Measurement Framework Research Articles

Measuring Wellbeing Across Culture and Context – are we Getting it Right? Evaluating the Variation in Wellbeing Conceptualisations Throughout the World

Researchers, practitioners, and policy makers have been increasingly interested in measuring wellbeing over the last two decades. However, with many measurement tools and frameworks being replicated in contexts distinct from where they were developed, it raises the question as to whether we are measuring the right things. This study draws on data collected through a systematic review of participatory wellbeing frameworks to better understand how wellbeing conceptualisations differ based on country context throughout the world. This analysis is one of the first of its kind, enabling a deeper and more comprehensive insight into cross-cultural understandings of wellbeing. The findings indicate that while there is some degree of universality in how wellbeing is conceptualised in different country contexts, cross-cultural variation is also evident. These findings have important implications for wellbeing measurement throughout the world, indicating that researchers, practitioners, and policymakers should exercise some caution when utilising wellbeing measurement tools and frameworks that were developed in contexts distinct from the population of interest. Furthermore, this study highlights the value of participatory approaches in better understanding these nuanced conceptualisations of wellbeing within different population groups throughout the world. Having greater awareness of cross-cultural differences in wellbeing conceptualisations will help ensure that we are more closely measuring what matters to people.

Generating Utilities for the Château-Santé Base: A Novel, Generic, and Patient-Centered Health-Outcome Measure

ObjectivesWe have developed a new patient-centered, preference-based generic health-outcome measure, Château-Santé Base (CS-Base), which is based on a novel multiattribute preference response (MAPR) measurement framework. This study aimed to generate a first utility set for the CS-Base, making it suitable for use in health-economic evaluations. MethodsCS-Base comprises 12 health attributes: mobility, vision, hearing, cognition, mood, anxiety, pain, fatigue, social functioning, daily activities, self-esteem, and independence, each with 4 levels. Our methodology to generate utilities for the CS-Base was 2-fold. First, we derived coefficients from patient MAPR data to calculate CS-Base values. Subsequently, these were normalized to a 0.0 to 1.0 utility scale, in which 0.0 signifies dead. The dead position was estimated using general population data from a discrete choice experiment (discrete choice experiment + dead), using a division-value strategy, which localize the position of states better or worse than dead. ResultsWe analyzed MAPR data from 3222 patients and discrete choice experiment + dead data from 1995 respondents. All MAPR coefficients were negative, logically ordered, and significantly different from the reference level. The dead position was denoted by a division value of −148.385. Utility values spanned from −0.071 to 1.0, and only 53 of 16 777 216 states were deemed worse than dead. ConclusionsThis study introduced the first CS-Base utility set, underlining a 2-step utility derivation method. This method, blending societal and patient views, surpasses traditional preference-based approaches, yielding firmer results. However, improvement of the normalization procedure is expected. Estimating CS-Base utilities is an ongoing process that gains precision over time.

Dynamic Evolution of Multi-Scale Ecosystem Services and Their Driving Factors: Rural Planning Analysis and Optimisation

Rural areas provide ecosystem services (ESs) to urban metropolitan regions. These services are threatened by the constant pressure of urbanisation and new interest in rural development. This has heightened the conflict between environmental concerns and developmental needs, thereby presenting significant land management and rural planning challenges. Employing a quantitative measurement and optimisation framework, we investigate six representative ES variables to assess planning strategies that can address this contradiction. We used a suburban rural area around Nanjing, China, as our study area. We collected spatial data from 2005 to 2020 at two scales (village level and 500 m grid) to map ESs, quantify interactions (trade-offs and synergies among ES bundles), and identify the social, ecological, and landscape drivers of rural change. Based on this, rural planning strategies for optimising ESs at different scales have been proposed. Our findings include (1) spatial heterogeneity in the distribution of ESs, (2) the identification of seven synergistic and eight trade-off pairs among ESs, (3) a spatial scale effect in suburban rural areas, and (4) the spatial trade-offs/synergies of ESs exhibiting a ‘Matthew effect’. The identification of key trade-offs and synergistic ES pairs and the categorisation of ES bundles form the basis for a multi-scale hierarchical management approach for ESs in the region. By examining the commonalities and variations in drivers across diverse scales, we established connections and focal points for spatial planning. We use these findings to propose spatial planning and landscape policy recommendations for rural suburban areas on multiple scales. This study aims to provide a comprehensive and detailed spatial optimisation strategy for rural areas that can help contribute to their revitalisation.

