Research in Developmental Disabilities 35 (2014) 2117–2128

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Research in Developmental Disabilities

Persons with moderate Alzheimer’s disease use simple technology aids to manage daily activities and leisure occupation Giulio E. Lancioni a,*, Nirbhay N. Singh b, Mark F. O’Reilly c, Jeff Sigafoos d, Caterina Renna e, Katia Pinto f, Floriana De Vanna g, Alessandro O. Caffo` a, Fabrizio Stasolla h a

University of Bari, Italy Medical College of Georgia, Georgia Regents University, Augusta, USA c University of Texas at Austin, TX, USA d Victoria University of Wellington, New Zealand e Domus Maxima Care Center, Casamassima, BA, Italy f Alzheimer Association Services, Bari, Italy g Memory Drops Day Center, Giovinazzo, BA, Italy h Lega F. D’Oro Research Center, Molfetta, Italy b

A R T I C L E I N F O

A B S T R A C T

Article history: Received 1 May 2014 Accepted 5 May 2014 Available online

Two studies assessed technology-aided programs to support performance of daily activities and selection/activation of music items with patients with moderate Alzheimer’s disease. In Study I, four patients were presented with activity-related pictorial instructions via a computer fitted with inexpensive, commercial software. In Study II, four patients were (a) presented with different music options and (b) allowed to select and activate the preferred option via a microswitch response. Study I showed that each patient learned to perform the two activities available with percentages of correct responses exceeding 85 by the end of the intervention. Study II showed that all patients learned to choose and activate music options. Psychology students, employed in a social validation check, scored the patients’ behavior within the program better than their behavior in a control situation. The relevance and usability of simplified pictorial-instruction programs and music choice programs for patients with moderate Alzheimer’s disease were discussed. ß 2014 Elsevier Ltd. All rights reserved.

Keywords: Alzheimer’s disease Daily activities Leisure Music Technology

1. Introduction Persons affected by Alzheimer’s disease experience a progressive decline of their condition with a gradual loss of their independence in daily functioning (Ambrose, 2012; Bernick, Cummings, Raman, Sun, & Aisen, 2012; Melrose et al., 2011; Perry, Monaco, Fadda, Caltagirone, & Carlesimo, 2014; Sikkes et al., 2013; Soto et al., 2012; Spalletta et al., 2012; Wilson et al., 2012). Indeed, they grow progressively less competent in important areas involving, among others, (1) managing medication and finances (Campbell et al., 2012; Cotrell, Wild, & Bader, 2006; Marson et al., 2000), (2) using typical communication

* Corresponding author at: Department of Neuroscience and Sense Organs, University of Bari, Via Quintino Sella 268, 70100 Bari, Italy. Tel.: +39 0805521410. E-mail addresses: [email protected], [email protected] (G.E. Lancioni). http://dx.doi.org/10.1016/j.ridd.2014.05.002 0891-4222/ß 2014 Elsevier Ltd. All rights reserved.

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means to interact with family and friends (e.g., using the telephone) (Nyga˚rd & Starkhammar, 2003, 2007; Perilli et al., 2012; Selwyn, Gorard, Furlong, & Madden, 2003), (3) performing daily activities such as preparing food (Lancioni et al., 2010; Martyr & Clare, 2012; Mihailidis, Boger, Canido, & Hoey, 2007), (4) managing orientation and travel within circumscribed and familiar places, such as home or day center (Caffo` et al., 2012; Lancioni, Perilli, et al., 2013; Provencher, Bier, Audet, & Gagnon, 2008), and (5) engaging in recreation activities such as listening to music (Cle´ment, Tonini, Khatir, Schiaratura, & Samsony, 2012; Lancioni, O’Reilly, et al., 2013; McHugh, Gardstrom, Hiller, Brewer, & Diestelkamp, 2012). In an attempt to slow down the apparently inevitable deterioration of these patients and maintain their basic adaptive skills for a longer time, professionals have resorted to two strategies. One strategy concerns pharmacological interventions, such as the use of memantine and acetylcholinesterase inhibitors (Darreh-Shori & Soininen, 2010; Ferris & Farlow, 2013; Konrath, Passos Cdos, Klein, & Henriques, 2013; Massoud & Le´ger, 2011; Rive et al., 2012; Tayeb, Yang, Price, & Tarazi, 2012). The other strategy concerns behavioral interventions, such as the use of reality orientation exercises, memory training, and stimulation enrichment (Bier et al., 2008; Boller, Jennings, Dieudonne´, Verny, & Ergis, 2012; Cotelli, Manenti, Zanetti, & Miniussi, 2012; Silverstein & Sherman, 2010; Small, 2012; Takeda, Tanaka, Okochi, & Kazui, 2012; Zanetti et al., 2001). Recently, behavioral intervention strategies supplemented by technology aids have been aimed at supporting the patients’ (a) daily activities, (b) orientation and travel within familiar indoor areas, and (c) telephone communication with their family and friends (Caffo` et al., 2014; Lancioni et al., 2011, 2012; Perilli et al., 2012; Perilli, Lancioni, Laporta, et al., 2013). For example, the strategies for helping the patients perform daily activities were based on the automatic (technologyregulated) presentation of instructions for the single steps of the activities targeted. The instructions, which varied across studies from verbal to visual, proved largely effective (Lancioni et al., 2008, 2010, 2011; Perilli, Lancioni, Hoogeveen, et al., 2013). Verbal instructions consisted of brief phrases describing the operations required by the single steps of the activities. Visual instructions consisted of (a) static pictorial or photographic representations of the material involved in the activity steps or (b) dynamic representations, that is, video clips of the operations required by the activity steps. The first of the two studies reported here was aimed at extending the research on pictorial instructions for supporting daily activities in patients with moderate Alzheimer’s disease. Specifically, it investigated the applicability and effectiveness of the simplest (most readily affordable) of the strategies so far tested (Lancioni, Singh, O’Reilly, Sigafoos, et al., 2013). Such strategy is based on static pictorial representations, which are presented through a laptop computer fitted with inexpensive video editing software (Pinnacle Studio, version 14, by COREL; www.pinnaclesys.com). The software allows staff to program (a) the time intervals between instructions (i.e., the time intervals that the computer has to wait before moving from one specific instruction to the next) and (b) the sound cues alerting the patients as soon as a new instruction appears. The second study assessed basic technology-aided strategies that would allow the patients to choose music items on their own rather than relying on others, as it often happens within daily settings (Chatterton, Thy, Baker, & Morgan, 2010; Ferrero-Arias et al., 2011; Lancioni, O’Reilly, et al., 2013; Raglio et al., 2010; Wall & Duffy, 2010). In practice, the patients (a) were to use a simple computer system, which presented them with different music options (e.g., different music styles and different singers or songs), and (b) could choose the preferred option through a small hand-pressure response performed on a microswitch that they had in their hand. Based on preliminary data (Lancioni, Singh, O’Reilly, Sigafoos, et al., 2013), one might expect Study I to provide new, satisfactory evidence in support of the simple strategy with pictorial instructions. Any such evidence would be considered practically relevant, as most daily contexts can be more easily inclined to adopt technology-aided intervention strategies when these are relatively easy to arrange as well as inexpensive (Godwin, Mills, Anderson, & Kunik, 2013; Nijhof, Van Gemert-Pijnen, Burns, & Seydel, 2013; Riikonen, Ma¨kela¨, & Pera¨la¨, 2010). Study II was expected to indicate a way to help patients with moderate Alzheimer’s disease maintain an active role (self-determination) during a leisure occupation known to be beneficial and enjoyable for them. An active role would be important to counter, at least temporarily, their tendency to passivity and marginality with possibly positive implications for their general enjoyment and status (i.e., the way they are perceived by others) (Fischer, Langner, Birbaumer, & Brocke, 2008; Lancioni, O’Reilly, et al., 2013). To assess these points, a social validation check was carried out with university psychology students rating the patients during sessions of Study II and during control sessions in which staff arranged music stimulation for them (Callahan, Henson, & Cowan, 2008; Lancioni et al., 2006). 2. Study I 2.1. Method 2.1.1. Participants Four patients (Jenny, Rosy, Annette, and Trudy) of 74–90 (M = 80) years of age participated. They were considered to function at a moderate level of Alzheimer’s disease with scores of 15–20 on the Mini-Mental State Examination (Folstein, Folstein, & McHugh, 1975). Annette and Trudy were also reported to have a mild form of depression for which they received specific medication. Pharmacological treatment for the Alzheimer’s condition, at the time of the study, was available for Jenny and Annette in the form of acetylcholinesterase inhibitors. Three criteria were followed for the inclusion of these patients in the study. First, they were no longer capable of performing simple and relevant daily activities, such as making tea and preparing a fruit salad or a snack. This inability reduced their opportunities of functional engagement within their living context. Second, in spite of such inability (closely linked to their difficulties to remember the sequence of steps involved in

