Candidate Items Research Articles

Multistart solution-based tabu search for the Set-Union Knapsack Problem

The NP-hard Set-Union Knapsack Problem is a general model able to formulate a number of practical problems. As a variant of the popular knapsack problem, SUKP is to find a subset of candidate items (an item is composed of several distinct weighted elements) such that a profit function is maximized while a knapsack capacity constraint is satisfied. We investigate for the first time a multistart solution-based tabu search algorithm for solving the problem. The proposed algorithm combines a solution-based tabu search procedure with a multistart strategy to ensure an effective examination of candidate solutions. We report computational results on 60 benchmark instances from the literature, including new best results (improved lower bounds) for 7 large instances. We show additional experiments to shed lights on the roles of the key composing ingredients of the algorithm. The code of the algorithm will be publicly available.

Revision of the Wisconsin Smoking Withdrawal Scale: Development of brief and long forms.

The assessment of tobacco withdrawal is important for both research and clinical purposes. This study describes the psychometric development of a revised version of the 28-item Wisconsin Smoking Withdrawal Scale (WSWS; Welsch et al., Experimental and Clinical Psychopharmacology, 1999, 7, p. 354). Because the different contexts of use sometimes permit only brief assessment, this revision has produced both a brief and longer form using an updated pool of candidate items. For the revised Wisconsin Smoking Withdrawal Scale 2 (WSWS2), a candidate pool of 37 items was developed to measure nine putative withdrawal constructs. The stem and wording of items were revised as was the response scale. Data for psychometric analyses were derived from three smoking cessation randomized clinical trials conducted at the University of Wisconsin Center for Tobacco Research and Intervention. Dimensionality, internal consistency, and item characteristic analyses of the candidate items were conducted in a derivation sample to ascertain the factor structure and to identify items that could be used in the WSWS2 scales. Confirmatory factor analyses (CFAs) of reduced item sets and factor structure were conducted in two validation samples along with reliability and validity analyses. Derivation and validation sample analyses yielded a longer version of the WSWS2 (WSWS2-L) with 19 items and six subscales (Craving, Negative Affect, Hunger, Sleep, Restlessness, and Concentration) and a brief 6-item version (WSWS2-B). In validation sample analyses, both the WSWS2-L and the WSWS2-B demonstrated good reliability and validity as well as good fit in CFAs. The WSWS2-L and WSWS2-B possess improved construct coverage, fewer items, and other enhancements relative to the WSWS. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Development of an ICF Core Set for adults with cerebral palsy: capturing their perspective on functioning.

AimTo examine the most relevant aspects of functioning of adults with cerebral palsy (CP) from their perspective, in order to develop an International Classification of Functioning, Disability and Health (ICF) Core Set for adults with CP.MethodWe conducted six focus group discussions with adults with CP without intellectual disability and seven interviews with adults with CP with intellectual disability and caregivers, addressing all ICF components. Meaningful concepts were identified from verbatim transcripts and linked to ICF categories by two independent researchers.ResultsIn total, 31 adults with CP without intellectual disability (mean [SD] age 46y 1mo [14y 1mo]; 20 females, 11 males; Gross Motor Function Classification System [GMFCS] levels I–IV) and seven adults with CP and intellectual disability (mean [SD] age 25y 8mo [6y 8mo]; four females, three males; GMFCS levels III–V) participated. We identified 132 unique second‐level categories: 47 body functions, seven body structures, 43 activities and participation, and 35 environmental factors. The most frequently mentioned categories were emotional function, pain, muscle tone function, support of family, products and technology, and health services.InterpretationAdults with CP experienced problems in a broad range of body functions and activities and indicated the importance of environmental factors for functioning. The identified categories will be added to the list of candidate items to reach consensus on an ICF Core Set for adults with CP. What this paper adds Including the lived experience is crucial for fully understanding functioning of adults with cerebral palsy (CP).Adults with CP perceive environmental factors as essential elements for everyday functioning.Adults with intellectual disability should be considered as a group with specific problems.

