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The network paradigm for psychiatric disorder nosology was proposed based on the hypothesis that mental disorders are caused by networks of symptoms that are themselves causally related. Researchers have widely applied and integrated this paradigm to examine a variety of mental disorders, particularly depression. Existing studies generally focus on the correlation structure of symptoms, inferring causal relationships. Thus, presumption of causality may not be justified. The goal of this review was to examine the assumptions necessary for causal inference in network studies of depression. Specifically, we examined whether and how network studies address common violations of causal assumptions (i.e. no measurement error, exchangeability, and positivity). Of the 41 studies reviewed, five (12%) studies discussed sources of confounding unrelated to measurement error; none discussed positivity; and five conducted post-hoc analysis for measurement error. Depression network studies, in principle, are conducted under the assumption that symptom relationships are causal. Yet, in practice, studies seldomly discussed or adequately tested assumptions required to infer causality. Researchers continue to design studies that are unable to support the credibility of the network paradigm for the study of depression. There is a critical need to ensure scientific efforts cease to perpetuate problematic designs and findings to a potentially unsubstantiated paradigm.
The Mini International Neuropsychiatric Inventory 7.0.2 (MINI-7) is a widely used tool and known to have sound psychometric properties; but very little is known about its use in low and middle-income countries (LMICs). This study aimed to examine the psychometric properties of the MINI-7 psychosis items in a sample of 8609 participants across four countries in Sub-Saharan Africa.
We examined the latent factor structure and the item difficulty of the MINI-7 psychosis items in the full sample and across four countries.
Multiple group confirmatory factor analyses (CFAs) revealed an adequate fitting unidimensional model for the full sample; however, single group CFAs at the country level revealed that the underlying latent structure of psychosis was not invariant. Specifically, although the unidimensional structure was an adequate model fit for Ethiopia, Kenya, and South Africa, it was a poor fit for Uganda. Instead, a 2-factor latent structure of the MINI-7 psychosis items provided the optimal fit for Uganda. Examination of item difficulties revealed that MINI-7 item K7, measuring visual hallucinations, had the lowest difficulty across the four countries. In contrast, the items with the highest difficulty were different across the four countries, suggesting that MINI-7 items that are the most predictive of being high on the latent factor of psychosis are different for each country.
The present study is the first to provide evidence that the factor structure and item functioning of the MINI-7 psychosis vary across different settings and populations in Africa.
Measurement of subjective animal welfare creates a special problem in validating the measurement indicators used. Validation is required to ensure indicators are measuring the intended target state, and not some other object. While indicators can usually be validated through looking for correlation between target and indicator under controlled manipulations, this is not possible when the target state is not directly accessible. In this paper, I outline a four-step approach using the concept of robustness, that can help with validating indicators of subjective animal welfare.
Though Cicero offers his most explicit, detailed critiques of Epicureanism in De Finibus and De Natura Deorum, his anti-Epicureanism consistently works itself into a wide swath of his theoretical writings over the last 13 years of his life. Therein Cicero consistently uses a rhetorical strategy whereby he avoids naming the Epicureans outright. Instead he employs a series of shorthand descriptions to attack the Epicureans for what he understands to be their basic tenets. In employing this tactic Cicero both slights the Epicureans by leaving them unnamed and reduces their philosophy to a set of behaviors that he thinks best encapsulate their beliefs. They fail by believing the soul to be mortal, by prioritizing an animal-like desire for pleasure over ratio and oratio, and by using quasi-commercial calculations to make ethical decisions. In each of these ways they fail most of all in Cicero’s eyes by representing a threat to the social fabric of the republic.
Hot executive functioning (EF) – EF under emotionally or motivationally salient conditions – is a putative etiology of attention-deficit/hyperactivity disorder (ADHD), disruptive behavior problems (DBPs), and their related impairments. Despite two decades of research, the present study is the first review of the construct in youth ADHD, with a particular focus on the role of task design, age, and DBPs, as well as relevant conceptual and methodological considerations. While certain hot EF tasks have been investigated extensively (e.g., choice impulsivity), substantial inconsistency in measurement of the broader construct remains, severely limiting conclusions. Future research should a) consider the extent to which various hot EF tasks relate to one another, a higher order factor, and other related constructs; b) further investigate task design, particularly the elicitation of emotion or motivation and its anticipated effect on EF; and c) incorporate multiple levels of analysis to validate similarities and differences among tasks with regard to the affective experiences and cognitive demands they elicit. With improved measurement and conceptual clarity, hot EF has potential to advance the literature on etiological pathways to ADHD, DBPs and associated impairments and, more broadly, may represent a useful tool for understanding the influence of emotion and motivation on cognition.
