Dataset Information

Using Visual Analogue Scales in eHealth: Non-Response Effects in a Lifestyle Intervention.

ABSTRACT: Visual analogue scales (VASs) have been shown to be valid measurement instruments and a better alternative to Likert-type scales in Internet-based research, both empirically and theoretically [1,2]. Upsides include more differentiated responses, better measurement level, and less error. Their feasibility and properties in the context of eHealth, however, have not been examined so far.The present study examined VASs in the context of a lifestyle study conducted online, measuring the impact of VASs on distributional properties and non-response.A sample of 446 participants with a mean age of 52.4 years (standard deviation (SD) = 12.1) took part in the study. The study was carried out as a randomized controlled trial, aimed at supporting participants over 8 weeks with an additional follow-up measurement. In addition to the randomized questionnaire, participants were further randomly assigned to either a Likert-type or VAS response scale version of the measures.Results showed that SDs were lower for items answered via VASs, 2P (Y ? 47 | n=55, P=.5) < .001. Means did not differ across versions. Participants in the VAS version showed lower dropout rates than participants in the Likert version, odds ratio = 0.75, 90% CI (0.58-0.98), P=.04. Number of missing values did not differ between questionnaire versions.The VAS is shown to be a valid instrument in the eHealth context, offering advantages over Likert-type scales. The results of the study provide further support for the use of VASs in Internet-based research, extending the scope to senior samples in the health context.Clinicaltrials.gov NCT01909349; https://clinicaltrials.gov/ct2/show/NCT01909349 (Archived by WebCite at http://www.webcitation.org/6h88sLw2Y).

SUBMITTER: Kuhlmann T

PROVIDER: S-EPMC4935790 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Using Visual Analogue Scales in eHealth: Non-Response Effects in a Lifestyle Intervention.

Kuhlmann Tim T Reips Ulf-Dietrich UD Wienert Julian J Lippke Sonia S

Journal of medical Internet research 20160622 6

<h4>Background</h4>Visual analogue scales (VASs) have been shown to be valid measurement instruments and a better alternative to Likert-type scales in Internet-based research, both empirically and theoretically [1,2]. Upsides include more differentiated responses, better measurement level, and less error. Their feasibility and properties in the context of eHealth, however, have not been examined so far.<h4>Objective</h4>The present study examined VASs in the context of a lifestyle study conducte ...[more]

PMID: 27334562

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Project description:BackgroundLifestyle-related diseases, such as stroke, heart disease, and diabetes, are examples of noncommunicable diseases. Noncommunicable diseases are now the leading cause of death in the world, and their major causes are lifestyle related. The number of eHealth interventions is increasing, which is expected to improve individuals' health literacy on lifestyle-related diseases.ObjectiveThis literature review aims to identify existing literature published in the past decade on eHealth interventions aimed at improving health literacy on lifestyle-related diseases among the general population using selected visual methods, such as educational videos, films, and movies.MethodsA systematic literature search of the PubMed database was conducted in April 2019 for papers written in English and published from April 2, 2009, through April 2, 2019. A total of 538 papers were identified and screened in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram. Finally, 23 papers were included in this review.ResultsThe 23 papers were characterized according to study characteristics (author and year of publication, study design and region where the study was conducted, study objective, service platform, target disease and participant age, research period, outcomes, and research method); the playback time of the educational videos, films, and movies; and the evaluation of the study's impacts on health literacy. A total of 7 studies compared results using statistical methods. Of these, 5 studies reported significant positive effects of the intervention on health literacy and health-related measures (eg, physical activity, body weight). Although most of the studies included educational content aimed at improving health literacy, only 7 studies measured health literacy. In addition, only 5 studies assessed literacy using health literacy measurement tools.ConclusionsThis review found that the provision of educational content was satisfactory in most eHealth studies using selected visual methods, such as videos, films, and movies. These findings suggest that eHealth interventions influence people's health behaviors and that the need for this intervention is expected to increase. Despite the need to develop eHealth interventions, standardized measurement tools to evaluate health literacy are lacking. Further research is required to clarify acceptable health literacy measurements.

