Ottawa University

Contents: Part I: Introduction. Structural Equation Models: The Basics. Using the EQS Program. Part II: Single-Group Analyses. Application 1: Testing for the Factorial Validity of a Theoretical Construct (First-Order CFA Model). Application 2: Testing for the Factorial Validity of Scores From a Measuring Instrument (First-Order CFA Model). Application 3: Testing for the Factorial Validity of Scores from a Measuring Instrument (Second-Order CFA Model). Application 4: Testing for the Validity of a Causal Structure. Part III: Multiple-Group Analyses. Application 5: Testing for the Factorial Invariance of a Measuring Instrument. Application 6: Testing for the Invariance of a Causal Structure. Application 7: Testing for Latent Mean Differences (First-Order CFA Model). Application 8: Testing for Latent Mean Differences (Second-Order CFA Model). Part IV: Other Important Topics. Application 9: Testing for Construct Validity: The Multitrait-Multimethod Model. Application 10: Testing for Change Over Time: The Latent Growth Curve Model. Application 11: Testing for Within- and Between-Level Variance: The Multilevel Model.

Because economic evaluations of health care services are being published with increasing frequency it is important to (a) evaluate them rigorously and (b) compare the net benefit of the application of one technology with that of others. Four "levels of evidence" that rate economic evaluations on the basis of their methodologic rigour are proposed. They are based on the quality of the methods used to estimate clinical effectiveness, quality of life and costs. With the use of the magnitude of the incremental net benefit of a technology, therapies can also be classified into five "grades of recommendation." A grade A technology is both more effective and cheaper than the existing one, whereas a grade E technology is less or equally effective and more costly. Those of grades B through D are more effective and more costly. A grade B technology costs less than $20,000 per quality-adjusted life-year (QALY), a grade C one $20,000 to $100,000/QALY and a grade D one more than $100,000/QALY. Many issues other than cost effectiveness, such as ethical and political considerations, affect the implementation of a new technology. However, it is hoped that these guidelines will provide a framework with which to interpret economic evaluations and to identify additional information that will be useful in making sound decisions on the adoption and utilization of health care services.

The Canadian Association of Occupational Therapists, in collaboration with Health and Welfare Canada have developed and published a conceptual model for occupational therapy, the Occupational Performance model. This paper describes the development of an outcome measure, The Canadian Occupational Performance Measure (COPM), which is designed to be used with these guidelines for client-centred clinical practice. The COPM is an outcome measure designed for use by occupational therapists to assess client outcomes in the areas of self-care, productivity and leisure. Using a semi-structured interview, the COPM is a five step process which measures individual, client-identified problem areas in daily function. Two scores, for performance and satisfaction with performance are obtained. This paper describes the rationale and development of the COPM as well as information about its use for therapists.

Microalgae are a diverse group of prokaryotic and eukaryotic photosynthetic microorganisms that grow rapidly due to their simple structure. They can potentially be employed for the production of biofuels in an economically effective and environmentally sustainable manner. Microalgae have been investigated for the production of a number of different biofuels including biodiesel, bio-oil, bio-syngas, and bio-hydrogen. The production of these biofuels can be coupled with flue gas CO2 mitigation, wastewater treatment, and the production of high-value chemicals. Microalgal farming can also be carried out with seawater using marine microalgal species as the producers. Developments in microalgal cultivation and downstream processing (e.g., harvesting, drying, and thermochemical processing) are expected to further enhance the cost-effectiveness of the biofuel from microalgae strategy.

The present series of studies sought to develop and conceptually validate a taxonomy of reasons that give rise to academic amotivation and to investigate its social antecedents and academic consequences. In Study 1 (N = 351), an exploratory factor analysis offered preliminary support for an academic amotivation taxonomy comprising four dimensions: ability beliefs, effort beliefs, characteristics of the task, and value placed on the task. In Study 2 (N = 349), the proposed taxonomy was further corroborated through 1st- and 2nd-order confirmatory factor analyses, and its discriminant validity and construct validity were documented. Study 3 (N = 741) offered evidence for a model of the relationships among social support (from parents, teachers, and friends), amotivation, and academic outcomes (e.g., achievement, academic self-esteem, intention to drop out). Results are considered in terms of an increased conceptual understanding of academic amotivation, and implications for curricula and interventions are discussed.