The Glasgow Composite Measure Pain Scale (CMPS) for dogs suffering acute pain, developed using psychometric methodology, measures pain to a level of precision suitable for clinical trials. However, for routine clinical use, where the emphasis is on speed, ease of use, and guidance for analgesia provision, a short form (CMPS-SF) was developed. The CMPS-SF comprises six behavioural categories with associated descriptive expressions (items): vocalisation (4), attention to wound (5), mobility (5), response to touch (6), demeanour (5) and posture/activity (5). Items are placed in increasing order of pain intensity and numbered accordingly. The observer chooses that item within each category which best describes the dog's behaviour and ranked scores are summed; the maximum pain score is 24, or 20 if mobility is impossible to assess. Veterinary surgeons in Glasgow, University College Dublin and North Carolina Veterinary Schools completed the CMPS-SF for 122 dogs undergoing post-operative care and thereafter were asked “Do you think this animal requires analgesia? Yes/No”. The population difference in median pain score, for dogs considered to require analgesia (seven) compared with those that did not (three), was highly statistically significant (P < 0.001). Consideration of a clinical decision-point for analgesia gave an intervention level of 6/24, and 5/20 when section B (mobility assessment) could not be carried out. Difficulties in recognising pain contribute to the sub-optimal use of analgesics in veterinary practice. The CMPS-SF provides a practical means of assessing acute post-operative pain and provides guidance with regard to analgesic requirement, so improving pain management and welfare. The CMPS-SF can be downloaded from the Glasgow Pain and Welfare website at http://www.gla.ac.uk/vet/painandwelfare.
The scientific study of animal welfare has generated a welter of complex, equivocal and often contradictory results. Consequently, there is little agreement about how impairment of welfare should be measured. While some solutions to this have been suggested, these have usually relied on more sophisticated versions of, or more control over, existing measures. However, we argue that the difficulties arise because of questionable assumptions in the definition and measurement of welfare, in particular the measurement of suffering and the assumed importance of individual well-being. We contend that welfare can be interpreted only in terms of what natural selection has designed an organism to do and how circumstances impinge on its functional design. Organisms are designed for self-expenditure and the relative importance of self-preservation and survival, and the concomitant investment of time and resources in different activities, varies with life history strategy. The traditional notions of coping and stress are anthropomorphisms based on homeostatic mechanisms of self-preservation in a long-lived species. Suffering-like states are viewed as generalized subjective states that are geared to avoiding deleterious circumstances with which the organism does not have specific adaptive mechanisms to deal. Attempts to measure suffering-like states directly are likely to remain inconclusive, at least for the foreseeable future, because such states are private and subjective, may take many forms fundamentally different from our own and are likely to depend on the operation of phenotype-limited priorities and decision rules. However, measuring the impact of circumstances on functional design via the organism ‘s decision rules provides a practicable means of giving benefit of the doubt by indicating when suffering, or an analogous subjective state, is likely.
Quality of life (QoL) is an abstract construct that has been formally recognised and widely used in human medicine. In recent years, QoL has received increasing attention in animal and veterinary sciences, and the measurement of QoL has been a focus of research in both the human and animal fields. Lord Kelvin said “When you cannot measure it, when you cannot express it in numbers — you have scarcely in your thoughts, advanced to a stage of science, whatever the matter may be” (Lord Kelvin 1893). So are we able to measure animal QoL? The psychometric measurement principles for abstract constructs such as human intelligence have been well rehearsed and researched. Application of traditional and newer psychometric approaches is becoming more widespread as a result of increasing human and animal welfare expectations which have brought a greater emphasis on the individual. In recent decades the field of human medicine has developed valid measures of experienced pain and QoL of individuals, including those who are not capable of self-report. More recently, researchers who are interested in the measurement of animal pain and QoL have begun to use similar methodologies. In this paper, we will consider these methodologies and the opportunities and difficulties they present.
Although the physiological and behavioural changes that can indicate poor welfare are generally agreed upon, using these measures in practice sometimes yields results that are hard to interpret. For example, different types of measure may suggest quite different things about an animal's welfare. Such contradictions are often due to the differing properties of the variables being measured. How each variable responds to a stressor can be affected by several factors - the type of unpleasant stimulus to which the animal is exposed; when and for how long exposure occurs; the animal's psychological state, eg does it feel that it is in control?; and the time at which the measurement is made, relative to the stressor. Typical responses also often differ between species and between individuals, and may even change in a single individual over time. Furthermore, some responses used to assess welfare lack specificity: they can be elicited by neutral or even pleasant events as well as by aversive ones. Appreciating these factors is vital when designing experiments, when choosing what to measure along with each welfare variable, and when interpreting results. Even after taking these factors into consideration, interpreting a result can still be difficult. One approach then is to consider the effects on welfare of the changes measured, eg if there is immunosuppression, does the animal succumb to disease? Another is to use the animal's behaviour to indicate its preference for, or aversion to, particular environments. Ultimately, however, interpreting welfare measures involves subjective judgements which will be influenced by the nature of our concern for the animal under consideration. By raising these problems, we hope that this review will highlight and clarify the apparent contradictions that sometimes emerge in scientific studies of animal welfare, and help researchers improve the designs of their experiments for the benefit of the animals concerned.
Standard methods for measuring latent traits from categorical data assume that response functions are monotonic. This assumption is violated when individuals from both extremes respond identically, but for conflicting reasons. Two survey respondents may “disagree” with a statement for opposing motivations, liberal and conservative justices may dissent from the same Supreme Court decision but provide ideologically contradictory rationales, and in legislative settings, ideological opposites may join together to oppose moderate legislation in pursuit of antithetical goals. In this article, we introduce a scaling model that accommodates ends against the middle responses and provide a novel estimation approach that improves upon existing routines. We apply this method to survey data, voting data from the U.S. Supreme Court, and the 116th Congress, and show that it outperforms standard methods in terms of both congruence with qualitative insights and model fit. This suggests that our proposed method may offer improved one-dimensional estimates of latent traits in many important settings.
Using a cognitive task (mental calculation) and a perceptual-motor task (stylized golf putting), we examined differential proficiency using the CWS index and several other quantitative measures of performance. The CWS index (Weiss & Shanteau, 2003) is a coherence criterion that looks only at internal properties of the data without incorporating an external standard. In Experiment 1, college students (n = 20) carried out 2- and 3-digit addition and multiplication problems under time pressure. In Experiment 2, experienced golfers (n = 12), also college students, putted toward a target from nine different locations. Within each experiment, we analyzed the same responses using different methods. For the arithmetic tasks, accuracy information (mean absolute deviation from the correct answer, MAD) using a coherence criterion was available; for golf, accuracy information using a correspondence criterion (mean deviation from the target, also MAD) was available. We ranked the performances of the participants according to each measure, then compared the orders using Spearman’s rs. For mental calculation, the CWS order correlated moderately (rs =.46) with that of MAD. However, a different coherence criterion, degree of model fit, did not correlate with either CWS or accuracy. For putting, the ranking generated by CWS correlated .68 with that generated by MAD. Consensual answers were also available for both experiments, and the rankings they generated correlated highly with those of MAD. The coherence vs. correspondence distinction did not map well onto criteria for performance evaluation.
Judgments and decisions can rely on rules to integrate cue information or on the retrieval of similar exemplars from memory. Research on exemplar-based processes in judgment has discovered several task variables influencing the dominant mode of processing. This research often aggregates data across participants or classifies them as using either exemplar-based or cue-based processing. It has been argued for theoretical and empirical reasons that both kinds of processes might operate together or in parallel. Hence, a classification of strategies may be a severe oversimplification that also sacrifices statistical power to detect task effects. We present a simple measurement tool combining both processing modes. The simple model contains a mixture parameter quantifying the relative contribution of both kinds of processes in a judgment and decision task. In three experiments, we validate the measurement model by demonstrating that instructions and task variables affect the mixture parameter in predictable ways, both in memory-based and screen-based judgments.
Health-related quality of life (HRQL) was defined for farmed animals and identified as an appropriate focus of integrative welfare measurement for farmed pigs that embraces measurement of positive welfare. The instrument for HRQL measurement was developed specifically for use by farmers and stockpersons, the prime carers of pigs, to increase ownership of welfare improvement amongst those groups. Using a psychometric approach to instrument development, relevant observations were determined by consultation with experienced farmers and stockpersons. These observations included causal variables (cause changes in HRQL) and indicator variables (manifest changes in HRQL). The variables selected as items in the structured questionnaire instrument were those most commonly applied by farmers and stockpersons and also were assigned similar quality-of-life impact by a range of experts including pig veterinary specialists and welfare scientists. The prototype instrument comprises a questionnaire with 98 causal variable items (covering five domains of welfare according with the Five Freedoms) and 30 indicator variable items. It was pre-tested with farmers and stockpersons on commercial farm units and was found to have content (face) validity and high utility. This tool is a novel measure of HRQL in farmed pigs that encompasses the measurement of positive welfare and promotes a move from welfare assurance to welfare enhancement. Further validation of the instrument is described in a companion paper in this issue.
The use of exchange rates based on Purchasing Power Parities to compare incomes across countries and over time has now become standard practice. But there are reasons to believe that this could lead to excessively inflated incomes for poorer countries and in some cases also inflate the extent of real changes over time. Estimates of gross domestic product growth in the Chinese and Indian economies in recent years provide examples of this.