DNN-BP: a novel framework for cuffless blood pressure measurement from optimal PPG features using deep learning model.

Continuous blood pressure (BP) provides essential information for monitoring one's health condition. However, BP is currently monitored using uncomfortable cuff-based devices, which does not support continuous BP monitoring. This paper aims to introduce a blood pressure monitoring algorithm based on only photoplethysmography (PPG) signals using the deep neural network (DNN). The PPG signals are obtained from 125 unique subjects with 218 records and filtered using signal processing algorithms to reduce the effects of noise, such as baseline wandering, and motion artifacts. The proposed algorithm is based on pulse wave analysis of PPG signals, extracted various domain features from PPG signals, and mapped them to BP values. Four feature selection methods are applied and yielded four feature subsets. Therefore, an ensemble feature selection technique is proposed to obtain the optimal feature set based on major voting scores from four feature subsets. DNN models, along with the ensemble feature selection technique, outperformed in estimating the systolic blood pressure (SBP) and diastolic blood pressure (DBP) compared to previously reported approaches that rely only on the PPG signal. The coefficient of determination ( ) and mean absolute error (MAE) of the proposed algorithm are 0.962 and 2.480 mmHg, respectively, for SBP and 0.955 and 1.499 mmHg, respectively, for DBP. The proposed approach meets the Advancement of Medical Instrumentation standard for SBP and DBP estimations. Additionally, according to the British Hypertension Society standard, the results attained Grade A for both SBP and DBP estimations. It concludes that BP can be estimated more accurately using the optimal feature set and DNN models. The proposed algorithm has the potential ability to facilitate mobile healthcare devices to monitor continuous BP.

Building Community Capital—The Role of Local Area Coordinators in Disability Services: A Critical Review

Local Area Coordination (LAC) roles have been implemented in disability services in many countries, supporting people living with disability to connect with formal and informal support in the community. Embedded in the National Disability Insurance Scheme in Australia, the aspiration is that this LAC role will connect people with disability to supports and enable the generation of greater community capacity and inclusion. Yet, with only a limited evidence base that demonstrates the impact of this approach, a clear measurement framework is needed to provide evidence of the realization of this aspiration. We propose that this impact could be demonstrated by applying a Community Capitals Framework (CCF) as the theoretical base for the LAC role and other community capacity initiatives, such as service navigation within disability reform of disability services. The CCF is premised on seven ‘capitals’—social, natural, cultural, human, political, financial and built that intersect and interact with each other to create positive spirals of change in communities. In this critical literature review, we apply the CCF to map and synthesize existing research on the LAC’s role in building community capital and examine the utility of the CCF as a map for LAC and service navigation practices to enhance community inclusion. For this review, we analyzed peer-reviewed journal papers and grey literature that focused on LAC community capacity building for people with disability in a disability service context published between 2000 and August 2023. Of the 17 publications that met the inclusion criteria, there was no published evidence that comprehensively examined or measured community capacity building consistent with the tenets of the CCF. However, our analysis showed that all capitals, with the exception of natural capital, had been considered, with some indication that investment in these capitals (particularly social capital) could be connected in the positive spiraling way suggested by the CCF. Given the paucity of existing evidence to inform the LAC aspiration for community capacity building, research informed by consumer priorities is needed to inform LAC and service navigation practices to address community needs. The CCF has the potential to develop our understanding of LAC and other community capacity-building initiatives through the measurement of LAC and service navigation services and consumer outcomes, as well as by informing investment to target growth capitals in communities.

