BACKGROUND: Blended face-to-face and web-based treatment is a promising way to deliver smoking cessation treatment. Since adherence has been shown to be an indicator of treatment acceptability and a determinant for effectiveness, we explored and compared adherence and predictors of adherence to blended and face-to-face alone smoking cessation treatments with similar content and intensity. OBJECTIVE: The objectives of this study were (1) to compare adherence to a blended smoking cessation treatment with adherence to a face-to-face treatment; (2) to compare adherence within the blended treatment to its face-to-face mode and web mode; and (3) to determine baseline predictors of adherence to both treatments as well as (4) the predictors to both modes of the blended treatment. METHODS: We calculated the total duration of treatment exposure for patients (N=292) of a Dutch outpatient smoking cessation clinic who were randomly assigned either to the blended smoking cessation treatment (n=130) or to a face-to-face treatment with identical components (n=162). For both treatments (blended and face-to-face) and for the two modes of delivery within the blended treatment (face-to-face vs web mode), adherence levels (ie, treatment time) were compared and the predictors of adherence were identified within 33 demographic, smoking-related, and health-related patient characteristics. RESULTS: We found no significant difference in adherence between the blended and the face-to-face treatments. Participants in the blended treatment group spent an average of 246 minutes in treatment (median 106.7% of intended treatment time, IQR 150%-355%) and participants in the face-to-face group spent 238 minutes (median 103.3% of intended treatment time, IQR 150%-330%). Within the blended group, adherence to the face-to-face mode was twice as high as that to the web mode. Participants in the blended group spent an average of 198 minutes (SD 120) in face-to-face mode (152% of the intended treatment time) and 75 minutes (SD 53) in web mode (75% of the intended treatment time). Higher age was the only characteristic consistently found to uniquely predict higher adherence in both the blended and face-to-face groups. For the face-to-face group, more social support for smoking cessation was also predictive of higher adherence. The variability in adherence explained by these predictors was rather low (blended R2=0.049; face-to-face R2=0.076). Within the blended group, living without children predicted higher adherence to the face-to-face mode (R2=0.034), independent of age. Higher adherence to the web mode of the blended treatment was predicted by a combination of an extrinsic motivation to quit, a less negative attitude toward quitting, and less health complaints (R2=0.164). CONCLUSIONS: This study represents one of the first attempts to thoroughly compare adherence and predictors of adherence of a blended smoking cessation treatment to an equivalent face-to-face treatment. Interestingly, although the overall adherence to both treatments appeared to be high, adherence within the blended treatment was much higher for the face-to-face mode than for the web mode. This supports the idea that in blended treatment, one mode of delivery can compensate for the weaknesses of the other. Higher age was found to be a common predictor of adherence to the treatments. The low variance in adherence predicted by the characteristics examined in this study suggests that other variables such as provider-related health system factors and time-varying patient characteristics should be explored in future research. TRIAL REGISTRATION: Netherlands Trial Register NTR5113; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5113.
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OBJECTIVE: This study aimed to examine the prevalence and predictors of reconstructive surgery among pediatric burn patients in the Netherlands.METHODS: Pediatric burn patients were identified through the Dutch Burn Repository R3. Eligibility criteria included a burn requiring hospital admission or surgical treatment at one of the Dutch burn centers in 2009-2019. First, patient, burn, and treatment characteristics were summarized using descriptive statistics. Second, time to the first reconstructive surgery was modelled using Kaplan Meier curves. Third, a prediction model was developed using univariate and multivariate logistic regression. The model's performance was assessed using calibration, discrimination, and explained variance. Fourth, internal validation was performed using bootstrapping.RESULTS: Approximately three percent (n = 84) of pediatric patients (n = 3072) required reconstructive surgery between the initial burn-related hospital admission and September 2021. Median time to the first reconstructive surgery was 1.2 (0.7-1.6) years. Most surgeries were performed on the face, arm, neck, hand, or anterior trunk, owing to contractures or hypertrophic scarring. Predictors of reconstruction included the etiology, anatomical site, extent of full-thickness burn, surgical treatment in the acute phase, and length of hospital stay.CONCLUSION: Our study provided an overview of the prevalence and independent predictors of reconstructive surgery in the pediatric burn population.
