Cost and time control of construction project: inhibiting factors and mitigating measures in practice

Despite the availability of various control techniques and project control software many construction projects still do not achieve their cost and time objectives. Research in this area so far has mainly been devoted to identifying causes of cost and time overruns. There is limited research geared towards studying factors inhibiting the ability of practitioners to effectively control their projects. To fill this gap, a survey was conducted on 250 construction project organizations in the UK, which was followed by face-to-face interviews with experienced practitioners from 15 of these organizations. The common factors that inhibit both time and cost control during construction projects were first identified. Subsequently 90 mitigating measures have been developed for the top five leading inhibiting factors—design changes, risks/uncertainties, inaccurate evaluation of project time/duration, complexities and non-performance of subcontractors were recommended. These mitigating measures were classified as: preventive, predictive, corrective and organizational measures. They can be used as a checklist of good practice and help project managers to improve the effectiveness of control of their projects.

Psychological risk factors for chronic post-surgical pain after inguinal hernia repair surgery:a prospective cohort study.

A significant proportion of patients experience chronic post-surgical pain (CPSP) following inguinal hernia surgery. Psychological models are useful in predicting acute pain after surgery, and in predicting the transition from acute to chronic pain in non-surgical contexts. This is a prospective cohort study to investigate psychological (cognitive and emotional) risk factors for CPSP after inguinal hernia surgery. Participants were asked to complete questionnaires before surgery and 1 week and 4 months after surgery. Data collected before surgery and 1 week after surgery were used to predict pain at 4 months. Psychological risk factors assessed included anxiety, depression, fear-avoidance, activity avoidance, catastrophizing, worry about the operation, activity expectations, perceived pain control and optimism. The study included 135 participants; follow-up questionnaires were returned by 119 (88.1%) and 115 (85.2%) participants at 1 week and 4 months after surgery respectively. The incidence of CPSP (pain at 4 months) was 39.5%. After controlling for age, body mass index and surgical variables (e.g. anaesthetic, type of surgery and mesh type used), lower pre-operative optimism was an independent risk factor for CPSP at 4 months; lower pre-operative optimism and lower perceived control over pain at 1 week after surgery predicted higher pain intensity at 4 months. No emotional variables were independently predictive of CPSP. Further research should target these cognitive variables in pre-operative psychological preparation for surgery. © 2011 European Federation of International Association for the Study of Pain Chapters.

Risk factors that predict maladaptive outcomes among sexually abused girls presenting for services at a community agency

The purpose of this study was to determine which factors predicted maladaptive outcomes in sexually abused children. Key factors were aggregated into four categories: abuse characteristics risk factors, individual-level risk factors, family disruption risk factors, and social disruption risk factors. It was hypothesized that (a) individual-level risk factors (e.g., school performance, child alcohol/substance abuse) and (b) abuse characteristics risk factors (e.g., longer duration/frequency of abuse, use of force/threats of force, intrafamilial abuse) would predict higher levels of trauma symptoms. Furthermore, it was hypothesized that (a) family disruption risk factors (e.g., family alcohol/substance use, family psychopathology) and (b) social disruption risk factors (e.g., parental divorce, homelessness, witnessing homicide or violence) would moderate the impact of prior sexual abuse and predict higher levels of trauma symptoms. ^ The participants were 110 female children (5 to 18 years old) presenting for treatment for sexual abuse at a community agency (The Journey Institute) in Miami, Florida. This study conducted a retrospective analysis of an archival data set collected over a three-year period (1998–2001). The measures completed upon intake included The Journey Psychosocial Assessment and The Trauma Symptom Checklist for Children (TSCC; Briere, 1996). Using Pearson correlations and hierarchical multiple regression analysis, this study found that abuse characteristics risk factors and individual-level risk factors were predictive of maladaptive outcomes in this sample of sexually abused girls. However, no moderating effects were found for family disruption risk factors or social disruption risk factors. Therefore, the results of these analyses provided support for the contention that abuse characteristics and individual-level risk factors were appropriate targets for treatment for sexually abused girls. Moreover, limitations of this study, implications for treatment, and directions for future research were discussed. ^