The development of incorpoRATE: A measure of physicians’ willingness to incorporate shared decision making into practice

ObjectivesTo develop ‘incorpoRATE’, a brief and broadly applicable measure of physicians’ willingness to incorporate shared decision making (SDM) into practice. MethodsincorpoRATE was developed across three phases: 1) A review of relevant literature to inform candidate domain and item development, 2) Cognitive interviews with US physicians to iteratively refine the measure, and 3) Pilot testing of the measure across a larger sample of US physicians to explore item and measure performance. ResultsThe final measure consists of seven items that assess physician perspectives on various components of SDM use that may present as barriers in practice. During pilot testing, the majority of physicians expressed positive opinions about the overall concept of SDM, yet were less comfortable acting on informed patient choices when there was known incongruence with their own recommendations. ConclusionsincorpoRATE is a novel physician-reported measure that assesses physicians’ willingness to incorporate SDM in practice. Practice implicationsincorpoRATE has the potential to help us further understand the limited adoption of SDM and areas of focus for improving the use of SDM in the future. We recommend that incorpoRATE be subject to further psychometric, real-world testing, in order to explore its performance across different samples of physicians and organizations.

Measuring the impact of burn injury on the parent-reported health outcomes of children 1-to-5 years: Item pool development for the Preschool1–5 Life Impact Burn Recovery Evaluation (LIBRE) Profile

Modern, reliable, and valid outcome measures are essential to understanding the health needs of young children with burn injuries. Burn-specific and age-appropriate legacy assessment tools exist for this population but are hindered by the limitations of existing paper-based instruments. The purpose of this study was to develop item pools comprised of questions appropriate for children aged 1–5 with burn injuries. Item development was based on a framework provided by previous work to develop the Preschool Life Impact Burn Recovery Evaluation (LIBRE) Conceptual Model. The Preschool LIBRE Conceptual Model work established four sub-domains of functioning for children with burns aged 1–5. Item development involved a systematic literature review, a qualitative item review process with clinical experts, and parent cognitive interviews. Four item pools were established: (1) communication and language development; (2) physical functioning; (3) psychological functioning and (4) social functioning for preschool-aged children with burn injuries. We selected and refined candidate items, recall periods, survey instructions, and response option choices through clinical and parental feedback during the qualitative review and cognitive interview processes. Item pools are currently being field-tested as part of the process to calibrate and validate the Preschool1–5 LIBRE Computer Adaptive Test (CAT) Profile.

Improving the Delivery of Function-Directed Care During Acute Hospitalizations: Methods to Develop and Validate the Functional Assessment in Acute Care Multidimensional Computerized Adaptive Test (FAMCAT)

Objective:To (1) develop a patient-reported, multidomain functional assessment tool focused on medically ill patients in acute care settings; (2) characterize the measure's psychometric performance; and (3) establish clinically actionable score strata that link to easily implemented mobility preservation plans. Design:This article describes the approach that our team pursued to develop and characterize this tool, the Functional Assessment in Acute Care Multidimensional Computer Adaptive Test (FAMCAT). Development involved a multistep process that included (1) expanding and refining existing item banks to optimize their salience for hospitalized patients; (2) administering candidate items to a calibration cohort; (3) estimating multidimensional item response theory models; (4) calibrating the item banks; (5) evaluating potential multidimensional computerized adaptive testing (MCAT) enhancements; (6) parameterizing the MCAT; (7) administering it to patients in a validation cohort; and (8) estimating its predictive and psychometric characteristics. Setting:A large (2000-bed) Midwestern Medical Center. Participants:The overall sample included 4495 adults (2341 in a calibration cohort, 2154 in a validation cohort) who were admitted either to medical services with at least 1 chronic condition or to surgical/medical services if they required readmission after a hospitalization for surgery (N=4495). Intervention:Not applicable. Main Outcome Measures:Not applicable. Results:The FAMCAT is an instrument designed to permit the efficient, precise, low-burden, multidomain functional assessment of hospitalized patients. We tried to optimize the FAMCAT's efficiency and precision, as well as its ability to perform multiple assessments during a hospital stay, by applying cutting edge methods such as the adaptive measure of change (AMC), differential item functioning computerized adaptive testing, and integration of collateral test-taking information, particularly item response times. Evaluation of these candidate methods suggested that all may enhance MCAT performance, but none were integrated into initial MCAT parameterization. Conclusions:The FAMCAT has the potential to address a longstanding need for structured, frequent, and accurate functional assessment among patients hospitalized with medical diagnoses and complications of surgery.