Does the Bangladesh Equity Market Expose to Disposition Effects Bias under Different Market Conditions?

The study provides an intuitive investigation into the disposition effect within frontier markets such as Bangladesh, particularly focusing on its behavior during various market conditions. The study’s novelty lies in its application of a methodological framework of the disposition effect measure of Weber and Camerer, aiming to understand the disposition effect through different market conditions. Dow Theory is applied to disparate bullish and bearish intermediate periods. Disposition effects persist for the entire study period, as well as the different market conditions except for the bearish Bangladesh equity market. The bullish and crisis markets exhibit a rather high disposition effect due to their respective market volatility. Stronger disposition effects are more pronounced for a crisis market in relation to a bullish market. In addition, the disposition effect in Bangladesh’s equity market oscillates in crisis periods. The documentation of the disposition effect in the Bangladesh equity market across market conditions suggests that investors’ psychology plays a crucial role in their decision processes. Individuals and professional investors should carefully design an appropriate strategy to control their decision-making process since the presence of disposition effects may impair the risk-return payoffs.

Enhancing Construction Performance: A Critical Review of Performance Measurement Practices at the Project Level

The construction industry faces significant challenges in measuring and assessing performance effectively. Conventional methods of measuring construction performance have become less effective, prompting a need to adopt non-financial performance measurements. This shift acknowledges the shortcomings of relying solely on financial performance measurement systems. As a result, there has been a substantial increase in research and focus on non-financial performance measurement systems in recent decades. This study focuses on analyzing performance measurement practices and key performance indicators (KPIs) in the construction industry, specifically at the project level. By examining 146 relevant articles, the study offers a thorough overview of various aspects of project performance. In addition to the traditional dimensions of the project management triangle (cost, time, and quality performance), the study emphasizes the importance of considering other dimensions. These include stakeholder performance, safety performance, technology utilization performance, value performance, environmental impact performance, and the application of maturity models. By incorporating these additional KPIs, a more comprehensive and holistic evaluation of project performance can be achieved. This study’s findings make notable contributions to the methodological framework of performance measurement in construction projects. By consolidating diverse research sources, the study offers valuable guidance for future research in the field of project performance. Moreover, it provides insights into selecting suitable performance measurement methods, empowering practitioners to effectively assess and manage project performance.

NDT Data-Supported Structural Reassessments based on Regression Relations in Measuring Data Analysis

Non-destructive Testing (NDT) yields valuable data on actual structural elements, supporting the assessment of existing infrastructures while minimizing additional structural damage caused by inspections. Simultaneously, the uncertainty in measurement, which quantifies the quality of measurement results, plays a crucial role in decisions aimed at, e.g., optimizing maintenance strategies, rehabilitation works and Structural Health Monitoring (SHM) implementations. The Guide to the Expression of Uncertainty in Measurement (GUM) framework has been already applied to non-destructive concrete testing. This necessitates an obligatory process in which extensive measurements with strictly limited scopes need to be conducted by expert personnel. This study aims to simplify and optimize existing NDT data analysis procedures by employing regression analysis, enabling the detection of structural features. The regression analysis yields a modifier for determining the correct depth of an object within the structural element as well as an intercept in the linear input-output formulation, with time of flight serving as the variable and wave velocity as its slope. The method is validated through laboratory experiments, including the use of an ultrasonic measurement system. The introduced method provides unbiased and accurately measured results, while the measurement data can be uncorrelated. Major advantages are faster computations, a wider scope and a notable reduction in the amount of needed information about the measuring process. Furthermore, the study illustrates how the regression relation approach, in combination with ultrasonic data describing the inner structure of a concrete element, can effectively support the reassessment of bridges in operation. To achieve this, the measurable positions of the resisting longitudinal tendons of a bridge structure are varied to investigate the displacement change under dynamic service loads. The findings reveal that the application of the proposed NDT analysis method, with its increased practicability, can enhance the efficiency of NDT data-supported structural reassessments in different scenarios.