The drivers of perception: Identifying the driving factors of resident perceptions of municipal service quality in cities of South Florida

The idea of comparative performance assessment is crucial. Recent study findings show that in South Florida the use by most municipalities of external benchmarks for performance comparison is virtually non-existent. On one level this study sought to identify the factors impacting resident perceptions of municipal service quality. On a different and more practical level, this study sought to identify a core set of measures that could serve for multi jurisdictional comparisons of performance. ^ This study empirically tested three groups of hypotheses. Data were collected via custom designed survey instruments from multiple jurisdictions, representing diverse socioeconomic backgrounds, and across two counties. A second layer of analysis was conducted on municipal budget documents for the presence of performance measures. A third layer of analysis was conducted via face-to-face interviews with residents at the point of service delivery. Research questions were analyzed using descriptive and inferential statistic methodologies. ^ Results of survey data yielded inconsistent findings. In absolute aggregated terms, the use of sociological determinants to guide inquiry failed to yield conclusive answers regarding the factors impacting resident perceptions of municipal service quality. At disaggregated community levels, however, definite differences emerged but these had weak predictive ability. More useful were the findings of performance measures reporting via municipal budget documents and analyses of interviews with residents at the point of service delivery. Regardless of socio-economic profile, neighborhood characteristics, level of civic engagement or type of community, the same aspects were important to citizens when making assessments of service quality. For parks and recreation, respondents most frequently cited maintenance, facility amenities, and program offerings as important while for garbage collection services timely and consistent service delivery mattered most. Surprisingly municipalities participating in the study track performance data on items indicated as important by citizen assessments but regular feed back from residents or reporting to the same is rarely done. ^ The implications of these findings suggest that endeavors, such as the one undertaken in this study, can assist in determining a core set of measures for cross jurisdictional comparisons of municipal service quality, improving municipal delivery of services, and to communicate with the public. ^

Using the Big -Five personality factors in the Minnesota Multiphasic Personality Inventory, California Psychological Inventory, and Inwald Personality Inventory to predict police performance

The purpose of this study was to determine the degree to which the Big-Five personality taxonomy, as represented by the Minnesota Multiphasic Personality Inventory (MMPI), California Psychological Inventory (CPI), and Inwald Personality Inventory (IPI) scales, predicted a variety of police officer job performance criteria. Data were collected archivally for 270 sworn police officers from a large Southeastern municipality. Predictive data consisted of scores on the MMPI, CPI, and IPI scales as grouped in terms of the Big-Five factors. The overall score on the Wonderlic was included in order to assess criterion variance accounted for by cognitive ability. Additionally, a psychologist's overall rating of predicted job fit was utilized to assess the variance accounted for by a psychological interview. Criterion data consisted of supervisory ratings of overall job performance, State Examination scores, police academy grades, and termination. Based on the literature, it was hypothesized that officers who are higher on Extroversion, Conscientiousness, Agreeableness, Openness to Experience, and lower on Neuroticism, otherwise known as the Big-Five factors, would outperform their peers across a variety of job performance criteria. Additionally, it was hypothesized that police officers who are higher in cognitive ability and masculinity, and lower in mania would also outperform their counterparts. Results indicated that many of the Big-Five factors, namely, Neuroticism, Conscientiousness, Agreeableness, and Openness to Experience, were predictive of several of the job performance criteria. Such findings imply that the Big-Five is a useful predictor of police officer job performance. Study limitations and implications for future research are discussed. ^

Treatment attrition among racial /ethnic minority adolescents participating in a brief motivational intervention for substance use problems: The influence of individual, social, cultural, and treatment factors

