Objective:Allied health assistants (AHAs) are an emerging group in allied health practice with the potential to improve quality of care and safety of patients. This systematic review summarizes the evidence regarding the roles and responsibilities of AHAs and describes the benefits and barriers to utilizing AHAs in current health care settings.Methods:A systematic process of literature searching was undertaken. A search strategy which included a range of electronic databases was searched using key terms. Studies which examined the roles and responsibilities of AHAs (across all allied health disciplines) were included in the review. Only publications written in the English language were considered, with no restriction on publication date. Two reviewers independently assessed eligibility of the articles. Data extraction was performed by the same reviewers. A narrative summary of findings was presented.Results:Of the initial 415 papers, 10 studies were included in the review. The majority of papers reported roles performed by general health care assistants or rehabilitation assistants who work in multiple settings or are not specifically affiliated to a health discipline. All current AHAs duties have elements of direct patient care and indirect support via clerical and administrative or housekeeping tasks. Benefits from the introduction of the AHA role in health care include improved clinical outcomes, increased patient satisfaction, higher-level services, and more “free” time for allied health professionals to concentrate on patients with complex needs. Barriers to the use of AHAs are related to blurred role boundaries, which raises issues associated with professional status and security.Conclusions:There is consensus in the literature that AHAs make a valuable contribution to allied health care. Whilst there are clear advantages associated with the use of AHAs to support allied health service delivery, ongoing barriers to their effective use persist.

BackgroundElectronic health (eHealth) literacy is needed to effectively engage with Web-based health resources. The 8-item eHealth literacy scale (eHEALS) is a commonly used self-report measure of eHealth literacy. Accumulated evidence has suggested that the eHEALS is unidimensional. However, a recent study by Sudbury-Riley and colleagues suggested that a theoretically-informed three-factor model fit better than a one-factor model. The 3 factors identified were awareness (2 items), skills (3 items), and evaluate (3 items). It is important to determine whether these findings can be replicated in other populations.ObjectiveThe aim of this cross-sectional study was to verify the three-factor eHEALS structure among magnetic resonance imaging (MRI) and computed tomography (CT) medical imaging outpatients.MethodsMRI and CT outpatients were recruited consecutively in the waiting room of one major public hospital. Participants self-completed a touchscreen computer survey, assessing their sociodemographic, scan, and internet use characteristics. The eHEALS was administered to internet users, and the three-factor structure was tested using structural equation modeling.ResultsOf 405 invited patients, 87.4% (354/405) were interested in participating in the study, and of these, 75.7% (268/354) were eligible. Of the eligible participants, 95.5% (256/268) completed all eHEALS items. Factor loadings were 0.80 to 0.94 and statistically significant (P<.001). All reliability measures were acceptable (indicator reliability: awareness=.71-.89, skills=.78-.80, evaluate=.64-.79; composite reliability: awareness=.89, skills=.92, evaluate=.89; variance extracted estimates: awareness=.80, skills=.79, evaluate=.72). Two out of three goodness-of-fit indices were adequate (standardized root mean square residual (SRMR)=.038; comparative fit index (CFI)=.944; root mean square error of approximation (RMSEA)=.156). Item 3 was removed because of its significant correlation with item 2 (Lagrange multiplier [LM] estimate 104.02; P<.001) and high loading on 2 factors (LM estimate 91.11; P<.001). All 3 indices of the resulting 7-item model indicated goodness of fit (χ211=11.3; SRMR=.013; CFI=.999; RMSEA=.011).ConclusionsThe three-factor eHEALS structure was supported in this sample of MRI and CT medical imaging outpatients. Although further factorial validation studies are needed, these 3 scale factors may be used to identify individuals who could benefit from interventions to improve eHealth literacy awareness, skill, and evaluation competencies.

Background High-quality healthcare requires practitioners who have technical competence and communication skills. Medical practitioners need interpersonal skills for gathering and transferring information to their patients, in addition to general consultation skills. Appropriate information gathering increases the likelihood of an accurate diagnosis. Transferring information should be performed in a way that promotes patient understanding and increases the probability of adherence to physician recommendations. This applies to: (i) primary prevention such as smoking cessation; (ii) secondary prevention including preparation for potentially threatening interventions; and (iii) tertiary care, including breaking bad news regarding treatment and prognosis. Discussion This debate paper delineates factors associated with undergraduate medical communication skills training where robust research is needed. Ten key principles are presented and discussed, which are intended to guide future research in this field and ensure high quality studies with methodological rigour are conducted. Summary The literature on communication skills training for medical school undergraduates continues to grow. A considerable portion of this output is represented by commentaries, descriptive studies or poorly designed interventions. As with any field of healthcare, quality research interventions are required to ensure practice is grounded in high-level evidence.

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