Comparing priority received by global health issues: a measurement framework applied to tuberculosis, malaria, diarrhoeal diseases and dengue fever

IntroductionThe relative priority received by issues in global health agendas is subjected to impressionistic claims in the absence of objective methods of assessment of priority. To build an approach for...

Assessing the WHO-UNICEF primary health-care measurement framework; Bangladesh, India, Nepal, Pakistan and Sri Lanka.

To assess the availability of information on indicators of the World Health Organization and United Nations Children's Fund primary health-care measurement framework in Bangladesh, India, Nepal, Pakistan and Sri Lanka and to outline the opportunities for and challenges to using the framework in these countries. We reviewed global and national data repositories for quantitative indicators of the framework and conducted a desk review of country documents for qualitative indicators in February-April 2023. We assessed data sources and cross-sectional survey tools to suggest possible sources of information on framework indicators that were not currently reported in the countries. We also identified specific indicators outside the framework on which information is collected in the countries and which could be used to measure primary health-care performance. Data on 54% (32/59) of the quantitative indicators were partially or completely available for the countries, ranging from 41% (24/59) in Pakistan to 64% (38/59) in Nepal. Information on 41% (66/163) of the qualitative subindicators could be acquired through desk reviews of country-specific documents. Information on input indicators was more readily available than on process and output indicators. The feasibility of acquiring information on the unreported indicators was moderate to high through adaptation of data collection instruments. The primary health-care measurement framework provides a platform to readily assess and track the performance of primary health care. Countries should improve the completeness, quality and use of existing data for strengthening of primary health care.

Legal Framework for Preventive and Proactive Measures under the Bangladesh of Mental Health Act 2018

Legal Framework for Preventive and Proactive Measures under the Bangladesh of Mental Health Act 2018

Resonance sonomanometry for noninvasive, continuous monitoring of blood pressure.

Cardiovascular disease is the leading cause of death worldwide. Existing methods for continuous, noninvasive blood pressure (BP) monitoring suffer from poor accuracy, uncomfortable form factors, or a need for frequent calibration, limiting their adoption. We introduce a new framework for continuous BP measurement that is noninvasive and calibration-free called resonance sonomanometry. The method uses ultrasound imaging to measure both the arterial dimensions and artery wall resonances that are induced by acoustic stimulation, which offers a direct measure of BP by a fully determined physical model. The approach and model are validated in vitro using arterial mock-ups and then in multiple arteries in human subjects. This approach offers the promise of robust continuous BP measurements, providing significant benefits for early diagnosis and treatment of cardiovascular disease.

Determination of sample size for various study designs in medical research: A practical primer.

Formulating a research question and selecting an appropriate study design for answering that question are crucial initial steps in the research process. The population, intervention, control group, and outcomes measures (PICO time and setting [TS]) framework provides a practical guide in this regard, which stands for population, intervention, control, outcome, type of research question, and study design. The various study designs have their own merits and demerits, and implementing the methodology meticulously requires knowledge of all of these. Similarly, different methods of sample size calculation are warranted based on the most appropriate study design and outcome variables of interest. Sometimes, a post hoc power analysis can be performed after the sample size calculation, to check whether the study was adequately powered or not. There are multiple validated free software tools for sample size calculation, including Open-Epi, R, StatCalc, etc. The practice by most researchers of reporting significant P values is to be replaced by reporting effect sizes, as the latter is a much better estimate of the strength of association. This review provides a comprehensive, ready reckoner for busy family physicians to quickly identify the appropriate study design for answering any applied research questions in their minds and estimating the sample size required for the same.

Measuring Subjective Well-being Capability: A Multi-Country Empirical Analysis in Europe

The main aim of this paper is to conceptualise and empirically estimate subjective well-being capability. The empirical demonstration of the conceptual framework is applied in a selection of European countries: Poland and its leading emigration destinations the United Kingdom, Germany, the Netherlands, Ireland, France and Italy. The paper advances the measure of subjective well-being capability (SWC) as the integration of the subjective well-being measure with the capability approach in a unified measurement framework. Following the development of a conceptual model, the theoretical framework is operationalized empirically to quantify measures of SWC across the selected countries using a Multiple Indicators and Multiple Causes Model. Data from the European Quality of Life Survey is employed. A comparative analysis compares the SWC measures across countries as well as comparing SWC with conventional well-being measures such as overall happiness and GDP per capita. The results of the study reveal a significant correlation between the SWC based on a general model for all countries, overall happiness, and GDP per capita. However, it also suggests that country-specific SWCs, calculated from tailored models, could substantially deviate from traditional well-being measurements. This attribute suggests that SWC could be a practical tool for assessing individual contexts, as reflected in the tailored models, even though it might not serve as the optimal instrument for country ranking (via the general MIMIC model).

A methodological study on the identification of ecological security change processes and zoning control strategies —— Based on the perspective of sustainable development

Ecological security (ES) is a crucial indicator for assessing the sustainable development of a region. Currently, most studies on ES primarily focus on process analysis, and the integration of environmental variability into the development of tailored control strategies for regions with varying ecological quality is overlooked. Therefore, in this study, we identified regional ES change processes, employed an optimized system to calculate the ecological security index (ESI), and identified ecological corridors (ECs) through the Minimum Constrained Resource (MCR) model to determine zoning strategies for typical arid regions, using the Ningxia region in the Yellow River Basin of China as an example. The findings showed that (1) from 2006 to 2020, the ESI values of most regions were between 0.2 and 0.4, with small but consistent increases in the ESI values over the years. (2) The proportion of regions with high ES ratings increased by 9.08 % across all districts and counties, and the center of gravity of ES shifted in a north–south and east–west direction. (3) The ESI exhibited a strong positive spatial correlation, characterized by spatial diffusion and spillover effects in most regions. (4) The ECs were predominantly distributed in a north–south direction, involving a total of 20 districts and counties. Based on the principles of sustainable development, we developed a model for the dynamic identification and zoning control of regional ES, aiming to provide a practical framework for effective ecological restoration and protection measures. Additionally, the strategies and methodologies presented in this study serve as important references for similar regions worldwide to facilitate the zoning control of ES, highlighting the broader significance and applicability of the study.

PENGEMBANGAN INSTRUMEN UNTUK MENGUKUR KOMPETENSI SOSIAL GURU BERBASIS GENDER EQUALITY AND SOCIAL INCLUSION (GESI) DI SEKOLAH INKLUSI

The social competence of teachers based on gender equality and social inclusion (GESI) in this research is the teacher's ability to communicate with children with special needs based on managing social dynamics and the teacher's framework for promoting social inclusion. The aim of this research is to create an instrument to measure teachers' social competence based on gender equality and social inclusion (GESI). The research method used is quantitative descriptive research. The development of the questionnaire in this study incorporates a measurement framework that provides a systematic method based on a combination of theoretical and psychometric approaches. The sample was 91 teachers who taught in four Bandung City State Elementary Schools. Based on the research results, data was obtained that the GESI-based social competency questionnaire consists of three aspects, namely attitudes towards inclusive education, empathy for students with special needs, and problem solving. The number of items in the questionnaire, namely 36 items, has met the standards of reliability, content validity, construct validity, and provides initial evidence for the use of the instrument with the aim of measuring the social competence of GESI-based teachers in inclusive schools.

THE ROLE OF LEAN SIX SIGMA IN BOOSTING COMPETITIVE ADVANTAGE IN THE GOVERNANCE OF HEALTHCARE ORGANIZATIONS: A CONCEPTUAL FRAMEWORK