The present study has the primary aim of examining the predictors of treatment attrition among racial/ethnic minority adolescents with substance use problems. This study explores the potential differential influence of specific individual, social, cultural, and treatment factors on treatment attrition within three racial/ethnic subgroups of adolescents. Participants: A unique feature of the study is the use of a racial/ethnic minority sample (N=453), [U.S.-born Hispanics (n = 262), Foreign-born Hispanics (n = 117), and African-Americans (n = 74)]. Multivariate logit analyses were used to examine the influence of specific factors on treatment attrition among the full sample of adolescents, as well as within each racial/ethnic subgroup. Consistent with expectations, multivariate logit analyses reveal that, the specific factors associated with attrition varied across the three racial/ethnic subgroups. Having parents with problem substance use, being on the waitlist, and being court mandated to treatment emerged as predictors of attrition among the US-born Hispanics, while only Conduct Disorder was significantly associated with greater attrition among foreign-born Hispanics. Finally, among African-Americans, parental crack/cocaine use, parental abstinence from alcohol, and being on the waitlist were predictive of attrition. Multiple factors were associated with treatment attrition among racial/ethnic minority adolescents with specific factors differentially predicting attrition within each racial/ethnic subgroup. African-American youth were more than twice as likely as their Hispanic counterparts to leave treatment prematurely. It is critically important to understand the predictors of attrition among racial/ethnic minority youth in order to better meet the needs of youth most at risk of dropping out. ^

Treatment attrition among racial/ethnic minority adolescents participating in a brief motivational intervention for substance use problems : the influence of individual, social, cultural, and treatment factors

The present study has the primary aim of examining the predictors of treatment attrition among racial/ethnic minority adolescents with substance use problems. This study explores the potential differential influence of specific individual, social, cultural, and treatment factors on treatment attrition within three racial/ethnic subgroups of adolescents. Participants: A unique feature of the study is the use of a racial/ethnic minority sample (N=453), [U.S.-born Hispanics (n = 262), Foreign-born Hispanics (n = 117), and African- Americans (n = 74)]. Multivariate logit analyses were used to examine the influence of specific factors on treatment attrition among the full sample of adolescents, as well as within each racial/ethnic subgroup. Consistent with expectations, multivariate logit analyses reveal that, the specific factors associated with attrition varied across the three racial/ethnic subgroups. Having parents with problem substance use, being on the waitlist, and being court mandated to treatment emerged as predictors of attrition among the US-born Hispanics, while only Conduct Disorder was significantly associated with greater attrition among foreign-born Hispanics. Finally, among African-Americans, parental crack/cocaine use, parental abstinence from alcohol, and being on the waitlist were predictive of attrition. Multiple factors were associated with treatment attrition among racial/ethnic minority adolescents with specific factors differentially predicting attrition within each racial/ethnic subgroup. African-American youth were more than twice as likely as their Hispanic counterparts to leave treatment prematurely. It is critically important to understand the predictors of attrition among racial/ethnic minority youth in order to better meet the needs of youth most at risk of dropping out.

Factors influencing university performance of associate in arts graduates transferring to the state university system

