Designing and Testing an Inventory for Measuring Social Media Competency of Certified Health Education Specialists

Objective: The aim of this study was to design, develop, and test the Social Media Competency Inventory (SMCI) for CHES and MCHES. Methods: The SMCI was designed in three sequential phases: (1) Conceptualization and Domain Specifications, (2) Item Development, and (3) Inventory Testing and Finalization. Phase 1 consisted of a literature review, concept operationalization, and expert reviews. Phase 2 involved an expert panel (n=4) review, think-aloud sessions with a small representative sample of CHES/MCHES (n=10), a pilot test (n=36), and classical test theory analyses to develop the initial version of the SMCI. Phase 3 included a field test of the SMCI with a random sample of CHES and MCHES (n=353), factor and Rasch analyses, and development of SMCI administration and interpretation guidelines. Results: Six constructs adapted from the unified theory of acceptance and use of technology and the integrated behavioral model were identified for assessing social media competency: (1) Social Media Self-Efficacy, (2) Social Media Experience, (3) Effort Expectancy, (4) Performance Expectancy, (5) Facilitating Conditions, and (6) Social Influence. The initial item pool included 148 items. After the pilot test, 16 items were removed or revised because of low item discrimination (r.90), or based on feedback received from pilot participants. During the psychometric analysis of the field test data, 52 items were removed due to low discrimination, evidence of content redundancy, low R-squared value, or poor item infit or outfit. Psychometric analyses of the data revealed acceptable reliability evidence for the following scales: Social Media Self-Efficacy (alpha=.98, item reliability=.98, item separation=6.76), Social Media Experience (alpha=.98, item reliability=.98, item separation=6.24), Effort Expectancy(alpha =.74, item reliability=.95, item separation=4.15), Performance Expectancy (alpha =.81, item reliability=.99, item separation=10.09), Facilitating Conditions (alpha =.66, item reliability=.99, item separation=16.04), and Social Influence (alpha =.66, item reliability=.93, item separation=3.77). There was some evidence of local dependence among the scales, with several observed residual correlations above |.20|. Conclusions: Through the multistage instrument-development process, sufficient reliability and validity evidence was collected in support of the purpose and intended use of the SMCI. The SMCI can be used to assess the readiness of health education specialists to effectively use social media for health promotion research and practice. Future research should explore associations across constructs within the SMCI and evaluate the ability of SMCI scores to predict social media use and performance among CHES and MCHES

Association Between Health Literacy, Electronic Health Literacy, Disease-Specific Knowledge, and Health-Related Quality of Life Among Adults With Chronic Obstructive Pulmonary Disease: Cross-Sectional Study

Background: Despite the relatively high prevalence of low health literacy among individuals living with chronic obstructive pulmonary disease (COPD), limited empirical attention has been paid to the cognitive and health literacy–related skills that can uniquely influence patients’ health-related quality of life (HRQoL) outcomes. Objective: The aim of this study was to examine how health literacy, electronic health (eHealth) literacy, and COPD knowledge are associated with both generic and lung-specific HRQoL in people living with COPD. Methods: Adults from the COPD Foundation’s National Research Registry (n=174) completed a cross-sectional Web-based survey that assessed sociodemographic characteristics, comorbidity status, COPD knowledge, health literacy, eHealth literacy, and generic/lung-specific HRQoL. Hierarchical linear regression models were tested to examine the roles of health literacy and eHealth literacy on generic (model 1) and lung-specific (model 2) HRQoL, after accounting for socioeconomic and comorbidity covariates. Spearman rank correlations examined associations between ordinal HRQoL items and statistically significant hierarchical predictor variables. Results: After adjusting for confounding factors, health literacy, eHealth literacy, and COPD knowledge accounted for an additional 9% of variance in generic HRQoL (total adjusted R2=21%; F9,164=6.09, P<.001). Health literacy (b=.08, SE 0.02, 95% CI 0.04-0.12) was the only predictor positively associated with generic HRQoL (P<.001). Adding health literacy, eHealth literacy, and COPD knowledge as predictors explained an additional 7.40% of variance in lung-specific HRQoL (total adjusted R2=26.4%; F8,161=8.59, P<.001). Following adjustment for covariates, both health literacy (b=2.63, SE 0.84, 95% CI 0.96-4.29, P<.001) and eHealth literacy (b=1.41, SE 0.67, 95% CI 0.09-2.73, P<.001) were positively associated with lung-specific HRQoL. Health literacy was positively associated with most lung-specific HRQoL indicators (ie, cough frequency, chest tightness, activity limitation at home, confidence leaving home, sleep quality, and energy level), whereas eHealth literacy was positively associated with 5 of 8 (60%) lung-specific HRQoL indicators. Upon controlling for confounders, COPD knowledge (b=−.56, SE 0.29, 95% CI −1.22 to −0.004, P<.05) was inversely associated with lung-specific HRQoL. Conclusions: Health literacy, but not eHealth literacy, was positively associated with generic HRQoL. However, both health literacy and eHealth literacy were positively associated with lung-specific HRQoL, with higher COPD knowledge indicative of lower lung-specific HRQoL. These results confirm the importance of considering health and eHealth literacy levels when designing patient education programs for people living with COPD. Future research should explore the impact of delivering interventions aimed at improving eHealth and health literacy among patients with COPD, particularly when disease self-management goals are to enhance HRQoL