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While consumers have become increasingly aware of the need for sustainability in fashion, many do not translate their intention to purchase sustainable fashion into actual behavior. Insights can be gained from those who have successfully transitioned from intention to behavior (i.e., experienced sustainable fashion consumers). Despite a substantial body of literature exploring predictors of sustainable fashion purchasing, a comprehensive view on how predictors of sustainable fashion purchasing vary between consumers with and without sustainable fashion experience is lacking. This paper reports a systematic literature review, analyzing 100 empirical articles on predictors of sustainable fashion purchasing among consumer samples with and without purchasing experience, identified from the Web of Science and Scopus databases.
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Objective To explore predictors of district nursing care utilisation for community-living (older) people in the Netherlands using claims data. To cope with growing demands in district nursing care, knowledge about the current utilisation of district nursing care is important. Setting District nursing care as a part of primary care. Participants In this nationwide study, claims data were used from the Dutch risk adjustment system and national information system of health insurers. Samples were drawn of 5500 pairs of community-living people using district nursing care (cases) and people not using district nursing care (controls) for two groups: all ages and aged 75+ years (total N=22 000). Outcome measures The outcome was district nursing care utilisation and the 114 potential predictors included predisposing factors (eg, age), enabling factors (eg, socioeconomic status) and need factors (various healthcare costs). The random forest algorithm was used to predict district nursing care utilisation. The performance of the models and importance of predictors were calculated. Results For the population of people aged 75+ years, most important predictors were older age, and high costs for general practitioner consultations, aid devices, pharmaceutical care, ambulance transportation and occupational therapy. For the total population, older age, and high costs for pharmaceutical care and aid devices were the most important predictors. Conclusions People in need of district nursing care are older, visit the general practitioner more often, and use more and/or expensive medications and aid devices. Therefore, close collaboration between the district nurse, general practitioner and the community pharmacist is important. Additional analyses including data regarding health status are recommended. Further research is needed to provide an evidence base for district nursing care to optimise the care for those with high care needs, and guide practice and policymakers’ decision-making.
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The body of evidence that the working alliance is associated with positive outcomes for mandated clients is growing. The aim of this research was to investigate the influence of several characteristics of probation officers (POs) and offenders on the course of the working alliance during probation supervision. This study examined the patterns on the four alliance subscales: Trust, Bond, Goals-Restrictions, and Reactance of the Working Alliance With Mandated Clients Inventory (WAMCI) in 201 offenders and their 137 POs. Three patterns on each alliance subscale were found: deteriorating, improving, and stable. Multinomial logistic analysis revealed that change of POs and the preference of the PO to maintain rules were associated with a deteriorating Trust pattern. From the perspective of the offenders, being motivated to take part in supervision was associated with a stable pattern on every alliance subscale, but having problems with substance use increased the likelihood of a deteriorating pattern on every alliance subscale.
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Due to the ageing population, the prevalence of musculoskeletal disorders will continue to rise, as well as healthcare expenditure. To overcome these increasing expenditures, integration of orthopaedic care should be stimulated. The Primary Care Plus (PC+) intervention aimed to achieve this by facilitating collaboration between primary care and the hospital, in which specialised medical care is shifted to a primary care setting. The present study aims to evaluate the referral decision following orthopaedic care in PC+ and in particular to evaluate the influence of diagnostic tests on this decision. Therefore, retrospective monitoring data of patients visiting PC+ for orthopaedic care was used. Data was divided into two periods; P1 and P2. During P2, specialists in PC+ were able to request additional diagnostic tests (such as ultrasounds and MRIs). A total of 2,438 patients visiting PC+ for orthopaedic care were included in the analysis. The primary outcome was the referral decision following PC+ (back to the general practitioner (GP) or referral to outpatient hospital care). Independent variables were consultation- and patient-related predictors. To describe variations in the referral decision, logistic regression modelling was used. Results show that during P2, significantly more patients were referred back to their GP. Moreover, the multivariable analysis show a significant effect of patient age on the referral decision (OR 0.86, 95% CI = 0.81– 0.91) and a significant interaction was found between the treating specialist and the period (p = 0.015) and between patient’s diagnosis and the period (p < 0.001). Despite the significant impact of the possibility of requesting additional diagnostic tests in PC+, it is important to discuss the extent to which the availability of diagnostic tests fits within the vision of PC+. In addition, selecting appropriate profiles for specialists and patients for PC+ are necessary to further optimise the effectiveness and cost of care.