The purpose of this study was to examine the factorsbehind the failure rates of Associate in Arts (AA)graduates from Miami-Dade Community College (M-DCC) transferring to the Florida State University System (SUS). In M-DCC's largest disciplines, the university failure rate was 13% for Business & Management, 13% for Computer Science, and 14% for Engineering. Hypotheses tested were: Hypothesis 1 (H1): The lower division (LD) overall cumulative GPA and/or the LD major field GPA for AA graduates are predictive of the SUS GPA for the Business Management, Computer Science, and Engineering disciplines. Hypothesis 2 (H2): Demographic variables (age, race, gender) are predictive of performance at the university among M-DCC AA graduates in Engineering, Business & Management, and Computer Science. Hypothesis 3 (H3): Administrative variables (CLAST -College Level Academic Skills Test subtests) are predictive of university performance (GPA) for the Business/Management, Engineering, and Computer Science disciplines. Hypothesis 4 (H4): LD curriculum variables (course credits, course quality points) are predictive of SUS performance for the Engineering, Business/Management and Computer Science disciplines. Multiple Regression was the inferential procedureselected for predictions. Descriptive statistics weregenerated on the predictors. Results for H1 identified the LD GPA as the most significant variable in accounting for the variability of the university GPA for the Business & Management, Computer Science, and Engineering disciplines. For H2, no significant results were obtained for theage and gender variables, but the ethnic subgroups indicated significance at the .0001 level. However, differentials in GPA may not have been due directly to the race factor but, rather, to curriculum choices and performance outcomes while in the LD. The CLAST computation variable (H3) was a significant predictor of the SUS GPA. This is most likely due to the mathematics structure pervasive in these disciplines. For H4, there were two curriculum variables significant in explaining the variability of the university GPA (number of required critical major credits completed and quality of the student's performance for these credits). Descriptive statistics on the predictors indicated that 78% of those failing in the State University System had a LD major GPA (calculated with the critical required university credits earned and quality points of these credits) of less than 3.0; and 83% of those failing at the university had an overall community college GPA of less than 3.0.

Improved Criteria for Estimating Calibration Factors for Highway Safety Manual (HSM) Applications

The Highway Safety Manual (HSM) estimates roadway safety performance based on predictive models that were calibrated using national data. Calibration factors are then used to adjust these predictive models to local conditions for local applications. The HSM recommends that local calibration factors be estimated using 30 to 50 randomly selected sites that experienced at least a total of 100 crashes per year. It also recommends that the factors be updated every two to three years, preferably on an annual basis. However, these recommendations are primarily based on expert opinions rather than data-driven research findings. Furthermore, most agencies do not have data for many of the input variables recommended in the HSM. This dissertation is aimed at determining the best way to meet three major data needs affecting the estimation of calibration factors: (1) the required minimum sample sizes for different roadway facilities, (2) the required frequency for calibration factor updates, and (3) the influential variables affecting calibration factors. In this dissertation, statewide segment and intersection data were first collected for most of the HSM recommended calibration variables using a Google Maps application. In addition, eight years (2005-2012) of traffic and crash data were retrieved from existing databases from the Florida Department of Transportation. With these data, the effect of sample size criterion on calibration factor estimates was first studied using a sensitivity analysis. The results showed that the minimum sample sizes not only vary across different roadway facilities, but they are also significantly higher than those recommended in the HSM. In addition, results from paired sample t-tests showed that calibration factors in Florida need to be updated annually. To identify influential variables affecting the calibration factors for roadway segments, the variables were prioritized by combining the results from three different methods: negative binomial regression, random forests, and boosted regression trees. Only a few variables were found to explain most of the variation in the crash data. Traffic volume was consistently found to be the most influential. In addition, roadside object density, major and minor commercial driveway densities, and minor residential driveway density were also identified as influential variables.

Simplified Predictive Instrument to Rule Out Acute Coronary Syndromes in a High-Risk Population.

BACKGROUND: It is unclear whether diagnostic protocols based on cardiac markers to identify low-risk chest pain patients suitable for early release from the emergency department can be applied to patients older than 65 years or with traditional cardiac risk factors. METHODS AND RESULTS: In a single-center retrospective study of 231 consecutive patients with high-risk factor burden in which a first cardiac troponin (cTn) level was measured in the emergency department and a second cTn sample was drawn 4 to 14 hours later, we compared the performance of a modified 2-Hour Accelerated Diagnostic Protocol to Assess Patients with Chest Pain Using Contemporary Troponins as the Only Biomarker (ADAPT) rule to a new risk classification scheme that identifies patients as low risk if they have no known coronary artery disease, a nonischemic electrocardiogram, and 2 cTn levels below the assay's limit of detection. Demographic and outcome data were abstracted through chart review. The median age of our population was 64 years, and 75% had Thrombosis In Myocardial Infarction risk score ≥2. Using our risk classification rule, 53 (23%) patients were low risk with a negative predictive value for 30-day cardiac events of 98%. Applying a modified ADAPT rule to our cohort, 18 (8%) patients were identified as low risk with a negative predictive value of 100%. In a sensitivity analysis, the negative predictive value of our risk algorithm did not change when we relied only on undetectable baseline cTn and eliminated the second cTn assessment. CONCLUSIONS: If confirmed in prospective studies, this less-restrictive risk classification strategy could be used to safely identify chest pain patients with more traditional cardiac risk factors for early emergency department release.

Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci.

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.

Karst hazard analysis towards the development of predictive karst models for southern Ontario

An investigation into karst hazard in southern Ontario has been undertaken with the intention of leading to the development of predictive karst models for this region. The reason these are not currently feasible is a lack of sufficient karst data, though this is not entirely due to the lack of karst features. Geophysical data was collected at Lake on the Mountain, Ontario as part of this karst investigation. This data was collected in order to validate the long-standing hypothesis that Lake on the Mountain was formed from a sinkhole collapse. Sub-bottom acoustic profiling data was collected in order to image the lake bottom sediments and bedrock. Vertical bedrock features interpreted as solutionally enlarged fractures were taken as evidence for karst processes on the lake bottom. Additionally, the bedrock topography shows a narrower and more elongated basin than was previously identified, and this also lies parallel to a mapped fault system in the area. This suggests that Lake on the Mountain was formed over a fault zone which also supports the sinkhole hypothesis as it would provide groundwater pathways for karst dissolution to occur. Previous sediment cores suggest that Lake on the Mountain would have formed at some point during the Wisconsinan glaciation with glacial meltwater and glacial loading as potential contributing factors to sinkhole development. A probabilistic karst model for the state of Kentucky, USA, has been generated using the Weights of Evidence method. This model is presented as an example of the predictive capabilities of these kind of data-driven modelling techniques and to show how such models could be applied to karst in Ontario. The model was able to classify 70% of the validation dataset correctly while minimizing false positive identifications. This is moderately successful and could stand to be improved. Finally, suggestions to improving the current karst model of southern Ontario are suggested with the goal of increasing investigation into karst in Ontario and streamlining the reporting system for sinkholes, caves, and other karst features so as to improve the current Ontario karst database.

Modelling the influence of biotic factors on species distribution patterns

Biotic interactions can have large effects on species distributions yet their role in shaping species ranges is seldom explored due to historical difficulties in incorporating biotic factors into models without a priori knowledge on interspecific interactions. Improved SDMs, which account for biotic factors and do not require a priori knowledge on species interactions, are needed to fully understand species distributions. Here, we model the influence of abiotic and biotic factors on species distribution patterns and explore the robustness of distributions under future climate change. We fit hierarchical spatial models using Integrated Nested Laplace Approximation (INLA) for lagomorph species throughout Europe and test the predictive ability of models containing only abiotic factors against models containing abiotic and biotic factors. We account for residual spatial autocorrelation using a conditional autoregressive (CAR) model. Model outputs are used to estimate areas in which abiotic and biotic factors determine species’ ranges. INLA models containing both abiotic and biotic factors had substantially better predictive ability than models containing abiotic factors only, for all but one of the four species. In models containing abiotic and biotic factors, both appeared equally important as determinants of lagomorph ranges, but the influences were spatially heterogeneous. Parts of widespread lagomorph ranges highly influenced by biotic factors will be less robust to future changes in climate, whereas parts of more localised species ranges highly influenced by the environment may be less robust to future climate. SDMs that do not explicitly include biotic factors are potentially misleading and omit a very important source of variation. For the field of species distribution modelling to advance, biotic factors must be taken into account in order to improve the reliability of predicting species distribution patterns both presently and under future climate change.