BACKGROUND: The Canadian C-Spine (cervical-spine) Rule (CCR) and the National Emergency X-Radiography Utilization Study (NEXUS) Low-Risk Criteria (NLC) are decision rules to guide the use of cervical-spine radiography in patients with trauma. It is unclear how the two decision rules compare in terms of clinical performance. METHODS: We conducted a prospective cohort study in nine Canadian emergency departments comparing the CCR and NLC as applied to alert patients with trauma who were in stable condition. The CCR and NLC were interpreted by 394 physicians for patients before radiography. RESULTS: Among the 8283 patients, 169 (2.0 percent) had clinically important cervical-spine injuries. In 845 (10.2 percent) of the patients, physicians did not evaluate range of motion as required by the CCR algorithm. In analyses that excluded these indeterminate cases, the CCR was more sensitive than the NLC (99.4 percent vs. 90.7 percent, P<0.001) and more specific (45.1 percent vs. 36.8 percent, P<0.001) for injury, and its use would have resulted in lower radiography rates (55.9 percent vs. 66.6 percent, P<0.001). In secondary analyses that included all patients, the sensitivity and specificity of CCR, assuming that the indeterminate cases were all positive, were 99.4 percent and 40.4 percent, respectively (P<0.001 for both comparisons with the NLC). Assuming that the CCR was negative for all indeterminate cases, these rates were 95.3 percent (P=0.09 for the comparison with the NLC) and 50.7 percent (P=0.001). The CCR would have missed 1 patient and the NLC would have missed 16 patients with important injuries. CONCLUSIONS: For alert patients with trauma who are in stable condition, the CCR is superior to the NLC with respect to sensitivity and specificity for cervical-spine injury, and its use would result in reduced rates of radiography.

BACKGROUND AND OBJECTIVES: Diagnosis of multiple sclerosis (MS) requires exclusion of diseases that could better explain the clinical and paraclinical findings. A systematic process for exclusion of alternative diagnoses has not been defined. An International Panel of MS experts developed consensus perspectives on MS differential diagnosis. METHODS: Using available literature and consensus, we developed guidelines for MS differential diagnosis, focusing on exclusion of potential MS mimics, diagnosis of common initial isolated clinical syndromes, and differentiating between MS and non-MS idiopathic inflammatory demyelinating diseases. RESULTS: We present recommendations for 1) clinical and paraclinical red flags suggesting alternative diagnoses to MS; 2) more precise definition of "clinically isolated syndromes" (CIS), often the first presentations of MS or its alternatives; 3) algorithms for diagnosis of three common CISs related to MS in the optic nerves, brainstem, and spinal cord; and 4) a classification scheme and diagnosis criteria for idiopathic inflammatory demyelinating disorders of the central nervous system. CONCLUSIONS: Differential diagnosis leading to MS or alternatives is complex and a strong evidence base is lacking. Consensus-determined guidelines provide a practical path for diagnosis and will be useful for the non-MS specialist neurologist. Recommendations are made for future research to validate and support these guidelines. Guidance on the differential diagnosis process when MS is under consideration will enhance diagnostic accuracy and precision.

