storage techniques utilized by small-scale farmers in Anambra State, Nigeria, due to lack of modern and appropriate storage technologies for grains. The specific objectives includes; socio-economic characteristics; methods of storage techniques; reasons for storing; effects of socio-economic factors on maize revenue; and challenges faced by the respondents. Multi- stage sampling techniques were employed to select sample size of 120 respondents. Primary data were collected through the use of questionnaire and interview schedule. Data obtained were analyzed with descriptive and inferential statistics. The results revealed that 65.8% were female, 67.5% married, 80.0% were literate, and annual income of N511.13. 80.0% stored maize in cribs and identified household consumption and increased income as their major reasons for storing maize. The regression analysis indicated a significant and positive relationship between total revenue and storage cost at 1% and 5% probability levels. The factors that constrained the respondents includes; pests and insects (m=2.92); lack of modern method and management (m=2.83); and lack of extension agents (m=2.75) The study suggests that the maize storage farmers should be encouraged to reduce pests and diseases, trained and motivated to use modern storage facilities. Finally, extension agents should sit-up to its responsibilities in the dissemination of useful information to maize farmers.

Individualized Virtual Reality for Increasing Self-Compassion: Evaluation Study.

Depression and anxiety are common and debilitating mental disorders with severe negative repercussions at both individual and societal levels. Although virtual reality (VR) has emerged as a safe and effective tool for the treatment of anxiety disorders, studies of the therapeutic application of VR to treat depression are more limited. The purpose of this study was to test whether a novel type of individualized VR (iVR) can be used to improve self-compassion and decrease depressive symptoms and to evaluate the usability and acceptability of this approach, as rated by participants. The iVR system was designed and developed based on the feedback obtained from a previous study, with improved appearance and feel of the avatar and enhanced graphical quality. A total of 36 young adult participants were recruited from a university community social media site. Participants were aware that the study was investigating a treatment for depression but were not recruited based on depression diagnosis. Participants were asked to complete 2 iVR sessions, spaced 2 weeks apart. At baseline and upon completion of each iVR session, participants were asked to complete validated measures of self-compassion and depression. Upon completion of both iVR sessions, additional measures were administered to assess participants' perceptions about the perceived usability and system acceptability of the iVR approach. Self-compassion was assessed at the beginning of session 1 (preintervention baseline) and at the end of session 1 (postintervention assessment). Owing to COVID-19 constraints, 36% (13/36) of the participants were unable to complete the follow-up iVR session. Self-compassion was assessed again for the remaining 64% (23/36) of the participants at the end of session 2 (postintervention assessment). Within-group analyses revealed that self-compassion was significantly increased at the end of both session 1 (P=.01) and session 2 (P=.03) relative to baseline. There was also a nonsignificant trend for depressive symptoms to be low at the end of session 2 relative to baseline. Both quantitative and qualitative participant data supported the iVR approach as being acceptable and usable. Although these data must be treated as preliminary owing to the small sample size and potential selection bias, the data provide encouraging initial evidence that iVR might be a useful tool to enhance self-compassion and reduce depressive symptoms, highlighting the need for randomized controlled trials in the future.