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Table 1 Steps for preparing coffee. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21.

Take the carafe with warm water. Take the coffee can. Take the spoon. Put a spoonful of coffee grains in the carafe. Steer the coffee in the carafe. Take the tray. Take the tray cloth. Put the tray cloth on the tray. Take white cups. Put the cups on the tray. Pour coffee into the cups. Take coffee spoons. Put the spoons next to the cups. Take napkins. Put the napkins on the tray. Take the sugar. Put the sugar on the tray. Take a small bottle of water. Put the bottle on the tray. Take plastic glasses. Put the glasses on the tray.

the activities), they (a) seemed to discriminate brief verbal instructions as well as photographs and drawings related to such activity steps, and (b) possessed the motor skills required to carry out those steps. Third, they as well as their families and staff were clearly interested in the use of technology as support for the performance of daily activities. The families had also provided informed consent for the patients’ involvement in this study, which was approved by a scientific and ethics committee. 2.1.2. Setting, activities, and data recording The study was carried out in a quiet room of the center for people with Alzheimer’s disease and other dementias that the patients attended. Two activities were available for each patient, that is, preparing a snack and coffee for Jenny and Rosy and preparing an orange drink and coffee or tea for Annette and Trudy. These activities were similar to those described in previous studies in this area (Lancioni et al., 2010, 2012; Perilli, Lancioni, Hoogeveen, et al., 2013) and included 16 steps (snack) or 20–24 steps (the other activities). Table 1 lists the steps required for preparing coffee. The patients sat at a table with the computer screen placed in a front/left position and the activity items available at the right and left sides of the table. Data recording concerned the patients’ performance of the activity steps. A step was considered correct if it matched its description within the activity sequence and occurred independent of prompting by the research assistant (see below). Interrater reliability was assessed in about 25% of the activity trials. The percentages of agreement (computed for the single trials by dividing the number of activity steps with identical rating by the total number of steps and multiplying by 100) were within the 80–100 range, with individual means exceeding 95. 2.1.3. Technology with pictorial instructions The technology included a laptop computer fitted with Pinnacle Studio software (version 14), that is, a commercially available video editing program (see Section 1). This software, which can be purchased for about $US50.00, allowed the research assistant to build a file with pictorial instructions for each activity (i.e., a file with 16–24 photos of the material being used for the different steps of the activity). The photos adopted for the single activities could present variations across patients, depending on their experience and the material employed. The photos were shown on the computer screen for specific times (e.g., between 5 and 30 s), which were programmed by the research assistant, based on observations of the patients’ performance of the related steps (Cohen-Mansfield et al., 2006; Lancioni et al., 2012). In fact, longer exposure times were programmed for the photos/instructions concerning more laborious (time-demanding) steps, and vice versa. The times could be rearranged in line with the patients’ progress. This rearrangement was a simple operation and could be done by the research assistant in a couple of minutes. Each change of photo/instruction on the screen, which occurred automatically at the end of the programmed exposure time, was signaled by a 3- or 4-s sound cue. This sound cue was to alert the patients and eventually direct their attention to the new photo. 2.1.4. Experimental conditions Each patient was exposed to a multiple probe across activities design (Barlow, Nock, & Hersen, 2009). Initially, there were baseline trials on each of the two activities available. Then, intervention trials started on one of the activities. When a clear improvement had occurred on it, new baseline trials were carried out on the other activity. Then, intervention started on the latter activity while continuing on the first (i.e., with a number of trials smaller than that being used for the second). Verbal and physical prompting/guidance from the research assistant was available during both baseline and intervention trials.

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During baseline trials, it occurred if the patient asked for help or failed to carry out any step for 20–30 s. During intervention trials, it occurred if the patient failed to carry out a step correctly either in relation to the pictorial instruction cueing it or as part of the next or next two step(s), that is, in relation to the next pictorial instruction(s) (Lancioni, Singh, O’Reilly, Sigafoos, et al., 2013). The end of the activity trials was followed by approval/praise from the research assistant (i.e., a few sentences that emphasized the patients’ efforts to perform well) both during baseline and intervention. 2.1.4.1. Baseline. During each baseline trial, the patient was asked to carry out the activity scheduled without pictorial instructions. A trial would end after all the steps had been carried out or after four or five instances of prompting/guidance by the research assistant had occurred and the patient did not know how to continue. 2.1.4.2. Intervention. The intervention on each of the activities was preceded by six to eight practice trials during which the research assistant prompted/guided the patient to follow the pictorial instructions for the performance of the activity steps and precluded errors throughout the activity. These trials were followed by regular intervention trials in which the patient continued to be provided with the pictorial instructions, but prompting/guidance by the research assistant occurred as described in Section 2.1.4. 2.2. Results Figs. 1–4 summarize the data for Jenny, Rosy, Annette, and Trudy, respectively. The light-gray bars refer to preparing coffee (Jenny and Rosy) and preparing an orange drink (Annette and Trudy). The dark-gray bars refer to preparing a snack (Jenny and Rosy) and preparing coffee or tea (Annette and Trudy). The bars represent mean percentages of correct steps per activity trial computed over blocks of activity trials. The number of trials included in each block is indicated by the numeral above it. Jenny’s mean percentages of correct steps during the initial baseline phase (i.e., four trials on preparing coffee and two trials on preparing a snack; see the first three bars of Fig. 1) were below 40. Introduction of the intervention on the first activity (i.e., the 29 trials represented by the fourth and fifth bar of Fig. 1) promoted an increase in Jenny’s percentages to a mean of about 85. The subsequent two baseline trials on the second activity (see the sixth bar of Fig. 1) did not show any real

