Evaluation & the Health Professions最新文献

Learning communities (LCs) stimulate the learning and cross-sectoral collaboration that are essential in multidisciplinary challenges, such as healthy weight approaches (HWAs). Previous research on two multidisciplinary LCs about HWAs devised a causal loop diagram (CLD) identifying dynamics (i.e., mechanisms) that describe the functioning of LCs during their starting phase (first 6 months after LC start). As LCs are likely to develop over project phases, this study aimed to ascertain whether and how the LC system dynamics were perceived to develop over time. Qualitative interviews conducted with the LC members at a second juncture were processed to be able to update the initial CLD. The updated diagram indeed illustrated how the multidisciplinary LCs were perceived to develop. The CLD became more extensive and consequently further explained three aspects: the complexity and interrelatedness of group dynamics, gaining insights through exchange, and conditions to execute actions. To ensure adequate group dynamics, learning, and action execution, LC stakeholders can regularly use the CLD as a blueprint to identify solutions for LC bottlenecks, such as members limitedly arranging the LC jointly. Future research is needed to investigate whether such developments are caused by different LC project phases and/or by the number of LC meetings and reflections.

Increasing numbers of research studies are completed entirely online, often using "crowdsourcing" platforms to recruit participants, such as Amazon's Mechanical Turk (MTurk) or Prolific. Over time, crowdsourced data collection has faced multiple threats to validity including bots, inattention, and misrepresentation. Fortunately, research and development of quality control techniques has resulted in approaches to conducting credible research using crowdsourcing platforms. However, advances in large language models (LLMs), particularly computer-using agents (CUAs), such as OpenAI's "Operator," may pose novel threats to the validity of crowdsourced research data in the future. This brief report explores how and why that might be the case and encourages further discussion of this issue.

This study aimed to investigate the construct of burnout in counseling trainees using item response theory. The psychometric properties of the Maslach Burnout Inventory-General Survey for Students (MBI-GS(S)) were examined with a sample of counseling trainees (N = 246). Based on the graded response model, the results supported only the three-factor solution of counseling trainees' burnout and provided little evidence for general burnout as a potential construct. Specific item-level information from multidimensional item response theory analysis is also presented, including item discrimination parameters, item difficulty location parameters, test information, and reliability. Implications for assessing and addressing counseling trainees' burnout in terms of educating future mental health professionals are discussed.

This methodological study aimed to assess the validity and reliability of the Received Social Support Scale for Persons with Mental Illness (rSSS-MI), developed by Chronister et al. (2022), by adapting it into Turkish. The study consisted of 274 people who applied to the psychiatry outpatient clinic of a state hospital between April 2023 and April 2024. Data were collected using a Personal Information Form, the Received Social Support Scale for Persons with Mental Illness, and the Multidimensional Scale of Perceived Social Support. The Turkish version of the rSSS-MI demonstrated a 3-factor structure consisting of 21-items, and the items' factor loadings ranged from 0.82 to 0.96. The goodness of fit indices were χ2/df = 3.335, GFI = 0.823, NFI = 0.933, TLI = 0.944, IFI = 0.952, CFI = 0.952, RMSEA = 0.092, and SRMR = 0.024. Additionally, Cronbach's alpha coefficient of the rSSS-MI was calculated as 0.98, and item-total score correlation coefficients were between 0.80 and 0.92. These findings indicate that the Turkish version of the rSSS-MI is a valid and reliable measurement tool.

Although there is growing interest in assessing the quality of life (QoL) in mental health services, there is currently no specific measurement tool for mental disorders in Turkey. This study aimed to evaluate the psychometric features of the Turkish version of the Mental Health Quality of Life Questionnaire (MHQoL). This methodological study was conducted with 310 patients diagnosed with mental disorders between October 2022 and June 2023. The MHQoL includes a descriptive system (MHQoL-7D) of seven items representing distinct dimensions- self-image, independence, mood, relationships, daily activities, physical health, and future- alongside a visual analog scale measuring general psychological well-being (MHQoL-VAS). Turkish MHQoL yielded a one-factor structure with 7 items and factor loadings ranging from 0.426 to 0.727. Goodness-of-fit indexes of the MHQoL were found to be χ2/df = 1.212, SRMR = 0.026, RMSEA = 0.026, GFI = 0.985, AGFI = 0.969, CFI = 0.995, IFI = 0.995, and TLI = 0.991. Cronbach's alpha coefficient was measured at 0.792, with item-total correlation coefficients from 0.378 to 0.609. Turkish MHQoL is a reliable and valid tool for evaluating QoL in individuals with mental health challenges.