The roles of dispositional coping style and social support in helping people with respiratory disease cope with a breathlessness crisis

© 2019 John Wiley & Sons Ltd Aim: To explore the role of coping moderators in self-management of breathlessness crises by people with advanced respiratory disease. Design: A secondary analysis of semi-structured interview data. Methods: Interviews with patients who had advanced respiratory disease, chronic breathlessness and at least one experience where they considered presenting to Emergency but self-managed instead (a “near miss”). Participants were recruited from New South Wales, Queensland, Victoria, South Australia or Tasmania. Eligible caregivers were those who contributed to Emergency-related decision-making. Interviews were coded inductively and then deductively against the coping moderators social support and dispositional coping style, defined by the Transactional Model of Stress and Coping. Results: Interviews were conducted between October 2015 - April 2016 with 20 patients and three caregivers. Social networks offered emotional and practical support but also had potential for conflict with patients' ‘hardy’ coping style. Patient hardiness (characterized by a sense of ‘commitment’ and ‘challenge’) promoted a proactive approach to self-management but made some patients less willing to accept support. Information-seeking tendencies varied between patients and were sometimes shared with caregivers. An optimistic coping style appeared to be less equivocally beneficial. Conclusion: This study shows that social support and coping style may influence how people self-manage through their breathlessness crises and identified ways coping moderators can facilitate or hinder effective self-management. Impact: This study confers insights into how social-support and coping style can be supported and optimized to facilitate breathlessness self-management. Acknowledging coping moderator interactions is beneficial for developing resources and strategies that recognise patient mastery

Reliability and Validity of the Telephone-Based eHealth Literacy Scale Among Older Adults: Cross-Sectional Survey

Background: Only a handful of studies have examined reliability and validity evidence of scores produced by the 8-item eHealth literacy Scale (eHEALS) among older adults. Older adults are generally more comfortable responding to survey items when asked by a real person rather than by completing self-administered paper-and-pencil or online questionnaires. However, no studies have explored the psychometrics of this scale when administered to older adults over the telephone. Objective: The objective of our study was to examine the reliability and internal structure of eHEALS data collected from older adults aged 50 years or older responding to items over the telephone. Methods: Respondents (N=283) completed eHEALS as part of a cross-sectional landline telephone survey. Exploratory structural equation modeling (E-SEM) analyses examined model fit of eHEALS scores with 1-, 2-, and 3-factor structures. Subsequent analyses based on the partial credit model explored the internal structure of eHEALS data. Results: Compared with 1- and 2-factor models, the 3-factor eHEALS structure showed the best global E-SEM model fit indices (root mean square error of approximation=.07; comparative fit index=1.0; Tucker-Lewis index=1.0). Nonetheless, the 3 factors were highly correlated (r range .36 to .65). Item analyses revealed that eHEALS items 2 through 5 were overfit to a minor degree (mean square infit/outfit values <1.0; t statistics less than –2.0), but the internal structure of Likert scale response options functioned as expected. Overfitting eHEALS items (2-5) displayed a similar degree of information for respondents at similar points on the latent continuum. Test information curves suggested that eHEALS may capture more information about older adults at the higher end of the latent continuum (ie, those with high eHealth literacy) than at the lower end of the continuum (ie, those with low eHealth literacy). Item reliability (value=.92) and item separation (value=11.31) estimates indicated that eHEALS responses were reliable and stable. Conclusions: Results support administering eHEALS over the telephone when surveying older adults regarding their use of the Internet for health information. eHEALS scores best captured 3 factors (or subscales) to measure eHealth literacy in older adults; however, statistically significant correlations between these 3 factors suggest an overarching unidimensional structure with 3 underlying dimensions. As older adults continue to use the Internet more frequently to find and evaluate health information, it will be important to consider modifying the original eHEALS to adequately measure societal shifts in online health information seeking among aging populations.Open Access Fundin