Development and validation of a scale to measure diabetes burnout

IntroductionThe aim of this study is to establish reliability and validity of the Diabetes Burnout Scale (DBS) among adults with type 1 diabetes (T1D). MethodsWe used a multi-stage, mixed methods approach to developing the DBS. First, the research team identified twenty-eight candidate items through a review of the literature and 117 qualitative narratives from adults living with T1D. Next, items were revised based on the expert (n = 20) and individual with T1D (n = 10) feedback. The resulting 18-item DBS measure along with validated measures of diabetes distress, depressive symptoms, and questions related to diabetes outcomes (i.e., last reported hemoglobin A1c [HbA1c] and Time-in-Range [TiR]) were completed by 1099 adults with T1D across the U.S. The sample was randomly divided into two subsets (n1 = 561, n2 = 538) for exploratory and confirmatory factor analyses (EFA/CFA) to determine the underlying structure of the DBS. Regression analyses examined the relationships of the DBS with self-reported glycemic control and socio-demographic characteristics. ResultsBased on the EFA three factors are identified and the DBS demonstrated strong internal consistency with Cronbach alphas (≥0.80). The validation and confirmatory analysis for the structure of the DBS provided consistent results with EFA. Higher burnout (overall DBS) was positively associated with diabetes distress (b = 0.74; p < 0.01) and depressive symptoms (b = 0.61; p < 0.01). Overall DBS, however was the strongest predictor for poorer HbA1c (r2 = 0.19; p < 0.01) and lower TiR (r2 = 0.17; p < 0.01) compared to diabetes distress and depressive symptoms. ConclusionThe 12-item DBS is a reliable and valid scale to measure diabetes burnout in adults with diabetes. The results provide a weak to strong degree of association between the validated DBS scale, T1-DDS and PHQ-8. The DBS can contribute to advancement of diabetes science by measuring diabetes burnout and informing clinical interventions to improve psychosocial care in individuals with diabetes.

The Development and Validation of the Robotics Learning Self-Efficacy Scale (RLSES)

Robotics education has gradually been emphasized in contemporary school curricula; however, assessment tools for robotics learning are still limited. Based on Bloom’s Taxonomy of educational objectives, this study aimed to develop the Robotics Learning Self-Efficacy Scale (RLSES) with a two-level construct of five dimensions for assessing students’ self-efficacy for learning robotics. A total of 181 elementary, junior high and senior high school students (5th–12th graders) with robotics learning experience were selected as the sample of this study. A questionnaire including 32 candidate items designed for the initial version of the RLSES was administered to the sample. An exploratory factor analysis was conducted and, finally, 16 items were drawn for the final RLSES under five subscales ( Comprehension, Practice, Analysis, Application, and Collaboration), with a total explained variance of 85.28%. The Cronbach’s alpha reliability was .97 for the overall scale, ranging from .87 to .95 for the subscales. The inter-correlation analysis showed evidence of discriminant validity. Regression analysis results supported that Practice and Comprehension self-efficacy were significant predictors of Analysis, Application, and Collaboration self-efficacy, confirming the two-level (2 × 3) construct of the RLSES. Significant differences among school levels were found and are discussed.