Project description:BackgroundRating scales like the visual analogue scale, VAS, and the verbal rating scale, VRS, are often used for pain assessments both in clinical work and in research, despite the lack of a gold standard. Interchangeability of recorded pain intensity captured in the two scales has been discussed earlier, but not in conjunction with taking the influence of pain etiology into consideration.MethodsIn this cross-sectional study, patients with their pain classified according to its etiology (chronic/idiopathic, nociceptive and neuropathic pain) were consecutively recruited for self-assessment of their actual pain intensity using a continuous VAS, 0-100, and a discrete five-category VRS. The data were analyzed with a non-parametric statistical method, suitable for comparison of scales with different numbers of response alternatives.ResultsAn overlapping of the VAS records relative the VRS categories was seen in all pain groups. Cut-off positions for the VAS records related to the VRS categories were found lower in patients with nociceptive pain relative patients suffering from chronic/idiopathic and neuropathic pain. When comparing the VAS records transformed into an equidistant five-category scale with the VRS records, systematic disagreements between the scales was shown in all groups. Furthermore, in the test-retest a low percentage of the patients agreed to the same pain level on the VAS while the opposite hold for the VRS.ConclusionThe pain intensity assessments on VAS and VRS are in this study, not interchangeable due to overlap of pain records between the two scales, systematic disagreements when comparing the two scales and a low percentage intra-scale agreement. Furthermore, the lower VAS cut-off positions relative the VRS labels indicate different meaning of the rated pain intensity depending on pain etiology. It is also indicated that the scales have non-linear properties and that the two scales probably have different interpretation. Our findings are in favor of using the VRS in pain intensity assessments but if still the VAS is preferred, the VAS data should be analyzed as continuous using statistical methods suitable for ordinal data. Furthermore, our findings indicate a risk to over or under estimate the patient's perceived pain when interpreting condensed VAS data.

Project description:BackgroundeHealth interventions can reach large populations and are effective in increasing physical activity (PA) and fruit and vegetable intake. Nevertheless, the effects of eHealth interventions are overshadowed by high attrition rates. Examining more closely when users decide to leave the intervention can help eHealth developers to make informed decisions about which intervention components should be reshaped or simply removed. Investigating which users are more likely to quit an intervention can inform developers about whether and how their intervention should be adapted to specific subgroups of users.ObjectiveThis study investigated the pattern of attrition in a Web-based intervention to increase PA, fruit, and vegetable intake. The first aim was to describe attrition rates according to different self-regulation components. A second aim was to investigate whether certain user characteristics are predictors for start session completion, returning to a follow-up session and intervention completion.MethodsThe sample consisted of 549 adults who participated in an online intervention, based on self-regulation theory, to promote PA and fruit and vegetable intake, called "MyPlan 1.0." Using descriptive analysis, attrition was explored per self-regulation component (eg, action planning and coping planning). To identify which user characteristics predict completion, logistic regression analyses were conducted.ResultsAt the end of the intervention program, there was an attrition rate of 78.2% (330/422). Attrition rates were very similar for the different self-regulation components. However, attrition levels were higher for the fulfillment of questionnaires (eg, to generate tailored feedback) than for the more interactive components. The highest amount of attrition could be observed when people were asked to make their own action plan. There were no significant predictors for first session completion. Yet, two subgroups had a lower chance to complete the intervention, namely male users (OR: 2.24, 95% CI=1.23-4.08) and younger adults (OR: 1.02, 95% CI=1.00-1.04). Furthermore, younger adults were less likely to return to the website for the first follow-up after one week (OR: 1.03, 95% CI=1.01-1.04).ConclusionsThis study informs us that eHealth interventions should avoid the use of extensive questionnaires and that users should be provided with a rationale for several components (eg, making an action plan and completing questions). Furthermore, future interventions should focus first on motivating users for the behavior change before guiding them through action planning. Though, this study provides no evidence for removal of one of the self-regulation techniques based on attrition rates. Finally, strong efforts are needed to motivate male users and younger adults to complete eHealth interventions.

Dataset Information

Using Visual Analogue Scales in eHealth: Non-Response Effects in a Lifestyle Intervention.

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Using Visual Analogue Scales in eHealth: Non-Response Effects in a Lifestyle Intervention.

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