People with schizophrenia die 15-20 years prematurely. Understanding mortality risk and aggravating/attenuating factors is essential to reduce this gap. We conducted a systematic review and random-effects meta-analysis of prospective and retrospective, nationwide and targeted cohort studies assessing mortality risk in people with schizophrenia versus the general population or groups matched for physical comorbidities or groups with different psychiatric disorders, also assessing moderators. Primary outcome was all-cause mortality risk ratio (RR); key secondary outcomes were mortality due to suicide and natural causes. Other secondary outcomes included any other specific-cause mortality. Publication bias, subgroup and meta-regression analyses, and quality assessment (Newcastle-Ottawa Scale) were conducted. Across 135 studies spanning from 1957 to 2021 (schizophrenia: N=4,536,447; general population controls: N=1,115,600,059; other psychiatric illness controls: N=3,827,955), all-cause mortality was increased in people with schizophrenia versus any non-schizophrenia control group (RR=2.52, 95% CI: 2.38-2.68, n=79), with the largest risk in first-episode (RR=7.43, 95% CI: 4.02-13.75, n=2) and incident (i.e., earlier-phase) schizophrenia (RR=3.52, 95% CI: 3.09-4.00, n=7) versus the general population. Specific-cause mortality was highest for suicide or injury-poisoning or undetermined non-natural cause (RR=9.76-8.42), followed by pneumonia among natural causes (RR=7.00, 95% CI: 6.79-7.23), decreasing through infectious or endocrine or respiratory or urogenital or diabetes causes (RR=3 to 4), to alcohol or gastrointestinal or renal or nervous system or cardio-cerebrovascular or all natural causes (RR=2 to 3), and liver or cerebrovascular, or breast or colon or pancreas or any cancer causes (RR=1.33 to 1.96). All-cause mortality increased slightly but significantly with median study year (beta=0.0009, 95% CI: 0.001-0.02, p=0.02). Individuals with schizophrenia <40 years of age had increased all-cause and suicide-related mortality compared to those ≥40 years old, and a higher percentage of females increased suicide-related mortality risk in incident schizophrenia samples. All-cause mortality was higher in incident than prevalent schizophrenia (RR=3.52 vs. 2.86, p=0.009). Comorbid substance use disorder increased all-cause mortality (RR=1.62, 95% CI: 1.47-1.80, n=3). Antipsychotics were protective against all-cause mortality versus no antipsychotic use (RR=0.71, 95% CI: 0.59-0.84, n=11), with largest effects for second-generation long-acting injectable anti-psychotics (SGA-LAIs) (RR=0.39, 95% CI: 0.27-0.56, n=3), clozapine (RR=0.43, 95% CI: 0.34-0.55, n=3), any LAI (RR=0.47, 95% CI: 0.39-0.58, n=2), and any SGA (RR=0.53, 95% CI: 0.44-0.63, n=4). Antipsychotics were also protective against natural cause-related mortality, yet first-generation antipsychotics (FGAs) were associated with increased mortality due to suicide and natural cause in incident schizophrenia. Higher study quality and number of variables used to adjust the analyses moderated larger natural-cause mortality risk, and more recent study year moderated larger protective effects of antipsychotics. These results indicate that the excess mortality in schizophrenia is associated with several modifiable factors. Targeting comorbid substance abuse, long-term maintenance antipsychotic treatment and appropriate/earlier use of SGA-LAIs and clozapine could reduce this mortality gap.

OBJECTIVE: To compare a restrictive red blood cell transfusion strategy with a more liberal strategy in volume-resuscitated critically ill patients with cardiovascular disease. SETTING: Twenty-two academic and three community critical care units across Canada. STUDY DESIGN: Randomized controlled clinical trial. STUDY POPULATION: Three hundred fifty-seven critically ill patients with cardiovascular diseases from the Transfusion Requirements in Critical Care trial who had a hemoglobin concentration of <90 g/L within 72 hrs of admission to the intensive care unit. INTERVENTIONS: Patients were randomized to a restrictive strategy to receive allogeneic red blood cell transfusions at a hemoglobin concentration of 70 g/L (and maintained between 70 and 90 g/L) or a liberal strategy to receive red blood cells at 100 g/L (and maintained between 100 and 120 g/L). RESULTS: Baseline characteristics in the restrictive (n = 160) and the liberal group (n = 197) were comparable, except for the use of cardiac and anesthetic drugs (p <.02). Average hemoglobin concentrations (85 +/- 6.2 vs. 103 +/- 6.7 g/L; p <.01) and red blood cell units transfused (2.4 +/- 4.1 vs. 5.2 +/- 5.0 red blood cell units; p <.01) were significantly lower in the restrictive compared with the liberal group. Overall, all mortality rates were similar in both study groups, including 30-day (23% vs. 23%; p = 1.00), 60-day, hospital, and intensive care unit rates. Changes in multiple organ dysfunction from baseline scores were significantly less in the restrictive transfusion group overall (0.2 +/- 4.2 vs. 1.3 +/- 4.4; p =.02). In the 257 patients with severe ischemic heart disease, there were no statistically significant differences in all survival measures, but this is the only subgroup where the restrictive group had lower but nonsignificant absolute survival rates compared with the patients in the liberal group. CONCLUSION: A restrictive red blood cell transfusion strategy generally appears to be safe in most critically ill patients with cardiovascular disease, with the possible exception of patients with acute myocardial infarcts and unstable angina.

Two decades ago, with the publication, we witnessed the rebirth of particle filtering (PF) as a methodology for sequential signal processing. Since then, PF has become very popular because of its ability to process observations represented by nonlinear state-space models where the noises of the model can be non-Gaussian. This methodology has been adopted in various fields, including finance, geophysical systems, wireless communications, control, navigation and tracking, and robotics. The popularity of PF has also spurred the publication of several review articles. In this article, the state of the art of resampling methods was reviewed. The methods were classified and their properties were compared in the framework of the proposed classifications. The emphasis in the article was on the classification and qualitative descriptions of the algorithms. The intention was to provide guidelines to practitioners and researchers.