Patient perceptions of health-related quality of life in giant cell arteritis: international development of a disease-specific patient-reported outcome measure.

ObjectivesGCA is a large vessel vasculitis (LVV) presenting with headache, jaw claudication, musculoskeletal and visual involvement. Current treatment is glucocorticoids and anti-IL-6 tocilizumab in refractory disease. The objective of this study was to explore the impact of GCA and its treatment on people’s health-related quality of life (HRQoL), to inform the development of a disease-specific patient-reported outcome measure (PROM) for use in clinical trials and practice.MethodsParticipants from the UK and Australia, with biopsy- or imaging-confirmed GCA, were interviewed to identify salient aspects of HRQoL in relation to GCA and its treatment. Purposive sampling included a range of demographic and disease features (cranial, LVV-GCA and visual involvement). Inductive analysis identified individual themes of importance, then domains. Candidate questionnaire items were developed from the individual themes, refined by piloting, cognitive interviews and a linguistic translatability assessment.ResultsThirty-six interviews were conducted to saturation with participants with GCA from the UK (25) and Australia (11). Mean age was 74 years, 23 (63.9%) were female, 13 (36.1%) had visual loss and 5 (13.9%) had LVV-GCA. Thirty-nine individual themes within five domains were identified: physical symptoms; activity of daily living and function; participation; psychological impact; and impact on sense of self and perception of health. Sixty-nine candidate items were developed from individual themes; piloting and refinement resulted in a 40-item draft questionnaire.ConclusionThis international qualitative study underpins the development of candidate items for a disease-specific PROM for GCA. The draft questionnaire is now ready for psychometric testing.

Coarse-to-fine: A dual-view attention network for click-through rate prediction

Click-Through Rate (CTR) prediction is one of the most challenging tasks in the advertising systems, which aims to estimate the probability of a candidate user clicking on a candidate item. Recently, CTR prediction has observed remarkable progress, due to the advances of the Deep Neural network (DNN) in learning representation. However, most of the existing DNN-based methods focus on modeling implicit information from the user aspect, while ignoring the correlations between the user and other objects in the historical interactive behaviors (e.g., user→items or user→users). Additionally, the large-scale historical interactive behaviors also bring the model a lot of difficulty in finding precise relations from redundant and noisy data. Targeted at the above issues, our paper introduces a simple yet effective model, which boosts the user-view and item-view (i.e., dual-view) to extract various interactive relationships for CTR prediction. Therefore, we name our model as Dual-View Attention Network (DVAN). More specifically, we propose a cross-domain attention module (i.e., user→items and item→users) to extract the coarse-level correlations, and a local homogeneous-domain attention module (i.e., user→users and item→items) to extract the fine-level correlations adaptively. In order to extract the accurate relationship from the large-scale historical behaviors, a novel selection mechanism is introduced to connect the cross-domain attention module and the local homogeneous-domain attention module, and thus builds representation from the coarse-level to the fine-level gradually. Experimental results on four public datasets have demonstrated the effectiveness of our method, which outperforms existing state-of-the-art methods.

An international mixed methods study to develop a new preference-based measure for women with breast cancer: the BREAST-Q Utility module