Single-group interrupted time-series analysis (ITSA) is a popular non-experimental study design in healthcare research. However, little guidance is available to inform the power requirements of ITSA studies under most common usages. We performed simulations to estimate the number of time periods (ranging from 10 to 100) required for percentage increases in level and trend (from baseline), to achieve statistical significance (p < 0.05, p < 0.01) with >80% and >90% power, when autocorrelation ranges from -0.90 to 0.90, and the intervention is introduced at 33%, 50% and 67% of the time series. Larger effect sizes were required for shorter studies, as well as with increasing autocorrelation, and when the intervention was introduced earlier or later than halfway in the time series. The required effect sizes were generally lower for estimating a change in the level of the time series as compared with the change in the trend, but the opposite was true when the number of time periods was larger. Simulations of studies with 10 time periods consistently produced unreliable estimates. The tables created from these analyses as well as a new community-contributed Stata package called POWER_ITSA will guide healthcare researchers in determining the most efficient way to achieve anticipated treatment effects in single-group ITSA studies.

Qualitative research methodologies offer critical contextual insights into community-engaged program evaluations, addressing limitations in solely quantitative approaches. While randomized controlled trials (RCTs) are inherently rigorous, their design does not consider nuanced contextual factors and lived experiences that are valuable to understanding a program's impact on community and health outcomes within diverse populations. In this theoretical discussion, we posit that qualitative methods, particularly when grounded in a Community-Based Participatory Research (CBPR) framework, foster trust and collaboration, yielding richer, more community-specific data to enhance program evaluation. We also provide evidence-based, practical consideration for conducting qualitative research for community-engaged program evaluations. We explore various qualitative approaches and their application in program evaluations. We highlight the iterative nature of qualitative data analysis and emphasize the importance of qualitative methodological rigor - including coding, triangulation, and member checking - to ensure the program evaluation's community value, credibility, and deeper contextual evaluation. Ultimately, we underscore the value of integrating qualitative methods throughout a program's lifecycle for comprehensive assessments, improved program effectiveness, and enhanced equity.

Stakeholder involvement (SI) is essential for effective and sustainable intervention implementation, yet practical guidance is lacking. This study mapped SI use in implementation science studies, identified gaps, and proposed a practical framework for improved SI planning. Using an evidence gap map approach, this study built on Mielke et al.'s (2022) methodology, which identified implementation studies from 2015-2020. The search was updated to include studies from 2021-2023 from PubMed, using the same search strategy and inclusion criteria. Data extraction followed the Guidance for Reporting on Involvement of Patients and the Public reporting checklist. From 10,184 studies, a random sample of 2,005 was screened, adding 162 implementation science studies to Mielke et al.'s 110, totaling 272 studies for SI analysis. SI was reported in 89% of studies, but often lacked depth and strategic planning. Stakeholders were mainly engaged during the preparatory phase. Most studies involved micro- and meso-level stakeholders, rarely including macro-level stakeholders. Few described stakeholder selection or preparation. SI was mostly consultative, via interviews, surveys, and focus groups, with limited active collaboration. SI processes and costs were rarely evaluated. Our findings underscore the need for structured, comprehensive SI planning and offer practical recommendations to strengthen SI efforts in implementation research.

Childhood vaccination is the most cost-effective public health intervention; however, coverage in slum-like areas remains a significant challenge because of unique socio-economic disparities and logistical barriers. We aimed to evaluate the interventions from the literature on improving vaccination coverage among children aged 12-23 months in slum areas using the WHO iEtD framework and the TOPSIS-Entropy method for decision-making in Bangladesh and identify stakeholders ranks and felt needs of interventions across study slums. This cross-sectional study was conducted in six slums in two city corporation areas in Dhaka, Bangladesh involving 67 demand-side and 35 supply-side stakeholders. Rating scores ranged from 0 to 1, indicating priority interventions. Our study highlights that demand-side stakeholders favour incentive interventions, whereas supply-side stakeholders support multicomponent strategies. For all stakeholders, educational interventions were ranked highest with a score of 0.745, followed by multicomponent interventions (score 0.666), incentive (score 0.651), and reminder/recall scoring (score 0.305). Educational interventions were identified as a shared priority (common ground), addressing the felt needs of both demand- and supply-side stakeholders. These findings support tailored context-specific approaches to enhance vaccination coverage and child health in vulnerable communities.

This study was conducted to adapt the Sinclair Compassion Questionnaire into Turkish and to test its validity and reliability. The sample of the methodological study consisted of 390 patients who were hospitalized in internal and surgical clinics. The data were collected between May 2022 and December 2022 using the Personal Information Form, Newcastle Nursing Care Satisfaction Scale and Sinclair Compassion Questionnaire. The Sinclair Compassion Questionnaire consists of 15 items, containing a single latent compassion factor. Validity analysis included content validity index, concurrent validity, convergent validity, exploratory factor analysis, confirmatory factor analysis, reliability analysis included test-retest and reliability analysis using Cronbach's alpha reliability coefficient. The content validity index of the scale was found to be between 0.88 and 1.00. Confirmatory factor analysis χ² = 283.754, dF = 71, RMSEA = 0.078, indicating a good/excellent fit for the model. The item means of the scale ranged between 4.43 ± 0.60 and 4.10 ± 0.47, and the factor loadings ranged between 0.672 and 0.824. Convergent validity is at an acceptable level (r = 0.674). The Cronbach's alpha coefficient of the scale was 0.94. The Sinclair Compassion Questionnaire is a valid and reliable instrument to assess patients' experiences of compassion in Turkish populations with acute and chronic diseases.