As the older adult population group has been increasing in size, there has been evidence of growing social isolation and loneliness in their lives. The increased use of information communication technology and Internet-supported interventions has stimulated an interest in the benefits of e-Interventions for older people and specifically in having a role in increasing social networks and decreasing loneliness. A systematic review of e-Interventions to reduce loneliness in older people was conducted with the aim to synthesize high quality evidence on the effectiveness of e-Interventions to decrease social isolation/loneliness for older people living in community/residential care. A systematic search of 12 databases for reviews published between 2000–2017 was conducted using search term synonyms for older people, social isolation and interventions. Three independent researchers screened articles and two reviewers extracted data. The Revised-Assessment of Multiple Systematic Reviews was used to assess the quality of reviews. The final search identified 12 reviews, which included 22 unique primary research studies evaluating e-Interventions for social isolation or loneliness. The reviews were of moderate quality and the primary studies showed a lack of rigor. Loneliness was most frequently measured using the University California Los Angeles Loneliness Scale. Despite the limitations of the reviewed studies, there is inconsistent and weak evidence on using e-Interventions for loneliness in older people.

There is a high prevalence of loneliness among older people, especially in residential care settings. Loneliness is often accompanied by maladaptive cognitions which can affect the maintenance and establishment of meaningful social connections. This study implemented and evaluated a low-intensity Cognitive Behavior Therapy (LI-CBT) mHealth-supported intervention which targeted maladaptive cognitions in older people (≥60 years) experiencing loneliness. The three-month intervention using WhatsApp was implemented with older people in four inner-city residential care facilities. The intervention included three components: technology acceptance, psycho-education, and individualized positively worded messages addressing maladaptive cognitions. The intervention was evaluated using a randomized control design. Key outcomes were measured pre-, post-, and one month after the intervention. There were significant changes in social cognition (YSQ-SF T₀–T₁–T₂, X² = 9.69, p = 0.008) and loneliness levels (total loneliness T₀–T₁–T₂, X² = 14.62, p = 0.001), and an increase in WhatsApp usage (T₀ = 26% vs. T₁ = 60%, X²=15.22, p = 0.019). At 1-month follow-up, even with a significant reduction in WhatsApp usage, a significant reduction in loneliness was maintained. LI-CBT delivered via instant messaging may be effective in reducing loneliness experienced by older people.

Background: Communication is an integral part of life and of nurse-patient relationships. Effective communication with patients can improve the quality of care. However, the specific communication needs of older adults can render communication between them and nurses as less effective with negative outcomes. Methods: This scoping review aims at describing the type of nonverbal communication used by nurses to communicate with older adults. It also describes the older adults’ perceptions of nurses’ nonverbal communication behaviors. It followed (Int J Soc Res 8: 19-32, 2005) framework. Grey literature and 11 databases were systematically searched for studies published in English and French, using search terms synonymous with nonverbal communication between nurses and older adults for the period 2000 to 2019. Results: The search revealed limited published research addressing nonverbal communication between older adults and nurses. The studies eligible for quality assessment were found to be of high quality. Twenty-two studies were included and highlighted haptics, kinesics, proxemics, and vocalics as most frequently used by nurses when communicating with older adults; while studies showed limited use of artefacts and chronemics. There was no mention of nurses’ use of silence as a nonverbal communication strategy. Additionally, there were both older adults’ positive and negative responses to nurses’ nonverbal communication behaviors. Conclusion: Nurses should be self-aware of their nonverbal communication behaviors with older adults as well as the way in which the meanings of the messages might be misinterpreted. In addition, nurses should identify their own style of nonverbal communication and understand its modification as necessary in accordance with patient’s needs.

The social, psychological, physical, and financial benefits of digital inclusion are of increasing importance for older persons. However, older persons are often less inclined to utilise technological communication with reports of perceived poor technology acceptance. In this context, a study was conducted to investigate communication technology acceptance in older persons living in residential care. A cross sectional survey of residents (≥60 yrs) of four inner city residences in Durban, South Africa was conducted to assess communication technology access and technology acceptance defined as Usage Behaviour. A researcher-administered questionnaire was based on the Senior Technology Acceptance Model (STAM). Descriptive statistics of STAM factors and structural equation model (SEM) were conducted to test this model, to quantify the importance of various technology acceptance factors on Usage Behaviour among older persons living in residential care. The survey had a 72.1% response rate (n=277). Most of the respondents owned mobile phones (87.6%), although there was low smartphone ownership. Family desire to communicate and ease of use motivated mobile phone acquisition. Behaviour Intention, Facilitating Conditions, Attitude to Life and Satisfaction and education level were significantly associated with Usage Behaviour. Gerontechnology Anxiety and Age showed significant negative associations with Usage Behaviour. The acceptance of communication technology in this setting was low and predominantly influenced by Attitudinal and Technological Context factors together with age and education.