BackgroundGeneric preference-based measures (PBM), though commonly used, may not be optimal for use in economic evaluations of breast cancer interventions. No breast cancer-specific PBM currently exists, and the generic PBMs fail to capture the unique concerns of women with breast cancer (e.g., body image, appearance, treatment-specific adverse effects). Hence, the objective of this study was to develop a breast cancer-specific PBM, the BREAST-Q Utility module.MethodsWomen diagnosed with breast cancer (stage 0–4, any treatment) were recruited from two tertiary hospitals in Canada and one in the US. The study followed an exploratory sequential mixed methods approach, whereby semi-structured interviews were conducted and at the end of the interview, participants were asked to list their top five health-related quality of life (HRQOL) concerns and to rate the importance of each item on the BREAST-Q. Interviews were audio-recorded, transcribed verbatim, and coded. Constant comparison was used to refine the codes and develop a conceptual framework. Qualitative and quantitative data were triangulated to develop the content of the Utility module that was refined through 2 rounds of cognitive debriefing interviews with women diagnosed with breast cancer and feedback from experts.ResultsInterviews were conducted with 57 women aged 55 ± 10 years. A conceptual framework was developed from 3948 unique codes specific to breasts, arms, abdomen, and cancer experience. Five top-level domains were HRQOL (i.e., physical, psychological, social, and sexual well-being) and appearance. Data from the interviews, top 5 HRQOL concerns, and BREAST-Q item ratings were used to inform dimensions for inclusion in the Utility module. Feedback from women with breast cancer (N = 9) and a multidisciplinary group of experts (N = 27) was used to refine the module. The field-test version of the HSCS consists of 10 unique dimensions. Each dimension is measured with 1 or 2 candidate items that have 4–5 response levels each.ConclusionThe field-test version of the BREAST-Q Utility module was derived from extensive patient and expert input. This comprehensive approach ensured that the content of the Utility module is relevant, comprehensive, and includes concerns that matter the most to women with breast cancer.

Development and Initial Validation of Micromanagement Scale for School Principals

The aim of this study is to develop a valid and reliable measurement tool that can be used to measure the level of school principals’ micromanagement behavior. After a comprehensive literature review, a candidate item pool with 52 items was created. While writing the items, micro-manager behaviors defined in the literature were adapted to school principals. The items were submitted to the expert opinion and necessary corrections were made in the items in line with the feedback from the experts. Candidate items were applied to two different samples to carry out validity and reliability analysis. Data obtained from the first sample of 304 teachers were used for exploratory factor analysis. The second sample group consisted of 353 teachers and the data obtained from this group was used for confirmatory factor analysis and reliability analysis. The findings support the four-dimensional structure of the scale with 27 items. The first dimension was named as “unable to subordinate self (15 items)”, the second dimension was “time manipulation (5 items)”, the third dimension was “excessive control over methodology (4 items)” and the fourth dimension was “excessive reporting (3 items)”. Findings from reliability analyses were also satisfactory. To determine the reliability of the scale Cronbach’s Alpha internal consistency coefficients were calculated. It was .958 for the first factor, .831 for the second, .776 for the third and .743 for the fourth and .959 for the total scale. In this context, it can be stated that the scale is valid and reliable. It can be used to determine the level of school principals’ micromanagement behavior and to associate this behavior with different organizational variables.

GAN-GLS: Generative Lyric Steganography Based on Generative Adversarial Networks

Steganography based on generative adversarial networks (GANs) has become a hot topic among researchers. Due to GANs being unsuitable for text fields with discrete characteristics, researchers have proposed GAN-based steganography methods that are less dependent on text. In this paper, we propose a new method of generative lyrics steganography based on GANs, called GAN-GLS. The proposed method uses the GAN model and the large-scale lyrics corpus to construct and train a lyrics generator. In this method, the GAN uses a previously generated line of a lyric as the input sentence in order to generate the next line of the lyric. Using a strategy based on the penalty mechanism in training, the GAN model generates non-repetitive and diverse lyrics. The secret information is then processed according to the data characteristics of the generated lyrics in order to hide information. Unlike other text generation-based linguistic steganographic methods, our method changes the way that multiple generated candidate items are selected as the candidate groups in order to encode the conditional probability distribution. The experimental results demonstrate that our method can generate high-quality lyrics as stego-texts. Moreover, compared with other similar methods, the proposed method achieves good performance in terms of imperceptibility, embedding rate, effectiveness, extraction success rate and security.