<h3>ABSTRACT</h3> This paper reports on the findings of a survey about attitudes now, and predictions for the future, regarding web advertising versus other media, with college students as the target. College students9 present attitude toward web advertising is compared to the attitudes of people familiar with the web in Ducoffe9s 1996 study. Among the more notable results: while Ducoffe9s sample did not find web advertising to be irritating, annoying, or insulting to peoples9 intelligence, our student sample did. Additionally, students predict that web advertising will overtake television advertising as the most valuable source of information for the future. The paper also offers a new pragmatic model of Attitude toward Advertising that enhances the explanatory power of the Ducoffe (1996) model by adding to the antecedent variables.

BACKGROUND: We undertook research to improve the AGREE instrument, a tool used to evaluate guidelines. We tested a new seven-point scale, evaluated the usefulness of the original items in the instrument, investigated evidence to support shorter, tailored versions of the tool, and identified areas for improvement. METHOD: We report on one component of a larger study that used a mixed design with four factors (user type, clinical topic, guideline and condition). For the analysis reported in this article, we asked participants to read a guideline and use the AGREE items to evaluate it based on a seven-point scale, to complete three outcome measures related to adoption of the guideline, and to provide feedback on the instrument's usefulness and how to improve it. RESULTS: Guideline developers gave lower-quality ratings than did clinicians or policy-makers. Five of six domains were significant predictors of participants' outcome measures (p < 0.05). All domains and items were rated as useful by stakeholders (mean scores > 4.0) with no significant differences by user type (p > 0.05). Internal consistency ranged between 0.64 and 0.89. Inter-rater reliability was satisfactory. We received feedback on how to improve the instrument. INTERPRETATION: Quality ratings of the AGREE domains were significant predictors of outcome measures associated with guideline adoption: guideline endorsements, overall intentions to use guidelines, and overall quality of guidelines. All AGREE items were assessed as useful in determining whether a participant would use a guideline. No clusters of items were found more useful by some users than others. The measurement properties of the seven-point scale were promising. These data contributed to the refinements and release of the AGREE II.

BACKGROUND: We established a program of research to improve the development, reporting and evaluation of practice guidelines. We assessed the construct validity of the items and user's manual in the beta version of the AGREE II. METHODS: We designed guideline excerpts reflecting high-and low-quality guideline content for 21 of the 23 items in the tool. We designed two study packages so that one low-quality and one high-quality version of each item were randomly assigned to each package. We randomly assigned 30 participants to one of the two packages. Participants reviewed and rated the guideline content according to the instructions of the user's manual and completed a survey assessing the manual. RESULTS: In all cases, content designed to be of high quality was rated higher than low-quality content; in 18 of 21 cases, the differences were significant (p < 0.05). The manual was rated by participants as appropriate, easy to use, and helpful in differentiating guidelines of varying quality, with all scores above the mid-point of the seven-point scale. Considerable feedback was offered on how the items and manual of the beta-AGREE II could be improved. INTERPRETATION: The validity of the items was established and the user's manual was rated as highly useful by users. We used these results and those of our study presented in part 1 to modify the items and user's manual. We recommend AGREE II (available at www.agreetrust.org) as the revised standard for guideline development, reporting and evaluation.

Quantum light-matter interfaces are at the heart of photonic quantum technologies. Quantum memories for photons, where non-classical states of photons are mapped onto stationary matter states and preserved for subsequent retrieval, are technical realizations enabled by exquisite control over interactions between light and matter. The ability of quantum memories to synchronize probabilistic events makes them a key component in quantum repeaters and quantum computation based on linear optics. This critical feature has motivated many groups to dedicate theoretical and experimental research to develop quantum memory devices. In recent years, exciting new applications, and more advanced developments of quantum memories, have proliferated. In this review, we outline some of the emerging applications of quantum memories in optical signal processing, quantum computation and non-linear optics. We review recent experimental and theoretical developments, and their impacts on more advanced photonic quantum technologies based on quantum memories.