PROGNOSTIC FACTORS PREDICTING FUNCTIONAL OUTCOME AT FOUR MONTHS FOLLOWING ACUTE ANKLE SPRAIN

PROGNOSTIC FACTORS PREDICTING FUNCTIONAL OUTCOME AT FOUR MONTHS FOLLOWING ACUTE ANKLE SPRAINBleakley C.M.1, O'Connor S.R.1, Tully M.A.2, Rocke L.G.3, MacAuley D.C.1, Bradbury I.4, Keegan S.4, McDonough S.M.11University of Ulster, Health & Rehabilitation Sciences Research Institute, Newtownabbey, United Kingdom, 2Queen's University, UKCRC Centre of Excellence for Public Health (NI), Belfast, United Kingdom, 3Royal Victoria Hospital, Department of Emergency Medicine, Belfast, United Kingdom, 4Frontier Science (Scotland), Kincraig, Inverness-shire, United KingdomPurpose: To identify clinically relevant factors assessed following acute ankle sprain that predict functional recovery at four months post-injury.Relevance: Ankle sprains are one of the most common musculoskeletal injuries with an estimated 5000 new cases occurring each day in the United Kingdom. In the acute phase, ankle sprains may be associated with pain and loss of function. In the longer-term there is a risk of residual problems including chronic pain or reinjury. Few studies have sought to examine factors associated with a poor long-term prognosis.Participants: 101 patients (Age: Mean (SD) 25.9 (7.9) years; Body Mass Index (BMI): 25.3 (3.5) kg/m2) with an acute grade 1 or 2 ankle sprain attending an accident and emergency department or sports injury clinic. Exclusion criteria included complete (grade 3) rupture of the ankle ligament complex, bony ankle injury or multiple injuries.Methods: Participants were allocated as part of a randomised controlled trial to an accelerated intervention incorporating intermittent ice and early therapeutic exercise or a standard protection, rest, ice, compression, and elevation intervention for one week. Treatment was then standardised in both groups and consisted of ankle rehabilitation exercises focusing on muscle strengthening, neuromuscular training, and sports specific functional exercises for a period of approximately four to six weeks. On initial assessment age, gender, mechanism of injury, presence of an audible pop or snap and the presence of contact during the injury were recorded. The following factors were also recorded at baseline and at one and four weeks post-injury: weight-bearing dorsi-flexion test, lateral hop test, presence of medial pain on palpation and a positive impingement sign. Functional status was assessed using the Karlsson score at baseline, at week four and at four months. Reinjury rates were recorded throughout the intervention phase and at four months.Analysis: A mixed between-within subjects analysis of variance (ANOVA) was used to determine the effect of each factor on functional status at week four and at four months. Significance was set at a Bonferroni adjusted level of 0.0125 (0.05/4).Results: Eighty-five participants (84%) were available at final follow-up assessment. Pain on weight-bearing dorsi-flexion and lateral hop tests at week four were both associated with a lower functional score at four months post-injury (P = 0.011 and P = 0.001). No other significant interactions were observed at any other timepoint (baseline or week one). There were only two reinjuries within the four month follow-up period with a further two reported at approximately six months post-injury. We were therefore unable to determine whether any factors were associated with an increased risk of reinjury.Conclusions: Potential prognostic factors on initial or early examination after acute ankle sprain did not help predict functional recovery at four months post-injury. However, pain on weight-bearing dorsi-flexion and lateral hop tests observed at four weeks were associated with a slower rate of recovery.Implications: Some clinical tests may help identify patients at risk of poor functional recovery after acute ankle sprain. However, further work is required to examine factors which may be predictive on initial assessment.Key-words: 1. Prognostic factors 2. Recovery 3. Ankle sprainFunding acknowledgements: Physiotherapy Research Foundation, Chartered Society of Physiotherapy, Strategic Priority Fund; Department of Employment and Learning, Northern Ireland.Ethics approval: Office for Research Ethics Committee (UK).

Predictive Analytics and Decision Support for Heart Failure patients

Thesis (Master's)--University of Washington, 2016-08