INTERVENTION

% of Correct Steps

BASELINE 14

100

15

BASELINE

[(Fig._1)TD$IG]

INTERVENTION 5 10

10

5

12

8

10

11

12

75 50

2

2

1

2

2

2

25 0

3

4

5

6

7

8

9

Blocks of Trials [ JENNY ] Fig. 1. Jenny’s data. The light- and dark-gray bars refer to preparing coffee and preparing a snack, respectively. The bars represent mean percentages of correct steps per activity trial computed over blocks of activity trials. The number of trials included in each block is indicated by the numeral above it.

% of Correct Steps

INTERVENTION BASELINE

11

100

11

BASELINE

[(Fig._2)TD$IG] INTERVENTION

10

5

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7

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75 50

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25 0

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Blocks of Trials [ ROSY ] Fig. 2. Rosy’s data plotted as in Fig. 1.

[(Fig._3)TD$IG]

INTERVENTION

% of Correct Steps

BASELINE

14 12

100

BASELINE

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INTERVENTION 6

7

25

17

10

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75 50

3

4

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25 0

4

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6

7

8

9

Blocks of Trials [ ANNETTE ] Fig. 3. Annette’s data. The light- and dark-gray bars refer to preparing an orange drink and preparing coffee, respectively. The data are plotted as in Fig. 1.

INTERVENTION

% of Correct Steps

BASELINE 12

100

12

BASELINE

[(Fig._4)TD$IG] INTERVENTION 7

12

7

40

23

8

9

10

11

12

12

75 50 25

3

3

3

3

0

1

2

3

4

5

6

7

Blocks of Trials [ TRUDY ] Fig. 4. Trudy’s data. The light- and dark-gray bars refer to preparing an orange drink and preparing tea, respectively. The data are plotted as in Fig. 1.

performance variations. The intervention on this activity (i.e., the last three dark-gray bars of Fig. 1 including a total of 32 trials) promoted an improvement similar to that observed with the first activity. The performance on the first activity during the last part of the intervention (i.e., the last three light-gray bars of Fig. 1 including a total of 18 trials) continued to be characterized by relatively high percentages of correct responding. Rosy’s overall performance on the same two activities used for Jenny was similar to that described for Jenny. Rosy received totals of 39 and 29 intervention trials for the two activities, respectively (see Fig. 2). Annette’s mean percentages of correct steps during the initial baseline phase (seven trials on preparing an orange drink and three trials on preparing coffee) were below 25. Introduction of the intervention on preparing an orange drink (i.e., 26 trials represented by the fourth and fifth bar of Fig. 3) led to clear performance improvement with a mean percentage of correct steps of about 85 (see fourth and fifth bar of Fig. 3). The subsequent three baseline trials on the second activity (see the sixth bar of Fig. 3) did not show performance changes. The intervention on this activity (i.e., the last three dark-gray bars of Fig. 3 including a total of 48 trials) promoted an improvement, which ultimately matched that observed with the first activity. The percentage of correct responding on the first activity during the last part of the intervention (i.e., the last three light-gray bars of Fig. 3 including a total of 30 trials) was above 90. Trudy’s overall performance was comparable to that described for Annette. Trudy received totals of 61 and 64 intervention trials for the two activities, respectively (see Fig. 4). 3. Study II 3.1. Method 3.1.1. Participants Four patients (Kathy, Beth, Sara, and Denis) of 75–89 (M = 81) years of age participated. They were considered to function at a moderate level of Alzheimer’s disease, with scores of 16–20 on the Mini-Mental State Examination (Folstein et al., 1975). Kathy was also reported as being affected by a mild form of depression and received medication for it. No specific pharmacological treatment for the Alzheimer’s condition was prescribed for any of the patients. They were known to have (a) no interest in daily activities such as those of Study I (which they generally refused to perform) and (b) a special predilection for music. Kathy and Beth liked classical music as well as popular music of their times,

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while Sara and Denis were mainly attracted by popular music of their times. Three criteria were used for their inclusion in the study. First, they depended on staff to have their music played, as they did not have the ability to operate a computer or record player. Second, they were capable of (a) understanding brief verbal questions and instructions as well as photographs related to music genre and/or singers and songs, and (b) operating a computer-linked pressure microswitch that would allow them music selection/activation responses. Third, the patients as well as their families and staff were keen to use computer-aided technology as a way to support independent music choice and activation. The families had also provided informed consent for the patients’ involvement in this study, which was approved by a scientific and ethics committee. 3.1.2. Setting, sessions, and data collection A quiet room of the center for people with Alzheimer’s disease and other dementias that the patients attended served as the setting for baseline and music sessions. Sessions involved the presence of only one participant and lasted 10 min or until any music piece activated before the 10-min mark had been played out. Data collection consisted of recording the music pieces that the patients activated (i.e., number and types). Interrater reliability was checked in about 25% of the sessions. Agreement (requiring that the recording of the music pieces activated corresponded for the two research assistants) was reported in more than 90% of the reliability sessions for each patient. 3.1.3. Technology for music selection and activation The technology used for music selection and activation included a laptop computer with an amplifier, a microswitch with related interface, and basic software. After staff interviews and observations of the patients’ general levels of functioning and preferences, two different choice programs were set up, one for Kathy and Beth and the other for Sara and Denis. For Kathy and Beth, each session presented choice situations including four preferred options. The first choice situation involved (1) classical music authors, (2) opera singers, (3) pop music male singers, and (4) pop music female singers. Each option was presented in a separate cell of the computer screen and scanned (illuminated) for 4–5 s. Prior to the scanning, the system verbally asked the patients to choose what they preferred. Concomitant with the scanning, each option was verbally identified by the system. The patients could select any option by activating the microswitch (a small pressure device that they had in their hand) when such option was being scanned and identified verbally. Once a selection was made, the computer screen presented a new choice situation involving four new options. For example, if the patients had selected classical music authors, the new choice situation involved Mozart, Beethoven, Verdi, and Vivaldi. If the patients had selected opera singers, the new choice situation involved Boccelli, Pavarotti, Callas, and Ricciarelli. Again, the patients were asked to choose what they preferred and then the scanning began. Once the patients had selected one of the options presented, a new choice situation appeared which was in line with the selection just operated. In the new situation, in fact, they would be presented with four compositions of the author just selected, four arias from the opera singer just selected, or four songs from the male or female pop singer just selected. The same sequence was followed as in the previous choice situations. Selection of one option activated it typically for 2–3 min. Thereafter, the sequence started again so that the patient could operate new selections and activate a new music piece. Patients’ failure to select an option led the system to repeat the scanning process and the request to choose what they preferred. The sequence of the options presented within the different choice situations changed across sessions. For Sara and Denis, the choice program included only pop music singers and songs. Initially, they were presented with a choice situation including four Italian pop music singers. The same procedural conditions were applied as for Kathy and Beth. The selection of one of the singers (via the pressure microswitch mentioned above) presented them with a new choice situation including two or three songs of that singer. Selection of one of the songs activated it. After the end of the song, the sequence restarted (i.e., as described for the previous patients). 3.1.4. Experimental conditions For each pair of patients (i.e., Kathy and Beth and Sara and Denis), the study was carried out according to a multiple probe across patients design (Barlow et al., 2009). Each pair started with baseline sessions. Then one of the two patients was introduced to intervention sessions. Once this patient managed selection responses and music activation, new baseline sessions and intervention occurred for the second patient. To extend the evaluation of the patients’ achievement with the technology-aided program and gather an appraisal of such program, a social validation check was carried out, in which university psychology students rated the patients’ behavior and the program after watching clips of intervention sessions and clips of control sessions in which staff arranged music stimulation. 3.1.4.1. Baseline. During baseline sessions, the patients sat in front of a table containing a record player and music records familiar to them and a computer. They were told that they could use them to listen to their preferred music. If they had no initiative within 3–4 min, the research assistant played a music piece for them to curb possible frustration. 3.1.4.2. Intervention. During intervention sessions, the patients sat in front of the same table as in baseline. However, the computer technology and microswitch were available and they worked as described in Section 3.1.3. The intervention sessions were preceded by 7–10 practice sessions in which the research assistants provided any guidance the patients needed to make selection responses and activate their preferred music.