Analysis of Rural Tourism Demand Characteristics and Experience Differences Based on Association Rule Mining

Whether the characteristics of rural tourism changes or not provides the scale and basis for judging whether the rural tourism landscape has changed, but it cannot provide a judgment on the impact of rural tourism landscape changes. The impact is relative to the rural tourism landscape goal. The determination of rural tourism landscape objectives provides a baseline for judging the direction and impact of rural tourism characteristics and provides a prerequisite for rural tourism landscape actions. The determination of the quality target of the rural tourism landscape is mainly determined by the internal process and external demand of the rural tourism landscape. Through in‐depth research on the frequent pattern growth algorithm FP‐Growth, the algorithm can find frequent item sets by not generating candidate item sets. The core of the algorithm is the frequent pattern tree FP‐tree, which can efficiently compress the transaction database. Based on the advantages of FP‐tree, this paper improves a FP_Apriori algorithm based on frequent pattern trees. This algorithm projects the entire transaction database onto the FP‐tree, avoiding a lot of I/O overhead. At the same time, I propose a more directional and targeted search strategy for FP‐tree, which reduces the running time of the algorithm and uses the principle of the Mapping_Apriori algorithm to prethin the frequent item sets. This article uses the text analysis method of network data to excavate the characteristics and internal structure of rural tourism demand. The rural tourism market has a wide range of needs and multiple levels, and traditional research methods such as questionnaires have limited sample size and sample structure. With the help of network data, text mining, and other statistical analysis methods, in‐depth empirical research on the characteristics and spatial structure of rural tourism in a certain region can cover more research groups. The research confirms that the results of using text analysis and questionnaire analysis on the perception of destination image are relatively consistent. Therefore, the network text analysis method is an effective tool to study the demand structure of the rural tourism market.

Measuring Bladder Health: Development and Cognitive Evaluation of Items for a Novel Bladder Health Instrument.

We describe the item development and cognitive evaluation process used in creating the Prevention of Lower Urinary Tract Symptoms Bladder Health Instrument (PLUS-BHI). Questions assessing bladder health were developed using reviews of published items, expert opinion, and focus groups' transcript review. Candidate items were tested through cognitive interviews with community-dwelling women and an online panel survey. Items were assessed for comprehension, language, and response categories and modified iteratively to create the PLUS-BHI. Existing measures of bladder function (storage, emptying, sensation components) and bladder health impact required modification of time frame and response categories to capture a full range of bladder health. Of the women 167 (18-80 years old) completed individual interviews and 791 women (18-88 years) completed the online panel survey. The term "bladder health" was unfamiliar for most and was conceptualized primarily as absence of severe urinary symptoms, infection, or cancer. Coping mechanisms and self-management strategies were central to bladder health perceptions. The inclusion of prompts and response categories that captured infrequent symptoms increased endorsement of symptoms across bladder function components. Bladder health measurement is challenged by a lack of awareness of normal function, use of self-management strategies to mitigate impact on activities, and a common tendency to overlook infrequent lower urinary tract symptoms. The PLUS-BHI is designed to characterize the full spectrum of bladder health in women and will be validated for research use.

ThyroidEx: Development and Preliminary Validation of a Thyroid Surgery Expectations Measure.

To address the lack of validated patient-reported outcome (PRO) instruments that define and quantify patient expectations in thyroid cancer surgery, we developed and initially validated ThyroidEx, a novel disease-specific PRO instrument. Survey study. Single-institution tertiary care cancer center. An expert panel drafted an initial set of thyroid cancer-specific concepts, which was used in semistructured concept elicitation interviews with patients with thyroid cancer 4 weeks before and 8 weeks after surgery. Candidate items were generated per patient responses and refined via cognitive interviewing and additional review by the expert panel. The draft ThyroidEx was then preoperatively administered to a separate cohort undergoing thyroid cancer surgery to establish a final item set and initial psychometric evidence. Prospective concept elicitation interviews generated 358 patient-elicited concepts (n = 15 patients). These were then placed into 70 unique subcategories from which 41 items were generated for cognitive interviews with 20 patients preoperatively and 28 postoperatively. After expert panel review, ThyroidEx included 18 items across 2 scales (Expectations and Concerns), with an additional item about beliefs. In the preoperative cohort in phase 2 (n = 67), internal consistency Cronbach's α values ranged from 0.81 to 0.89. Descriptive analysis showed significant differences between patients' concerns and expectations and clinicians' perceptions. Defining expectations represents an important modifier in the measurement of PROs. Preliminary validation of ThyroidEx revealed incongruent expectations between expert opinion and patients. Future development and implementation of ThyroidEx may affect preoperative consultation and the consent process.