BACKGROUND: An international expert panel convened by the Independent Scientific Committee on Drugs developed a multi-criteria decision analysis model of the relative importance of different types of harm related to the use of nicotine-containing products. METHOD: The group defined 12 products and 14 harm criteria. Seven criteria represented harms to the user, and the other seven indicated harms to others. The group scored all the products on each criterion for their average harm worldwide using a scale with 100 defined as the most harmful product on a given criterion, and a score of zero defined as no harm. The group also assessed relative weights for all the criteria to indicate their relative importance. FINDINGS: Weighted averages of the scores provided a single, overall score for each product. Cigarettes (overall weighted score of 100) emerged as the most harmful product, with small cigars in second place (overall weighted score of 64). After a substantial gap to the third-place product, pipes (scoring 21), all remaining products scored 15 points or less. INTERPRETATION: Cigarettes are the nicotine product causing by far the most harm to users and others in the world today. Attempts to switch to non-combusted sources of nicotine should be encouraged as the harms from these products are much lower.

Research on roles and identities generally represents a micro perspective that does not account for the reconstruction of professional role identity, owing to insufficient attention to institutional forces. We trace institutional influences on professional role identity reconstruction and extend theory by building bridges across institutional, organizational, and individual levels of analysis. Findings indicate that agentic reconstruction of professional role identity is enabled and constrained by an institutional environment that provides interpretive, legitimating, and material resources that professionals adopt and adapt. Institutional forces also impact organizational arrangements that further influence microlevel agency. We elaborate interactions among these three levels of analysis.

OBJECTIVE: To provide primary care clinicians with an up-to-date and practical overview of the diagnosis and management of psoriasis. QUALITY OF EVIDENCE: PubMed, MEDLINE, EMBASE, and Cochrane databases were searched for relevant meta-analyses, randomized controlled trials, systematic reviews, and observational studies about the diagnosis and management of psoriasis. MAIN MESSAGE: Psoriasis is a chronic, multisystem inflammatory disease with predominantly skin and joint involvement. Beyond the physical dimensions of disease, psoriasis has an extensive emotional and psychosocial effect on patients, affecting social functioning and interpersonal relationships. As a disease of systemic inflammation, psoriasis is associated with multiple comorbidities, including cardiovascular disease and malignancy. The diagnosis is primarily clinical and a skin biopsy is seldom required. Depending on the severity of disease, appropriate treatment can be initiated. For mild to moderate disease, first-line treatment involves topical therapies including corticosteroids, vitamin D3 analogues, and combination products. These topical treatments are efficacious and can be safely initiated and prescribed by primary care physicians. Patients with more severe and refractory symptoms might require further evaluation by a dermatologist for systemic therapy. CONCLUSION: Many patients with psoriasis seek initial evaluation and treatment from their primary care providers. Recognition of psoriasis, as well as its associated medical and psychiatric comorbidities, would facilitate timely diagnosis and appropriate management with effective and safe topical therapies and other medical and psychological interventions, as needed. More severe and refractory cases might warrant referral to a dermatologist for further evaluation and possible systemic therapy.

OBJECTIVE: Machine learning (ML) and artificial intelligence (AI) are rapidly becoming the most talked about and controversial topics in radiology and medicine. Over the past few years, the numbers of ML- or AI-focused studies in the literature have increased almost exponentially, and ML has become a hot topic at academic and industry conferences. However, despite the increased awareness of ML as a tool, many medical professionals have a poor understanding of how ML works and how to critically appraise studies and tools that are presented to us. Thus, we present a brief overview of ML, explain the metrics used in ML and how to interpret them, and explain some of the technical jargon associated with the field so that readers with a medical background and basic knowledge of statistics can feel more comfortable when examining ML applications. CONCLUSION: Attention to sample size, overfitting, underfitting, cross validation, as well as a broad knowledge of the metrics of machine learning, can help those with little or no technical knowledge begin to assess machine learning studies. However, transparency in methods and sharing of algorithms is vital to allow clinicians to assess these tools themselves.

The primary goal of the current study was to develop a novel experimental paradigm with which to study the influence of psychologically based interrogation techniques on the likelihood of true and false confessions. The paradigm involves guilty and innocent participants being accused of intentionally breaking an experimental rule, or "cheating." In the first demonstration of this paradigm, we explored the influence of two common police interrogation tactics: minimization and an explicit offer of leniency, or a "deal." Results indicated that guilty persons were more likely to confess than innocent persons, and that the use of minimization and the offer of a deal increased the rate of both true and false confessions. Police investigators are encouraged to avoid interrogation techniques that imply or directly promise leniency, as they appear to reduce the diagnostic value of any confession that is elicited.

Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.