ObjectivesThe objective of this review was to assess the benefit of using electronic, mobile and telehealth tools for vulnerable patients with chronic disease and explore the mechanisms by which these impact patient self-efficacy and self-management.DesignWe searched MEDLINE, all evidence-based medicine, CINAHL, Embase and PsychINFO covering the period 2009 to 2018 for electronic, mobile or telehealth interventions. Quality was assessed according to rigour and relevance. Those studies providing a richer description (‘thick’) were synthesised using a realist matrix.Setting and participantsStudies of any design conducted in community-based primary care involving adults with one or more diagnosed chronic health condition and vulnerability due to demographic, geographic, economic and/or cultural characteristics.ResultsEighteen trials were identified targeting a range of chronic conditions and vulnerabilities. The data provided limited insight into the mechanisms underpinning these interventions, most of which sought to persuade vulnerable patients into believing they could self-manage their conditions through improved symptom monitoring, education and support and goal setting. Patients were relatively passive in the interaction, and the level of patient response attributed to their intrinsic level of motivation. Health literacy, which may be confounded with motivation, was only measured in one study, and eHealth literacy was not assessed.ConclusionsResearch incorporating these tools with vulnerable groups is not comprehensive. Apart from intrinsic motivation, health literacy may also influence the reaction of vulnerable groups to technology. Social persuasion was the main way interventions sought to achieve better self-management. Efforts to engage patients by healthcare providers were lower than expected. Use of social networks or other eHealth mechanisms to link patients and provide opportunities for vicarious experience could be further explored in relation to vulnerable groups. Future research could also assess health and eHealth literacy and differentiate the specific needs for vulnerable groups when implementing health technologies.

Three of the four known mouse collectin genes have been mapped to chromosome 14. To further characterize the spatial relationship of these genes, a bacterial artificial chromosome (BAC) library of mouse chromosome 14 was screened using mouse surfactant protein (SP)-A and -D complementary DNAs (cDNAs). One large clone hybridized to both SP-A and SP-D cDNAs and was found by polymerase chain reaction (PCR) to contain sequences from one of the mouse mannose-binding lectin genes (Mbl1). We used Southern mapping and subcloning of overlapping restriction fragments to characterize the gene locus. Mapping was confirmed by fluorescent in situ hybridization of fiber-stretched BAC DNA and by Southern hybridization of restriction endonuclease-digested and PCR-amplified genomic DNA. We found that the SP-A, Mbl1, and SP-D genes reside contiguously within a 55-kb region. The SP-A and Mbl1 genes are in the same 5' to 3' orientation and 16 kb apart. The SP-D gene is in the opposite orientation to the two other collectin genes, 13 kb away from the 3' end of the Mbl1 gene. The mouse SP-D gene had not previously been characterized. We found its size (13 kb) and organization to be similar to that of human SP-D. Exon I is untranslated. The second exon is a hybrid exon that contains signal for initiation of translation, signal peptide, N-terminal domain, and the first seven collagen triplets of the collagen-like domain of the protein. Four short exons (III through VI) encode the collagen-like domain of the protein, and exons VII and VIII the linking and the carbohydrate-recognition domains, respectively.

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