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Table 2 Questionnaire items for the social validation check. 1. 2. 3. 4. 5. 6.

Do you think that Do you think that Do you think that Do you think that Do you think that Would you find it

the patient is happy/relaxed within this program condition? this condition helps the patient display an active role and self-determination? this condition helps the patient have a positive and competent image? this condition could have beneficial effects within a daily program for these patients? this condition is easy to implement within a day center for these patients? interesting to implement this condition?

3.1.4.3. Social validation check. The social validation check involved the participation of 44 university psychology students (39 women and 5 men) who attended undergraduate or graduate courses and were between 21 and 30 (M = 23) years of age. These students, who represented a convenience sample (Pedhazur & Schmelkin, 1991), were interested in disability matters (i.e., had taken a course or had been involved in research dealing with disability), but had no connections with this study. They were divided into four groups of 11. Each group watched two 3-min video-clips of one of the four patients. For five or six students, the first clip involved the initial part of a computer-aided session while the second clip involved the initial 3 min of a control session. For the other five or six students, the order of the clips was reversed. Two research assistants selected the clips on the basis of their representativeness of the patients’ behavior during the technology-aided sessions and the control sessions (i.e., six or seven sessions in which staff set up music for them, as prior to the study). After watching the clips, the students rated the conditions on a six-item questionnaire (see Table 2). The items dealt with patients’ enjoyment, selfdetermination, and social image, as well as with the benefits and practicality/applicability of the conditions, and the students’ personal interest in the conditions. For each item, the rating could vary from 1 to 5, which represented least and most positive values, respectively. 3.2. Results The two panels of Fig. 5 summarize the data for Kathy and Beth, respectively. The two panels of Fig. 6 summarize the data for Sara and Denis, respectively. Within each panel, the bars represent mean frequencies of music pieces activated per session, over a block of sessions. The number of sessions included in the blocks/bars is indicated by the numerals above them. The black squares represent mean selection percentages for the most frequently selected music options (Kathy and Beth) or Italian singers (Sara and Trudy) within the same blocks of sessions. Below each black square, there is a label identifying the music option or singer referred to by the square. The labels ‘‘CA,’’ ‘‘OS,’’ and ‘‘PM’’ used in Fig. 5 indicate classical music authors, opera singers, and pop male singers, respectively. The labels ‘‘MI,’’ ‘‘MO,’’ ‘‘VI,’’ and ‘‘PI’’ used in Fig. 6 refer to the Italian singers’ names.

[(Fig._5)TD$IG]

4 3

BASELINE

INTERVENTION KATHY 10

10

10

10

10

10

10

100

11

75

2

Mean Frequencies

2

25

OS

OS

PM

CA

CA

CA

PM

CA

0

0

BETH 7

4

7

7

7

7

8

8

100

8

3

75

2

50

1

2

2

1

2

Mean Percentages

1

50

25

OS

OS

OS

OS

OS

OS

OS

OS

3

4

5

6

7

8

9

10

0

0

Blocks of Sessions Fig. 5. The two panels summarize the data for Kathy and Beth, respectively. The bars represent mean frequencies of music pieces activated per session, over blocks of sessions. The number of sessions included in the blocks is indicated by the numerals above them. The black squares represent mean selection percentages for the most frequently selected music options (i.e., classical music authors, opera singers, and pop male singers, labeled as ‘‘CA,’’ ‘‘OS,’’ and ‘‘PM’’) within the blocks of sessions.

[(Fig._6)TD$IG]

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4 3

BASELINE

INTERVENTION SARA 9

10

10

10

10

10

10

100

10

75

2

Mean Frequencies

50

2

25

MI

PI

MO

MO

MI

MO

VI

MO

0

0

DENIS 8

4

8

9

9

9

9

9

9

100

3

75

2

50

1

2

2

1

2

Mean Percentages

1

25

MO

PI

MO

MO

MO

MO

MO

MO

3

4

5

6

7

8

9

10

0

0

Blocks of Sessions Fig. 6. The two panels summarize the data for Sara and Denis, respectively, which are plotted as in Fig. 4 except that the music options represented by the black squares are Italian singers.

Kathy’s baseline levels (two sessions) were zero, as she did not activate any music piece on her own. During the intervention (81 sessions), she activated a mean of about three music pieces per session. Her mean selection percentages for the most frequently selected music option varied between 28 and 39 across blocks of sessions. Classical music authors represented the music option with the highest selection percentage in four of the eight blocks of sessions. Beth’s baseline and intervention data (4 and 59 sessions) were similar to those reported for Kathy, except that opera singers represented the music option with the highest selection percentage (i.e., between 42 and 71) in all eight blocks of sessions. Sara and Denis’ baseline data (two and four sessions) matched those of the other participants. Their intervention data (79 and 70 sessions) showed mean frequencies of songs activated of about three per session. The mean selection percentages for the most frequently selected singer varied between 33 and 45 for Sara, and 31 and 51 for Denis. Sara showed variations in her selection preferences. Denis’ highest selection percentages concerned the same singer in seven of the eight blocks of sessions. The results of the social validation check are summarized in Table 3. The table reports the raters’ mean scores and standard deviations for the single questionnaire items over the two conditions. The 44 raters’ mean scores per item varied between 1.57 and 3.39 in relation to the control condition (i.e., sessions with no technology in which staff set up music) and between 3.66 and 4.09 in relation to the intervention condition (i.e., with the use of the technology). The score differences between conditions analyzed with paired t tests were statistically significant for all items except the one dealing with the practicality/applicability of the conditions. The significant t values ranged from 8.89 to 16.74 (p < 0.01) (Hastie, Tibshirani, & Friedman, 2009).

Table 3 Raters’ mean scores (M) and standard deviations (SD) for the questionnaire items over the two conditions. Items

Conditions Intervention

1 2 3 4 5 6

Control

M

SD

M

SD

3.66 4.09 3.75 4.02 3.75 4.02

0.71 0.74 0.69 0.76 0.87 0.79

2.32 1.57 1.70 1.82 3.39 2.36

0.64 0.59 0.70 0.81 1.04 1.08

Note: Rating scale used anchors of 1: very low and 5: very high.

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4. General discussion The results of Study I support preliminary evidence on the positive impact of a simplified technology package for presenting activity-related pictorial instructions to patients with moderate Alzheimer’s disease (Lancioni, Singh, O’Reilly, Sigafoos, et al., 2013). The results of Study II show that technology-aided programs allowed patients with moderate Alzheimer’s disease to select their preferred music options and activate music pieces independently. The patients’ behavior during the program was also rated favorably (i.e., by the students involved in the social validation check) in terms of happiness, self-determination, and social status. Obviously, Study II was a preliminary research effort in this area with a small number of participants, thus the results (albeit very interesting) should be taken with some caution (Chatterton et al., 2010; Ferrero-Arias et al., 2011; Lancioni, O’Reilly, et al., 2013; Raglio et al., 2010; McHugh et al., 2012). In light of the above, a number of considerations might be put forward. First, the improvement shown by the patients involved in Study I could be considered relevant on a personal basis as well as from the standpoint of their context. Indeed, the patients’ mean levels of correct performance across activities always exceeded 85% by the end of the intervention and such an achievement could have provided them a sense of satisfaction and reassurance and also an improved sense of respect from staff and caregivers in general (Brown, Schalock, & Brown, 2009; De Joode, van Heugten, Verhey, & van Boxtel, 2010; Friedman, Wamsley, Liebel, Saad, & Eggert, 2009; Lancioni, Singh, O’Reilly, Sigafoos, et al., 2009; Lancioni, Singh, O’Reilly, Zonno, et al., 2009; Perales, Cosco, Stephan, Haro, & Brayne, 2013; Scherer, Craddock, & Mackeogh, 2011; Sunderland, Catalano, & Kendall, 2009). From the standpoint of the context, the improvement could be considered noteworthy in two ways, that is, (a) it offered the possibility of arranging new occupational opportunities for the patients and (b) it was obtained through a technology that is commercially available (thus easily accessible) and largely inexpensive (Godwin et al., 2013; Nijhof et al., 2013; Riikonen et al., 2010; Wood, Harris, Snider, & Patchel, 2005; Wood, Womack, & Hooper, 2009). In fact, such technology involves a simple computer equipped with a software program of about $US50.00. Second, although highly encouraging the data of Study I do not allow a final statement about the actual efficacy and overall applicability of the technology adopted. Such a statement could be made only after the present technology has been compared to more sophisticated technology solutions that were recently assessed, with reasonably large numbers of patients (Barlow et al., 2009; Kazdin, 2001; Kennedy, 2005; Lancioni et al., 2010, 2012; Perilli, Lancioni, Hoogeveen, et al., 2013). Based on previous evidence in this area and the performance of the participants of Study I, it might be reasonable to assume that the present technology will compare satisfactorily with previous solutions when the participants (a) show mild or moderate levels of Alzheimer’s disease, (b) have no difficulties discriminating and responding to pictorial instructions, and (c) respond to sound cues calling their attention to the computer screen. These participants may be able to reach a high level of correct performance even if they are not always accurate in performing each activity step in relation to the matching instruction (Lancioni, Singh, O’Reilly, Sigafoos, et al., 2013). Indeed, they may be able to adjust to the instructions (e.g., waiting for the relevant instruction after performing two steps in succession). Third, the positive results obtained with the program variations adopted in Study II (i.e., one variation for Kathy and Beth and the other variation for Sara and Denis) are technically and practically promising. Yet, as indicated above, the preliminary nature of the study and the small number of participants involved makes it impossible to draw definite conclusions at this time. Only careful replication efforts would be able to determine the generality of the present data and the final applicability of this approach in daily contexts (Barlow et al., 2009; Kennedy, 2005). Positive replication results would suggest that patients like those involved in Study II may manage their leisure music activities with the likelihood of enjoying them more than when they are arranged by staff or caregivers (Fischer et al., 2008; Halpern, 2012; Lancioni, O’Reilly, et al., 2013; Lancioni, Singh, O’Reilly, Green, et al., 2013). An active role during these activities would (a) make the patients attract more positive attention and respect, and (b) ensure that they require less strict supervision, with practical and social/psychological advantages for their caregivers (Chou, Kro¨ger, & Lee, 2010; Coogle, Parham, & Rachel, 2011; Gitlin et al., 2008; Lancioni, Singh, O’Reilly, Green, et al., 2013; Letts et al., 2011; Perilli, Lancioni, Hoogeveen, et al., 2013). Fourth, the two program variations for music selection and activation used in Study II as well as the technology arranged for them can be seen as an affordable basis (i.e., with an estimated cost of less than $US2000.00) to be improved in line with ¨ stergren, 2011; De Joode, van Boxtel, Verhey, & van Heugten, 2012; De Joode, new data from new research (Borg, Larsson, & O van Heugten, Verhey, & van Boxtel, 2013; Hubbard Winkler et al., 2010; Lemoncello, Sohlberg, Fickas, & Prideaux, 2011; Melnyk, 2012; Pilotto et al., 2011). Additional developments of these programs are at present difficult to envisage given the limited experience with them and the limited amount of data so far collected. The aspects that could be easily explored concern (a) the number of options to include in the various choice situations, and (b) the instrument adopted for the response/selection. The number of options could occasionally be extended beyond four or reduced to only two, depending on the characteristics of the patients involved in the program. The response instrument could involve a variety of microswitches besides the pressure device used in the two program variations of Study II. For example, one could consider the use of a mini shock absorber device attached to the patients’ hand that the patients activate with a simple hand clapping response (Lancioni, Singh, O’Reilly, Green, et al., 2013). In conclusion, the results of the two studies are very encouraging, but additional evidence is necessary to determine (a) the overall applicability and relative effectiveness of the intervention technology used in Study I, (b) the representativeness of the data of Study II, and (c) possible solutions for upgrading the technology used in Study II. In light of the above, one of the most immediate goals of new research might involve studies comparing the technology of Study I with the technologies used

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in previous studies in this area (with presentation of verbal or pictorial instructions and video prompts partially guided by optic sensors monitoring the patients’ performance) (Lancioni et al., 2010, 2012; Perilli, Lancioni, Hoogeveen, et al., 2013) across groups of patients with different levels of functioning. A second, immediate goal of new research might involve replication studies with the technology solutions employed in Study II (Barlow et al., 2009; Kennedy, 2005). A third goal of new research might involve interviews of staff and families about the technology solutions used in the two studies reported to gather their opinion about those solutions and their suggestions for improvement (Callahan et al., 2008; Lancioni et al., 2006; Perilli, Lancioni, Hoogeveen, et al., 2013). References Ambrose, C. T. (2012). Neuroangiogenesis: A vascular basis for Alzheimer’s disease and cognitive decline during aging. Journal of Alzheimer’s Disease, 32, 773–788. Barlow, D. H., Nock, M., & Hersen, M. (2009). Single-case experimental designs: Strategies for studying behavior change (3rd ed.). New York: Allyn & Bacon. Bernick, C., Cummings, J., Raman, R., Sun, X., & Aisen, P. (2012). Age and rate of cognitive decline in Alzheimer disease: Implications for clinical trials. Archives of Neurology, 69, 901–905. Bier, N., Provencher, V., Gagnon, L., Van der Linden, M., Adam, S., & Desrosiers, J. (2008). New learning in dementia: Transfer and spontaneous use of learning in everyday life functioning. Two case studies. Neuropsychological Rehabilitation, 18, 204–235. Boller, B., Jennings, J. M., Dieudonne´, B., Verny, M., & Ergis, A. M. (2012). Recollection training and transfer effects in Alzheimer’s disease: Effectiveness of the repetition-lag procedure. Brain and Cognition, 78, 169–177. ¨ stergren, P. O. (2011). The right to assistive technology: For whom, for what, and by whom? Disability and Society, 26, 151–167. Borg, J., Larsson, S., & O Brown, R. I., Schalock, R. L., & Brown, I. (2009). Quality of life: Its application to persons with intellectual disabilities and their families – Introduction and overview. Journal of Policy and Practice in Intellectual Disabilities, 6, 2–6. Caffo`, A. O., De Caro, M. F., Picucci, L., Notarnicola, A., Settanni, A., Livrea, P., et al. (2012). Reorientation deficits are associated with amnestic mild cognitive impairment. American Journal of Alzheimer’s Disease and Other Dementias, 27, 321–330. Caffo`, A. O., Hoogeveen, F., Groenendaal, M., Perilli, V., Damen, M., Stasolla, F., et al. (2014). Comparing two different orientation strategies for promoting indoor traveling in people with Alzheimer’s disease. Research in Developmental Disabilities, 35, 572–580. Callahan, K., Henson, R., & Cowan, A. K. (2008). Social validation of evidence-based practices in autism by parents, teachers, and administrators. Journal of Autism and Developmental Disorders, 38, 678–692. Campbell, N. L., Boustani, M. A., Skopeljia, E. N., Gao, S., Unverzagt, F. W., & Murray, M. D. (2012). Medication adherence in older adults with cognitive impairment: A systematic evidence-based review. American Journal of Geriatric Pharmacotherapy, 10, 165–177. Chatterton, W., Thy, M. M., Baker, F., & Morgan, K. (2010). The singer of the singing: Who sings individually to persons with dementia and what are the effects? American Journal of Alzheimer’s Disease and Other Dementias, 25, 641–649. Chou, Y. C., Kro¨ger, T., & Lee, Y. C. (2010). Predictors of job satisfaction among staff in residential settings for persons with intellectual disabilities: A comparison between three residential models. Journal of Applied Research in Intellectual Disabilities, 23, 279–289. Cle´ment, S., Tonini, A., Khatir, F., Schiaratura, L., & Samsony, S. (2012). Short and long term effects of musical intervention in severe Alzheimer’s disease. Music Perception, 29, 533–541. Cohen-Mansfield, J., Creedon, M. A., Malone, T., Parpura-Gill, A., Dakheel-Ali, M., & Heasley, C. (2006). Dressing of cognitively impaired nursing home residents: Description and analysis. The Gerontologist, 46, 89–96. Coogle, C., Parham, I. A., & Rachel, C. A. (2011). Job satisfaction and career commitment among Alzheimer’s care providers: Addressing turnover and improving staff empowerment. American Journal of Alzheimer’s Disease and Other Dementias, 26, 521–527. Cotelli, M., Manenti, R., Zanetti, O., & Miniussi, C. (2012). Non-pharmacological intervention for memory decline. Frontiers in Human Neuroscience, 6 http:// dx.doi.org/10.3389/fnhum.2012.00046 Cotrell, V., Wild, K., & Bader, T. (2006). Medication management and adherence among cognitively impaired older adults. Journal of Gerontological Social Work, 47, 31–46. Darreh-Shori, T., & Soininen, H. (2010). Effects of cholinesterase inhibitors on the activities and protein levels of cholinesterases in the cerebrospinal fluid of patients with Alzheimer’s disease: A review of recent clinical studies. Current Alzheimer Research, 7, 67–73. De Joode, E. A., van Boxtel, M. P. J., Verhey, F. R., & van Heugten, C. M. (2012). Use of assistive technology in cognitive rehabilitation: Exploratory studies of the opinions and expectations of healthcare professionals and potential users. Brain Injury, 26, 1257–1266. De Joode, E., van Heugten, C., Verhey, F., & van Boxtel, M. (2010). Efficacy and usability of assistive technology for patients with cognitive deficits: A systematic review. Clinical Rehabilitation, 24, 701–714. De Joode, E. A., van Heugten, C. M., Verhey, F. R., & van Boxtel, M. P. J. (2013). Effectiveness of an electronic cognitive aid in patients with acquired brain injury: A multicentre randomised parallel-group study. Neuropsychological Rehabilitation, 23, 133–156. Ferrero-Arias, J., Gon˜i-Imı´zcoz, M., Gonza´lez-Bernal, J., Lara-Ortega, F., Da Silva-Gonza´lez, A., & Dı´ez-Lopez, M. (2011). The efficacy of nonpharmacological treatment for dementia-related apathy. Alzheimer Disease and Associated Disorders, 25, 213–219. Ferris, S. H., & Farlow, M. (2013). Language impairment in Alzheimer’s disease and benefits of acetylcholinesterase inhibitors. Clinical Intervention in Aging, 8, 1007–1014. Fischer, T., Langner, R., Birbaumer, N., & Brocke, B. (2008). Arousal and attention: Self-chosen stimulation optimizes cortical excitability and minimizes compensatory effort. Journal of Cognitive Neuroscience, 20, 1443–1453. Folstein, M., Folstein, S. E., & McHugh, P. R. (1975). Mini-mental state a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198. Friedman, B., Wamsley, B. R., Liebel, D. V., Saad, Z. B., & Eggert, G. M. (2009). Patient satisfaction, empowerment, and health and disability status effects of a disease management-health promotion nurse intervention among medicare beneficiaries with disabilities. The Gerontologist, 49, 778–792. Gitlin, L. N., Winter, L., Burke, J., Chernett, N., Dennis, M. P., & Hauck, W. W. (2008). Tailored activities to manage neuropsychiatric behaviors in persons with dementia and reduce caregiver burden: A randomized pilot study. American Journal of Geriatric Psychiatry, 16, 229–239. Godwin, K. M., Mills, W. L., Anderson, J. A., & Kunik, M. E. (2013). Technology-driven interventions for caregivers of persons with dementia: A systematic review. American Journal of Alzheimer’s Disease and Other Dementias, 28, 216–222. Halpern, A. R. (2012). Dementia and music: Challenges and future directions. Music Perception, 29, 543–545. Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: Data mining, inference, and prediction (2nd ed.). New York: Springer. Hubbard Winkler, S. L., Vogel, B., Hoenig, H., Cowper Ripley, D. C., Wu, S., Fitzgerald, S. G., et al. (2010). Cost, utilization, and policy of provision of assistive technology devices to veterans poststroke by medicare and VA. Medical Care, 48, 558–562. Kazdin, A. E. (2001). Behavior modification in applied settings (6th ed.). New York: Wadsworth. Kennedy, C. (2005). Single case designs for educational research. New York: Allyn & Bacon. Konrath, E. L., Passos Cdos, S., Klein, L. C., & Henriques, A. T. (2013). Alkaloids as a source of potential anticholinesterase inhibitors for the treatment of Alzheimer’s disease. The Journal of Pharmacy and Pharmacology, 65, 1701–1725. Lancioni, G. E., La Martire, M. L., Singh, N. N., O’Reilly, M. F., Sigafoos, J., Pinto, K., et al. (2008). Persons with mild or moderate Alzheimer’s disease managing daily activities via verbal instruction technology. American Journal of Alzheimer’s Disease and Other Dementias, 23, 552–562. Lancioni, G. E., O’Reilly, M. F., Singh, N. N., Groeneweg, J., Bosco, A., Tota, A., et al. (2006). A social validation assessment of microswitch-based programs for persons with multiple disabilities employing teacher trainees and parents as raters. Journal of Developmental and Physical Disabilities, 18, 383–391.

G.E. Lancioni et al. / Research in Developmental Disabilities 35 (2014) 2117–2128

2127

Lancioni, G. E., O’Reilly, M. F., Singh, N. N., Sigafoos, J., Grumo, G., Pinto, K., et al. (2013). Assessing the impact and social perception of self-regulated music stimulation with patients with Alzheimer’s disease. Research in Developmental Disabilities, 34, 139–146. Lancioni, G. E., Perilli, V., O’Reilly, M. F., Singh, N. N., Sigafoos, J., Bosco, A., et al. (2013). Technology-based orientation programs to support indoor travel by persons with moderate Alzheimer’s disease: Impact assessment and social validation. Research in Developmental Disabilities, 34, 286–293. Lancioni, G. E., Perilli, V., Singh, N. N., O’Reilly, M. F., Sigafoos, J., Bosco, A., et al. (2011). Persons with mild or moderate Alzheimer’s disease use a basic orientation technology to travel to different rooms within a day center. Research in Developmental Disabilities, 32, 1895–1901. Lancioni, G. E., Perilli, V., Singh, N. N., O’Reilly, M. F., Sigafoos, J., Cassano, G., et al. (2012). Technology-aided pictorial cues to support the performance of daily activities by persons with mild or moderate Alzheimer’s disease. Research in Developmental Disabilities, 33, 265–273. Lancioni, G. E., Singh, N. N., O’Reilly, M. F., Green, V. A., Ferlisi, G., Ferrarese, G., et al. (2013). Self-regulated music stimulation for persons with Alzheimer’s disease: Impact assessment and social validation. Developmental Neurorehabilitation, 16, 17–26. Lancioni, G. E., Singh, N. N., O’Reilly, M. F., Sigafoos, J., Pangrazio, M. T., Megna, M., et al. (2009). Persons with moderate Alzheimer’s disease improve activities and mood via instruction technology. American Journal of Alzheimer’s Disease and Other Dementias, 24, 246–257. Lancioni, G. E., Singh, N. N., O’Reilly, M. F., Sigafoos, J., Renna, C., Ventrella, M., et al. (2013). Supporting daily activities and indoor travel of persons with moderate Alzheimer’s disease through standard technology resources. Research in Developmental Disabilities, 34, 2351–2359. Lancioni, G. E., Singh, N. N., O’Reilly, M. F., Sigafoos, J., Tatulli, E., Rigante, V., et al. (2010). Technology-aided verbal instructions to help persons with mild or moderate Alzheimer’s disease perform daily activities. Research in Developmental Disabilities, 31, 1240–1250. Lancioni, G., Singh, N., O’Reilly, M., Zonno, N., Flora, A., Cassano, G., et al. (2009). Persons with mild and moderate Alzheimer’s disease use verbal-instruction technology to manage daily activities: Effects on performance and mood. Developmental Neurorehabilitation, 12, 181–190. Lemoncello, R., Sohlberg, M., Fickas, S., & Prideaux, J. (2011). A randomised controlled crossover trial evaluating television assisted prompting (TAP) for adults with acquired brain injury. Neuropsychological Rehabilitation, 21, 825–846. Letts, L., Edwards, M., Berenyi, J., Moros, K., O’Neill, C., O’Toole, C., et al. (2011). Using occupations to improve quality of life, health and wellness, and client and caregiver satisfaction for people with Alzheimer’s disease and related dementias. American Journal of Occupational Therapy, 65, 497–504. Marson, D. C., Sawrie, S. M., Snyder, S., McInturff, B., Stalvey, T., Boothe, A., et al. (2000). Assessing financial capacity in patients with Alzheimer disease: A conceptual model and prototype instrument. Archives of Neurology, 57, 877–884. Martyr, A., & Clare, L. (2012). Executive function and activities of daily living in Alzheimer’s disease: A correlational meta-analysis. Dementia and Geriatric Cognitive Disorders, 33, 189–203. Massoud, F., & Le´ger, G. C. (2011). Pharmacological treatment of Alzheimer disease. The Canadian Journal of Psychiatry, 56, 579–588. McHugh, L., Gardstrom, S., Hiller, J., Brewer, M., & Diestelkamp, W. S. (2012). The effect of pre-meal, vocal re-creative music therapy on nutritional intake of residents with Alzheimer’s disease and related dementias: A pilot study. Music Therapy Perspectives, 30, 32–42. Melnyk, B. M. (2012). The role of technology in enhancing evidence-based practice, education, healthcare quality, and patient outcomes: A call for randomized controlled trials and comparative effectiveness research. Worldviews on Evidence-Based Nursing, 9, 63–65. Melrose, R. J., Ettenhofer, M. L., Harwood, D., Achamallah, N., Campa, O., Mandelkern, M., et al. (2011). Cerebral metabolism, cognition, and functional abilities in Alzheimer disease. Journal of Geriatric Psychiatry and Neurology, 24, 127–134. Mihailidis, A., Boger, J., Canido, M., & Hoey, J. (2007). The use of an intelligent prompting system for people with dementia. ACM Interactions, 14, 34–37. Nijhof, N., Van Gemert-Pijnen, J. E., Burns, C. M., & Seydel, E. R. (2013). A personal assistant for dementia to stay at home safe at reduced cost. Gerontechnology, 11, 469–479. Nyga˚rd, L., & Starkhammar, S. (2003). Telephone use among noninstitutionalized persons with dementia living alone: Mapping out difficulties and response strategies. Scandinavian Journal of Caring Sciences, 17, 239–249. Nyga˚rd, L., & Starkhammar, S. (2007). The use of everyday technology by people with dementia living alone: Mapping out the difficulties. Aging & Mental Health, 11, 144–155. Pedhazur, E., & Schmelkin, L. (1991). Measurement design and analysis: An integrated approach. New York: Psychology Press. Perales, J., Cosco, T. D., Stephan, B. C. M., Haro, J. M., & Brayne, C. (2013). Health-related quality-of-life instruments for Alzheimer’s disease and mixed dementia. International Psychogeriatrics, 25, 691–706. Perilli, V., Lancioni, G. E., Hoogeveen, F., Caffo`, A. O., Singh, N. N., O’Reilly, M. F., et al. (2013). Video prompting versus other instruction strategies for persons with Alzheimer’s disease. American Journal of Alzheimer’s Disease and Other Dementias, 28, 393–402. Perilli, V., Lancioni, G. E., Laporta, D., Paparella, A., Caffo`, A. O., Singh, N. N., et al. (2013). A computer-aided telephone system to enable five persons with Alzheimer’s disease to make phone calls independently. Research in Developmental Disabilities, 34, 1991–1997. Perilli, V., Lancioni, G. E., Singh, N. N., O’Reilly, M. F., Sigafoos, J., Cassano, G., et al. (2012). Persons with Alzheimer’s disease make phone calls independently using a computer-aided telephone system. Research in Developmental Disabilities, 33, 1014–1020. Perry, R., Monaco, M., Fadda, L., Caltagirone, C., & Carlesimo, G. A. (2014). Neuropsychological correlates of behavioral symptoms in Alzheimer’s disease, frontal variant of frontotemporal, subcortical vascular, and lewy body dementias: A comparative study. Journal of Alzheimer’s Disease, 39, 669–677. Pilotto, A., D’Onofrio, G., Benelli, E., Zanesco, A., Cabello, A., Margeli, M. C., et al. (2011). Information and communication technology systems to improve quality of life and safety of Alzheimer’s disease patients: A multicenter international survey. Journal of Alzheimer’s Disease, 23, 131–141. Provencher, V., Bier, N., Audet, T., & Gagnon, L. (2008). Errorless-based techniques can improve route finding in early Alzheimer’s disease: A case study. American Journal of Alzheimer’s Disease and Other Dementias, 23, 47–56. Raglio, A., Bellelli, G., Traficante, D., Gianotti, M., Ubezio, M. C., Gentile, S., et al. (2010). Efficacy of music therapy treatment based on cycles of sessions: A randomised control trial. Aging and Mental Health, 14, 900–904. Riikonen, M., Ma¨kela¨, K., & Pera¨la¨, S. (2010). Safety and monitoring technologies for the homes of people with dementia. Gerontology, 9, 32–45. Rive, B., Aarsland, D., Grishchenko, M., Cochran, J., Lamure, M., & Toumi, M. (2012). Cost-effectiveness of memantine in moderate and severe Alzheimer’s disease in Norway. International Journal of Geriatric Psychiatry, 27, 573–582. Scherer, M. J., Craddock, G., & Mackeogh, T. (2011). The relationship of personal factors and subjective well-being to the use of assistive technology devices. Disability and Rehabilitation, 33, 811–817. Selwyn, N., Gorard, S., Furlong, J., & Madden, L. (2003). Older adults’ use of information and communications technology in everyday life. Aging & Society, 23, 561–582. Sikkes, S. A., Pijnenburg, Y. A., Knol, D. L., de Lange-de Klerk, E. S., Scheltens, P., & Uitdehaag, B. M. (2013). Assessment of instrumental activities of daily living in dementia: Diagnostic value of the Amsterdam instrumental activities of daily living questionnaire. Journal of Geriatric Psychiatry and Neurology, 26, 244–250. Silverstein, N. M., & Sherman, R. (2010). Taking control of Alzheimer’s disease. Gerontology and Geriatrics Education, 31, 274–288. Small, J. (2012). A new frontier in spaced retrieval memory training for persons with Alzheimer’s disease. Neuropsychological Rehabilitation, 22, 329–361. Soto, M. E., Secher, M., Gillette-Guyonnet, S., Abellan van Kan, G., Andrieu, S., Nourhashemi, F., et al. (2012). Weight loss and rapid cognitive decline in communitydwelling patients with Alzheimer’s disease. Journal of Alzheimer’s Disease, 28, 647–654. Spalletta, G., Calatagirone, C., Girardi, P., Gianni, W., Casini, A. R., & Palmer, K. (2012). The role of persistent and incident major depression on rate of cognitive deterioration in newly diagnosed Alzheimer’s disease patients. Psychiatry Research, 198, 263–268. Sunderland, N., Catalano, T., & Kendall, E. (2009). Missing discourses: Concepts of joy and happiness in disability. Disability and Society, 24, 703–714. Takeda, M., Tanaka, T., Okochi, M., & Kazui, H. (2012). Non-pharmacological intervention for dementia patients. Psychiatry and Clinical Neurosciences, 66, 1–7. Tayeb, H. O., Yang, H. D., Price, B. H., & Tarazi, F. I. (2012). Pharmacotherapies for Alzheimer’s disease: Beyond cholinesterase inhibitors. Pharmacology and Therapeutics, 134, 8–25. Wall, M., & Duffy, A. (2010). The effects of music therapy for older people with dementia. British Journal of Nursing, 19, 108–113. Wilson, R. S., Segawa, E., Boyle, P. A., Anagnos, S. E., Hizel, L. P., & Bennett, D. A. (2012). The natural history of cognitive decline in Alzheimer’s disease. Psychology and Aging, 27, 1008–1017.

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Wood, W., Harris, S., Snider, M., & Patchel, S. A. (2005). Activity situations on an Alzheimer’s disease special care unit and resident environmental interaction, time, use, and affect. American Journal of Alzheimer’s Disease and Other Dementias, 20, 105–118. Wood, W., Womack, J., & Hooper, B. (2009). Dying of boredom: An exploratory case study of time use, apparent affect, and routine activity situations on two Alzheimer’s special care units. American Journal of Occupational Therapy, 63, 337–350. Zanetti, O., Zanieri, G., Di Giovanni, G., De Vreese, L. P., Pezzini, A., Metitieri, T., et al. (2001). Effectiveness of procedural memory stimulation in mild Alzheimer’s disease patients: A controlled study. Neuropsychological Rehabilitation, 11, 263–272.