Development of the Global Network for Women\u2019s and Children\u2019s Health Research\u2019s socioeconomic status index for use in the network\u2019s sites in low and lower middle-income countries

BackgroundSocioeconomic status (SES) is an important determinant of health globally and an important explanatory variable to assess causality in epidemiological research. The 10th Sustainable Development Goal is to reduce disparities in SES that impact health outcomes globally. It is easier to study SES in high-income countries because household income is representative of the SES. However, it is well recognized that income is poorly reported in low- and middle- income countries (LMIC) and is an unreliable indicator of SES. Therefore, there is a need for a robust index that will help to discriminate the SES of rural households in a pooled dataset from LMIC.MethodsThe study was nested in the population-based Maternal and Neonatal Health Registry of the Global Network for Women’s and Children’s Health Research which has 7 rural sites in 6 Asian, sub-Saharan African and Central American countries. Pregnant women enrolling in the Registry were asked questions about items such as housing conditions and household assets. The characteristics of the candidate items were evaluated using confirmatory factor analyses and item response theory analyses. Based on the results of these analyses, a final set of items were selected for the SES index.ResultsUsing data from 49,536 households of pregnant women, we reduced the data collected to a 10-item index. The 10 items were feasible to administer, covered the SES continuum and had good internal reliability and validity. We developed a sum score-based Item Response Theory scoring algorithm which is easy to compute and is highly correlated with scores based on response patterns (r = 0.97), suggesting minimal loss of information with the simplified approach. Scores varied significantly by site (p < 0.001). African sites had lower mean SES scores than the Asian and Central American sites. The SES index demonstrated good internal consistency reliability (Cronbach’s alpha = 0.81). Higher SES scores were significantly associated with formal education, more education, having received antenatal care, and facility delivery (p < 0.001).ConclusionsWhile measuring SES in LMIC is challenging, we have developed a Global Network Socioeconomic Status Index which may be useful for comparisons of SES within and between locations. Next steps include understanding how the index is associated with maternal, perinatal and neonatal mortality.Trial Registration NCT01073475Plain English summarySocioeconomic status (SES) is an important determinant of health globally, and improving SES is important to reduce disparities in health outcomes. It is easier to study SES in high-income countries because it can be measured by income and what income is spent on, but this concept does not translate easily to low and middle income countries. We developed a questionnaire that includes 10 items to determine SES in low-resource settings that was added to an ongoing Maternal and Neonatal Health Registry that is funded by the National Institutes of Child Health and Human Development’s Global Network. The Registry includes sites that collect outcomes of pregnancies in women and their babies in rural areas in 6 countries in South Asia, sub-Saharan Africa and Central America. The Registry is population based and tracks women from early in pregnancy to day 42 post-partum. The questionnaire is easy to administer and has good reliability and validity. Next steps include understanding how the index is associated with maternal, fetal and neonatal mortality.