This study aims to present a conceptual framework that brings together reward and recognition, and customer focus (organizational factors), which can help organizations achieve a competitive advantage (CA) through applying Lean Six Sigma (LSS) in healthcare. A critical review of the models of reward and recognition, and customer focus, LSS, and CA measures was performed to create the conceptual framework. A synthesis of the existing literature provides the basis for the development of the conceptual framework of the LSS measures. The independent variables are reward and recognition, and customer focus. The mediator variable in this framework is LSS, and CA is employed as the dependent variable. The framework offers a systematic method of evaluating the determinants of LSS in healthcare. Accordingly, the newly developed conceptual framework identifies and describes the direct associations between organizational factors and CA in the healthcare (HC) sector and the indirect associations through LSS. This study is important for professionals working in HC seeking to achieve CA in hospitals. Additionally, this study is valuable to researchers and academics working in the LSS field as it explores the importance of LSS implementation in hospitals. In addition, limited studies have been conducted to explore the status of LSS implementation in HC and this study is expected to provide theoretical contributions to the LSS approach in healthcare.

A forest companies typology regarding their contribution to circular economy: a sustainability reporting-based analysis

Relatively recently, the residuals of forest industry have been considered very important and useful to be reused through bioeconomy and circular economy practices in order to reduce the use of non-renewable natural resources. The majority of current studies have been based on interview protocols and questionnaire-based surveys to examine how managers of forest industry contribute to sustainable development and circular economy. Despite the usefulness of these surveys, there is a degree of subjectivity in the respondents' responses and an orientation to what forest companies propose to do in the circular economy. To overcome the weaknesses of previous research, this paper aims at drawing appropriate information from sustainability reporting of a sample of forest companies to provide a more unambiguous understanding of the way that forest companies meet the circular economy principles. Thus, a circular economy measurement framework is developed which is based on scoring systems and GRI guidelines to draw reliable and harmonized information from corporate sustainability reporting. Furthermore, it results in a four-type company typology according to the number of the circular economy principles and the number of items they achieve for each principle such as pioneer circular company, lagging circular company, innovative circular company and infant circular company. The suggested framework is tested on a sample of 20 forest companies with higher revenue in 2022. The findings show that half of the sampled companies can be considered as infants at the CE practices, while a positive statistical relationship is revealed between forest companies’ circular economy practices and their revenues.

Advancing the practice of public procurement performance measurement: a framework for conceptualizing efficiency and effectiveness

IMPACT This article provides a conceptual, applied framework for public procurement performance measurement. A reimagined systems–theoretical approach reveals a conceptual model by which public managers and policy-makers can understand their current public procurement key performance indicators (KPIs). Focusing on distinctions between the public and private appreciation of efficiency and effectiveness, the model was applied to three European Single Market Scoreboard public procurement KPIs to illustrate where measures tend to fail. Implications from an empirical analysis of aggregated contract notice and award data suggest public procurement performance measures are symbolic indicants rather than true measures of performance unless normalized across the appropriate unit of analysis which are heterogeneous and, in the case of multilevel governance, often have different procurement goals and policy priorities. The model identifies the theoretical challenges facing the metrics used to assess the performance of procurement systems, while acknowledging that, in practice, these metrics may not always be used in isolation for assessment. Recommendations for practice and generalizability across various government regimes and public KPIs are provided.

Can cycling compensate the distributional inequity of public service facilities? Evidence from Shenzhen, China

Most traditional studies measure accessible equity of public service facilities (PSFs) statically, and tend to neglect travelling scope disparities among people with different travelling abilities and conditions. This study offers a new perspective for dynamically assessing the actual occupancy of PSFs from both the provision and demand sides. Taking Shenzhen as an example, and employing big data on shared-bike orders, we explored the compensation mechanism of cycling for the distributional inequity of PSFs, with a two-phase measurement framework. First, the Gini index and Lorenz curve were adopted to compare the distributional equality of the grids’ originally-allocated PSFs (based on the division of block-scale grids) and their cycling-accessed PSFs (based on delineation of the cycling scope with shared-bike orders). Second, a spatial lag model was established to reveal the exact factors affecting the ability to improve the PSF occupancy through cycling. The results showed that cycling compensated the distributional inequity of PSFs. This compensation effect varied among groups of different ages, genders, and incomes. Moreover, mixed land use and the low density of trunk roads promoted this compensation. These findings can provide decision-makers with references for future PSF planning in Shenzhen, and other similar cities worldwide.