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Cleanliness is one of the key determinants of overall customer satisfaction in train stations. Customers’ perception of cleanliness is not limited to cleaning only but depends on multiple predictors. A better understanding of these predictors may contribute to the optimisation of perceived cleanliness in train stations. The current study was designed to examine how objective predictors (measures of cleaning quality), subjective predictors (e.g., customers’ perception of lighting, scent, staff), and demographic variables relate to perceived cleanliness in train stations. Data on cleaning quality were gathered by trained cleaning inspectors and data on subjective predictors of cleanliness were obtained through surveys collected at 25 train stations in the Netherlands (N = 19.206). Data were examined using correlation and regression analysis. Positive and significant correlates of perceived cleanliness in train stations were found, including: perception of scent, lighting, colour, and staff. In regression analysis, customers’ perception of scent and lighting appeared to be powerful predictors of perceived cleanliness. These findings underline that customers’ perception of cleanliness is not only influenced by cleaning quality, but also by other predictors, such as scent, lighting, colour, and staff behaviour.
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Identifying factors that predict health-related quality of life (QOL) following hematopoietic SCT, is important in estimating patients’ abilities to adjust to the consequences of their disease and treatment. As the studies that have been published on this subject are scattered, the present study aimed to systematically review prognostic factors for health-related QOL after auto- and allo-SCT in hematological malignancies. A systematic, computerized search in Medline, EMBASE, PsycINFO and the Cochrane Library was conducted from 2002 to June 2010. The methodological quality of the studies was assessed using an adaptation of Hayden's criteria list. Qualitative data synthesis was performed to determine the strength of the scientific evidence. In all, 35 studies fulfilled the selection criteria. Strong–moderate evidence was found for GVHD, conditioning regimen, being female, younger age, receiving less social support and pre-transplant psychological distress as predictors of various aspects of health-related QOL following hematopoietic SCT. The results of this review may help transplant teams in selecting patients at risk for experiencing a diminished health-related QOL following hematopoietic SCT. Follow-up treatment can be provided in order to promote QOL.
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From the literature three types of predictors for factor scores are available. These are characterized by the constraints: linear, linear conditionally unbiased, and linear correlation preserving. Each of these constraints generates a class of predictors. Best predictors are defined in terms of L?wner's partial matrix order applied to matrices of mean square error of prediction. It is shown that within the first two classes a best predictor exists and that it does not exist in the third. Copyright ? 1996 by Marcel Dekker, Inc.
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Objective: Systematic review to identify predictors for dropout during interdisciplinary pain management programmes. Data sources: PubMed, PsycINFO, CINAHL, Embase, and SPORTDiscus were searched from inception to 22 June 2017. Study selection: Screening, data-extraction and quality assessment was carried out independently by 2 researchers. Data synthesis: Eight studies with low methodological quality were included in this review. Out of 63 potential predictors identified in univariate analyses, significant results were found for 18 predictors of dropout in multiple logistic regression analyses in 4 domains, as described by Meichenbaum & Turk: (i) sociodemographic domain (2); (ii) patient domain (8); (iii) disease domain (6); and (iv) treatment domain (2). Conclusion: This systematic review presents an overview of predictors of dropout. The literature with regard to the prediction of dropout has focused mainly on patient characteristics and is still in the stage of model development. Future research should focus on therapist/therapy-related predictors and the interaction between these predictors. This review suggests future research on this topic, in order to generate better outcomes in interdisciplinary pain management programmes.
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