Using screen video capture software to aide and inform cognitive interviewing

Web-based surveys are a salient tool in the repertoire of social and behavioral scientists. The increase in web-based surveys is understandable considering the distinct advantages offered, including: (a) lower costs and reduced labor time, (b) ability to directly transfer data into statistical packages (reducing coding errors), (c) customization options enabling more attractive presentation, (d) ability to reduce respondent burden by embedding skip patterns, and (e) access to larger sample sizes in different geographic regions. It is important to note, however, that administering web-based surveys also introduces distinct sources of error (e.g., coverage, sampling and non-response). Regardless of format (e.g., paper-and-pencil or web-based), specific, prescribed steps must be followed when constructing an instrument in order to reduce survey error and lend credence to the data collected before subsequent analysis is performed. One of those crucial stages integral to the pretesting process is cognitive interviewing. Cognitive interviewing is a qualitative process, encompassing two main techniques: think aloud interviewing and verbal probing. Collectively, these two methods seek to (a) produce information on what the respondent is thinking while answering the questions, (b) the cognitive processes used to answer the questions, and (c) how the respondent answers the questions. The purpose of this article is to provide a practical guide outlining how Camtasia, a screen video capture software, can aide and inform the cognitive interview process

Use of eHealth technologies to enable the implementation of musculoskeletal Models of Care: Evidence and practice

Musculoskeletal (MSK) conditions are the second leading cause of morbidity-related burden of disease globally. EHealth is a potentially critical factor that enables the implementation of accessible, sustainable and more integrated MSK models of care (MoCs). MoCs serve as a vehicle to drive evidence into policy and practice through changes at a health system, clinician and patient level. The use of eHealth to implement MoCs is intuitive, given the capacity to scale technologies to deliver system and economic efficiencies, to contribute to sustainability, to adapt to low-resource settings and to mitigate access and care disparities. We follow a practice-oriented approach to describing the ‘what’ and ‘how’ to harness eHealth in the implementation of MSK MoCs. We focus on the practical application of eHealth technologies across care settings to those MSK conditions contributing most substantially to the burden of disease, including osteoarthritis and inflammatory arthritis, skeletal fragility-associated conditions and persistent MSK pain

The positive role of hope on the relationship between loneliness and unhappy conditions in Hungarian young adults: How pathways thinking matters!

In this study, we examined loneliness and hope components as predictors of unhappy conditions (viz., anxious symptoms, depressive symptoms, & suicidal ideation) in young adults. The sample was comprised of 489 Hungarian college students. Results of conducting hierarchical regression analyses indicated that loneliness and hope pathways (but not hope agency) were important unique predictors of anxious symptoms, depressive symptoms, and suicidal ideation. Moreover, in part, consistent with the notion that hope might buffer the negative effects of loneliness on unhappy conditions, evidence for a significant Loneliness × Hope Pathways interaction effect in predicting each of the three indices of unhappy conditions was found. In contrast, the Loneliness × Hope Agency interaction effect was not found to be significant. Some implications of the present findings for the study and treatment of unhappy conditions in adults are discussed