Dataset Information

Development and Validation of a Rating Scale of Pain Expression during Childbirth (ESVADOPA).

ABSTRACT: One of the most representative symptoms during childbirth is pain, which is one of the most prominent concerns of pregnant women. There are different instruments to assess pain, all of which require interrupting the woman, thus interfering with the intimacy of childbirth. This study seeks to develop and validate a rating scale of the expression of childbirth pain that does not require the mother's attention and respects her privacy during labor. The study was conducted at a regional hospital in a border town in southern Spain between November 2018 and September 2019. Scale items were developed following a review of the scientific literature, and experts judged the content validity. After a pilot test, the scale was psychometrically evaluated. The psychometric tests consisted of internal consistency analysis, exploratory factor analysis, and determination of the content, construct, and convergent validity. The scale was evaluated by 36 experts in the field and was then applied to 55 women during the active phase of childbirth. The final version of the Rating Scale of Pain Expression during Childbirth (in Spanish, Escala de Valoración de la Expresión del Dolor durante el Trabajo de Parto-ESVADOPA) consists of six items in two dimensions. The scale had a Cronbach's alpha coefficient of 0.78, and the content validity measured by Aiken's V co-efficient was also 0.78. The exploratory factor analysis yielded two dimensions that explained 68.08% of the total variance. For convergent validity, a comparison was made with the visual analogue scale, yielding a medium-high value of 0.641. As indicated by the internal consistency and by the content and construct validity outcomes, the ESVADOPA successfully measures pain expression during childbirth and represents a suitable tool for pain expression during birth without the need for intervention or the need for the mother to speak the same language as the midwife.

SUBMITTER: Navarro-Prado S

PROVIDER: S-EPMC7459959 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development and Validation of a Rating Scale of Pain Expression during Childbirth (ESVADOPA).

Navarro-Prado Silvia S Sánchez-Ojeda María Angustias MA Martín-Salvador Adelina A Luque-Vara Trinidad T Fernández-Gómez Elisabet E Caro-Morán Elena E

International journal of environmental research and public health 20200812 16

One of the most representative symptoms during childbirth is pain, which is one of the most prominent concerns of pregnant women. There are different instruments to assess pain, all of which require interrupting the woman, thus interfering with the intimacy of childbirth. This study seeks to develop and validate a rating scale of the expression of childbirth pain that does not require the mother's attention and respects her privacy during labor. The study was conducted at a regional hospital in ...[more]

PMID: 32806536

Similar Datasets

Project description:Background: Oromandibular dystonia manifests with sustained or task-specific contractions of the masticatory, tongue, and/or other muscles in the stomatognathic system. Since its symptoms can vary, it has been difficult to objectively measure disease severity and post-treatment changes. Objective: To develop and validate a comprehensive measurement tool for oromandibular dystonia. Methods: An examiner-rated scale included three subscales for severity, disability, and pain, modified specifically for oromandibular dystonia from the Toronto Western Spasmodic Torticollis Rating Scale-2. To evaluate the severity of each subtype of oromandibular dystonia, four of the six items were selected according to the subtype (jaw closing dystonia, tongue dystonia, jaw opening dystonia, jaw deviation [protrusion] dystonia, and lip dystonia). A patient-administered questionnaire based on clinical features and other relevant aspects associated with oromandibular dystonia was developed, which included five subscales: general, eating, speech, cosmetic, and social/family life. The questionnaire, examiner-rated scale, and four subscales (sleep, annoyance, mood, and psychosocial functioning) of the Cervical Dystonia Impact Profile-58 were combined to construct the oromandibular dystonia rating scale (OMDRS). The reliability and validity of the scale were assessed using clinimetric testing. Results: Six hundred and eighteen patients with oromandibular dystonia (394 women and 224 men; mean age, 51.7 years) were evaluated by the OMDRS. The overall OMDRS showed high-level internal consistency measured by Cronbach's alpha (0.95) with a logical factor structure. Cronbach's alpha for the subscales was satisfactory to excellent, ranging from 0.72 to 0.94. All items revealed acceptable inter-rater reliability (kappa > 0.4, interclass correlation coefficient > 0.6). Repeated ratings of videotapes revealed acceptable intra-rater reliability for all items (kappa > 0.76, interclass correlation coefficient > 0.86). Test-retest reliability showed a significant (p < 0.001) correlation efficiency. The OMDRS showed significant (p < 0.001) convergent and discriminant validity and significant (p < 0.001) sensitivity to changes after botulinum toxin therapy. Conclusion: The OMDRS can be useful for the comprehensive evaluation of disease severity, disability, psychosocial functioning, and impact on the quality of life as well as therapeutic changes in patients with oromandibular dystonia.