Research has identified loss aversion as a strong and robust phenomenon, but has also revealed some moderators affecting the magnitude of its effect on decision making. In the current article, we draw attention to the fact that even the measurement of loss aversion itself may affect its magnitude by inducing a focus on either losses or gains. In three studies, we provide empirical evidence for such a measurement-induced focus. In all studies we used coin-toss gambles—in which there is a 50/50 chance to win or to lose—to assess gain/loss ratios as a measure of loss aversion. Participants either filled out the loss side or the gain side of this gain/loss ratio. The studies consistently showed that—using within- and between-subject designs and anticipated and real coin-toss gambles—the strength of loss aversion depended on the measurement format (fill-in-the-loss versus fill-in-the-gain); filling in the loss side increased loss aversion. Moreover, loss aversion was more affected by the stakes of the gamble in the fill-in-the-loss format than in the fill-in-the-gain format.
In two studies, time preferences for financial gains and losses at delays of up to 50 years were elicited using three different methods: matching, fixed-sequence choice titration, and a dynamic “staircase” choice method. Matching was found to create fewer demand characteristics and to produce better fits with the hyperbolic model of discounting. The choice-based measures better predicted real-world outcomes such as smoking and payment of credit card debt. No consistent advantages were found for the dynamic staircase method over fixed-sequence titration.
Regret is one of the most common emotions, but researchers generally measure it in an ad-hoc, unvalidated fashion. Three studies outline the construction and validation of the Regret Elements Scale (RES), which distinguishes between an affective component of regret, associated with maladaptive affective outcomes, and a cognitive component of regret, associated with functional preparatory outcomes. The present research demonstrates the RES’s relationship with distress (Study 1), appraisals of emotions (Study 2), and existing measures of regret (Study 3). We further demonstrate the RES’s ability to differentiate regret from other negative emotions (Study 2) and related traits (Study 3). The scale provides both a new theoretical perspective on regret, and a tool for researchers interested in measuring post-decisional regret.
The development of a novel structured questionnaire instrument to measure health-related quality of life (HRQL) in individual farmed pigs was described previously (companion paper). The instrument embraces the measurement of positive welfare, and was developed with farmers and stockpersons, for use by them on-farm. This paper describes the development of a scoring methodology for the instrument and provides evidence for its construct validity. Field testing on four commercial farm units indicated that scores for health and affect correctly allocated 88.7% of pigs to known treatment groups and strongly predicted previously defined intervention levels. The tool was also used in an experimental study alongside other measures to identify the impact of early-life challenges (mixing of pregnant gilts and tail-docking neonatal pigs) on subsequent pig welfare, and identified long-term changes in HRQL of prenatally stressed piglets, a finding supported by other measures. This work describes a novel approach to farm-level welfare assessment in which entirely animal-based HRQL measurement can provide a measure of welfare at the herd level while retaining information about individuals within the herd and about aspects of provision that can be targets of intervention to improve welfare, and promotes a move from welfare assurance to welfare enhancement.
Prospect Theory proposed that the (dis)utility of losses is always more than gains due to a phenomena called ‘loss-aversion’, a result obtained in multiple later studies over the years. However, some researchers found reversed or no loss-aversion for affective judgments of small monetary amounts but, those findings have been argued to stem from the way gains versus losses were measured. Thus, it was not clear whether loss-aversion does not show with affective judgments for smaller magnitudes, or it is a measurement error. This paper addresses the debate concerning loss-aversion (in the prospect theoretic sense) and judgments about the intensity of gains and losses. We measured affective prospective judgments for monetary amounts using measurement scales that have been argued to be suitable for measuring loss-aversion and hence rule out any explanations regarding measurement. Both in a gambling scenario (Experiments 1 and 2) and in the context of fluctuating prices (Experiments 3a and 3b), potential losses never loomed larger than gains for low magnitudes, indicating that it is not simply a measurement error. Moreover, for the same participant, loss aversion was observable at high magnitudes. Further, we show that loss-aversion disappears even for higher monetary values, if contextually an even larger anchor is provided. The results imply that Prospect Theory’s value function is contextually dependent on magnitudes.
Health system performance assessment (HSPA) is a promising tool to evaluate health system capacity in achieving health systems goals and informed policy for health systems strengthening. Despite its importance, no universal definition is available at global level to support HSPA implementation. This chapter highlights the evolution of HSPA frameworks, which mostly follow the scope and boundaries of health systems. Key characteristics of successful HSPA include regularity, transparency, comprehensiveness, being analytical and systematic, which result in valid assessment and inform policy. HSPA requires selection of indicators suitable to the country context; the criteria for selecting indicators include importance, relevance, feasibility, reliability and validity. Hospital performance assessment, a subset of the HSPA, is necessary as it consumes signification portion of health resources. HPSA also contributes to monitoring achievement of SDG targets 3.8.1 and 3.8.2 on Universal Health Coverage as committed by countries. The chapter concludes by providing evidence how Thailand's health system performed in response to COVID-19 pandemic.