Rasch analysis of the long-term conditions questionnaire (LTCQ) and development of a short-form (LTCQ-8)

BackgroundThe aim of the current study was to evaluate the structural validity of the 20-item long-term conditions questionnaire (LTCQ) and to explore a potential short-form version of the scale using Rasch analysis.MethodsData were collected through postal surveys (February 2016–January 2017) from a sample of 1,211 participants diagnosed with at least one long-term condition (LTC). Identified participants were invited through either local authorities for a social care cohort (n = 294) or primary care practices for a health care cohort (n = 917). Participants were mailed a survey, including the LTCQ, demographic questions, a comorbidities measure, and other validated outcome measures. Respondents were invited to complete a follow-up survey including the LTCQ for assessment of reproducibility.ResultsThe main assumptions of the Rasch model from the LTCQ were fulfilled, although infit and outfit indices indicated some items showed misfit. Misfitted items, items that did not have a preceding set or showed some local dependence were removed one at a time, with the remaining candidate items to form an 8-item short version, the LTCQ-8. The Rasch model for the LTCQ-8 explained 64% variance and had a reliability estimate greater than 0.80. Several items in the LTCQ showed uniform differential item function (DIF) in relation to the number of reported LTCs, age, cohort and type of LTCs, but fewer items exhibited DIF in the LTCQ-8. Spearman’s rho correlations between the LTCQ and the LTCQ-8 were strong across the total sample and various subgroups. Correlations between the LTCQ-8 and all reference measures were moderate to strong, and comparable to correlations found between the LTCQ and these measures.ConclusionsThe LTCQ measures a unidimensional construct, and it is therefore acceptable to use a summed total score. The LTCQ-8 also met the assumption of unidimensionality and had comparable construct validity with the LTCQ. Additional validation is required in an independent sample.

Development of the Labor Pain Relief Attitude Questionnaire for pregnant women (LPRAQ-p)

BackgroundReceiving epidural analgesia during labor can possibly have negative consequences for mother and child. Yet, the use of epidural analgesia rapidly increased in the Netherlands over the last decade. Since antenatal plans for labor pain relief have been related to epidural analgesia use during labor, the aim of the current study was to develop a Labor Pain Relief Attitude Questionnaire for pregnant women (LPRAQ-p).MethodsThree focus group interviews were conducted with pregnant women, new mothers and caregivers and 13 candidate items were derived. Psychometric properties were tested with explorative factor analysis in sample I (N = 429) and a subsequent confirmatory factor analysis in a different sample II (N = 432).ResultsThe explorative factor analysis suggested a two-factor seven-item solution: a ‘women’s perception’ and ‘social environment’ subscale. The confirmatory factor analysis confirmed an excellent six-item model fit with appropriate internal consistency. Higher scores on the six-item LPRAQ-p indicate greater willingness for request of pain relief medication during labor. Two-tailed t-tests showed that women with elevated levels of depression and pregnancy-specific distress symptoms, nulliparous women and multiparous women with complications during a previous delivery had greater willingness for request of pain relief medication during labor. Linear regression showed that the most important association with higher scores on the LPRAQ-p were high pregnancy-specific distress symptoms.ConclusionsThis study showed the LPRAQ-p to be a valid instrument to evaluate attitude towards labor pain relief in pregnant women. High scores on this questionnaire are associated with high levels of pregnancy-specific distress symptoms.

The Computational Thinking Scale for Computer Literacy Education

Computational thinking has received tremendous attention from computer science educators and educational researchers in the last decade. However, most prior literature defines computational thinking as thinking outcomes rather than thinking processes. Based on Selby and Woodland’s framework, this study developed and validated the Computational Thinking Scale (CTS) to assess all students’ thought processes of computational thinking for both general and specific problem-solving contexts in five dimensions: abstraction, decomposition, algorithmic thinking, evaluation and generalization. A survey including 25 candidate items for CTS as well as demographic variables was administered to 388 junior high school students in Taiwan. An explorative factor analysis using the principal axis method with the oblimin rotation was used to validate the scale. Finally, 19 items were extracted successfully under the designed five dimensions, with a total explained variance of 64.03% and an overall reliability of 0.91. Results of the demographic comparisons showed that boys had a greater disposition than girls in decomposition thinking when solving problems using computer programming. In addition, programming learning experience, especially self-directed learning and after-school learning, had significant positive effects on all dimensions of CTS. Several future studies are suggested using this tool.