Project description:BackgroundWith thousands of health apps in app stores globally, it is crucial to systemically and thoroughly evaluate the quality of these apps due to their potential influence on health decisions and outcomes. The Mobile App Rating Scale (MARS) is the only currently available tool that provides a comprehensive, multidimensional evaluation of app quality, which has been used to compare medical apps from American and European app stores in various areas, available in English, Italian, Spanish, and German. However, this tool is not available in Arabic.ObjectiveThis study aimed to translate and adapt MARS to Arabic and validate the tool with a sample of health apps aimed at managing or preventing obesity and associated disorders.MethodsWe followed a well-established and defined "universalist" process of cross-cultural adaptation using a mixed methods approach. Early translations of the tool, accompanied by confirmation of the contents by two rounds of separate discussions, were included and culminated in a final version, which was then back-translated into English. Two trained researchers piloted the MARS in Arabic (MARS-Ar) with a sample of 10 weight management apps obtained from Google Play and the App Store. Interrater reliability was established using intraclass correlation coefficients (ICCs). After reliability was ascertained, the two researchers independently evaluated a set of additional 56 apps.ResultsMARS-Ar was highly aligned with the original English version. The ICCs for MARS-Ar (0.836, 95% CI 0.817-0.853) and MARS English (0.838, 95% CI 0.819-0.855) were good. The MARS-Ar subscales were highly correlated with the original counterparts (P<.001). The lowest correlation was observed in the area of usability (r=0.685), followed by aesthetics (r=0.827), information quality (r=0.854), engagement (r=0.894), and total app quality (r=0.897). Subjective quality was also highly correlated (r=0.820).ConclusionsMARS-Ar is a valid instrument to assess app quality among trained Arabic-speaking users of health and fitness apps. Researchers and public health professionals in the Arab world can use the overall MARS score and its subscales to reliably evaluate the quality of weight management apps. Further research is necessary to test the MARS-Ar on apps addressing various health issues, such as attention or anxiety prevention, or sexual and reproductive health.

Project description:BackgroundMobile health apps (MHA) have the potential to improve health care. The commercial MHA market is rapidly growing, but the content and quality of available MHA are unknown. Instruments for the assessment of the quality and content of MHA are highly needed. The Mobile Application Rating Scale (MARS) is one of the most widely used tools to evaluate the quality of MHA. Only few validation studies investigated its metric quality. No study has evaluated the construct validity and concurrent validity.ObjectiveThis study evaluates the construct validity, concurrent validity, reliability, and objectivity, of the MARS.MethodsData was pooled from 15 international app quality reviews to evaluate the metric properties of the MARS. The MARS measures app quality across four dimensions: engagement, functionality, aesthetics and information quality. Construct validity was evaluated by assessing related competing confirmatory models by confirmatory factor analysis (CFA). Non-centrality (RMSEA), incremental (CFI, TLI) and residual (SRMR) fit indices were used to evaluate the goodness of fit. As a measure of concurrent validity, the correlations to another quality assessment tool (ENLIGHT) were investigated. Reliability was determined using Omega. Objectivity was assessed by intra-class correlation.ResultsIn total, MARS ratings from 1,299 MHA covering 15 different health domains were included. Confirmatory factor analysis confirmed a bifactor model with a general factor and a factor for each dimension (RMSEA = 0.074, TLI = 0.922, CFI = 0.940, SRMR = 0.059). Reliability was good to excellent (Omega 0.79 to 0.93). Objectivity was high (ICC = 0.82). MARS correlated with ENLIGHT (ps<.05).ConclusionThe metric evaluation of the MARS demonstrated its suitability for the quality assessment. As such, the MARS could be used to make the quality of MHA transparent to health care stakeholders and patients. Future studies could extend the present findings by investigating the re-test reliability and predictive validity of the MARS.

Dataset Information

Development and Validation of a Rating Scale of Pain Expression during Childbirth (ESVADOPA).

Publications

Development and Validation of a Rating Scale of Pain Expression during Childbirth (ESVADOPA).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets